POPULATION-BASED PLATFORM FOR IDENTIFICATION OF IMMUNOGENIC PEPTIDES

Abstract

The description relates to methods for identifying polypeptide fragments that are immunogenic to a specific human subject, methods for preparing pharmaceutical compositions comprising such polypeptide fragments, pharmaceutical compositions comprising such polypeptide fragments, and treatment methods using such compositions. The methods include identifying a polypeptide fragment that binds to multiple HLA groups of individual subjects.

Description

POPULATION-BASED IMMUNOGENIC PEPTIDE IDENTIFICATION PLATFORM COUNTRYSIDE The disclosure relates to methods for predicting whether a polypeptide is immunogenic for a specific human subject, methods for identifying fragments of a polypeptide that are immunogenic for a specific human subject, methods for preparing precision pharmaceutical compositions, or kits comprising said polypeptide fragments. , specific pharmaceutical compositions for a human subject comprising said polypeptide fragments and methods of treatment using said compositions. BACKGROUND For decades, scientists have assumed that chronic disease was beyond the reach of a person's natural defenses. Recently, however, a significant number of tumor regressions observed in individuals treated with antibodies that block immune-inhibiting molecules has accelerated the field of cancer immunotherapy. These clinical findings demonstrate that reactivation of existing T cell responses produces significant clinical benefit for individuals. These advances have renewed enthusiasm for the development of cancer vaccines that induce tumor-specific T cell responses. Despite the promise, current immunotherapy is effective in only a fraction of individuals. Furthermore, most cancer vaccine trials have failed to demonstrate statistically significant efficacy due to a low rate of tumor regression and anti-tumor T cell responses in individuals. Similar failures have been reported with therapeutic and preventive vaccines that sought to include T cell responses in the field of HIV and allergies. There is a need to overcome the clinical failures of immunotherapies and vaccines. COMPENDIUM In antigen presenting cells (APC), protein antigens are processed to form peptides. These peptides bind to human leukocyte antigen (HLA) molecules and are presented on the cell surface as peptide-HLA complexes to T cells. Different individuals express different HLA molecules, and different HLA molecules present different peptides. Thus, according to the state of the art, a peptide, or a fragment of a larger polypeptide, is identified as being immunogenic for a specific human subject if it is presented by an HLA molecule that is expressed by the subject. In other words, the state of the art describes immunogenic peptides as HLA-restricted epitopes. However, HLA-restricted epitopes induce T cell responses in only a fraction of individuals expressing the HLA molecule. Peptides that activate a T cell response in one individual are inactive in others despite matching HLA alleles. Therefore, it was unknown how an individual's HLA molecules present the antigen-derived epitopes that positively activate T cell responses. As provided herein, multiple HLAs expressed by an individual must present the same peptide to activate a T cell response. Thus, fragments of a polypeptide antigen that are immunogenic for a specific individual are those that can be bind to multiple HLA class I (activate cytotoxic T cells) or class II (activate helper T cells) expressed by that individual. Accordingly, in a first aspect the disclosure provides a method for predicting the cytotoxic T cell response rate and / or the helper T cell response rate of a specific or target human population to the administration of a polypeptide or to the administration of a drug. a pharmaceutical composition, kit, or polypeptide panel comprising one or more polypeptides as active ingredients, wherein the method comprises (i) selecting or defining a relevant model human population comprising multiple subjects, each defined by HLA class I genotype and / or HLA class II genotype; (ii) determining for each subject in the model human population whether the polypeptide(s) together comprise (a) at least one amino acid sequence that is a T cell epitope capable of binding to at least two HLA class I molecules from the subject; and / or (b) at least one amino acid sequence that is a T cell epitope capable of binding to at least two HLA class II molecules from the subject; and (iii) predicting A. the cytotoxic T cell response rate of said human population, wherein a higher proportion of the model human population meeting the requirements of step (ii)(a) predicts a higher response rate of cytotoxic T lymphocytes in said human population; and / or B. the T helper cell response rate of said human population, wherein a higher proportion of the model human population meeting the requirements of step (ii)(b) predicts a higher T cell response rate auxiliaries in said human population. The description further provides a method for predicting the clinical response rate of a specific or target human population to the administration of a pharmaceutical composition, kit or panel of polypeptides comprising one or more polypeptides as active ingredients, wherein the method comprises (i) selecting or defining a relevant model human population comprising multiple subjects, each defined by HLA class I genotype; (ii) determining (a) for each subject in the model human population whether the active ingredient polypeptide(s) together comprise at least two different amino acid sequences, each of which is a T cell epitope capable of binding to at least two HLA class I molecules of the subject, wherein, optionally, the at least two different amino acid sequences are comprised in the amino acid sequence of two different polypeptide antigens that are targeted by the active ingredient polypeptides; (b) in the po model population the mean amount of target polypeptide antigens comprising at least one amino acid sequence A. which is a T cell epitope capable of binding to at least three HLA class I molecules from the individual subjects of the model population; and B. which is comprised in the amino acid sequence of the polypeptides of the active ingredient; and / or (c) in the model population the mean number of expressed target polypeptide antigens comprising at least one amino acid sequence A. which is a T cell epitope capable of binding to at least three HLA class I molecules of the individual subjects of the model population; and B. which is comprised in the amino acid sequence of the polypeptides of the active ingredient; and (iii) predicting the clinical response rate of said human population, wherein a higher proportion of the model human population meeting the requirements of step (ii)(a), a higher mean amount of target polypeptides in step (ii)(b) or a higher mean amount of target polypeptides expressed in step (ii)(c) predicts a higher clinical response rate in said human population. The disclosure further provides methods of treating a human subject in need thereof, wherein the method comprises administering to the subject a polypeptide, pharmaceutical composition, or kit of polypeptides from a panel of polypeptides that has been identified or selected based on their rate of predicted clinical or immune response determined as described above; its use in a method of treating a relevant human subject; and its use in the manufacture of a medicament for treating a relevant subject. The description also provides a method of designing or preparing a polypeptide, or a polynucleic acid encoding a polypeptide, for use in a method of inducing an immune response in a subject of a specific or target human population, wherein the method comprises (i) selecting or defining (a) a relevant model human population comprising multiple subjects, each defined by HLA class I genotype and / or by HLA class II genotype; and / or (b) a relevant model human population comprising multiple subjects, each defined by HLA class I genotype and a relevant model human population comprising multiple subjects, each defined by HLA class II genotype; (ii) identifying a fragment of up to 50 consecutive amino acids of a target polypeptide antigen comprising or consisting of A. a capable T cell epitope, in a high percentage of the subjects of a selected or defined model population in step (i ) that is defined by HLA class I genotype, binding to at least three HLA class I molecules from individual subjects; B. a T cell epitope capable, in a high percentage of the subjects of a model population selected or defined in step (i) that is defined by the HLA class II genotype, of binding to at least three HLA class II molecules II of individual subjects; oC. a T cell epitope capable, in a high percentage of the subjects of a model population selected or defined in step (i) that is defined by the HLA class I genotype, of binding to at least three HLA class I molecules I from individual subjects and a T cell epitope capable, in a high percentage of the subjects of a model population selected or defined in step (i) that is defined by HLA class II genotype, of binding to at least three HLA class II molecules from individual subjects; (iii) if the polypeptide fragment selected in step (ii) consists of an amino acid sequence that is an HLA class I binding epitope, optionally selecting a longer fragment of the target polypeptide antigen, wherein the fragment longer comprises or consists of an amino acid sequence that D. comprises the selected fragment in step (ii); and E. is an HLA class II molecule-binding T cell epitope capable, in a high percentage of subjects of a model population selected or defined in step (i) that is defined by HLA class II genotype, of bind to at least three or as many HLA class II molecules as possible from individual subjects; and (iv) designing or preparing a polypeptide or polynucleic acid encoding a polypeptide comprising or consisting of one or more polypeptide fragments identified in step (ii) or step (iii), wherein, optionally, the fragment of The polypeptide is flanked at the N- and / or C-terminus by additional amino acids that do not form part of the target polypeptide antigen sequence. The description provides a method of inducing an immune response in a subject of a specific or target human population, where the method comprises designing or preparing a polypeptide, a panel of polypeptides, a polynucleic acid encoding a polypeptide, or a pharmaceutical composition or kit. for use in said specific or target human population as described above and administering the polypeptides, polynucleic acid, pharmaceutical composition or polypeptides of the active ingredient of the kit to the subject. The description provides a polypeptide, a panel of polypeptides, a polynucleic acid, a pharmaceutical composition or a kit for use in a method of inducing an immune response in a subject of a specific or target human population, wherein the polypeptide, panel polypeptide, polynucleic acid, pharmaceutical composition or kit is designed or prepared as described above for use in said specific or target human population, and wherein the composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier or preservative . The present description provides a pharmaceutical composition, a panel of polypeptides or a kit for use in a method of inducing an immune response in a human subject, wherein the pharmaceutical composition, panel of polypeptides or kit comprises as active ingredients a first peptide and a second peptide and, optionally, one or more additional peptides, wherein each peptide comprises an amino acid sequence that is a T cell epitope capable of binding to at least three HLA class I molecules of at least 10% of human subjects, wherein the T cell epitope of the first region, the second region and, optionally, any additional regions are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one diluent, carrier or pharmaceutically acceptable preservative. The disclosure provides a pharmaceutical composition, polypeptide panel, or kit for use in a method of inducing an immune response in a human subject, wherein the pharmaceutical composition, polypeptide panel, or kit comprises an active ingredient polypeptide comprising a first region and a second region and, optionally, one or more additional regions, wherein each region comprises an amino acid sequence that is a T cell epitope capable of binding to at least three HLA class I molecules of at least the 10% of human subjects, wherein the T cell epitope of the first region, the second region and, optionally, any additional regions are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one diluent pharmaceutically acceptable carrier, preservative or carrier. The description provides a pharmaceutical composition, polypeptide panel or kit for use in a method of treating cancer in a subject in need thereof, wherein the pharmaceutical composition, polypeptide panel or kit comprises as active ingredients a first peptide and a second peptide and, optionally, one or more additional peptides, wherein each peptide comprises an amino acid sequence that is an HLA class T-binding T cell epitope, and wherein for said T cell epitope at least 10 % of human subjects who have cancer i. express a tumor-associated antigen selected from the antigens listed in Table 2 or Table 5 below that comprises said T cell epitope; yii. have at least three HLA class I molecules capable of binding to said T cell epitope; wherein said T cell epitope of the first peptide, the second peptide and, optionally, any additional peptide are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier or preservative. The disclosure provides a pharmaceutical composition, polypeptide panel, or kit for use in a method of treating cancer in a subject in need thereof, wherein the pharmaceutical composition, polypeptide panel, or kit comprises an active ingredient polypeptide comprising a first region and a second region, and optionally one or more additional regions, wherein each region comprises an amino acid sequence that is an HLA class I binding T cell epitope, and wherein for said T cell epitope at least 10% of human subjects having cancer (a) express a tumor-associated antigen selected from the antigens listed in Table 2 or Table 5 below comprising said T cell epitope; and (b) have at least three HLA class I molecules capable of binding to said T cell epitope; wherein said T cell epitope of the first region, the second region and, optionally, any additional region are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier or preservative. The disclosure provides a pharmaceutical composition, polypeptide panel or kit for use in a method of treating a cancer selected from colorectal, breast, ovarian, melanoma, non-melanoma skin cancer, lung, prostate, kidney, bladder, stomach, liver, cervix, esophagus, non-Hodgkin's lymphoma, leukemia, pancreatic cancer, uterine body, lip, oral cavity, thyroid, brain, nervous system gallbladder, larynx, pharynx, myeloma, nasopharyngeal cancer, Hodgkin's lymphoma, testicular cancer and Kaposi's sarcoma in a subject who needs it, where the pharmaceutical composition, polypeptide panel or kit comprises as active ingredients a first peptide and a second peptide and, optionally, one or more additional polypeptides, wherein each peptide comprises an amino acid sequence that is an epitope of HLA class I binding T cells, and wherein for said epitope d and T cells at least 10% of human subjects having said cancer (a) express a tumor-associated antigen selected from the antigens listed in Table 2 or Table 5 below comprising said T cell epitope; and (b) have at least three HLA class I molecules capable of binding to said T cell epitope; wherein said T cell epitope of the first peptide, the second peptide and, optionally, any additional peptide are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier or preservative. The disclosure provides a pharmaceutical composition, polypeptide panel or kit for use in a method of treating a cancer selected from colorectal, breast, ovarian, melanoma, non-melanoma skin cancer, lung, prostate, kidney, bladder, stomach, liver, cervix, esophagus, non-Hodgkin's lymphoma, leukemia, pancreatic cancer, uterine body, lip, oral cavity, thyroid, brain, nervous system gallbladder, larynx, pharynx, myeloma, nasopharyngeal cancer, Hodgkin's lymphoma, testicular cancer and Kaposi's sarcoma in a subject in need thereof, where the pharmaceutical composition, polypeptide panel or kit comprises a polypeptide of the active ingredient comprising a first region and a second region and, optionally, one or more additional regions, wherein each region comprises an amino acid sequence that is an epitope of HLA class I binding T cells, and wherein e for said T-cell epitope at least 10% of human subjects having said cancer (a) express a tumor-associated antigen selected from the antigens listed in Table 2 or Table 5 below comprising said lymphocyte epitope T; and (b) have at least three HLA class I molecules capable of binding to said T cell epitope; wherein said T cell epitope of the first polypeptide, the second polypeptide and, optionally, any additional polypeptides are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier or preservative. The disclosure provides a method of treating a human subject in need thereof, wherein the method comprises administering to the subject a polypeptide, a panel of polypeptides, a pharmaceutical composition, or the polypeptides of the active ingredient from a kit described above, where it has been determined that the subject expresses at least three HLA class I molecules and / or at least three HLA class II molecules capable of binding to the polypeptide or one or more of the polypeptides of the active ingredient of the pharmaceutical composition or kit. In another aspect, the invention provides a system comprising (a) a storage module configured to store data comprising the HLA class I and / or class II genotypes of each subject in a model population of human subjects; and the amino acid sequence of one or more test polypeptides; wherein the model population is representative of a test target human population; and (b) a computing module configured to identify and / or quantify amino acid sequences in the test polypeptide(s) that are capable of binding multiple HLA class I molecules from each subject in the model population and / or the amino acid sequences in the test polypeptide(s) that are capable of binding multiple HLA class II molecules from each subject in the model population. The description will now be described in more detail, by way of example and not limitation, and by reference to the accompanying drawings. Many equivalent modifications and variations will be apparent to those skilled in the art when provided with the present disclosure. Accordingly, the exemplary embodiments of the stated description are considered illustrative and not exhaustive. Various changes may be made to the described embodiments without departing from the scope of the description. All documents cited herein, either above or below, are expressly incorporated by reference in their entirety. The present description includes the combination of the aspects and preferred features described, except in the case that said combination clearly cannot be admitted or it is established that it is expressly avoided. As used in this specification and the appended claims, the singular forms "a", "an", and "the" include plural references unless the context clearly dictates otherwise. Thus, for example, reference to "a peptide" includes two or more such peptides. The section headings are used herein for convenience only and should not be construed as limiting in any way. DESCRIPTION OF THE FIGURES Figure 1: ROC curve of HLA-restricted PEPI biomarkers. Figure 2: ROC curve of <1 PEPT3+ test for determination of diagnostic accuracy. Figure 3A: PEPI3+ distribution of HLA class I compared to CD8+ T-cell responses measured by a state-of-the-art assay among the peptide pools used in the CD8+ T-cell response assays. PEPI3+ restricted by HLA class I. The overall percentage of agreement (OPA) of 90% between T-cell responses and PEPI3+ peptides demonstrates the utility of the described peptides for predicting the ensemble of T-cell responses induced by PEPI3+. vaccination of individuals. Figure 3B: PEPI3+ distribution of HLA class I compared to CD8+ T-cell responses measured by a state-of-the-art assay between peptide pools used in the CD8+ T-cell response assays. HLA class I restricted epitopes (PEPI1+). The OPA between predicted epitopes and CD8+ T cell responses was 28% (not statistically significant). Darkest gray: true positive (TP), peptide responses detected; and of T lymphocytes; Light gray: false negative (FN), only T cell responses detected; Lightest gray: false positive (FP), only peptide detected; Dark gray: true negative (TN): neither peptides nor T cell responses were detected. Figure 4A: HLA class II PEPI distribution compared to CD4+ T cell responses measured by a state-of-the-art assay between the peptide pools used in the assays. PEPI4+ restricted by HLA class II. 67% OPA between PEPI4+ and CD4+ T cell responses (p=0.002). Darkest gray: true positive (TP), peptide responses detected; and of T lymphocytes; Light gray: false negative (FN), only T cell responses detected; Lightest gray: false positive (FP), only peptide detected; Dark gray: true negative (TN): neither peptides nor T cell responses were detected. Figure 4B: HLA class II PEPI distribution compared to CD4+ T cell responses measured by a state-of-the-art assay between the peptide pools used in the assays. HLA class II restricted epitopes. The OPA between HLA class II restricted epitopes and CD4+ T cell responses was 66% (not statistically significant). Darkest gray: true positive (TP), peptide responses detected; and of T lymphocytes; Light gray: false negative (FN), only T cell responses detected; Lightest gray: false positive (FP), only peptide detected; Dark gray: true negative (TN): neither peptides nor T cell responses were detected. Figure 5A and 5B: Multiple HLA-binding peptides defining the set of HPV-16 LPV vaccine-specific T cell responses from 18 VIN-3 and 5 cervical cancer patients. HLA class I restricted PEPI3 counts. Light gray: immune responders measured after vaccination in the clinical trial; Dark gray: immune non-responders measured after vaccination in the clinical trial. The results show that ≥3 HLA class I binding peptides predict CD8+ T cell reactivity and ≥4 HLA class II binding peptides predict CD4+ T cell reactivity. Figure 5C and 5D: Multiple HLA-binding peptides defining the set of HPV-16 LPV vaccine-specific T cell responses from 18 VIN-3 and 5 cervical cancer patients. HLA class II restricted PEPI3 counts derived from LPV antigens from each patient. Light gray: immune responders measured after vaccination in the clinical trial; Dark gray: immune non-responders measured after vaccination in the clinical trial. The results show that éé3 HLA class I binding peptides predict the reactivity of CD8+ T cells and éé4 HLA class II binding peptides predict the reactivity of CD4+ T cells. Figure 6A: The multiple HLA class I binding peptides that define the HPV vaccine-specific T-cell responses set from 2 patients. A: Four HPV antigens in the HPV vaccine. The boxes represent the length of the amino acid sequences from the N-terminus to the C-terminus. Figure 6B: The multiple HLA class I binding peptides that define the HPV vaccine-specific T-cell responses set from 2 patients. Process to identify multiple HLA-binding peptides from two patients: HLA sequences from the patients marked as 4-digit HLA genotype to the right of the patient ID. The location of the 1st amino acid of the 54 and 91 epitopes that can bind to patient HLA 12-11 and patient 14-5 (PEPI1+) respectively are illustrated with lines. PEPI2 represents peptides selected from PEPI1+ that can bind to multiple HLAs of a patient (PEPI2+). PEPI3 represents peptides that can bind to =3 HLA of a patient (PEPI3+). PEPI4 represents peptides that can bind to ^4 HLA of a patient (PEPI4+). PEPI5 represents peptides that can bind to a patient's HLA éé5 (PEPI5+). PEPI6 represents the peptides that can bind to 6 HLA of a patient (PEPI6). Figure 6C: The multiple HLA class I-binding peptides defining the HPV vaccine-specific T cell response array from 2 patients. The vaccine-specific PEPI3+ pool of DNA from two patients characterizes their vaccine-specific T cell responses. Figure 7: Correlation between PEPI3+ ^1 score and CTL response rates of peptide targets determined in clinical trials. Figure 8: Correlation between PEPI3+ score =11 and clinical immune response rate (IRR) of immunotherapy vaccines. Dotted lines: 95% confidence band. Figure 9: Correlation between PEPI3+ score =12 and disease control rate (DCR) of immunotherapy vaccines. Dotted lines: 95% confidence band. Figure 10: HLA map of Rindopepimut on HLA alleles of subjects in the model population. Figure 11: Probability of vaccine antigen expression in tumor cells from patient XYZ. There is a greater than 95% probability that 5 of the 12 target antigens in the vaccination regimen are expressed in the patient's tumor. Therefore, the 12-peptide vaccines together can induce immune responses against at least 5 ovarian cancer antigens with a probability of 95% (AGP95). There is an 84% chance that each peptide will induce immune responses in patient XYZ. AGP50 is the mean (expected value) =7.9 (it is a measure of the efficacy of the vaccine in attacking patient XYZ's tumor). Figure 12: MRI findings of patient XYZ treated with the personalized vaccine (PIT). This highly pretreated late-stage ovarian cancer patient exhibited an unexpected target response after treatment with the ΡΓΓ vaccine. These MRI findings suggest that the PIT vaccine in conjunction with chemotherapy significantly reduced tumor burden. The patient is now continuing treatment with the PIT vaccine. Figure 13: Probability of vaccine antigen expression in ABC patient tumor cells. There is a probability of more than 95% that 4 of the 13 target antigens in the vaccination are expressed in the patient's tumor. Therefore, the 12-peptide vaccines together can induce immune responses against at least 4 breast cancer antigens with a probability of 95% (AGP95). There is an 84% chance that each peptide will induce immune responses in patient ABC. AGP50 is the mean (expected value) of the discrete probability distribution = 6.45 (it is a measure of the efficacy of the vaccine in attacking patient ABC's tumor). Figure 14: Example of peptide interest site analysis: PRAME antigen sites in 433 patients from the model population. On the y-axis are the 433 patients of the model population, on the x-axis is the amino acid sequence of the PRAME antigen (CTA). Each data point represents a PEPI presented by ^3 HLA class I from a patient starting at the specified amino acid position. The two most frequent PEPIs (referred to as best EPIs) of the PRAME antigen are highlighted in dark gray (peptide hotspots = PEPI hotspots). Figure 15: CTA expression curve calculated by analysis of tumor-specific antigen (CTA) expression frequency data in human breast cancer tissues. (Cell line data were not included). Figure 16A: Distribution of antigen expression for breast cancer based on calculation of multiple antigen responses from expression frequencies of the 10 different selected CTAs. A: non-cumulative distribution to calculate the expected value for the amount of antigens expressed (AG50). This value shows that 6.14 vaccine antigens are likely to be expressed by breast tumor cells. Figure 16B: Distribution of antigen expression for breast cancer based on calculation of multiple antigen responses from expression frequencies of the 10 different selected CTAs. Cumulative distribution curve of the minimum amount of expressed antigens (CTA expression curve). This shows that at least 4 vaccine antigens will be expressed with 95% probability in the breast cancer cell (AG95). Figure 17A: Distribution of PEPI-represented antigens (breast cancer vaccine-specific CTA antigens with <1 PEPI, designated "AP") within the model population (n=433) for breast cancer vaccine. A: non-cumulative distribution of APs where the average amount of APs is: AP5O=5.3O, which means that on average almost 6 CTAs will have PEPI in the model population. Figure 17B: Distribution of PEPI-represented antigens (breast cancer vaccine-specific CTA antigens with <1 PEPI, designated "AP") within the model population (n=433) for breast cancer vaccine. Cumulative distribution curve of the minimum amount of PA in the model population (n=433). This shows that at least one vaccine antigen will have PEPI in 95% of the model population (n=433) (AP95=1). Figure 18A: Distribution of expressed antigens represented by PEPI (tumor-expressed breast cancer vaccine-specific CTA antigens, for which <1 PEPI is predicted, termed "AGP") within the model population (n=433) calculated with CTA expression rates for breast cancer. A: non-cumulative distribution of AGP where the expected value for the amount of expressed CTA represented by PEPI is AGP50=3.37. AGP50 is a measure of the efficacy of the described breast cancer vaccine in targeting the breast tumor in an unselected patient population. AGP50 = 3.37 means that at least 3 CTAs from the vaccine are likely to be expressed by breast tumor cells and display PEPI in the model population. Figure 18B: Distribution of expressed antigens represented by PEPI (tumor-expressed breast cancer vaccine-specific CTA antigens, for which <1 PEPI is predicted, termed "AGP") within the model population (n=433) calculated with CTA expression rates for breast cancer. The cumulative distribution curve of the minimum amount of AGP in the model population (n=433) shows that at least 1 of the vaccine CTAs will have PEPI in 92% of the population and the remaining 8% of the population will probably not have PEPI. AGP not at all (AGP95=0, AGP92=1). Figure 19: CTA expression curve calculated by analysis of tumor-specific antigen (CTA) expression frequency data in human colorectal cancer tissues. (Cell line data were not included). Figure 20A: Distribution of antigen expression for colorectal cancer based on calculation of multiple antigen responses from expression frequencies of the 7 different selected CTAs. Non-cumulative distribution to calculate the expected value for the amount of vaccine antigens expressed in colorectal cancers (AG50). This value shows that 4.96 vaccine antigens are likely to be expressed by colorectal tumor cells. Figure 20B: Distribution of antigen expression for colorectal cancer based on calculation of multiple antigen responses from expression frequencies of the 7 different selected CTAs. Cumulative distribution curve of the minimum amount of expressed antigens (CTA expression curve). This shows that at least 3 antigens will be expressed with 95% probability in the colorectal cancer cell (AG95). Figure 21 A: Distribution of PEPI-represented antigens (CTA colorectal cancer vaccine-specific antigens predicted for <1 PEPI, designated "AP") within the model population (n=433) for colorectal cancer. Non-cumulative distribution of AP where the average amount of AP is: AP50=4.73, which means that on average 5 CTA will be represented by PEPT in the model population. Figure 2IB: Distribution of PEPI-represented antigens (CTA colorectal cancer vaccine-specific antigens predicted for <1 PEPI, designated "AP") within the model population (n=433) for colorectal cancer. Cumulative distribution curve of the minimum amount of PA in the model population (n=433). This shows that 2 or more antigens will be represented by PEPI in 95% of the model population (n=433) (AP95=2). Figure 22A: Distribution of expressed antigens represented by PEPI (tumor-expressed colorectal cancer vaccine-specific CTA antigens, for which <1 PEPI is predicted, termed "AGP") within the model population (n=433) calculated with CTA expression rates for colorectal cancer. Non-cumulative distribution of AGP where the expected value for the amount of expressed CTA represented by PEPI is AGP50=2.54. AGP50 is a measure of the efficacy of the described colorectal cancer vaccine in targeting colorectal tumors in an unselected patient population. AGP50 = 2.54 means that probably at least 2-3 CTAs from the vaccine will be expressed by colorectal tumor cells and will present PEPI in the model population. Figure 22B: Distribution of expressed antigens represented by PEPI (tumor-expressed colorectal cancer vaccine-specific CTA antigens, for which <1 PEPI is predicted, termed "AGP") within the model population (n=433) calculated with CTA expression rates for colorectal cancer. The cumulative distribution curve of the minimum amount of AGP in the model population (n=433) shows that at least 1 of the vaccine CTAs will be expressed and will also present PEPI in 93% of the population (AGP93=1). Figure 23: Schematic showing exemplary amino acid positions in overlapping HLA class I and HLA class II binding epitopes in a 30-mer peptide. Figure 24: Antigenicity of PolyPEPI1018 CRC vaccine in a general population. The antigenicity of PolyPEPI1018 in a subject is determined by the AP count, which indicates the amount of vaccine antigens that induce T cell responses in a subject. The AP count of PolyPEPI1018 was determined in each of the 433 subjects in the model population using the PEPI test, and then the AP50 count was calculated for the model population. The AP50 of PolyPEPI1018 in the model population is 4.73. The mean number of immunogenic antigens (ie, antigens with <1 PEPI) on P0IÍPEPIIOI8 in a general population is 4.73. Abbreviations: AP = antigens with <1 PEPI. Left panel: cumulative distribution curve. Right panel: different distribution curve. Figure 25: Efficacy of PolyPEPIlOL 8 CRC vaccine in a general population. Vaccine-induced T cells can recognize and kill tumor cells if the tumor cell presents a PEPI in the vaccine. The amount of AGP (PEPI-expressed antigens) is an indicator of vaccine efficacy in an individual, and depends on the potency and antigenicity of PolyPEPIlOl8. The mean number of immunogenic CTAs (ie AP [antigens expressed with <1 PEPI]) in P0IÍPEPIIOI8 is 2.54 in the model population. The probability that PolyPEPI1018 will induce T-cell responses against multiple antigens in one subject (ie, mAGP) in the model population is 77%. DESCRIPTION OF THE SEQUENCES SEQ ID NOs: 1 to 20 present the 9mer T-cell epitopes described in Table 30. SEQ ID NOs: 21 to 40 present the 9mer T-cell epitopes described in Table 33. SEQ ID NOs: 41-71 (81 to 111) present the breast cancer vaccine peptides set forth in Table 31. SEQ ID NOs 72-102 (112 to 142) present the colorectal cancer vaccine peptides set forth in Table 34. SEQ ID NOs 103-115 (159 to 171) present the additional peptide sequences described in Table 17. SEQ ID NOs: 116-128 (362-374) present the custom vaccine peptides designed for patient XYZ described in Table 26. SEQ ID NOs: 129-140 (375-386) present the custom designed vaccine peptides for the ABC patient described in Table 29. SEQ ID NOs: 141-188 (387-434) present additional 9-mer T cell epitopes described in Table 41. DETAILED DESCRIPTION HLA genotypes HLAs are encoded by the most polymorphic genes in the human genome. Each person has one maternal and one paternal allele for the three HLA class I molecules (HLA-A*, HLA-B*, HLA-C*) and four HLA class II molecules (HLA-DP*, HLA- DQ*, HLA-DRB1*, HLA-DRB3* / 4* / 5*). In practice, each person expresses a different combination of 6 HLA class T and 8 HLA class TT molecules presenting different epitopes of the same protein antigen. The function of HLA molecules is to regulate T cell responses. However, until now it was unknown whether a person's HLAs regulate T cell activation. The nomenclature used to designate the amino acid sequence of the HLA molecule is as follows: gene name*allele:protein number, which, for example, can be seen as: HLA-A*02:25. In this example, "02" refers to the allele. In most cases, alleles are defined by serotypes, which means that the proteins of a given allele will not react with each other in serological tests. Protein numbers ("25" in the example above) are assigned consecutively as the protein is discovered. A new protein number is assigned for any protein with a different amino acid sequence (eg, even a change of one amino acid in the sequence is considered a different protein number). Other information on the nucleic acid sequence of a given locus can be attached to the HLA nomenclature, but this information is not necessary for the methods described herein. The HLA class I genotype or the HLA class II genotype of an individual may refer to the actual amino acid sequence of each HLA class I or class II in an individual, or it may refer to nomenclature, such as described above, which designates, minimally, the allele and protein number of each HLA gene. An HLA genotype can be obtained or determined using any suitable method. For example, the sequence can be determined through sequencing of HLA gene loci using methods and protocols known in the art. Alternatively, an individual's HLA pool may be stored in a database and accessed using methods known in the art. HLA-epitope binding A given HLA from a subject will only present to T cells a limited number of different peptides produced by processing protein antigens on an APC. As used herein, "display" or "present", when used in connection with HLA, refers to the binding between a peptide (epitope) and an HLA. In this sense, "displaying" or "presenting" a peptide is synonymous with "binding" to a peptide. As used herein, the term "epitope" or "T cell epitope" refers to a contiguous amino acid sequence found within a protein antigen that possesses a binding affinity for (is capable of binding to) ) one or more HLAs. An epitope is HLA- and antigen-specific (HLA-epitope pairs, predicted by known methods), but not subject-specific. An epitope, T-cell epitope, polypeptide, polypeptide fragment, or composition comprising a polypeptide or fragment thereof is "immunogenic" for a specific human subject if it is capable of inducing a T-cell response (a cytotoxic T-lymphocyte response or a helper T-lymphocyte response) in that subject. In some cases, the T helper cell response is a Thl-type helper T cell response. In some instances, an epitope, T-cell epitope, polypeptide, polypeptide fragment, or composition comprising a polypeptide or fragment thereof is "immunogenic" for a specific human subject if it is more likely to induce a specific human response. of T cells or an immune response in the subject that a different T cell epitope (or, in some cases, two different T cell epitopes each) capable of binding to a single HLA molecule from the subject. The terms "T cell response" and "immune response" are used interchangeably herein and refer to the activation of T cells and / or the induction of one or more effector functions following recognition of one or more T cell pairs. HLA-epitope binding. In some cases, an "immune response" includes an antibody response since HLA class II molecules stimulate helper responses that are involved in the induction of CTL responses and long-lasting antibody responses. Effector functions include cytotoxicity, cytokine production and proliferation. In accordance with the present description, an epitope, a T cell epitope or a fragment of a polypeptide is immunogenic for a specific subject if it is capable of binding to at least two, or in some cases at least three, HLA class I or at least two, or in some cases at least three or at least four, HLA class II of the subject. For the purpose of the present description, we have coined the term "personal epitope" or "PEPI" to distinguish subject-specific epitopes from HLA-specific epitopes. A "PEPI" is a polypeptide fragment consisting of a contiguous amino acid sequence of the polypeptide that is a T cell epitope capable of binding one or more HLA class I molecules from a specific human subject. In other instances, a "PEPI" is a fragment of a polypeptide consisting of a contiguous amino acid sequence of the polypeptide that is a T cell epitope capable of binding one or more HLA class I molecules from a specific human subject. In other words, a "PEPI" is a T cell epitope that is recognized by the HLA pool of a specific individual. Unlike an "epitope," PEPTs are individual-specific because different individuals have different HLA molecules that each bind to different T cell epitopes. "PEPI1", as used herein, refers to a peptide, or a fragment of a polypeptide, that can bind to an HLA class I molecule (or, in specific contexts, an HLA class I molecule). II) of an individual. "PEPI1+" refers to a peptide, or a fragment of a polypeptide, that can bind to one or more HLA class I molecules of an individual. "PEPI2" refers to a peptide, or a fragment of a polypeptide, that can bind to two HLA class I (or II) molecules of an individual. "PEPI2+" refers to a peptide, or a fragment of a polypeptide, that can bind to two or more HLA class I (or II) molecules of an individual, that is, a fragment identified according to a method of the description. "PEPI3" refers to a peptide, or a fragment of a polypeptide, that can bind to three HLA class I (or II) molecules in an individual. "PEPI3+" refers to a peptide, or a fragment of a polypeptide, that can bind to three or more HLA class I (or II) molecules in an individual. "PEPI4" refers to a peptide, or a fragment of a polypeptide, that can bind to four HLA class I (or II) molecules of an individual. "PEPI4+" refers to a peptide, or a fragment of a polypeptide, that can bind to four or more HLA class I (or II) molecules of an individual. "PEPI5" refers to a peptide, or a fragment of a polypeptide, that can bind to five HLA class I (or II) molecules in an individual. "PEPI5+" refers to a peptide, or a fragment of a polypeptide, that can bind to five or more HLA class I (or II) molecules in an individual. "PEPI6" refers to a peptide, or a fragment of a polypeptide, that can bind to all six HLA class I (or six HLA class II) molecules in an individual. Generally speaking, epitopes displayed by HLA class I molecules are about nine amino acids in length and epitopes displayed by HLA class II molecules are about fifteen amino acids in length. For the purposes of the present description, however, an epitope may be more or less than nine (for HLA class I) or more or less than fifteen (for HLA class II) amino acids in length, so long as the epitope is capable of to bind to HLA. For example, an epitope that is capable of binding to HLA class I can be between 7, 8 or 9 and 9, 10 or 11 amino acids in length. An epitope that is capable of binding to an IT class HUA may be between 13, 14 or 15 and 15, 16 or 17 amino acids in length. Thus, the present disclosure includes, for example, a method of predicting whether a polypeptide is immunogenic for a relevant human subject population or cohort (eg, in a model population) or identifying a fragment of a polypeptide as immunogenic. for a relevant human subject population or cohort (eg, in a model population), wherein the method comprises the steps of (i) determining whether the polypeptide comprises: a. a sequence of between 7 and 11 consecutive amino acids that is capable of binding to at least two class I HUAs from the subject; ob. a sequence of between 13 and 17 consecutive amino acids that is capable of binding to at least two HLA class II of the subject; and (ii) predicting that the polypeptide is immunogenic for the subject if the polypeptide comprises at least one sequence that meets the requirements of step (i); predicting that the polypeptide is not immunogenic for the subject if the polypeptide does not comprise at least one sequence that meets the requirements of step (i); or identifying said consecutive sequence of amino acids as the sequence of a fragment of the polypeptide that is immunogenic for the subject. Using techniques known in the art it is possible to determine the epitopes that will bind to a known HLA. Any suitable method may be used, so long as the same method is used to determine multiple HLA-epitope binding pairs that are directly compared. For example, biochemical analysis can be used. It is also possible to use lists of epitopes known to bind via a given HLA. It is also possible to use predictive or modeling software to determine which epitopes can be bound by a given HLA. Examples are provided in Table 1. In some cases, a T cell epitope is capable of binding a given HLA if it has an IC50 or predicted IC50 of less than 5000 nM, less than 2000 nM, less than 1000 nM, or less than 500 nM. Table 1. Exemplary software to determine epitope-HLA binding. As provided herein, a presentation of T cell epitopes by multiple HLAs from an individual is generally needed to activate a T cell response. Accordingly, the methods of the disclosure comprise determining whether a polypeptide has a sequence that is a T cell epitope capable of binding to at least two HLA class I molecules or at least two HLA class II (PEPI2+) molecules from a human subject (eg, in a model human population). The best predictor of a cytotoxic T cell response to a given polypeptide is the presence of at least one T cell epitope presented by three or more HLA class I molecules from an individual (<1 PEPI3+). Accordingly, in some instances the method comprises determining whether a polypeptide has a sequence that is a T cell epitope capable of binding three HLA class I molecules from a specific human subject. In some instances, the method comprises determining whether a polypeptide has a sequence that is a T cell epitope capable of binding only three HLA class I from a human subject (eg, in a model human population). A T helper cell response can be predicted by the presence of at least one T cell epitope presented by three or more (<1 PEPI3+) or 4 or more (<1 PEPI4+) HLA class II in an individual. Thus, in some instances, the method comprises determining whether a polypeptide has a sequence that is a T-cell epitope capable of binding to at least three class II HLAs from a human subject (eg, in a human population). model). In other cases, the method comprises determining whether a polypeptide has a sequence that is an epitope of T cells capable of binding to at least four HLA class II from a human subject. In other cases, the method comprises determining whether a polypeptide has a sequence that is a T-cell epitope capable of binding only three and / or only four HLA class II from a human subject. In some instances, the disclosed methods and compositions can be used to predict whether a polypeptide / fragment will induce a cytotoxic T cell response and a helper T cell response in a human subject. The polypeptide / fragment comprises an amino acid sequence that is a T cell epitope capable of binding to multiple HLA class I molecules from the subject and an amino acid sequence that is a T cell epitope capable of binding to multiple HLA class I molecules from the subject. class II of the subject. HLA class I binding and HLA class II binding epitopes may completely or partially overlap. In some cases, such fragments of a polypeptide can be identified by screening for an amino acid sequence that is a T cell epitope capable of binding multiple (eg, at least two or at least three) HLA molecules from class I from the subject, and then analysis of one or more longer fragments of the polypeptide that extend at the N- and / or C-terminus to bind one or more or as many as possible (i.e., when there is no binding PEPI3+). to suitable HLA class II available) from HLA class II molecules from the subject or from a high percentage of subjects in a population. Such subjects may have two HLA alleles encoding the same HLA molecule (eg two copies for HLA-A*02:25 in case of homozygosity). The HLA molecules encoded by these alleles all bind to the same T cell epitopes. For the purposes of this description "binding to at least two HLA molecules from the subject", as used herein, includes to HLA molecules encoded by two identical HLA alleles in a single subject. In other words, "bind to at least two HLA molecules from the subject" and the like can be expressed otherwise as "bind to HLA molecules encoded by at least two alleles of HLA from the subject". polypeptide antigens As used herein, the term "polypeptide" refers to a full-length protein, a portion of a protein, or a peptide characterized as a chain of amino acids. As used herein, the term "peptide" refers to a short polypeptide comprising between 2, or 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 and 10, 11, 12, 13, 14, 15, 20, 25, 30, 35, 40, 45, or 50 amino acids. The terms "fragment" or "fragment of a polypeptide", as used herein, refer to an amino acid chain or amino acid sequence typically of reduced length relative to the reference polypeptide or a reference polypeptide and which it comprises, on the common part, an amino acid sequence identical to the reference polypeptide. Said fragment, according to the description, can be included, where appropriate, in a larger polypeptide of which it is a constituent. In some cases, the fragment may comprise the full length of the polypeptide, for example, where the entire polypeptide, such as a 9 amino acid peptide, is a single T cell epitope. In some cases, the polypeptide is or the polypeptide consists of all or part of an antigen that is expressed by a pathogenic organism (for example, a bacterium or a parasite), a virus, or a cancer cell, that is associated with a response or autoimmune disorder or a cell-associated disease, or that is an allergen or an ingredient in a medicament or pharmaceutical composition, such as an immunotherapy or vaccine composition. In some instances, the method of the disclosure comprises an initial step of identifying or selecting a suitable polypeptide, eg, a polypeptide as described further below. The polypeptide or antigen may be expressed in the cells or specifically in diseased cells of the specific or targeted human population (eg, a tumor-associated antigen, a polypeptide expressed by an intracellular virus, parasite, or bacteria, or the in vivo product of immunotherapy composition or vaccine) or acquired from the environment (eg, a food, an allergen, or a drug). The polypeptide or antigen may be present in a sample taken from a subject of the specific or targeted human population. HLA and polypeptide antigens can be precisely defined by nucleotide or amino acid sequences and sequenced using methods known in the art. The polypeptide or antigen may be a cancer or tumor associated antigen (TAA). TAAs are proteins expressed in cancer or tumor cells. The cancer or tumor cell may be present in a sample obtained from a subject of the specific or targeted human population. Examples of TAAs include novel antigens (neoantigens) expressed during tumorigenesis, products of oncogenes and tumor suppressor genes, overexpressed or aberrantly expressed cellular proteins (eg, HER2, MUC1), antigens produced by oncogenic viruses (eg. , EBV, HPV, HCV, HBV, HTLV), testicular cancer antigens (CTA)(eg, MAGE family, NY-ESO), and cell type-specific differentiation antigens (eg, MART- 1). TAA sequences can be found experimentally, in published scientific articles, or through publicly available databases, such as the database of the Ludwig Institute for Cancer Research (www.cta.lncc.br / ), Cancer Immunity Database (cancerimmunity.org / peptide / ), and TANTIGEN Tumor T-Lymphocyte Antigen Database (cvc.dfci.harvard .edu / tadb / ). In some cases, the polypeptide or antigen is not expressed or is minimally expressed in normal healthy cells and tissues, but is expressed (in those cells or tissues) in a high proportion of (with a high frequency in) subjects who have a disease or particular condition, such as a type of cancer or a cancer derived from a particular tissue or cell type, for example, breast cancer, ovarian cancer, or melanoma. An additional example is colorectal cancer. Other non-limiting examples of cancer include non-melanoma skin cancer, lung cancer, prostate cancer, kidney cancer, bladder cancer, stomach cancer, liver cancer, cervical cancer, esophagus cancer, non-Hodgkin's lymphoma, leukemia, pancreatic cancer, uterine, lip, oral cavity, thyroid, brain, nervous system, gallbladder, larynx, pharynx, myeloma, nasopharyngeal cancer, Hodgkin's lymphoma, testicular cancer, and Kaposi's sarcoma. Alternatively, the polypeptide may be expressed at low levels in normal healthy cells, but at high levels (overexpressed) in diseased (eg, cancer) cells or in subjects having the disease or condition. In some cases, the polypeptide is expressed at, or expressed at, a high level relative to normal healthy subjects or cells in at least 2%, 5%, 10%, 15%, 20%, 25 %, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or more of such individuals, or of a human subpopulation corresponding to the target or model subject or population. For example, the population may be matched to the subject by ethnicity, geographic location, gender, age, disease, stage or type of disease, genotype, or expression of one or more biomarkers. In some cases, expression frequencies can be determined from scientific literature and published figures. In some cases, the method of the description comprises a step of identification or selection of said polypeptide. In some cases, the polypeptide is associated with or highly (over)expressed in cancer cells or solid tumors. Exemplary cancers include carcinomas, sarcomas, lymphomas, leukemias, germ cell tumors, or blastomas. The cancer may or may not be a hormone-dependent or hormone-related cancer (eg, an estrogen- or androgen-related cancer). The tumor can be malignant or benign. The cancer may or may not be metastatic. In some cases, the polypeptide is a testicular cancer antigen (CTA). CTAs are not normally expressed beyond embryonic development in healthy cells. In healthy adults, CTA expression is limited to male germ cells that do not express HLA and cannot present antigens to T cells. Therefore, CTAs are considered expressing neoantigens when expressed on cancer cells. CTA expression is (i) specific for tumor cells, (ii) more frequent in metastases than in primary tumors, and (iii) is conserved between metastases from the same patient (Gajewski ed. Targeted Therapeutics in Melanoma. Springer, New York. 2012 ). The polypeptide may be a mutational neoantigen, which is expressed by a cell, eg, a cancer cell, of the individual, but altered from the analogous protein in a normal or healthy cell. In some instances, the methods of the disclosure comprise the step of identifying a polypeptide that is a mutational neoantigen or that is a mutational neoantigen in the specific human subject, or of identifying a neoepitope. For example, the neoantigen may be present in a sample obtained from the subject. Mutational neoepitopes or neoantigens can be used to target disease-associated cells, eg, cancer cells, that express the neoantigen or a neoantigen comprising the neoepitope. Mutations in a polypeptide expressed by a cell, eg, a cell in a sample taken from a subject, can be detected, for example, by sequencing, but most do not induce an immune response against cells expressing neoantigens. Currently, the identification of mutational neoantigens that do induce an immune response is based on the prediction of HLA-restricted mutational epitopes and also the in vitro evaluation of the immunogenicity of the predicted epitopes in the individual's blood sample. This process is inaccurate, long and expensive. Identification of mutational epitopes (eg, neoepitopes) that bind to multiple HLA molecules reproducibly defines the immunogenicity of mutational neoantigens. Thus, in some instances according to the disclosure, the polypeptide is a mutational neoantigen and the immunogenic fragment of the polypeptide comprises a neoantigen-specific mutation (or consists of a neoepitope). The polypeptide may be an intracellularly expressed viral protein. Examples include HPV16 E6, E7; HIV Tat, Rcv, Gag, Pol, Env; HTLV-Tax, Rcx, Gag, Env, human herpes virus proteins, dengue virus proteins. The polypeptide may be an intracellularly expressed parasite protein, eg malarial proteins. The polypeptide may be an active ingredient of a pharmaceutical composition, such as a vaccine or immunotherapy composition, optionally a candidate active ingredient for a novel pharmaceutical composition. The term "active ingredient", as used herein, refers to a polypeptide that is intended to induce an immune response and may include a polypeptide product of a vaccine or immunotherapy composition produced in vivo after administration to a subject. . For a DNA or RNA immunotherapy composition, the polypeptide may be produced in vivo by the cells of a subject to whom the composition is administered. For a cell-based composition, the polypeptide may be processed and / or presented by cells of the composition, eg, autologous dendritic cells or antigen presenting cells pulsed with the polypeptide or comprising an expression construct encoding the polypeptide. The pharmaceutical composition may comprise a polynucleotide or a cell encoding one or more polypeptides of the active ingredient. In other cases, the polypeptide may be a target polypeptide antigen of a pharmaceutical composition, a vaccine, or immunotherapy. A polypeptide is a target polypeptide antigen if the composition is designed to induce an immune response (eg, a cytotoxic T-lymphocyte response) that is directed at the polypeptide. A target polypeptide antigen is typically a polypeptide that is expressed by a pathogenic organism, a virus, or a diseased cell such as a cancer cell. A target polypeptide antigen may be a TAA or a CTA. Currently, >200 clinical trials are investigating cancer vaccines with tumor antigens. The polypeptide may be an allergen that enters an individual's body, for example, via the skin, lungs, or oral routes. Some non-limiting examples of suitable polypeptides include those listed in one or more of Tables 2 to 6. Genetic sequences can be obtained by sequencing biological materials. Sequencing can be performed by any suitable method that determines DNA and / or RNA and / or amino acid sequences. The description uses HLA genotypes and amino acid sequences. However, methods for identifying the HLA genotype of an individual's genetic sequences and methods for obtaining amino acid sequences derived from DNA or RNA sequence data are not the subject of the disclosure. Prediction of an individual's immune response to a polypeptide antigen Specific polypeptide antigens induce immune responses in only a fraction of human subjects. Currently, there is no diagnostic test that can predict whether a polypeptide antigen is likely to induce an immune response in an individual. In particular, there is a need for a test that can predict whether a person is an immune responder to an immunotherapy or vaccine composition. In accordance with the present disclosure, the polypeptide antigen-specific T cell response of an individual is defined by the presence within the polypeptide of one or more fragments that can be presented through multiple HLA class I molecules or multiple HLA class II molecules of the individual. In some instances, the disclosure involves a method of predicting whether a subject will have an immune response to administration of a polypeptide, wherein an immune response is predicted if the polypeptide is immunogenic according to any method described herein. A cytotoxic T cell response is predicted if the polypeptide comprises at least one amino acid sequence that is a T cell epitope capable of binding to at least two HLA class I molecules from the subject. A T helper cell response is predicted if the polypeptide comprises at least one amino acid sequence that is a T cell epitope capable of binding to at least two HLA class II molecules from the subject. No cytotoxic T cell response is predicted if the polypeptide does not comprise any amino acid sequence that is a T cell epitope capable of binding to at least two HLA class I molecules from the subject. No helper T cell response is predicted if the polypeptide does not comprise any amino acid sequence that is a T cell epitope capable of binding to at least two HLA class II molecules from the subject. In some cases, the polypeptide is an active component of a pharmaceutical composition, and the method comprises predicting the development or production of anti-drug antibodies (ADA) to the polypeptide. The pharmaceutical composition may be a drug selected from those listed in Table 8. According to the present description, the development of ADA will occur if, or to the extent that, an active component polypeptide is recognized by multiple HLA molecules. class II from the subject, generating a T helper cell response to support an antibody response to the active ingredient. The presence of said epitopes (PEPI) can predict the development of ADA in the subject. The method may further comprise selecting or recommending for treatment of the human subject administering to the subject a pharmaceutical composition predicted to induce little or no ADA, and optionally further administering the composition to the subject. In other cases, the method predicts that the pharmaceutical composition will induce unacceptable ADA, and the method further comprises selecting, recommending, or treating the subject with a different treatment or therapy. The polypeptide may be a checkpoint inhibitor. The method may comprise predicting whether the subject will respond to treatment with the checkpoint inhibitor. Table 8 - Exemplary drugs associated with ADA-related adverse events There is also currently no test that can predict the likelihood that a person will have a clinical response to, or derive clinical benefit from, an immunotherapy or vaccine composition. This is important because currently measured T cell responses in a cohort of individuals participating in immunotherapy or vaccine clinical trials correlate poorly with clinical responses. That is, the clinical responder subpopulation is substantially smaller than the immune responder subpopulation. Therefore, to allow for the personalization of vaccines and immunotherapies, it is important to predict not only the likelihood of an immune response in a specific subject, but also whether the drug-induced immune response will be clinically effective (eg, whether it can destroy cancer cells, cells infected with pathogens or pathogens). The presence in an immunotherapy or vaccine composition of at least two polypeptide fragments (epitopes) that can bind to at least three HLA class I from an individual (<2 ΡΕΡΙ3+) predicts a clinical response. In other words, if <2 PEPI3+ can be identified within the active ingredient polypeptides of an immunotherapy or vaccine composition, an individual is likely to be a clinical responder. A "clinical response" or "clinical benefit" as used herein may be the prevention or delay in onset of a disease or condition, the improvement of one or more symptoms, the induction or prolongation of remission, or the delay of a relapse, recurrence or deterioration, or any other improvement or stabilization of a subject's disease state. Where appropriate, a "clinical response" may correlate with "disease control" or an "objective response" as defined by the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines. In some cases, the description involves a method of predicting whether the subject will have a clinical response to the administration of a pharmaceutical composition such as an immunotherapy or vaccine composition comprising one or more polypeptides as active ingredients. The method may comprise determining whether the polypeptide(s) together comprise at least two different sequences, each of which is a T cell epitope capable of binding to at least two, or in some cases at least three, HLA-class molecules. I of the subject; and predicting that the subject will have a clinical response to administration of the pharmaceutical composition if the polypeptide(s) together comprise at least two different sequences, each of which is a T cell epitope capable of binding to at least two, or in some cases three, HLA class I molecules from the subject; or that the subject will not have a clinical response to administration of the pharmaceutical composition if the polypeptide(s) together do not comprise more than one sequence that is a T cell epitope capable of binding to at least two, or in some cases three, molecules of HLA class I of the subject. For the purposes of this method, two T cell epitopes are "different" from each other if they have different sequences, and in some cases also if they have the same repeating sequence in a target polypeptide antigen. In some cases, different T cell epitopes on a target polypeptide antigen do not overlap with each other. In some cases, all fragments of one or more polypeptides or polypeptides of the active ingredient that are immunogenic to a human subject are identified using the methods described herein. Identification of at least one fragment of the polypeptides that is a T cell epitope capable of binding to at least two or at least three HLA class I molecules from the subject predicts that the polypeptides will or is likely to elicit a T cell response. T cytotoxic in the subject. Identification of at least one fragment of the polypeptides that is a T-cell epitope capable of binding to at least two, at least three, or at least four HLA class II molecules from the subject predicts that the polypeptides will or is likely to cause a T helper cell response in the subject. Identification of any fragment of the polypeptides that is a T-cell epitope capable of binding to at least two or at least three HLA class I molecules from the subject predicts that the polypeptides will not or likely will not elicit a T cell response. T cytotoxic in the subject. Identification of any fragment of the polypeptides that is a T-cell epitope capable of binding to at least two, at least three, or at least four HLA class II molecules from the subject predicts that the polypeptides will not or likely will not cause a T helper cell response in the subject. The identification of at least two fragments of one or more polypeptides of the active ingredient of an immunotherapy or vaccine composition, where each fragment is a T cell epitope capable of binding to at least two or at least three HLA class I molecules of the subject predicts that the subject is more likely to have, or will have, a clinical response the composition. Identification of fewer than two fragments of one or more polypeptides that are T cell epitopes capable of binding to at least two or at least three HLA class I molecules from the subject predicts that the subject is less likely to have, or will not have, , a clinical response to the composition. Without wishing to be bound by theory, one reason for the increased likelihood of clinical benefit from a vaccine / immunotherapy comprising at least two multi-HLA-binding PEPIs is that diseased cell populations, such as cancer or tumor cells or cells infected by viruses or pathogens such as HIV, are usually heterogeneous both within and between affected subjects. A specific cancer patient, for example, may or may not express or overexpress a particular cancer-associated target polypeptide antigen of a vaccine or their cancer may comprise heterogeneous cell populations, some of which (over)express the antigen and some of which of which not. Furthermore, the likelihood of developing resistance decreases when a vaccine / immunotherapy includes or targets more multi-HLA binding PEPIs because the patient is less likely to develop resistance to the composition through mutation of the targeted PEPIs. The probability that a subject will respond to treatment is therefore increased by (i) the presence of more multi-HLA binding PEPI in the active ingredient polypeptides; (ii) the presence of PEPI on more target polypeptide antigens; and (iii) the (over)expression of the target polypeptide antigens in the subject or in diseased cells of the subject. In some cases, the expression of the target polypeptide antigens in the subject may be known, for example, if there are target polypeptide antigens in a sample obtained from the subject. In other cases, the probability that a specific subject, or diseased cells from a specific subject, will (over)express a specific target polypeptide antigen or any combination of target polypeptide antigens can be determined using population expression frequency data. The population expression frequency data may refer to a population corresponding to the subject and / or the disease or the intention-to-treat population. For example, the frequency or probability of expression of a particular cancer-associated antigen in a particular cancer or subject having a particular cancer, eg, breast cancer, can be determined by detecting the antigen in the tumor, eg, breast cancer. eg, breast cancer tumor samples. In some cases, such expression frequencies can be determined from scientific publications and published figures. In some cases, a method of the invention comprises a step of determining the frequency of expression of a relevant target polypeptide antigen in a relevant population. A series of pharmacodynamic biomarkers are described to predict the activity / effect of vaccines in individual human subjects as well as in populations of human subjects. The biomarkers were developed specifically for cancer vaccines, but similar biomarkers can be used for other immunotherapy compositions or vaccines. These biomarkers facilitate more efficient vaccine development and also lower the cost of development, and can be used to evaluate and compare different compositions. The following are exemplary biomarkers. • AG95 - Potency of a Vaccine: The amount of antigens in a cancer vaccine that a specific tumor type expresses with a 95% probability. AG95 is an indicator of vaccine potency and is independent of the immunogenicity of the vaccine antigens. AG95 is calculated from tumor antigen expression rate data. Such data can be obtained from experiments published in peer-reviewed scientific journals. Technically, AG95 is determined from the binomial distribution of antigens in the vaccine, and considers all possible variations and expression rates.• PEPI3+ count - immunogenicity of a vaccine in a subject: vaccine-derived PEPI3+ are personal epitopes that are they bind to at least 3 HLAs in a subject and induce T cell responses. PEPI3+ can be determined using the PEPI3+ test in subjects whose full 4-digit HLA genotype is known. • PA count - antigenicity of a vaccine in a subject: amount of PEPI3+ vaccine antigens. Vaccines contain target polypeptide antigen sequences expressed by diseased cells. The PA count is the number of antigens in the vaccine that contain PEPI3+, and the PA count represents the number of antigens in the vaccine that can induce T cell responses in a subject. The AP count characterizes the subject's vaccine antigen-specific T cell responses as it depends only on the subject's HLA genotype and is independent of the subject's disease, age, and medication. The correct value is between 0 (no PEPI presented by the antigen) and the maximum amount of antigens (all antigens present PEPI).• AP50 - antigenicity of a vaccine in a population: The average amount of vaccine antigens with a PEPI in a population. The AP50 is suitable for the characterization of vaccine antigen-specific T cell responses in a given population as it is dependent on the HLA genotype of subjects in a population.• AGP count - efficacy of a vaccine in a subject: amount of tumor-expressed vaccine antigens with PEPI. The AGP count indicates the amount of tumor antigens that the vaccine recognizes and induces a T-lymphocyte response against them (achieves the target). The AGP count depends on the rate of expression of the vaccinia antigen in the subject's tumor and the subject's HLA genotype. The correct value is between 0 (no PEPI presented by the expressed antigen) and the maximum number of antigens (all antigens are expressed and present a PEPI).• AGP50 - efficacy of a cancer vaccine in a population: the amount Mean number of vaccine antigens expressed in PEPI-indicated tumor (ie, AGP) in a population. The AGP50 indicates the mean amount of tumor antigens that can be recognized by vaccine-induced T cell responses. AGP50 depends on the expression rate of the antigens in the indicated tumor type and the immunogenicity of the antigens in the target population. AGP50 can estimate vaccine efficacy in different populations and can be used to compare different vaccines in the same population. The calculation of AGP50 is similar to that used for AG50, except that the expression is weighted by the appearance of PEPI3+ in the subject on the expressed vaccine antigens. In a theoretical population, where each subject has a PEPI of each vaccine antigen, the AGP50 will be equal to AG50. In another theoretical population, where no subject has a PEPI from any vaccine antigen, the AGP50 will be 0. In general, the following statement is valid: 0 > AGP50 > AG50.• mAGP - a candidate biomarker for the selection of potential responders: the probability that a cancer vaccine will induce T cell responses against multiple antigens expressed in the indicated tumor. mAGP is calculated from the expression rates of vaccinia antigens in e.g. eg, the tumor and the presence of vaccine-derived PEPI in the subject. Technically, based on the AGP distribution, the mAGP is the sum of the probabilities of the multiple AGPs (<2 AGPs). The results of a prediction as stated above can be used to inform a physician's decisions regarding treatment of the subject. Therefore, in some cases the polypeptide is an active ingredient, for example, of a vaccine or immunotherapy composition, the method of the disclosure predicts that the subject will have, is likely to have, or has a minimal probability above a threshold of having an immune response and / or a clinical response to a treatment comprising administering the active ingredient polypeptide to the subject, and the method further comprises selecting the treatment or selecting the immunotherapy or vaccine composition for treating the specific human subject. Also provided is a method of treatment with a subject-specific pharmaceutical composition, kit, or panel of polypeptides comprising one or more polypeptides as active ingredients, wherein the pharmaceutical composition, kit, or panel of polypeptides has been determined to have a likely minimum threshold of inducing a clinical response in the subject, wherein the probability of response was determined using a method described herein. In some cases, the trough threshold is defined by one or more of the pharmacodynamic biomarkers described herein, for example, a trough PEPI3+ count (eg, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 or more PEPI3+), a minimum AGP count (for example, AGP = at least 2 or at least 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 or more), and / or a minimum mAGP (eg, AGP = at least 2 or at least 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12 or more). For example, in some cases a subject is selected for treatment if his or her probability of a response directed to a predefined number of target polypeptide antigens, optionally where target polypeptide antigens are (predicted) to be expressed, is greater than a predetermined threshold (eg, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 or more). Alternatively, the method may predict that the polypeptide(s) in the composition will not elicit a T cell response and / or a clinical response in the subject and further comprises selecting a different treatment for the subject. Prediction of an autoimmune or toxic immune response to a polypeptide antigen Differences between HLAs can influence the likelihood that a subject will experience immune toxicity from a drug or polypeptide administered to the subject. A toxic immune response may be present if a polypeptide administered to the subject comprises a fragment that corresponds to a fragment of an antigen expressed on normal healthy cells of the subject and that comprises an amino acid that is a T cell epitope capable of binding to multiple HLA molecules. of class I of the subject. Thus, some instances according to the disclosure involve identifying a toxic immunogenic region or fragment of a polypeptide or identifying subjects who may experience immune toxicity in response to administration of one or more polypeptides or fragments thereof. The polypeptide can be an active ingredient of a vaccine or immunotherapy composition as described herein. The method may comprise determining whether the polypeptides comprise a sequence that is a T cell epitope capable of binding to at least two, or in other cases at least three, HLA class I molecules from the subject. In some cases, the method comprises determining that the polypeptide comprises a sequence that is a T cell epitope capable of binding to at least four or at least five HLA class I molecules from the subject; or an amino acid sequence that is a T cell epitope capable of binding to at least four, at least five, at least six, or at least seven class II HLAs from the subject. The method may further comprise identifying said sequence as immunogenic toxic to the subject or predicting a toxic immune response in the subject. In other cases, none of said amino acid sequences are identified and the method further comprises predicting any toxic immune response in the subject. The method may further comprise selecting or recommending for treatment of the subject the administration of one or more polypeptides or a pharmaceutical composition that is predicted to induce little or no immune toxicity, and optionally further treating the subject by administering the polypeptide. The disclosure also provides a method of treating a subject in need thereof by administering said polypeptide or composition to the subject. In some instances, a method described herein further comprises mutating a polypeptide predicted to be immunogenic for a subject, or predicted to be immunogenic in a proportion of subjects in a human population. Also provided is a method of reducing the immunogenicity of a polypeptide that has been identified as immunogenic in a subject or in a proportion of a human population as described herein. The polypeptide can be mutated to reduce the amount of PEPI in the polypeptide or to reduce the amount of HLA class I or class II molecules from the subject or said population that bind to the fragment of the polypeptide identified as being immunogenic in the subject or in a proportion of that population. In some cases, the mutation may reduce or prevent a toxic immune response or may increase efficacy by preventing the development of ADA in the subject or in a proportion of that population. The mutated polypeptide may further be selected or recommended for treatment of the subject or a subject of said population. The subject may be further treated by administration of the mutated polypeptide. The disclosure also provides a method of treating a subject in need thereof by administering said mutated polypeptide to the subject. Predicting the Immune Response of a Human Population to a Polypeptide Antigen The methods described herein can be used to predict the response or response rate of a broader human population to the administration of one or more polypeptides or compositions comprising one. or more polypeptides. In some cases, a method of the description can be repeated for multiple human subjects to predict the response or response rate in those subjects. In other cases, the description method can be repeated for each subject in a relevant sample or model population of subjects, and the results can be used to predict or define the response or response rate in a larger human population represented by the sample. or model population. The sample / model population may be relevant to the intention-to-treat population for a pharmaceutical composition. A relevant population is one that is representative of or similar to the population for which treatment with the pharmaceutical composition is intended or among which treatment is intended. In some cases, the sample / model population is representative of the entire human race. In other cases, the model sample / population may be matched by disease or subject to the broader population (subpopulation), for example, by ethnicity, geographic location, gender, age, disease or cancer, disease stage or type or cancer, genotype, expression of one or more biomarkers, partially by HLA genotype (eg, subjects having one or more particular HLA alleles). For example, the sample / model population may have HLA class I and / or class II genomes that are representative of those found in the world population, or in subjects who have a particular disease, condition, or ethnic background from a geographic location. or who have a biomarker associated with the particular disease (for example, women who have the BRCA mutation for a breast cancer vaccine). In some cases, the sample / model population is representative of at least 70%, 75%, 80%, 84%, 85%, 86%, 90% or 95% of the broader population by HLA diversity and / or HLA frequency. The method may comprise the step of selecting or defining a relevant sample or model population. Each subject in the sample / model population is minimally defined by their HLA class I or class II genotype, e.g. eg, complete 4-digit HLA class I genotype. The data on the HLA genotype of the sample / model population may be stored, recorded or retrieved from a database or may be an in silico model human population. In some cases, the methods described herein can be used to conduct an in silico clinical trial that predicts the proportion of immune responders or the proportion of clinical responders in a population for a given drug, such as an immunotherapy composition or vaccine. This is useful for preselecting drugs that are likely to have high efficacy rates for clinical trials. A population of individuals or a subpopulation of individuals may comprise the study cohort of an in silico clinical trial of a drug. Each individual in the study cohort is characterized by their HLA genotype. The proportion of individuals in the study cohort who have <1 PEPI2+, <1 PEPI3+, <1 PEPI4+, or <1 PEPI5+ derived from the drug polypeptides can be calculated. For the purposes of this description, this has been referred to as the "PEPI Score". Unless otherwise stated, "PEPI score" refers specifically to PEPI3+ score <1. This PEPI score predicts the proportion of subjects with T cell responses in a clinical trial conducted with the same drug in a relevant cohort of subjects. The disclosure provides a method of conducting an in silico assay for a vaccine or immunotherapy composition having one or more active polypeptide ingredients. The in silico assay can predict the cytotoxic T cell response rate of a human population. The method may comprise: (i) selecting or defining an in silico model human population comprising multiple subjects, each defined by HLA class I genotype, wherein the in silico model human population may correspond or be representative or relevant to intent-to-treat, said human population in which the cytotoxic T-lymphocyte response rate is predicted; (ii) determining for each subject in the in silico model human population whether the active ingredient polypeptide(s) comprise at least one sequence that is PEPI2+, PEPI3+, PEPI4+, or PEPI5+ (depending on the size, route of administration, and adjuvants of the polypeptide composition); and (iii) predicting the cytotoxic T lymphocyte response rate (of said human population), wherein a higher proportion of the in silico model human population meeting the requirements of step (ii) predicts a higher lymphocyte response rate. T cytotoxic. The proportion of the in silico model human population meeting the requirements of step (ii) can be correlated with, or correspond to, the predicted response rate in the intention-to-treat population. The correlation between the presence of HLA-restricted epitopes and immune response rates and / or clinical response rates has not been demonstrated with prior art clinical trials. This raises the question about the mechanism of action of immunotherapies. The examples provided herein show that activation of cytotoxic T lymphocytes (CTLs) against multiple targets may be required for a clinically meaningful response, eg, against heterogeneous tumors. So far, the CTL responses reported in clinical trials do not represent multiple targets or multiple HLAs. For example, a melanoma peptide vaccine targeting two antigens (tyrosinase and gplOO) elicited CTL responses in 52% of patients, but only 12% had clinical benefit. Using an in silico model population of 433 subjects, a PEPI3+ score <1 of 42% was determined (in 42% at least one vaccine-derived epitope could be identified that could be presented by at least three HLA class I from the subject). ) and a PEPI3+ score <2 of 6% (in 6% at least two vaccine-derived epitopes could be identified that could be presented by at least three HLA class II from the subject). This explains why the clinical investigators found no correlation between CTL response rate and clinical response in their trial: the peptides in the vaccine performed poorly in the trial because there were only a few patients where two different peptides from the vaccine were able to activate CTL responses. The discrepancy between the results of the clinical trial and our in silico trial is based on the different populations, since the populations of each of them had subjects with different HLA genotypes. However, the response rate results provided by the in silico assay in the model population are a good predictor of the response rate result in the clinical trial population. Thus, a method of performing an in silico assay for an immunotherapy or vaccine composition having one or more active ingredient polypeptides is described herein. The in silico assay can predict the clinical response rate of a human population. The method may comprise (i) selecting or defining an in silico model human population comprising multiple subjects defined by HLA class I genotype, wherein the in silico model human population may correspond to or be representative of said human population (relevant to the intention-to-treat population) in which the clinical response rate is predicted; (ii) determining for each subject in the in silico model human population whether the active ingredient polypeptide(s) comprise at least two different sequences, each of which is a T cell epitope capable of binding to at least three, at least four or at least five HLA class I from the subject; and (iii) predicting the clinical response rate (of said human population), wherein a higher proportion of the in silico model human population meeting the requirements of step (ii) predicts a higher clinical response rate. The proportion of the in silico model human population meeting the requirements of step (ii) can be correlated with, or correspond to, the predicted response rate in the intention-to-treat population. An equivalent method can be used to predict, for example, the immune toxicity rate, checkpoint inhibitor response rate, ADA development rate, or T helper cell response rate of a human population (or subpopulation) to the administration of a polypeptide or pharmaceutical composition comprising one or more polypeptides as active ingredients. In some cases, the method may be repeated for one or more additional polypeptides or fragments thereof or pharmaceutical, immunotherapy or vaccine compositions. Polypeptides, fragments or compositions can be classified according to their predicted response rates in said human population. This method is useful for selecting the most effective and safest polypeptide drugs for the intention-to-treat population. Design and preparation of pharmaceutical compositions In some aspects, the disclosure provides a method of designing or preparing a polypeptide, or a polynucleic acid encoding a polypeptide, for inducing an immune response, cytotoxic T-cell response, or helper T-cell response in a human subject ( eg, in an intention-to-treat or target population). The description also provides an immunogenic composition or pharmaceutical composition, a kit or panel of peptides, methods of designing and preparing the same, compositions obtainable by these methods and their use in a method of inducing an immune response, a cytotoxic T-lymphocyte response or a helper T-lymphocyte response in the subject, or a method of treating, vaccinating, or providing immunotherapy to a subject. The methods involve identifying and / or selecting a T cell epitope that binds to multiple, e.g. eg, at least three, HLA class I molecules from individual subjects across the target population at a high frequency, and designing and / or preparing a polypeptide comprising one or more of said epitopes (PEPI3+). Such high-frequency population PEPI3+ are referred to herein as "better EPI". According to the present disclosure, the best EPIs induce immune responses in a high proportion of human subjects in the specific or targeted human population. The polypeptide may be an active ingredient in a pharmaceutical composition, kit, or panel of polypeptides for use in a method of treating a subject of the specific or target human population. The composition / kit may optionally further comprise at least one pharmaceutically acceptable diluent, carrier or preservative and / or additional polypeptides not comprising any better EPI. The polypeptides may be of non-natural origin or genetically modified. The kit may comprise one or more separate containers, each containing one or more of the active ingredient peptides. The composition / kit may be a personalized medicament to prevent, diagnose, alleviate, treat or cure an individual's disease, such as cancer. In some cases, the best EPI is capable of binding multiple, eg, at least three HLA class I molecules and / or at least three HLA class II molecules from a high percentage of subjects in a sample or population. model, as described herein. In some cases, a "high" percentage can be at least or more than 1%, 2%, 5%, 10%, 12%, 15%, 16%, 17%, 18% , 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43% , 44%, 45%, 46%, 47%, 48%, 49%, or 50% of the relevant human subject population or subpopulation. In some cases, a "high" percentage is relative to the percentage of subjects in the population who have other PEPI3+. For example, PEPI3+ may be the most common in the population, or more common than 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 97% or 99% of all PEPI3+, PEPI4+ and / or PEPI4+ in one or more reference target polypeptide antigens. In some cases, the probability that the target polypeptide antigen will be expressed in a subject from the specific or target population is considered to determine the overall probability that the best EPI will induce an immune response directed at a polypeptide antigen expressed by a subject from that population. the specific or target human population. In some cases, the bestEPI is predicted to express the relevant target polypeptide antigen and multiple, for example, at least three HLA class I molecules or at least three HLA class II molecules capable of binding the bestEPI in at least or more than 1%, 2%, 5%, 10%, 12%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 32%, 33%, 34% , 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%, 45%, 46%, 47%, 48%, 49%, or 50% of the relevant human subject population. In some cases, multiple T cell / PEPI3+ epitopes, optionally from one or more target polypeptide antigens, can be classified by the percentage of subjects in the model or intent-to-treat population who have multiple, e.g., at least three molecules. HLA class I or at least three HLA class II molecules capable of binding to each fragment; or by the percentage of subjects in the model or intent-to-treat population predicted to express the target polypeptide antigen comprising the fragment and multiple, for example, at least three HLA class I molecules or at least three HLA class I molecules. HLA class II capable of binding to the fragments. The peptide or composition can be designed to comprise one or more PEPI3+ selected based on their classification. Typically, each bestEPI is a fragment of a target polypeptide antigen, and polypeptides comprising one or more of the bestEPIs are the target polypeptide antigens for treatment, vaccination, or immunotherapy. The method may comprise the step of identifying one or more suitable target polypeptide antigens. Typically, each target polypeptide antigen will be associated with the same disease or condition, pathogenic organism, group of pathogenic organisms, virus, or type of cancer. The composition, kit or panel may comprise or the method may comprise selecting for each best EPI a sequence of up to 50, 45, 40, 35, 30, 25, 20, 19, 18, 17, 16, 15, 14, 13, 12 , 11, 10, or 9 consecutive amino acids of the target polypeptide antigen, such as a polypeptide described herein, where these consecutive amino acids comprise the best EPI amino acid sequence. In some cases, the amino acid sequence is flanked at the N- and / or C-terminus by additional amino acids that are not part of the consecutive sequence of the target polypeptide antigen. In some cases, the sequence is flanked by up to 41, 35, 30, 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 additional amino acid at the N-terminus and / or C or between the target polypeptide fragments. In other cases, each polypeptide consists of a fragment of a target polypeptide antigen or consists of two or more such fragments arranged end-to-end (arranged sequentially in the peptide end-to-end) or overlapping in a single peptide (where two or more of the fragments comprise partially overlapping sequences, eg, where two best EPIs in the same polypeptide are 50 amino acids apart). When fragments of different polypeptides or different regions of the same polypeptide are brought together in a genetically modified peptide, there is a possibility that neo-epitopes will be generated around the junction. Such neoepitopes encompass at least one amino acid of each fragment on both sides of the junction, and may be referred to herein as linker amino acid sequences. Neoepitopes can induce unwanted T cell responses against healthy cells (autoimmunity). Peptides can be designed, or polypeptides tested, to avoid, eliminate, or minimize neoepitopes that correspond to a fragment of a protein expressed in normal healthy human cells and / or neoepitopes that are capable of binding to at least two, in some cases at least three or at least four HLA class I molecules from the subject, or in some cases at least two, at least three, four or five HLA class II molecules from the subject. In some cases, the peptide is designed, or the polypeptide is tested, to eliminate polypeptides having a binding neoepitope that is capable of binding in more than a threshold percentage of human subjects in a specific, target, or model population to at least two HLA class I molecules expressed by individual subjects in the population. In some cases, the threshold is 30%, 20%, 15%, 10%, 5%, 2%, 1%, or 0.5% of that population. The methods of the disclosure can be used to identify or analyze such neoepitopes as described herein. Alignment can be determined using known methods, such as BLAST algorithms. Software for performing BLAST analysis is publicly available through the National Center for Biotechnology Information (http: / / www.ncbi.nlm.nih.gov / ). The at least two best EPIs of the polypeptides in the composition may target a single antigen (eg, a polypeptide vaccine comprising two multi-HLA binding PEPIs derived from a single antigen, eg, a tumor-associated antigen , vaccine / immunotargeting) or may target different antigens (eg, a polypeptide vaccine comprising a multi-HLA-binding PEPI derived from an antigen, eg, a tumor-associated antigen, and a second multi-HLA binding PEPI derived from a different antigen, eg, a different tumor-associated antigen, both targets of the vaccine / immunotherapy). In some cases, the active ingredient polypeptides together comprise, or the method comprises, a total of or at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 , 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39 or 40 or more better PPE different. The best EPIs can be fragments of one or more different target polypeptide antigens. By identifying specific fragments of each target polypeptide antigen that are immunogenic for a high proportion of subjects in a target population, it is possible to incorporate multiple such fragments, optionally from multiple different target polypeptide antigens, into a single or multiple active ingredient polypeptides. active ingredient polypeptides intended for use in combination or to maximize the number of T cell clones that can be activated by one or more polypeptides of a given length. Currently, most immunotherapy and vaccine compositions target only a single polypeptide antigen. However, in accordance with the present disclosure, it is in some instances beneficial to provide a pharmaceutical composition or active ingredient polypeptide targeted to two or more different polypeptide antigens. For example, most cancers or tumors are heterogeneous, meaning that cancer or tumor cells from a subject (over)express different antigens. Tumor cells from different cancer patients also express different combinations of tumor-associated antigens. The cancer immunogenic compositions that are most likely to be effective are those that target multiple antigens expressed by the tumor, and thus more cancer or tumor cells, in an individual human subject or in a population. The beneficial effect of combining multiple best EPIs in a single treatment (administration of one or more pharmaceutical compositions that together comprise multiple EPIs) can be illustrated by the personalized vaccine polypeptides described in Examples 15 and 16 below. Exemplary CTA expression probabilities in ovarian cancer are as follows: BAGE: 30%; MAGE A9: 37%; MAGE A4: 34%; MAGE A10: 52%. If patient XYZ were treated with a vaccine comprising PEPI only in BAGE and MAGE A9, the probability of having a mAGP (multiple antigens expressed with PEPI) would be 11%. If patient XYZ were treated with a vaccine comprising only PEPI for the MAGE A4 and MAGE A10 CTAs, the probability of having a multiAGP would be 19%. However, if a vaccine contains all 4 of these CTAs (BAGE, MAGE A9, MAGE A4, and MAGE A10), the probability of having a mGP would be 50%. In other words, the effect would be greater than the combined mAGP odds for both treatments with two PEPIs (mGP odds for BAGE / MAGE + mAGP odds for MAGE A4 and MAGE A10). Patient XYZ's PIT vaccine described in Example 15 contains an additional 9 PEPIs and thus the probability of having a mAGP is greater than 99.95%. Likewise, the probabilities of exemplary CTA expression in breast cancer are as follows: MAGE C2: 21%; MAGE Al: 37%; SPC1: 38%; MAGE A9: 44%. Treatment of patient ABC with a vaccine comprising PEPI alone in MAGE C2: 21% and MAGE Al has a probability of mAGP of 7%. Treatment of patient ABC with a vaccine comprising PEPI only in SPC1: 38%; MAGE A9 has a mAGP probability of 11%. Treatment of patient ABC with a vaccine comprising PEPI in MAGE C2: 21%; MAGE Al: 37%; SPC1: 38%; MAGE A9 has a mGP probability of 44% (44 > 7 + 11). Patient ABC's PIT vaccine described in Example 16 contains an additional 8 PEPIs and therefore the probability of having a mAGP is greater than 99.93%. Accordingly, in some cases the best EPIs of the active ingredient polypeptides are from two or more different target polypeptide antigens, eg, different antigens associated with a specific disease or condition, eg, different cancer or tumor-associated antigens or antigens. expressed by a target pathogen. In some cases, the PEPIs are from a total of or at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, or 40 or more different target polypeptide antigens. The different target polypeptide antigens can be any different polypeptides that are useful to target or can be selectively addressed with different PEPI3+. In some cases, the different target polypeptide antigens are non-homologous or non-paralogous or have less than 95%, 90%, 85%, 80%, 75%, 70%, 60%, or 50% sequence identity throughout the full length of each polypeptide. In some cases, the different polypeptides are the ones that do not share any PEPI3+. Alternatively, in some cases the PEPI3+ are from different target polypeptide antigens when they are not shared with other polypeptide antigens that are targeted by the active ingredient polypeptides. In some cases, one or more or each of the immunogenic polypeptide fragments is from a polypeptide that is present in a sample taken from a human subject (eg, from the target population). This indicates that the polypeptide is expressed in the subject, eg, a cancer or tumor associated antigen or a testicular cancer antigen expressed by cancer cells of the subject. In some cases, one or more or each of the polypeptides is a mutational neoantigen or an expression neoantigen of the subject. One or more or each fragment may comprise a neoantigen-specific mutation. In other cases, one or more or each of the immunogenic polypeptide fragments is from a target polypeptide antigen that is generally not expressed or minimally expressed in normal healthy tissue or cells, but is expressed in a high proportion of (with a high frequency in) subjects or in the diseased cells of a subject having a particular disease or condition, as described above. The method may comprise identifying or selecting said target polypeptide antigen. In some cases, two or more or each of the immunogenic polypeptide fragments / best EPIs are from different cancer- or tumor-associated antigens, where each of these is (over)expressed at a high frequency in subjects having one type of cancer. or a cancer derived from a particular tissue or cell type. In some cases, the immunogenic polypeptide fragments are from a total of or at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 cancer-associated polypeptides or different tumor. In some cases, one or more, each or at least one, at least two, at least three, at least four, at least five, at least six, or at least seven of the polypeptides are selected from the antigens listed in any of tables 2 to 7. In some cases, one or more or each of the target polypeptide antigens is a testicular cancer antigen (CTA). In some cases, the best EPI / immunogenic polypeptide fragments are at least 1, at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 , 18, 19, 20, 21, 22, 23, 24 or 25 CTAs, of a total of 3 or more different target polypeptide antigens, where optionally 1, 2 or all three or at least three are CTAs, of 4 or more different polypeptide antigens, where optionally 1, 2, 3 or all four or at least 1, 2, 3 or 4 are CTA, from 5 or more different polypeptide antigens, where optionally 1, 2, 3, 4 or all five or at least 1, 2, 3, 4 or 5 are CTAs, from 6 or more different polypeptide antigens, wherein optionally 1, 2, 3, 4, 5 or all six or at least 1, 2, 3, 4, 5 or 6 are CTAs, from 7 or more different polypeptide antigens, where optionally 1, 2, 3, 4, 5, 6 or all 7 or at least 1, 2, 3, 4, 5, 6 or 7 are CTA, or from 8 or more different polypeptide antigens, where optionally 1, 2, 3, 4, 5, 6, 7 or all 8 or at least 1, 2, 3, 4, 5, 6, 7 or 8 They are CTAs. In some cases, one or more or each of the target polypeptide antigens is expressed by a bacterium, a virus or a parasite. In some cases, one or more of the polypeptide fragments comprise an amino acid sequence that is a T cell epitope capable of binding to at least two or at least three HLA class I from a high percentage of subjects in the population, and one or more of the polypeptide fragments comprise an amino acid sequence that is a T cell epitope capable of binding to at least two, at least three, or at least four class II HLAs from the subject of a high percentage of subjects in the population , wherein HLA class I and HLA class II binding fragments may optionally overlap. A composition prepared by such a method can elicit a cytotoxic T-lymphocyte response and a helper T-lymphocyte response in the subject. Immunogenic and Pharmaceutical Compositions, Methods of Treatment and Modes of Administration In some aspects, the description refers to a pharmaceutical composition, kit or panels of polypeptides as described above having one or more polypeptides as active ingredients. These may be for use in a method of inducing an immune response, treating, vaccinating, or providing immunotherapy to a subject, and the pharmaceutical composition may be a vaccine or immunotherapy composition. Said treatment comprises administering one or more polypeptides or pharmaceutical compositions that together comprise all the polypeptides of the active ingredient of the treatment to the subject. Multiple polypeptides or pharmaceutical compositions can be administered together or sequentially, for example, all of the pharmaceutical compositions or polypeptides can be administered to the subject within a period of 1 year, 6 months, 3 months or 60, 50, 40 or 30 days. The immunogenic or pharmaceutical compositions or kits described herein may comprise, in addition to one or more immunogenic peptides, a pharmaceutically acceptable excipient, carrier, diluent, buffer, stabilizer, preservative, adjuvant, or other materials known to those of skill in the art. Said materials are preferably non-toxic and preferably do not interfere with the pharmaceutical activity of the active ingredients. The pharmaceutical carrier or diluent can be, for example, solutions containing water. The exact nature of the carrier or other material may depend on the route of administration, e.g. g., orally, intravenously, cutaneously or subcutaneously, nasally, intramuscularly, intradermally, and intraperitoneally. The pharmaceutical compositions of the disclosure may comprise one or more "pharmaceutically acceptable carriers". These are usually large slowly metabolized macromolecules, such as proteins, saccharides, polylactic acids, polyglycolic acids, polymeric amino acids, amino acid copolymers, sucrose (Paoletti et al., 2001, Vaccine, 19:2118), trehalose (WO 00 / 56365) , lactose and lipid aggregates (such as oil droplets or liposomes). Such carriers are known to those skilled in the art. Pharmaceutical compositions may also contain diluents, such as water, saline, glycerol, etc. Additionally, there may be auxiliary substances present, such as wetting or emulsifying agents, pH buffering substances, and the like. Sterile pyrogen-free phosphate-buffered physiological saline is a typical carrier (Gennaro, 2000, Remington: The Science and Practice of Pharmacy, 20th edition, ISBN:0683306472). The pharmaceutical compositions of the disclosure may be in lyophilized or aqueous form, ie, solutions or suspensions. Liquid formulations of this type allow the compositions to be administered directly from their packaged form, without the need for reconstitution in an aqueous medium, and thus are ideal for injection. The pharmaceutical compositions may be presented in vials or may be presented in pre-filled syringes. Syringes may or may not have needles. A syringe will include a single dose, while a vial may include a single dose or multiple doses. The liquid formulations of the disclosure are also suitable for the reconstitution of other medicaments from a lyophilized form. When a pharmaceutical composition is used for such extemporaneous reconstitution, the disclosure provides a kit, which may comprise two vials, or may comprise a pre-filled syringe and a vial, where the contents of the syringe are used to reconstitute the contents of the vial prior to injection. injection. The pharmaceutical compositions of the disclosure may include an antimicrobial agent, particularly when packaged in a multi-dose format. Antimicrobial agents such as 2-phenoxyethanol or parabens (methyl, ethyl, propyl parabens) can be used. Any preservative is preferably present at low levels. The preservative may be added exogenously and / or may be a component of the bulk antigens that are mixed to form the composition (eg, present as a preservative in pertussis antigens). The pharmaceutical compositions of the disclosure may comprise detergent, e.g. g., Tween (polysorbate), DMSO (dimethylsulfoxide), DMF (dimethylformamide). Detergents are generally present at low levels, e.g. cj., <0.01%, but can also be used at higher levels, e.g. g., 0.01 - 50%. The pharmaceutical compositions of the disclosure may include sodium salts (eg, sodium chloride) and free phosphate ions in solution (eg, through the use of a phosphate buffer). In certain embodiments, the pharmaceutical composition may be encapsulated in a suitable carrier to deliver the peptides to antigen-presenting cells or to increase stability. As the skilled artisan will appreciate, various vehicles are suitable for delivering a pharmaceutical composition of the disclosure. Non-limiting examples of suitable structured fluid delivery systems may include nanoparticles, liposomes, microemulsions, micelles, dendrimers, and other phospholipid-containing systems. Methods for incorporating pharmaceutical compositions into delivery vehicles are known in the art. To increase the immunogenicity of the composition, the pharmacological compositions may comprise one or more adjuvants and / or cytokines. Suitable adjuvants include an aluminum salt, such as aluminum hydroxide or aluminum phosphate, but may also be a calcium, iron, or zinc salt, may be an insoluble suspension of acylated tyrosine or acylated sugars, or may be cationic derived saccharides. or Anionically, Polyphosphazenes, Biodegradable Microspheres, Monophosphorylated Lipid A (MPL), Lipid A Derivatives (eg, Reduced Toxicity), 3-O-Deacetylated MPL [3D-MPL], Quil A, Saponin, QS21, Adjuvant Freund's incomplete (Difeo Laboratories, Detroit, Mich.), Merck's adjuvant 65 (Merck and Company, Inc., Rahway, N.I.), AS-2 (Smith-Kline Beecham, Philadelphia, Pa.), CpG oligonucleotides, bioadhesives, and mucoadhesives, microparticles, liposomes, polyoxyethylene ether formulations, polyoxyethylene ester formulations, muramyl peptides, or imidazoquinolone compounds (eg, imiquamod and its homologues). Human immunomodulators suitable for use as adjuvants in the disclosure include cytokines, such as interleukins (eg, IL-1, IL-2, IL-4, IL-5, IL-6, IL-7, IL- 12, etc.), macrophage colony-stimulating factor (M-CSF), tumor necrosis factor (TNF), granulocyte-macrophage colony-stimulating factor (GM-CSF) can also be used as adjuvants . In some embodiments, the compositions comprise an adjuvant selected from the group consisting of Montanide ISA-51 (Seppic, Inc., Fairfield, N.J., United States of America), QS-21 (Aquila Biopharmaceuticals, Inc., Lexington, Mass., United States of America), GM-CSF, Cyclophosamide, Calmcttc-Gucrin (BCG) bacillus, Corynbacterium parvum, Icvamisol, Azimezone, Isoprinisone, Dinitrochlorobenzene (DNCB), Keyhole limpet hemocyanin (KLH), Freund's adjuvant (complete and incomplete ), mineral gels, aluminum hydroxide (Alum), lysolecithin, pluronic polyols, polyanions, oil emulsions, dinitrophenol, diphtheria toxin (DT). By way of example, the cytokine may be selected from the group consisting of transforming growth factor (TGF) such as, but not limited to, TGF-α and TGF-β; insulin-like growth factor type I and / or insulin-like growth factor type II; erythropoietin (EPO); an osteoinductive factor; an interferon such as, but not limited to, interferon-, α, -β, and -γ; a colony-stimulating factor (CSF) such as, but not limited to, macrophage-CSF (M-CSF); granulocyte-macrophage-CSF (GM-CSF); and granulocyte-CSF (G-CSF). In some embodiments, the cytokine is selected from the group consisting of nerve growth factors such as NGF-β; platelet growth factor; a transforming growth factor (TGF) such as, but not limited to, TGF-α. and TGF-β; insulin-like growth factor type I and insulin-like growth factor type II; erythropoietin (EPO); an osteoinductive factor; an interferon (IFN) such as, but not limited to, IFN-a, IFN-β, and EFN-γ; a colony stimulating factor (CSF) such as macrophage-CSF (M-CSF); granulocyte-macrophage-CSF (GM-CSF); and granulocyte-CSF (G-CSF); an interleukin (II) such as, but not limited to, IL-1, IL-1.alpha., IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL -9, IL-10, IL-11, IL-12; IL-13, IL-14, IL-15, IL-16, IL-17, IL-18; LIF; kit-ligand or FLT-3; angiostatin; thrombospondin; endostatin; a tumor necrosis factor (TNF); and LT. It is expected that an adjuvant or cytokine may be added in an amount of from about 0.01 mg to about 10 mg per dose, preferably in an amount of from about 0.2 mg to about 5 mg per dose. Alternatively, the adjuvant or cytokine may be in a concentration of between about 0.01 and 50%, preferably in a concentration of between about 2% and 30%. In certain aspects, the pharmaceutical compositions of the disclosure are prepared by physically mixing the adjuvant and / or cytokine with the PEPIs under suitable sterile conditions according to known techniques to produce the final product. Examples of suitable polypeptide fragment compositions and methods of administration are provided in Esseku and Adeyeye (2011) and Van den Mooter G. (2006). The preparation of vaccine and immunotherapy compositions is generally described in Vaccine Design ("The subunit and adjuvant approach" (ed. Powell M. F. & Newman M. J. (1995) Plenum Press, New York). Encapsulation within liposomes, which is also contemplates, is described by Fullerton, US Patent 4,235,877. In some embodiments, the compositions described herein are prepared as a nucleic acid vaccine. In some embodiments, the nucleic acid vaccine is a DNA vaccine. In some embodiments, DNA vaccines, or gene vaccines, comprise a plasmid with a suitable promoter and transcriptional and translational control elements and a nucleic acid sequence encoding one or more polypeptides of the invention. In some embodiments, plasmids also include sequences to enhance, for example, expression levels, intracellular targeting, or proteasome processing. In some embodiments, DNA vaccines comprise a viral vector containing a nucleic acid sequence encoding one or more polypeptides of the disclosure. In additional aspects, the compositions described herein comprise one or more peptide-encoding nucleic acids determined to have immunoreactivity with a biological sample. For example, in some embodiments, compositions comprise one or more nucleotide sequences encoding 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more peptides comprising a fragment that is a T cell epitope capable of binding to at least three HLA class I molecules and / or at least three HLA class II molecules from a patient. In some embodiments, the peptides are derived from an antigen expressed in cancer. In some embodiments, the DNA or gene vaccine also encodes immunomodulatory molecules to manipulate the resulting immune responses, eg, to increase the potency of the vaccine, stimulate the immune system, or reduce immunosuppression. Strategies to increase the immunogenicity of DNA or gene vaccines include encoding xenogeneic versions of antigens, fusion of antigens to molecules that activate T cells or activate associative recognition, DNA vector priming followed by viral vector boosting and the use of immunomodulatory molecules. In some embodiments, the DNA vaccine is delivered by needle, gene gun, aerosol injector, patch, microneedle, abrasion, among other ways. In some forms, the DNA vaccine is incorporated into liposomes or other forms of nanobodies. In some embodiments, the DNA vaccine includes a delivery system selected from the group consisting of a transfection agent; protamine; a protamine liposome; a polysaccharide particle; a cationic nanoemulsion; a cationic polymer; a cationic polymer liposome; a cationic nanoparticle; a cationic lipid and cholesterol nanoparticle; a cationic lipid, cholesterol and PEG nanoparticle; a dendrimer nanoparticle. In some embodiments, DNA vaccines are administered by inhalation or ingestion. In some embodiments, the DNA vaccine is introduced into the blood, thymus, pancreas, skin, muscle, tumor, or other sites. In some embodiments, the compositions described herein are prepared as an RNA vaccine. In some embodiments, the RNA is non-replicating mRNA or virally derived self-amplifying RNA. In some embodiments, the non-replicating mRNA encodes the peptides described herein and contains the 5' and 3' untranslated regions (UTRs). In some embodiments, the virally derived self-amplifying RNA encodes not only the peptides described herein but also the viral replication machinery that enables intracellular RNA amplification and abundant protein expression. In some embodiments, the RNA is introduced directly into the individual. In some embodiments, the RNA is chemically synthesized or transcribed in vitro. In some embodiments, mRNA is produced from a linear DNA template using an RNA polymerase from phage T7, T3, or Sp6, and the resulting product contains an open reading frame encoding the peptides described herein, flanking UTRs, a 5' cap and a poly(A) tail. In some embodiments, various versions of 5' caps are added during or after the transcription reaction using a vaccinia virus capping enzyme or by incorporation of synthetic cap or anti-reverse cap analogs. In some embodiments, an optimal length of poly(A) tail is added to the mRNA, either directly from the encoding DNA template or through the use of poly(A) polymerase. The RNA encodes one or more peptides comprising a fragment that is a T cell epitope capable of binding to at least three HLA class I molecules and / or at least three HLA class II molecules from a patient. In some embodiments, the fragments are derived from an antigen expressed in cancer. In some embodiments, the RNA includes signals to enhance stability and translation. In some embodiments, the RNA also includes unnatural nucleotides to increase half-life or modified nucleosides to change the immunostimulatory profile. In some embodiments, RNAs are delivered by needle, gene gun, aerosol injector, patching, microneedling, abrasion, among other ways. In some forms, the RNA vaccine is incorporated into liposomes or other forms of nanobodies that facilitate cellular uptake of the RNA and protect it from degradation. In some embodiments, the RNA vaccine includes a delivery system selected from the group consisting of a transfection agent; protamine; a protamine liposome; a polysaccharide particle; a cationic nanoemulsion; a cationic polymer; a cationic polymer liposome; a cationic nanoparticle; a cationic lipid and cholesterol nanoparticle; a cationic lipid, cholesterol and PEG nanoparticle; a dendrimer nanoparticle; and / or naked mRNA; Naked mRNA electroporated in vivo; mRNA complexed with protamine; mRNA associated with a positively charged cationic oil-in-water nanoemulsion; mRNA associated with a chemically modified dendrimer and complexed with polyethylene glycol (PEG)-lipid; mRNA that complexes with protamine on a PEG-lipid nanoparticle; mRNA associated with a cationic polymer such as polyethyleneimine (PEI); mRNA associated with a cationic polymer such as PEI and a lipid component; mRNA associated with a polysaccharide (eg chitosan), particle or gel; mRNA in a cationic lipid nanoparticle (eg, lipids of l,2-dioleoyloxy-3-trimethylammoniompropane (DOTAP) or dioleoylphosphatidylethanolamine (DOPE)); mRNA that forms complexes with cationic lipids and cholesterol; or mRNA that forms complexes with cationic lipids, cholesterol, and PEG-lipid. In some embodiments, the RNA vaccine is administered by inhalation or ingestion. In some embodiments, the RNA is introduced into the blood, thymus, pancreas, skin, muscle, tumor, or other sites, and / or by intradermal, intramuscular, subcutaneous, intranasal, intranodal, intravenous, intrasplenic, intratumoral or other route of administration. The polynucleotide or oligonucleotide components may be naked nucleotide sequences or in combination with cationic lipids, polymers, or targeting systems. They can be supplied through any available technique. For example, the polynucleotide or oligonucleotide can be introduced by needle injection, preferably intradermally, subcutaneously, or intramuscularly. Alternatively, the polynucleotide or oligonucleotide can be delivered directly through the skin using a delivery device such as particle-mediated gene delivery. The polynucleotide or oligonucleotide can be administered topically to skin or mucosal surfaces, for example, by intranasal, oral, or intrarectal administration. Uptake of polynucleotide or oligonucleotide constructs can be enhanced through various known transfection techniques, for example, including the use of transfection agents. Examples of these agents include cationic agents, eg, calcium phosphate and DEAE-Dextran, and lipofectants, eg, lipofectam and transfectam. The dosage of the polynucleotide or oligonucleotide to be administered can be altered. Administration is typically a "prophylactically effective amount" or a "therapeutically effective amount" (as the case may be, although prophylaxis may be considered therapy), where this is sufficient to elicit a clinical response or to show clinical benefit to the individual, p. eg, an amount effective to prevent or delay the onset of the disease or condition, to ameliorate one or more symptoms, to induce or prolong remission, or to delay relapse or recurrence. The dose can be determined according to various parameters, especially according to the substance used; the age, weight and condition of the individual treated; the route of administration; and the necessary regimen. The amount of antigen in each dose is selected as an amount that induces an immune response. A physician will be able to determine the route of administration and dosage necessary for any particular individual. The dose may be provided as a single dose or may be provided as multiple doses, eg, taken at regular intervals, eg, 2, 3, or 4 doses administered hourly. Typically, peptides, polynucleotides, or oligonucleotides are typically administered in the range of 1 pg to 1 mg, more typically 1 pg to 10 pg for particle-mediated delivery and 1 pg to 1 mg, more typically 1-100 pg. , more typically 5-50 pg for other pathways. In general, each dose is expected to comprise 0.01-3 mg of antigen. An optimal amount for a particular vaccine can be determined through studies involving observation of immune responses in subjects. Examples of the techniques and protocols mentioned above can be found in Remington's Pharmaceutical Sciences, 20th edition, 2000, pub. Lippincott, Williams & Wilkins. In some cases according to the description, more than one peptide or peptide composition is administered. Two or more pharmaceutical compositions may be administered together / simultaneously and / or at different times or sequentially. Thus, the description includes sets of pharmaceutical compositions and uses thereof. The use of a combination of different peptides, optionally directed to different antigens, is important to overcome the challenge of the genetic heterogeneity of tumors and the HLA heterogeneity of individuals. The use of the peptides of the disclosure in combination expands the group of individuals who may experience clinical benefit from vaccination. Multiple PEPI pharmaceutical compositions, manufactured for use in a regimen, can define a drug product. Routes of administration include, but are not limited to, intranasal, oral, subcutaneous, intradermal, and intramuscular. Subcutaneous administration is particularly preferred. Subcutaneous administration, for example, may be by injection into the abdomen, the lateral and anterior portions of the upper arm or thigh, the scapular area of ​​the back, or the upper ventrodorsal gluteal area. The compositions of the disclosure can also be administered in one or more doses, as well as by other routes of administration. For example, such routes include, intracutaneous, intravenous, intravascular, intraarterial, intraperitoneal, intrathecal, intratracheal, intracardiac, intralobular, intramedullary, intrapulmonary, and intravaginal routes. Depending on the desired duration of treatment, the compositions according to the description can be administered once or several times, also intermittently, eg monthly for several months or years and in different dosages. Solid dosage forms for oral administration include capsules, tablets, pills, powders, pellets, and granules. In such solid dosage forms, the active ingredient is commonly combined with one or more pharmaceutically acceptable excipients, examples of which are provided above. Oral preparations such as aqueous suspensions, elixirs, or syrups may also be administered. For these, the active ingredient can be combined with various sweetening or flavoring agents, colorants and, if desired, emulsifying and / or suspending agents, as well as diluents such as water, ethanol, glycerin and combinations of these. One or more compositions of the description can be administered, or the methods and uses for treatment according to the description can be carried out, alone or in combination with other compositions or pharmacological treatments, for example, chemotherapy, immunotherapy and / or vaccine. The other compositions or therapeutic treatments, for example, may be one or more of those set forth herein, and may be administered simultaneously or sequentially (before or after) with the composition or treatment of the disclosure. In some cases, treatment may be given in combination with checkpoint blockade / checkpoint inhibitor therapy, costimulatory antibodies, cytotoxic or non-cytotoxic chemotherapy and / or radiation therapy, targeted therapy, or monoclonal antibody therapy. Chemotherapy has been shown to sensitize tumors to be killed by vaccination-induced tumor-specific cytotoxic T cells (Ramakrishnan et al. J Clin Invest. 2010;120(4):1111-1124). Examples of chemotherapy agents include alkylating agents including nitrogen mustards such as mechlorethamine (HN2), cyclophosphamide, ifosfamide, melphalan (L-sarcolysin), and chlorambucil; anthracyclines; epothilones; nitrosoureas such as carmustine (BCNU), lomustine (CCNU), semustine (methyl-CCNU), and cstrcptozocin (cstrcptozotocin); triazines such as dccarbazine (DTIC); dimethyltriazenoimidazole-carboxamide; ethylenimines / methylmelamines such as hexamethylmelamine, thiotepa; alkyl sulfonates such as busulfan; antimetabolites including folic acid analogs such as methotrexate (ametopterin); alkylating agents, antimetabolites, pyrimidine analogs such as fluorouracil (5-fluorouracil; 5-FU), floxuridine (fluorodeoxyuridine; FUdR), and cytarabine (cytosine arabinoside); purine analogs and related inhibitors such as mercaptopurine (6-mercaptopurine; 6-MP), thioguanine (6-thioguanine; TG), and pentostatin (2'-deoxycoformycin); epipodophyllotoxins; enzymes such as L-asparaginase; biological response modifiers such as IFNα, IL-2, G-CSF and GM-CSF; platinum coordination complexes such as cisplatin (cis-DDP), oxaliplatin, and carboplatin; anthracendones such as mitoxantrone and anthracycline; substituted urea such as hydroxyurea; methylhydrazine derivatives including procarbazine (N-methylhydrazine, MIH) and procarbazine; adrenocortical suppressants such as mitotane (ο,ρ'-DDD) and aminoglute timid; taxol and analogs / derivatives; hormones / hormone therapy and agonists / antagonists including adrenocorticosteroid antagonists such as prednisone and equivalents, dexamethasone and aminoglutethimide, progestins such as hydroxyprogesterone caproate, medroxyprogesterone acetate and megestrol acetate, estrogens such as diethylstilbestrol and ethinylestradiol equivalents, antiestrogens such as tamoxifen, androgens including testosterone propionate and fluoxymesterone / equivalents, antiandrogens such as flutamide, gonadotropin-releasing hormone analogs, and leuprolide and nonsteroidal antiandrogens such as flutamide; natural products including vinca alkaloids such as vinblastine (VLB) and vincristine, epipodophyllotoxins such as etoposide and teniposide, antibiotics such as dactinomycin (actinomycin D), daunorubicin (daunomycin; rubidomycin), doxorubicin, bleomycin, plicamycin (mithramycin), and mitomycin (mitomycin C), enzymes such as L-asparaginase, and biological response modifiers such as interferon alphenomes. In some cases, the method of treatment is a method of vaccination or a method of providing immunotherapy. As used herein, "immune" is the treatment of a disease or condition by inducing or enhancing an immune response in an individual. In certain embodiments, immunotherapy refers to a therapy comprising the administration of one or more drugs to an individual to elicit T cell responses. In a specific embodiment, immunotherapy refers to a therapy comprising the administration or expression of polypeptides containing one or more PEPIs to an individual to elicit a T cell response to recognize and kill cells that display the PEPI(s) on their cell surface along with an HLA class I. In another specific embodiment, immunotherapy comprises the administration of one or more plus PEPI to an individual to elicit a cytotoxic T cell response against cells presenting tumor-associated antigens (TAAs) or cancer-associated antigens (CTAs) that comprise the PEPI(s) on their cell surface. In another embodiment, immunotherapy refers to a therapy comprising the administration or expression of polypeptides containing one or more PEPIs presented by HLA class II to an individual to elicit a helper T cell response to provide costimulation for cytotoxic T cells that recognize and destroy diseased cells that present the PEPI(s) on their cell surface along with an HLA class I. In yet another specific embodiment, immunotherapy refers to a therapy comprising the administration of one or more drugs to an individual that reactivate lymphocytes existing T cells to destroy target cells. The theory is that the cytotoxic T cell response will eliminate the cells presenting the PEPI(s), thus improving the individual's clinical condition. In some cases, immunotherapy can be used to treat tumors. In other cases, immunotherapy can be used to treat diseases or disorders based on intracellular pathogens. In some cases, the description refers to the treatment of cancer or the treatment of solid tumors. The treatment can be of malignant or benign cancers or tumors of any type of cell, tissue or organ. The cancer may or may not be metastatic. Exemplary cancers include carcinomas, sarcomas, lymphomas, leukemias, germ cell tumors, or blastomas. The cancer may or may not be a hormone-dependent or hormone-related cancer (eg, an estrogen- or androgen-related cancer). In other cases, the description refers to the treatment of a viral, bacterial, fungal or parasitic infection, or any other disease or condition that can be treated with immunotherapy. systems The description provides a system comprising a storage module configured to store data comprising the HLA class I and / or class II genotypes of each subject in a model population of human subjects; and the amino acid sequence of one or more test polypeptides; wherein the model population is representative of a test target human population; and a computing module configured to identify and / or quantify amino acid sequences in the test polypeptide(s) that are capable of binding multiple HLA class I molecules from each subject in the model population and / or amino acid sequences in the test polypeptide(s) that are capable of binding multiple HLA class II molecules from each subject in the model population. The system may further comprise an output module configured to display any output prediction or treatment selection or recommendation described herein or the value of any pharmacodynamic biomarker described herein. Additional modalities of the description 1. A pharmaceutical composition for the treatment of a disease or disorder in a subject of a target human population, comprising one or more polypeptides, each comprising at least a first region and a second region, where ( a) the first region is 10-50 amino acids in length and comprises a first amino acid sequence that is a T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of the subjects in the target population; and (b) the second region is 10-50 amino acids in length and comprises a second amino acid sequence that is a T cell epitope that binds to at least three HLA class I molecules of at least 10% of the subjects in the target population and / or at least three HLA class II molecules from at least 10% of the subjects in the target population; wherein the amino acid sequence of the T cell epitope of each of the first region and the second region comprises different sequences. 2. The pharmaceutical composition of item 1 comprising at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11 or at least 12 different polypeptides. 3. The pharmaceutical composition of item 1 comprising 2-40 different polypeptides.4. The pharmaceutical composition of item 1, wherein the T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population comprises between 7 and 11 amino acids, and / or the T cell epitope that binds to at least three HLA class II molecules from at least 10% of subjects in the target population comprises between 13 and 17 amino acids. 5. The pharmaceutical composition of item 1, wherein the first region 10-50 amino acids in length is from an antigen; and the second region of 10-50 amino acids in length is from the same antigen or a different antigen.6. The pharmaceutical composition of item 1, where the epitopes of the first region and the second region are from a single antigen.7. The pharmaceutical composition of item 1, where the epitopes of the first region and the second region are from two or more different antigens.8. The pharmaceutical composition of item 5, wherein the antigen is a cancer-associated antigen, a tumor-associated antigen or an antigen expressed by a target pathogenic organism, an antigen expressed by a virus, an antigen expressed by a bacterium, an antigen expressed by a fungus, an antigen associated with an autoimmune disorder, or is an allergen. 9. The pharmaceutical composition of item 5, wherein the antigen is selected from the antigens listed in tables 2 to 7.10. The pharmaceutical composition of item 6, where the two or more different antigens are selected from the antigens listed in tables 2 to 7 and / or different antigens associated with cancer.11. The pharmaceutical composition of item 9, where one or more of the antigens are testicular cancer antigens (CTA).12. The pharmaceutical composition of item 1, wherein the polypeptide or polypeptides also comprise up to 10 amino acids that flank the epitope of T lymphocytes that are not part of a consecutive sequence that flanks the epitope in a corresponding antigen.13. The pharmaceutical composition of item 1, wherein the polypeptide or polypeptides have been analyzed to eliminate substantially all neoepitopes that span a junction between the first region and the second region and that (i) corresponds to a fragment of a human polypeptide expressed in cells healthy; (ii) is a T cell epitope capable of binding to at least three HLA class I molecules from at least 10% of subjects in a target population; or(iii) meets the requirements (i) and (ii). 14. The pharmaceutical composition of item 1, wherein the target population is cancer patients and wherein each of the first region and the second region comprises an amino acid sequence that is an epitope of HLA class I binding T cells , and wherein for each T-cell epitope (i) at least 10% of subjects in the target population express a tumor-associated antigen selected from the antigens listed in Table 2 comprising the T-cell epitope; and (ii) at least 10% of subjects in the target population have at least three HLA class I molecules capable of binding the T cell epitope; wherein the T cell epitope of the first region and the second region are different from each other. 15. The pharmaceutical composition of item 1 that also comprises a pharmaceutically acceptable adjuvant, diluent, carrier, preservative or a combination of these. 16. The pharmaceutical composition of item 15, wherein the adjuvant is selected from the group consisting of Montanide ISA-51, QS-21, GM-CSF, cyclophosamide, bacillus Calmette-Guerin (BCG), corynbacterium parvum, levamisole, azimezone , Isoprinisone, Dinitrochlorobenzene (DNCB), Keyhole Limpet Hemocyanin (KLH), Freund's Adjuvant (Complete), Freund's Adjuvant (Incomplete), Mineral Gels, Aluminum Hydroxide (Alum), Lysolecithin, Pluronic Polyols, Polyanions, Oil Emulsions, dinitrophenol, diphtheria toxin (DT), and combinations of these.17. A kit comprising one or more separate containers, each container comprising: (i) one or more polypeptides comprising at least a first region and a second region, where (a) the first region of 10-50 amino acids in length comprises a first amino acid sequence that is a T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of subjects in the target population; and (b) the second region of 10-50 amino acids in length comprises a second amino acid sequence that is a T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of the subjects in the target population; wherein the amino acid sequence of the T cell epitope of each of the first region and the second region comprises different sequences; and (ii) a pharmaceutically acceptable adjuvant, diluent, carrier, preservative, or a combination of these. 18. The item 19 kit that also includes a prospectus.19. A pharmaceutical composition comprising: one or more nucleic acid molecules expressing one or more polypeptides comprising at least a first region and a second region, where (a) the first region of 10-50 amino acids in length comprises a first sequence of amino acid that is a T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of subjects in the target population; and (b) the second region of 10-50 amino acids in length comprises a second amino acid sequence that is a T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of the subjects in the target population; wherein the amino acid sequence of the T cell epitope of each of the first region and the second region comprises different sequences. twenty.A method of preparing a polypeptide, or a polypeptide-encoding polynucleic acid, for use in a method of inducing an immune response in a subject from a target human population, wherein the method comprises: (i) selecting: (a ) a relevant model human population comprising multiple subjects, each defined by HLA class I genotype and / or by HLA class II genotype; or (b) a relevant model human population comprising multiple subjects, each defined by HLA class I genotype and a relevant model human population comprising multiple subjects, each defined by HLA class II genotype; (ii) identifying a fragment of up to 50 consecutive amino acids of an antigen comprising: (a) a capable T cell epitope, in a high percentage of the subjects of the model population selected in step (i) that is defined by the HLA class I genotype, to bind to at least three HLA class I molecules from individual subjects in the model population; (b) a T cell epitope capable, in a high percentage of subjects in the selected model population in step (i) which is defined by the HLA class II genotype, binding to at least three HLA class II molecules from the individual subjects of the model population; or (c) a T cell epitope capable, in a high percentage of the subjects of the model population selected in step (i) that is defined by the HLA class I genotype, of binding to at least three HLA molecules of the individual subjects of the model population and a capable T cell epitope, in a high percentage of the subjects of the model population selected in step (i) that is defined by the HLA class II genotype, of bind to at least three HLA class II molecules from the individual subjects of the model population; and (iii) preparing a polypeptide, or a polynucleic acid encoding a polypeptide, comprising one or more fragments identified in step (ii). 21. The method of item 20 further comprising, prior to step (iii), selecting a longer fragment of the antigen if the fragment selected in step (ii) is an HLA class I binding epitope, wherein the fragment longer comprises an amino acid sequence that (a) comprises the selected fragment in step (ii); and (b) is a capable HLA class II molecule-binding T cell epitope, in a high percentage of the subjects of the model population selected in step (i) that is defined by the HLA class II genotype , to bind to at least three or as many HLA class II molecules as possible from individual subjects in the model population. 22. The method of item 20 further comprising, before step (iii), repeating steps (i) to (ii) to identify one or more additional amino acid sequences of up to 50 consecutive amino acids of the same polypeptide or a polypeptide different from the first amino acid sequence.23. A method of inducing an immune response in a subject of a target human population, wherein the method comprises administering to the subject a pharmaceutical composition comprising one or more polypeptides comprising at least a first region and a second region, wherein (a) the The first region is 10-50 amino acids in length and comprises a first amino acid sequence that is a T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population. and / or at least three HLA class II molecules from at least 10% of subjects in the target population; and (b) the second region is 10-50 amino acids in length and comprises a second amino acid sequence that is a T cell epitope that binds to at least three HLA class I molecules of at least 10% of the subjects in the target population and / or at least three HLA class II molecules from at least 10% of the subjects in the target population; wherein the amino acid sequence of the T cell epitope of each of the first region and the second region comprises different sequences. 24.The method of item 23 further comprising, prior to the administration step, determining whether the subject is likely to have a clinical response to the administration of a pharmaceutical composition (i) by testing a biological sample from the subject to determine the HLA genotype of the subject; (ii) determining that the pharmaceutical composition comprises two or more sequences that are a T cell epitope capable of binding to at least three HLA class I molecules of the subject; and (iii) determining the probability that a tumor from the subject expresses one or more antigens corresponding to the T cell epitopes identified in step (ii) using the population expression data for each antigen, to identify the probability that the subject has a clinical response to administration of the pharmaceutical composition. 25. The method of item 23, wherein the first region 10-50 amino acids in length is from an antigen; and the second region of 10-50 amino acids in length is from the same antigen or a different antigen.26. The method of item 23, where the epitopes of the first region and the second region are from two or more different antigens.27. The method of item 25, where the antigen is a cancer-associated antigen, a tumor-associated antigen or an antigen expressed by a target pathogenic organism, an antigen expressed by a virus, an antigen expressed by a bacterium, an antigen expressed by a fungus, an antigen associated with an autoimmune disorder, or is an allergen.28. The method of item 23, wherein the T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population comprises between 7 and 11 amino acids, and / or the T cell epitope that binds to at least three HLA class II molecules from at least 10% of subjects in the target population comprises between 13 and 17 amino acids.29. A pharmaceutical composition for the treatment of a disease or disorder in a subject of a target human population comprising (a) at least two polypeptides, wherein each of the at least two polypeptides is 10-50 amino acids in length and comprises a sequence amino acid molecule that is a T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population, and / or at least three HLA class II molecules from at least less than 10% of subjects in the target population, wherein the amino acid sequence of the T cell epitope of each of the at least two polypeptides are different from each other; and (b) a pharmaceutically acceptable adjuvant. 30. The pharmaceutical composition of item 29 comprising at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11 or at least 12 polypeptides different.31. The pharmaceutical composition of item 29 comprising 3-40 different polypeptides.32. The pharmaceutical composition of item 29, wherein the T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population comprises between 7 and 11 amino acids, and / or the T cell epitope that binds to at least three HLA class II molecules from at least 10% of subjects in the target population comprises between 13 and 17 amino acids. 33. The pharmaceutical composition of item 29, wherein the epitopes of the amino acid sequences of the at least two polypeptides are from a single antigen.34. The pharmaceutical composition of item 29, where the epitopes of the amino acid sequences of the at least two polypeptides are from two or more different antigens.35. The pharmaceutical composition of item 33, wherein the antigen is a cancer-associated antigen, a tumor-associated antigen or an antigen expressed by a target pathogenic organism, an antigen expressed by a virus, an antigen expressed by a bacterium, an antigen expressed by a fungus, an antigen associated with an autoimmune disorder, or is an allergen.36. The pharmaceutical composition of item 33, wherein the antigen is selected from the antigens listed in tables 2 to 7.37. The pharmaceutical composition of item 34, where the two or more different antigens are selected from the antigens listed in tables 2 to 7 and / or different antigens associated with cancer.38.The pharmaceutical composition of item 37, where one or more of the antigens are testicular cancer antigens (CTA).39. The pharmaceutical composition of item 29, wherein each of the at least two polypeptides that are 10-50 amino acids in length is from the same antigen or a different antigen.40. The pharmaceutical composition of item 29, wherein the at least two different polypeptides further comprise up to 10 amino acids flanking the epitope of T lymphocytes that are not part of a consecutive sequence flanking the epitope on a corresponding antigen.41. The pharmaceutical composition of item 29, wherein two of the at least two polypeptides are arranged end-to-end or overlap in a linked polypeptide.42. The pharmaceutical composition of item 41 comprising two or more different linked polypeptides, wherein the two or more different linked polypeptides comprise different epitopes from each other.43. The pharmaceutical composition of item 42, wherein the bound polypeptides have been analyzed to remove substantially all neoepitopes encompassing a junction between the two polypeptides and which (i) corresponds to a fragment of a human polypeptide expressed in healthy cells; (ii) is a T cell epitope capable of binding to at least three HLA class I molecules from at least 10% of subjects in a target population; or(iii) meets the requirements (i) and (ii). 44. The pharmaceutical composition of item 29, where the target population is cancer patients and where each polypeptide comprises an amino acid sequence that is an epitope of HLA class I binding T cells, and where for each epitope of T cells (i) at least 10% of the subjects in the target population express a tumor-associated antigen selected from the antigens listed in Table 2 comprising the T cell epitope; and (ii) at least 10% of subjects in the target population have at least three HLA class I molecules capable of binding the T cell epitope; wherein the T cell epitope of the at least two polypeptides are different from each other. 45. The pharmaceutical composition of item 29 that also comprises a pharmaceutically acceptable diluent, carrier, preservative or a combination of these.46. The pharmaceutical composition of item 29, where the adjuvant is selected from the group consisting of Montanide ISA-51, QS-21, GM-CSF, cyclophosamide, bacillus Calmette-Guerin (BCG), corynbacterium parvum, levamisole, azimezone, isoprinisone , Dinitrochlorobenzene (DNCB), Keyhole Limpet Hemocyanin (KLH), Freund's Adjuvant (Complete), Freund's Adjuvant (Incomplete), Mineral Gels, Aluminum Hydroxide (Alum), Lysolecithin, Pluronic Polyols, Polyanions, Oil Emulsions, Dinitrophenol, diphtheria toxin (DT) and combinations of these.47. A pharmaceutical composition for the treatment of a disease or disorder in a subject of a target human population comprising (a) a polypeptide 10-50 amino acids in length and comprising a T cell epitope that binds to at least three molecules of HLA class I from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of subjects in the target population; and (b) a pharmaceutically acceptable adjuvant. 48. The pharmaceutical composition of item 47 comprising at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11 or at least 12 different polypeptides, where each of the different polypeptides is 10-50 amino acids in length and comprises a T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of the subjects in the target population, where the amino acid sequence of the T cell epitope of each of the different polypeptides are different each. 49. The pharmaceutical composition of item 48 comprising 2-40 different polypeptides.50. The pharmaceutical composition of item 47, wherein the T cell epitope that binds to at least three HLA class I molecules of the subject comprises between 7 and 11 amino acids, and / or the T cell epitope that binds to at least three HLA class II molecules comprise between 13 and 17 amino acids.51. The pharmaceutical composition of item 48 comprising at least two different polypeptides, wherein the epitopes of the at least two different polypeptides are from a single antigen.52. The pharmaceutical composition of item 48 comprising at least two different polypeptides, wherein the epitopes of the at least two different polypeptides are from two or more different antigens.53. The pharmaceutical composition of item 51, wherein the antigen is an antigen expressed by a cancer cell, a neoantigen expressed by a cancer cell, a cancer-associated antigen, a tumor-associated antigen, or an antigen expressed by a target pathogenic organism, a antigen expressed by a virus, an antigen expressed by a bacterium, an antigen expressed by a fungus, an antigen associated with an autoimmune disorder, or is an allergen.54. The specific pharmaceutical composition for a human subject of item 51, wherein the antigen is selected from the antigens listed in tables 2 to 7.55. The pharmaceutical composition specific for a human subject of item 51 comprising at least two different polypeptides, wherein two of the polypeptides are arranged end-to-end or overlap in a linked polypeptide.56.The pharmaceutical composition specific for a human subject of item 47, wherein the adjuvant is selected from the group consisting of Montanide ISA-51, QS-21, GM-CSF, cyclophosamide, bacillus Calmette-Guerin (BCG), corynbacterium parvum. Levamisole, Azimezone, Isoprinisone, Dinitrochlorobenzene (DNCB), Keyhole Limpet Hemocyanin (KLH), Freund's Adjuvant (Complete), Freund's Adjuvant (Incomplete), Mineral Gels, Aluminum Hydroxide (Alum), Lysolecithin, Pluronic Polyols, Polyanions, oil emulsions, dinitrophenol, diphtheria toxin (DT) and combinations of these. 57. The pharmaceutical composition specific for a human subject of item 47 comprising at least two different polypeptides, wherein two of the at least two polypeptides are arranged end-to-end or overlap in a linked polypeptide.58. The specific pharmaceutical composition for a human subject of item 57 comprising two or more different linked polypeptides, wherein the two or more different linked polypeptides comprise different epitopes from each other.59. The specific pharmaceutical composition for a human subject of item 58, wherein the bound polypeptides have been analyzed to eliminate substantially all neoepitopes that span a junction between the two polypeptides and that (i) corresponds to a fragment of a human polypeptide expressed in cells healthy from the subject; (ii) is a T cell epitope capable of binding to at least two HLA class I molecules from the subject; or(iii) meets the requirements (i) and (ii). 60. The pharmaceutical composition specific for a human subject of item 48, wherein the at least two polypeptides do not comprise any amino acid sequence that (i) corresponds to a fragment of a human polypeptide expressed in healthy cells; or (ii) corresponds to a fragment of a human polypeptide expressed in healthy cells and is a T cell epitope capable of binding to at least two HLA class I molecules of the subject. 61. A method of identifying and treating a subject from a target population of cancer patients likely to have a clinical response to the administration of a pharmaceutical composition according to item 1, wherein the method comprises (i) performing an assay of a biological sample from the subject to determine the HLA genotype of the subject; (ii) determines that the pharmaceutical composition comprises two or more sequences that are a T cell epitope capable of binding to at least three HLA class I molecules from the subject; (iii) determine!' the probability that a subject's tumor expresses one or more antigens corresponding to the T cell epitopes identified in step (ii) using the population expression data for each antigen, to identify the probability that the subject will have a clinical response to the administration of the pharmaceutical composition; and (iv) administering the composition of item 1 to the identified subject. 62. The method of item 61 further comprising, prior to the administration step, performing an assay on a tumor sample from a subject to determine that the three or more peptides of the pharmaceutical composition comprise two or more different amino acid sequences, each one of which is a. a fragment of a cancer-associated antigen expressed by cancer cells of the subject as determined in step (i); and b. a T cell epitope capable of binding to at least three HLA class I molecules from the subject; and confirm that the subject is likely to have a clinical response to the method of treatment. 63. The method of item 61, wherein the composition comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at minus Io at least 12 different polypeptides.64. The method of item 61, where the composition comprises 2-40 different polypeptides.65. The method of item 61, wherein the T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population comprises between 7 and 11 amino acids, and / or the T cell epitope that binds to at least three HLA class II molecules from at least 10% of subjects in the target population comprises between 13 and 17 amino acids.66.The method of item 61, where the first region of 10-50 amino acids in length is from an antigen; and the second region of 10-50 amino acids in length is from the same antigen or a different antigen.67. The method of item 61, where the epitopes of the first region and the second region are from a single antigen.68. The method of item 61, where the epitopes of the first region and the second region are from two or more different antigens.69. The method of item 67, where the antigen is a cancer-associated antigen or a tumor-associated antigen.70. The method of item 67, where the antigen is selected from the antigens listed in Table 2. 71. The method of item 67, where the two or more different antigens are selected from the antigens listed in Table 2 and / or different antigens associated with cancer.72. The item 71 method, where one or more of the antigens are testicular cancer antigens (CTA).73. The method of item 61, where the polypeptide or polypeptides also comprise up to 10 amino acids that flank the epitope of T lymphocytes that are not part of a consecutive sequence that flanks the epitope in a corresponding antigen.74. The method of item 61, wherein the polypeptide(s) have been analyzed to remove substantially all neoepitopes that span a junction between the first region and the second region and that (i) corresponds to a fragment of a human polypeptide expressed in healthy cells ;(ii) is a T cell epitope capable of binding to at least three HLA class I molecules from at least 10% of subjects in a target population; or(iii) meets the requirements (i) and (ii). 75. The method of item 61, wherein the target population is cancer patients and wherein each of the first region and the second region comprises an amino acid sequence that is an epitope of HLA class I binding T cells, and wherein for each T cell epitope (iii) at least 10% of subjects in the target population express a tumor associated antigen selected from the antigens listed in Table 2 comprising the T cell epitope; and (iv) at least 10% of subjects in the target population have at least three HLA class I molecules capable of binding the T cell epitope; wherein the T cell epitope of the first region and the second region are different from each other. 76. The method of item 61, wherein the composition further comprises a pharmaceutically acceptable adjuvant, diluent, carrier, preservative or a combination of these.77. The method of item 61, where the adjuvant is selected from the group consisting of Montanide ISA-51, QS-21, GM-CSF, cyclophosamide, bacillus Calmette-Guerin (BCG), corynbacterium parvum, levamisole, azimezone, isoprinisone, Dinitrochlorobenzene (DNCB), Keyhole Limpet Hemocyanin (KLH), Freund's Adjuvant (Complete), Freund's Adjuvant (Incomplete), Mineral Gels, Aluminum Hydroxide (Alum), Lysolecithin, Pluronic Polyols, Polyanions, Oil Emulsions, Dinitrophenol, Toxin diphtheria (DT) and combinations of these. 78. A kit comprising: (a) a first composition comprising (i) a first polypeptide 10-50 amino acids in length and comprising a T cell epitope that binds to at least three HLA class I molecules of at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of subjects in the target population; and (ii) a pharmaceutically acceptable adjuvant; (b) a second composition comprising (i) a second polypeptide 10-50 amino acids in length and comprising a T cell epitope that binds to at least three HLA class molecules I from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of subjects in the target population; and (ii) a pharmaceutically acceptable adjuvant, wherein the first polypeptide and the second polypeptide comprise different T cell epitopes. 79. The kit of item 78, wherein the first composition and / or the second composition comprise one or more additional polypeptides , wherein each additional polypeptide is 10-50 amino acids in length and comprises an amino acid sequence that is a T cell epitope that binds to at least three HLA class I molecules from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of the subjects in the target population, wherein the amino acid sequences comprise different epitopes of T.80 cells. A method of identifying and treating a subject from a target population of cancer patients likely to have an immune response to the administration of a pharmaceutical composition according to item 1, wherein the method comprises (i) assaying a biological sample of the subject to determine the HLA genotype of the subject; (ii) determining that the pharmaceutical composition comprises two or more sequences that are a T cell epitope capable of binding to at least three HLA class I molecules of the subject; (iii) administering the composition of item 1 to the identified subject. 81. A pharmaceutical composition comprising: a nucleic acid molecule that expresses two or more polypeptides, where each polypeptide is 10-50 amino acids in length and comprises a T cell epitope that binds to at least three HLA class molecules I from at least 10% of subjects in the target population and / or at least three HLA class II molecules from at least 10% of subjects in the target population, where each of the two or more polypeptides comprises a different T cell epitope, wherein the polypeptides do not comprise amino acid sequences that are adjacent to each other in a corresponding antigen. examples Example 1 - Process of HLA-epitope binding prediction and validation The predicted binding between HLA and particular epitopes (9-mer peptides) was based on the Immune Epitope Database tool for epitope prediction (www.iedb.org). The HLA I-epitope binding prediction process was validated by comparison with HLA I-epitope pairs determined by laboratory experiments. A dataset of HLA I-epitope pairs reported in peer-reviewed publications or public immunological databases was compiled. The matching rate was determined with the experimentally determined data set (Table 9). The HLA I-binding epitope pairs in the dataset were correctly predicted with a probability of 93%. Coincidentally, HLA I-non-junctional epitope pairs were also correctly predicted with a probability of 93%. Table 9. Analytical specificity and sensitivity of the HLA-epitope binding prediction process. The accuracy of the prediction of multiple HLA binding epitopes was determined. Based on the analytical specificity and sensitivity using the 93% probability for true positive and true negative predictions and the 7% probability (=100% - 93%) for false positive and false negative prediction, the probability can be calculated. of the existence of a multiple HLA-binding epitope in a person. The probability of multiple HLAs binding to an epitope shows the relationship between the amount of HLAs that bind to an epitope and the minimum expected amount of actual binding. According to the PEPI definition, three is the minimum expected number of HLAs to bind an epitope (bold). Table 10. Accuracy of predictions of multiple HLA binding epitopes. The validated HLA-epitope binding prediction process was used to determine all of the HLA-epitope binding pairs described in the examples below. Example 2 - Multiple HLA Epitope Presentation Predicts Cytotoxic T Lymphocyte (CTL) Response Presentation of one or more epitopes of a polypeptide antigen by one or more HLA I of an individual was determined to predict a CTL response. The study was carried out through a retrospective analysis of six clinical trials, carried out in 71 cancer patients and 9 HIV-infected patients (Table 11)1'7. Patients in these studies were treated with an HPV vaccine, three different NY-ESO-1-specific cancer vaccines, an HIV-1 vaccine, and a CTLA-4-specific monoclonal antibody (Ipilimumab) that was shown to reactivate CTL against the NY-ESO-1 antigen in patients with melanoma. All of these clinical trials measured antigen-specific CD8+ CTL responses (immunogenicity) in study subjects after vaccination. In some cases, a correlation between CTL responses and clinical responses was indicated. No patient was excluded from the retroactive study for any reason other than data availability. 157 patient data sets (Table 11) were randomized with a standard random number generator to create two independent cohorts for training and evaluation studies. In some cases, the cohorts contained multiple datasets from the same patient, resulting in a training cohort of 76 datasets from 48 patients and an evaluation / validation cohort of 81 datasets from 51 patients. Table 11. Compendium of patient data sets The indicated CTL responses from the training data sets were compared to the HLA I restriction profile of the epitopes (9 mers) of the vaccine antigens. HLA I genotype and antigen sequences of each patient were obtained from publicly available protein sequence databases or peer-reviewed publications and the HLA I-epitope binding prediction process was blinded to clinical CTL response data. from the patients. The number of epitopes of each antigen predicted to bind to at least 1 (PEPI1+), or at least 2 (PEPI2+), or at least 3 (PEPI3+), or at least 4 (PEPI4+), or at least 5 (PEPI5+) or all 6 (PEPI6) HLA class I molecules from each patient and the amount of bound HLA were used as classifiers for the indicated CTL responses. The true positive rate (sensitivity) and true negative rate (specificity) were determined from the training data set for each classifier (amount of HLA bound) separately. ROC analysis was performed for each classifier. In a ROC curve, the true positive rate (sensitivity) was plotted against the false positive rate (1-specificity) for different cut-off points (Figure 1). Each point on the ROC curve represents a sensitivity / specificity pair corresponding to a particular decision threshold (epitope count (PEPI)). The area under the ROC curve (AUC) is a measure of how well the classifier can be distinguished between two diagnostic groups (CTL responder or non-responder). The analysis unexpectedly revealed that epitope presentation predicted by multiple HLA class I from a subject (PEPI2+, PEPI3+, PEPI4+, PEPI5+, or PEPI6), was in all cases a better predictor of CTL response than epitope presentation by only one or more HLA class I (PEPI1+, AUC=0.48, Table 12). Table 12. Determination of the diagnostic value of the PEPI biomarker by ROC analysis. The CTL response of an individual was best predicted by considering epitopes of an antigen that could be presented by at least 3 HLA class I from an individual (PEPI3+, AUC=0.65, Table 12). The PEPI3+ threshold count (number of antigen-specific epitopes presented by 3 or more HLAs from an individual) that best predicted a positive CTL response was 1 (Table 13). In other words, at least one antigen-derived epitope is presented by at least 3 HLA class I from a subject (<1 PEPI3+), then the antigen can trigger at least one CTL clone and the subject is a CTL responder. probable. Using the <1 PEPI3+ threshold to predict likely CTL responders ("<1 PEPI3+ test") provided a diagnostic sensitivity of 76% (Table 13). Table 13. Determination of the <1 PEPI3+ threshold for predicting likely CTL responders in the training data set. Example 3 - Validation of the test <1 PEPI3+ The test cohort of 81 data sets from 51 patients was used to validate the <1 PEPI3+ threshold for predicting an antigen-specific CTL response. For each data set in the test cohort, it was determined whether the <1 PEPI3+ threshold (at least one epitope derived from antigens presented by at least three HLA class I from the individual) was reached. This was compared to experimentally determined CTL responses indicated from clinical trials (Table 14). Clinical validation demonstrated that a PEPI3+ peptide induces a CTL response in a individual with a probability of 84%. 84% is the same value that was determined in the analytical validation of the prediction of PEPI3+, epitopes that bind to at least 3 HLA of an individual (Table 10). These data provide strong evidence that immune responses are induced by PEPI in individuals. Table 14. Diagnostic performance characteristics of the <1 PEPI3+ test (n=81). ROC analysis determined diagnostic accuracy, using the PEPI3+ count as cut-off values ​​(Figure 2). The AUC value = 0.73. For ROC analysis, an AUC of 0.7 to 0.8 was generally considered an objective diagnosis. A PEPI3+ count of at least 1 (<1 PEPI3+) best predicted a CTL response in the test data set (Table 15). This result confirmed the threshold determined during training (Table 12). Table 15. Confirmation of the <1 PEPI3+ threshold for predicting likely CTL responders in the test / validation data set. Example 4 - <1 PEPI3+ Test Predicts CD8+ CTL Reactivities The <1 PEPI3+ test was compared to a previously reported method for predicting a specific human CTL response to polypeptide antigens. The HLA genotypes of 28 VIN-3 and cervical cancer patients who received the HPV-16 synthetic long peptide vaccine (LPV) in two different clinical trials were determined from DNA samples8 9 10. LPV consists of long peptides that cover the viral oncoproteins HPV-16 E6 and E7. The amino acid sequence of LPV was obtained from these publications. The publications also indicate the T cell responses of each vaccinated patient to the overlapping peptide pools of the vaccine. For each patient, epitopes (9 mers) of LPV presented by at least three patient HLA class I (PEPI3+) were identified and their distribution among peptide pools determined. Peptides comprising at least one PEPI3+ (<1 PEPI3+) were predicted to induce a CTL response. Peptides not comprising PEPI3+ were predicted not to induce a CTL response. The <1 PEPI3+ test correctly predicted 489 of 512 negative CTL responses and 8 of 40 positive CTL responses measured after vaccination (FIG. 3A). Overall, the agreement between the <1 PEPI3+ test and experimentally determined CD8+ T cell reactivity was 90% (p<0.001). For each patient, the distribution between peptide groups of epitopes that are presented by at least one HLA class I patient (<1 PEPI1+, prediction of HLA-restricted epitopes, prior art method) was also determined. <1 PEPI1+ correctly predicted 116 of 512 negative CTL responses and 37 of 40 positive CTL responses measured after vaccination (FIG. 3B). Overall, the agreement between HLA-restricted epitope prediction (<1 PEPI1+) and CD8+ T cell reactivity was 28% (not significant). Example 5 - Prediction of HLA Class II Restricted CD4+ T Helper Cell Epitopes 28 VIN-3 and cervical cancer patients receiving HPV-16 synthetic long peptide vaccine (LPV) in two different clinical trials (as described in Example 4) were investigated for helper CD4+ T responses. after vaccination with LPV (FIG. 4). The sensitivity of prediction of HLA class II restricted epitopes was 78%, as the next-generation tool predicted 84 positive responses (positive CD4+ T cell reactivity to a group of peptides for DP alleles from one person) of 107 (sensitivity = 78%). The specificity was 22% as it was able to rule out 7 negative responses out of 31. Overall, the agreement between HLA-restricted class II epitope prediction and CD4+ T cell reactivity was 66%, which is not statistically significant. significant. Example 6 - The <1 PEPI3+ Test Predicts T-Cell Responses to Full-Length LPV Polypeptides Using the same studies reported as in Examples 4 and 5, the <1 PEPI3+ test was used to predict patient CD8+ and CD4+ T cell responses to the full-length E6 and E7 polypeptide antigens of the LPV vaccine. Results were compared with experimentally determined responses and reported. The test correctly predicted CD8+ T-cell reactivity (PEPI3+) in 11 of 15 VIN-3 patients with positive CD8+ T-cell reactivity test results (sensitivity 73%, PPV 85%) and in 2 of 5 patients with cervical cancer (40% sensitivity, 100% PPV). CD4+ T cell reactivities (PEPI4+) correctly predicted 100% of VIN-3 and cervical cancer patients (Figure 5). HLA class I and class II restricted PEPI3+ count was also found to correlate with indicated clinical benefit for LPV vaccinated patients. Patients with higher PEPI3+ counts had a complete or partial response after 3 months. Example 7 - Case Study pGX3001 is a DNA vaccine based on HPV16 containing full length E6 and E7 antigens with a linker in between. pGX3002 is a DNA vaccine based on HPV18 containing full length E6 and E7 antigens with a linker in between. A phase II clinical trial investigated the T cell responses of 17 HPV-infected patients with cervical cancer who were vaccinated with pGX3001 and pGX3002 (VGX-3100 vaccination)1. Figure 5-6 shows for two illustrative patients (patient 12-11 and patient 14-5) the position of each epitope (9mer) presented by at least 1 (PEPI1+), at least 2 (PEPI2+), at least 3 ( PEPI3+), at least 4 (PEPI4+), at least 5 (PEPI5+), or all 6 (PEPI6) HLA class I from these patients within the full-length sequence of the two HPV-16 antigens and the two HPV antigens -18. Patient 12-11 had an overall PEPI1+ count of 54 for the combined vaccines (54 epitopes presented by one or more HLA class I). Patient 14-5 had a PEPI1+ count of 91. Therefore, patient 14-5 has a higher PEPI1+ count than patient 12-11 with respect to all four HPV antigens. PEPI1+ represent the distinct sets of HLA-restricted epitopes specific to vaccine antigens from patients 12-11 and 14-5. Only 27 PEPI1+ were common between these two patients. For PEPI3+ counts (number of epitopes presented by three or more patient HLA class I), the results for patients 12-11 and 14-5 were reversed. Patient 12-11 had a PEPI3+ count of 8, which includes at least one PEPI3+ on each of the four HPV 16 / 18 antigens. Patient 14-5 had a PEPI3+ count of 0. The reported immune responses of these two patients were consistent with PEPI3+ counts, not PEPI1+ counts. Patient 12-11 developed immune responses to each of the four antigens after vaccination as measured by ELISpot, while patient 14-5 did not develop immune responses to any of the four vaccine antigens. A similar pattern was seen when the PEPI1+ and PEPI3+ pools of the 17 patients in the trial were compared. There was no correlation between PEPI1+ count and experimentally determined T cell responses indicated from the clinical trial. However, a correlation was observed between the T-cell immunity predicted by the <1 PEPI3+ test and the indicated T-cell immunity. The <1 PEPI3+ test predicted immune responders to the HPV DNA vaccine. Furthermore, the diversity of the patient's PEPI3+ pool resembled the diversity of T cell responses typically found in cancer vaccine trials. Patients 12-3 and 12-6, similar to patient 14-5, did not have PEPI3+ that predicted that the HPV vaccine could not activate T cell immunity. The rest of the patients had at least one PEPI3 that predicted the likelihood that HPV vaccine could activate T cell immunity. 11 patients had multiple PEPI3+ predicting that HPV vaccine possibly activates polyclonal T cell responses. Patients 15-2 and 15-3 were able to develop high magnitude T cell immunity to HPV E6, but low immunity to E7. Other patients 15-1 and 12-11 had the same magnitude response to E7 from HPV18 and HPV16, respectively. Example 8 - Design of a model population to perform in silico assays and identify candidate precision vaccine targets for a large population An in silico human trial cohort of 433 subjects with full 4-digit HLA class I genotype (2 x HLA-A*xx:xx; 2 x HLA-B*xx:xx; 2 x HLA-C* xx:xx) and demographic information. This model population has subjects of mixed ethnicity who have a total of 152 different HLA alleles representing >85% of currently known G groups of alleles. A "large population" database containing 7,189 subjects characterized with a 4-digit HLA genotype and demographic information was also established. The large population has 328 different HLA class I alleles. The HLA allele distribution of the model population was significantly correlated with the large population (Table 16) (Pearson p<.001). Therefore, the model population of 433 patients represents a population 16 times larger. The model population represents 85% of the human race as provided by HLA diversity as well as HLA frequency. Table 16. Statistical analysis of HLA distributions in "model population" versus "large population". Example 9 - In silico assays based on the identification of multiple HLA-binding epitopes that predict T cell response rates reported from clinical trials The goal of this study is to determine if a model population, such as that described in Example 8, can be used to predict CTL reactivity rates of vaccines, ie, used in in silico efficacy assays. Twelve cancer antigen-derived peptide vaccines that induced T cell responses in a subpopulation of subjects were identified from peer-reviewed publications. These peptides have been investigated in clinical trials involving a total of 172 patients (4 ethnicities). T cell responses induced by the vaccine peptides have been determined from blood samples and are indicated. Immune response rate was determined as the percentage of study subjects with positive T cell responses measured in clinical trials (FIG. 7). Table 17. Clinical trials conducted with peptide vaccines. The 12 peptides with the <1 PEPI3+ test were investigated in each of the 433 subjects in the model population described in Example 8. The "<1 PEPI3+ score" was calculated for each peptide as the proportion of subjects in the model population who has at least one vaccine-derived epitope that can bind to at least three subject-specific HLA class I (<1 PEPI3+). If the corresponding clinical trial stratified patients for the selected population of HLA alleles, the model population was also filtered for subjects with the respective alleles (example: WT1, HLA-A*0201). Experimentally determined response rates reported in the trials were compared with <1 PEPI3+ scores. The overall percentage of agreement (OPA) was calculated with the paired data (Table 18). A linear correlation was observed between the PEPT3+ score <1 and the response rate (R2 = 0.77) (Figure 7). This result shows that the identification of peptides that are predicted to bind to multiple HLAs in an individual is useful for in silico predicting the outcome of clinical trials. Table 19. Comparison of PEPI3+ <1 scores and CTL response rates of 12 peptide vaccines. Example 10. In silico assays based on the identification of multiple HLA-binding epitopes that predict T cell response rates reported from clinical trials II Nineteen clinical trials with published immune response rates (IRR) conducted with peptide- or DNA-based vaccines were identified (Table 19). These trials involved 604 patients (9 ethnicities) and covered 38 vaccines derived from tumor and viral antigens. Vaccine antigen-specific CTL responses were measured in each study patient, and the response rate in clinical study populations was calculated and reported. Each vaccine peptide from the 19 clinical trials was investigated with the test <1 PEPI3+ in each subject of the model population. The <1 PEPI3+ score for each peptide was calculated as the proportion of subjects in the model population having at least one vaccine-derived PEPI3+. Reported experimentally determined response rates from trials were compared to PEPI scores, as in Example 9 (Table 20). A linear correlation was observed between the response rate and the score <1 PEPI3+ (R2 = 0.70) (Figure 8). This result confirms that the identification of peptides that are predicted to bind to multiple HLAs from an individual can predict the T cell responses of subjects, and in silico assays can predict the result of clinical trials. * % of subjects in model population with vaccine-derived sfl PEPI3+ Example 11 - In silico assay based on the identification of multiple HLA-binding epitopes in a multi-peptide vaccine that predicts the indicated immune response rate from clinical trials IMA901 is a therapeutic vaccine for renal cell cancer (RCC) that comprises 9 peptides derived from tumor-associated peptides (TUMAPs) that occur naturally in human cancer tissue. A total of 96 HLA-A*02+ subjects with advanced RCC were treated with IMA901 in two independent clinical studies (Phase I and Phase II). Each of the 9 peptides of IMA901 have been identified in the prior art as HLA-A2 restricted epitopes. Based on currently accepted standards, all are strong candidate peptides for enhancing T-cell responses against kidney cancer in trial subjects, since their presence has been detected in kidney cancer patients, and because trial patients are specifically selected to have at least one HLA molecule capable of presenting each of the peptides. For each subject in the model population, the amount of the nine IMA901 vaccine peptides that were capable of binding three or more HLAs was determined. As each peptide in the IMA901 vaccine is a 9mer, this corresponds to the PEPI3+ count. Results were compared to immune response rates reported in phase I and phase II clinical trials (Table 22). Table 22. Immune response rates in the model population and in two clinical trials to IMA901 *Number of patients tested for immune responses The results of the phase I and phase II study show the variability of immune responses to the same vaccine in different trial cohorts. In general, however, there was good agreement between the response rates predicted by the <2 PEPI3+ test and the reported clinical response rates. In a retrospective analysis, clinical investigators from the trials discussed above found that subjects who responded to multiple IMA901 vaccine peptides were significantly (p = 0.019) more likely to experience disease control (stable disease, partial response) than subjects who only responded to one peptide or who had no response. 6 of 8 subjects (75%) who responded to multiple peptides experienced clinical benefit in the trial, as opposed to 14% and 33% of 0 and 1 peptide responders, respectively. The phase II randomized trial confirmed that immune responses to multiple TUMAPs were associated with longer overall survival. As the presence of PEPI adequately predicted TUMAP responders, clinical responders to IMA901 are likely to be patients who may have <2 TUMAP PEPI. This subpopulation is only 27% of HLA-A*()2 screened patients, and based on the clinical trial result, 75% of this subpopulation is expected to experience clinical benefit. The same clinical results suggest that 100% of patients experience clinical benefit if patient selection is based on TUMAP <3 PEPI, although this population would only represent 3% of the HLA-A*02 screened patient population. These results suggest that the rate of disease control (stable disease or partial response) is between 3% and 27% in the patient population investigated in clinical trials of IMA901. In the absence of a complete response, only a portion of these patients may have a survival benefit. These findings explain the lack of improved survival in the phase III clinical trial of IMA901. These results also demonstrated that HLA-A*02 enrichment of the study population was not sufficient to meet the primary overall survival endpoint in the Phase III IMA901 trial. As indicated by investigators of the IMA901 trial, there is a need to develop a companion diagnosis (CDx) to select likely responders to peptide vaccines. These findings also suggest that selection of patients with <2 TUMAP-specific PEPIs may provide sufficient enrichment to demonstrate significant clinical benefit of IMA901. Example 12 - In silico assay based on the identification of multiple HLA-binding epitopes derived from vaccines that predict reported experimental clinical response rates A correlation was determined between the <2 PEPI3+ score of the immunotherapy vaccines determined in the model population described in Example 8 and the reported disease control rate (DCR, proportion of patients with complete and partial responses and stable disease). determined in clinical trials. Seventeen clinical trials conducted with peptide- and DNA-based cancer immunotherapy vaccines that have published disease control rates (DCR) or target response rate (ORR) were identified from peer-reviewed scientific journals (Tables 23). These trials involved 594 patients (5 ethnicities) and covered 29 tumor and viral antigens. DCRs were determined according to the Response Evaluation Criteria in Solid Tumors (RECIST), which is the current standard for clinical trials, where clinical responses are based on changes in maximal cross-sectional dimensions42,43,44. In case DCR data were not available, objective response rate (ORR) data was used, which is also defined according to RECIST guidelines. Table 24 compares the <2 PEPI3+ score for each vaccine in the model population and the published DCR or ORR. A correlation between predicted and measured DCR was observed, providing further evidence that not only the immunogenicity, but also the potency of cancer vaccines depends on multiple HLA sequences of individuals (R2 = 0.76 ) (figure 9). Table 23. Selected clinical trials for disease control rate (DCR) prediction. *Montanide ISA51 VG as an adjuvant **Disease response was assessed according to the International Myeloma Task Force response criteria43 Table 24. Disease Control Rates (DCR) and MultiPEPI Scores (Predicted DCR) in 17 Clinical Trials. Example 13 In Silico Assays Based on the Identification of Multiple HLA Binding Epitopes Predicting Cellular Immune Response Rates Indicated for a Vaccine Targeted to a Mutational Antigen Epidermal growth factor receptor variant III (EGFRvIII) is a tumor-specific mutation that is widely expressed in glioblastoma multiforme (GBM) and other neoplasms. The mutation involves an 801 bp in-frame deletion of the EGFR extracellular domain that splits a codon and produces a novel glycine at the fusion junction.1, 2 This mutation encodes a constitutively active tyrosine kinase that enhances tumor formation and tumor cell migration and improves resistance against radiation and chemotherapy.3, 4'5' 6' 7'8' 9 This insert produces a tumor-specific epitope not found in normal adult tissues, making it that EGERvITT is a suitable target candidate for antitumor immunotherapy.10 Rindopepimut is a 13-amino acid peptide vaccine (LEEKKGNYVVTDHC) that encompasses the EGFRvIII mutation with an additional C-terminal cysteine ​​residue.11 In a phase II clinical study, keyhole limpet hemocyanin-conjugated peptide (KLH) was administered to patients with newly diagnosed EGFRvIII-expressing GBM. The first three vaccinations were given biweekly, beginning 4 weeks after radiation completion. Subsequent vaccinations were given monthly until radiographic evidence of tumor progression or death was obtained. All vaccines were administered intradermally in the inguinal region. Immunological evaluation showed only 3 of 18 patients who developed cellular immune response evaluated by DTH reaction test. An in silico test was performed with the model population of 433 subjects with the Rindopepimut sequence. 4 of 433 subjects had PEPI3+, confirming the low immunogenicity found in the phase II study (Table 25). Table 25. Results of the clinical trial and the in silico study. An HLA map of Rindopepimut on the HLA alleles of subjects in the model population (Figure 10) illustrates that very few HLA-A and HLA-C alleles can bind the vaccine epitopes, which explains the lack of PEPI3+ in the in silico cohort. In a recent phase III clinical study, inefficacy was demonstrated when 745 patients participated and were randomly assigned to Rindopepimut and temozolomide (n=371) or control and temozolomide (n=374) groups.12 The trial was canceled due to inefficacy after interim analysis. The analysis showed no significant difference in overall survival: median overall survival was 20.1 months (95% CI 18.5-22.1) in the Rindopepimut group versus 20.0 months (18.1-21 .9) in the control group (HR 1.01, 95% CI 0.79-1.30; p=0.93). References for Example 13 1 Bigner et al. Characterization of the epidermal growth factor receptor in human glioma cell lines and xenografts. Cancer Res 1990;50:8017-22.2 Libermann et al. Amplification, enhanced expression and possible rearrangement of EGF receptor gene in primary human brain tumors of glial origin. Nature 1985;313:144-7.3 Chu et al. Receptor dimerization is not a factor in the signaling activity of a transforming variant epidermal growth factor receptor (EGFRvIII). Biochem J 1997; 324: 855-61.4 Batra et al. Epidermal growth factor ligand-independent, unregulated, cell-transforming potential of a naturally occurring human mutant EGFRvIII gene. Cell Growth Differ 1995;6:1251-9.5 Nishikawa et al. A mutant epidermal growth factor receptor common in human glioma confers enhanced tumorigenicity. PNAS 1994; 91: 7727-31.6 Lammering et al. Inhibition of the type III epidemic growth factor receptor variant mutant receptor by dominant-negative EGFR-CD533 enhances malignant glioma cell radiosensitivity. Clin Cancer Res 2004; 10: 6732-43.7 Nagane et al. A common mutant epidermal growth factor receptor confers enhanced tumorigenicity on human glioblastoma cells by increasing proliferation and reducing apoptosis. Cancer Res 1996; 56: 5079-86. 8 Lammering et al. Radiation-induced activation of a common variant of EGFR confers enhanced radioresistance. Radiother Oncol 2004; 72: 267-73.9 Montgomery et al. Expression of oncogenic epidermal growth factor receptor family kinases induces paclitaxel resistance and alters β-tubulin isotype expression. J Biol Chem 2000; 275: 17358-63.10 Humphrey et al. Anti-synthetic peptide antibody reacting at the fusion junction of deletion-mutant epidermal growth factor receptors in human glioblastoma. PNAS 1990; 87: 4207-11.11 Sampson et al. Immunologic Escape After Prolonged Progression-Free Survival With Epidermal Growth Factor Receptor Variant III Peptide Vaccination in Patients With Newly Diagnosed Glioblastoma. J Clin Oncol 28:4722-4729.12 Weller et al. Rindopepimut with temozolomide for patients with newly diagnosed, EGFRvIII- expressing glioblastoma (ACT IV): a randomized, double-blind, international phase 3 trial. Lancet Oncol 2017; 18(10): 1373-1385. Example 14. Multiple HLA-binding peptides from individuals can predict immunotoxicity Thrombopoietin (TPO) is a highly immunogenic protein drug that causes toxicity in many patients. EpiVax / Genentech used state-of-the-art technology to identify HLA class II restricted epitopes and found that the most immunogenic region of TPO is located at the C-terminus of TPO (US20040209324 Al). In accordance with the present disclosure, multiple HLA class II binding epitopes (PEPI3+) of TPO were determined in 400 genotyped HLA class II US subjects. Most of the PEPI3+ peptides from these individuals are located within the N-terminal region of TPO between amino acids 1-165. PEPI3+ were sporadically identified in some subjects also in the C-terminal region. However, our results were different from those of the prior art. The published literature confirmed the results described, demonstrating experimental proof that the immunotoxic region is located at the N-terminus of TPO. 40, 41 Most individuals treated with the drug TPO produced ADA anti-drug antibodies (ADAs) against this region. of the drug. These antibodies not only abolished the therapeutic effect of the drug, but also caused systemic adverse events, i.e., immunotoxicity, such as antibody-dependent cytotoxicity (ADCC) and complement-dependent cytotoxicity associated with thrombocytopenia, neutropenia, and anemia. These data demonstrate that identification of multiple HLA-binding peptides from individuals predicts TPO immunotoxicity. Thus, the description is useful for identifying the toxic immunogenic region of drugs, for identifying subjects likely to experience drug immunotoxicity, for identifying regions of a polypeptide drug that can be targeted by ADAs, and for identifying subjects likely to have ADA. Example 15 Personalized Immunotherapy Composition for the Treatment of Ovarian Cancer This example describes the treatment of a patient with ovarian cancer with a personalized immunotherapy composition, where the composition was specifically designed for the patient based on her HLA genotype according to the description described herein. This example and Example 16 below provide clinical data to support the principles regarding the binding of epitopes across multiple HLAs of a subject to induce a cytotoxic T-lymphocyte response on which the present disclosure is based. The HLA class I and class II genotype of the patient with XYZ metastatic ovarian adenocarcinoma was determined from a saliva sample. To develop a personalized pharmaceutical composition for patient XYZ, thirteen peptides were selected, each of which met the following two criteria: (i) derived from an antigen expressed in ovarian cancers, as reported in peer-reviewed scientific publications; and (ii) comprises a fragment that is a T cell epitope capable of binding to at least three HLA class I from patient XYZ (Table 26). In addition, each peptide is optimized to bind to the maximum amount of HLA class II in the patient. Table 26: XYZ Ovarian Cancer Patient Personalized Vaccine Eleven PEPI3 peptides in this immunotherapy composition can induce XYZ T cell responses with 84% probability and the two PEPI4 peptides (POC01-P2 and POCOÍ-P5) with 98% probability, according to validation of the PEPI test shown in Table 10. T cell responses are directed at 13 antigens expressed on ovarian cancers. Expression of these cancer antigens in patient XYZ was not evaluated. Instead, the probability of successful cancer cell killing was determined based on the probability of antigen expression on the patient's cancer cells and the positive predictive value of the test of <1 PEPI3+ (AGP count). The AGP count predicts the efficacy of a vaccine in a subject: amount of vaccine antigens expressed in the tumor (ovarian adenocarcinoma) of the patient with PEPI. The AGP count indicates the amount of tumor antigens that the vaccine recognizes and induces a T cell response against the patient's tumor (hits the target). The AGP count depends on the rate of expression of the vaccinia antigen in the subject's tumor and the subject's HLA genotype. The correct value should be between 0 (no PEPI presented by the expressed antigen) and the maximum number of antigens (all antigens are expressed and present a PEPI). The probability that patient XYZ expresses one or more of the 12 antigens is shown in Figure 11. AGP95 = 5, AGP50 = 7.9, mAGP = 100%, AP = 13. A pharmaceutical composition for patient XYZ may be composed of at least 2 of the 13 peptides (Table 26), since it was determined that the presence in an immunotherapy or vaccine composition of at least two polypeptide fragments (epitopes) that can bind to at least three HLAs from an individual (<2 PEPI3+) predicts a clinical response. The peptides are synthesized, dissolved in a pharmaceutically acceptable solvent and mixed with an adjuvant prior to injection. It is desirable that the patient receive personalized immunotherapy with at least two peptide vaccines, but it is preferable to increase the probability of killing cancer cells and decrease the possibility of relapse. For the treatment of patient XYZ, the 12 peptides were formulated as 4 x 3 / 4 peptide (POCOl / 1, POCOl / 2, POCOl / 3, POCOl / 4). A treatment cycle is defined as the administration of the 13 peptides in 30 days. Patient History: Diagnosis: metastatic ovarian adenocarcinoma Age: 51 Family history: colon and ovarian cancer (mother), breast cancer (grandmother) Tumor pathology: BRCal-185delAG, BRAF-D594Y, MAP2K1-P293S, NOTCH1-S2450N • 2011: first diagnosis of ovarian adenocarcinoma; Wertheim operation and chemotherapy; lymph node removal • 2015: Metastases in pericardial adipose tissue, excised • 2016: Liver metastases • 2017: Retroperitoneal and mesenteric lymph nodes have progressed; early peritoneal carcinomatosis with accompanying small ascites Previous therapy: • 2012: Paclitaxel-carboplatin (6x)• 2014: Caelyx-carboplatin (lx)• 2016-2017 (9 months): Lymparza (Olaparib) 2x400 mg / day, oral• 2017: Hycamtin inf. 5x2.5 mg (3x one series / month), treatment with PIT vaccine started on April 21, 2017. Table 27 Peptide Treatment Schedule for Patient XYZ Patient's Tumor MRI Findings (Onset April 15, 2016) • Disease was primarily confined to the liver and lymph nodes. Use of MRI limits detection of lung (pulmonary) metastases• May 2016 - January 2017: Olaparib treatment• Dec / 25 / 2016 (prior to PIT vaccine treatment) There was a dramatic reduction in tumor burden with confirmation of the response obtained in FU2• January - March 2017 - TOPO Protocol (topoisomerase)• April 6, 2017 FU3 demonstrated the reappearance of existing lesions and the appearance of new lesions that lead to disease progression• April 21, 2017 INITIAL PIT• 21 / 07 / 17 (after 2nd cycle of PIT) FU4 demonstrated continued growth of lesions, general enlargement of the pancreas, and abnormal parapancreatic signal along with increased ascites• 26 / 07 / 17 - CBP+Gem+Avastin• 20 / Sep / 17 (after 3 cycles of PIT) FU5 showed reversal of lesion growth and improvement of pancreatic / parapancreatic signal. Findings suggest pseudoprogression• Nov 28 / 17 (after 4 cycles of PIT) FU6 demonstrated best response with resolution of non-target lesions The MRI data for patient XYZ is shown in Table 28 and Figure 12. Table 28. Injury Response Compendium Table Example 16 Design of personalized immunotherapy composition for the treatment of breast cancer The HLA class I and class II genotype of the ABC metastatic breast cancer patient was determined from a saliva sample. To develop a personalized pharmaceutical composition for patient ABC, twelve peptides were selected, each of which met the following two criteria: (i) derived from an antigen expressed in breast cancers, as reported in peer-reviewed scientific publications; and (ii) comprises a fragment that is a T cell epitope capable of binding to at least three class I HLAs from patient ABC (Table 29). In addition, each peptide is optimized to bind to the maximum amount of HLA class II in the patient. The twelve peptides target twelve breast cancer antigens. The probability that patient ABC expresses one or more of the 12 antigens is shown in Figure 13. Table 29. 12 peptides for the ABC breast cancer patient Predicted efficacy: AGP95=4; 95% probability that the PIT vaccine induces CTL responses against 4 CTAs expressed in BRC09 breast cancer cells. Additional efficacy parameters: AGP50 = 6.3, mAGP = 100%, AP = 12. Efficacy detected after vaccination with the 12 peptides: 83% reduction in tumor metabolic activity (PET CT data). For the treatment of patient ABC, the 12 peptides were formulated as 4x3 peptide (PBR01 / 1, PBR01 / 2, PBR01 / 3, PBR01 / 4). A treatment cycle is defined as the administration of the 12 different peptide vaccines in 30 days. Patient History Diagnosis: bilateral metastatic breast carcinoma: right breast is ER positive, PR negative, Her2 negative; the left breast is ER, PR, and Her2 negative. First diagnosis: 2013 (4 years before treatment with the PIT vaccine) 2016: extensive metastatic disease with lymph node involvement both above and below the diaphragm. Multiple liver and lung metastases. 2016-2017 treatment: Etrozole, Ibrance (Palbociclib) and Zoladex Results Mar 7 2017: before treatment with PIT vaccine Hepatic multi-metastatic disease with real extrinsic compression of the origin of the common bile duct and massive dilatation of the entire intrahepatic biliary tract. Celiac, hilar hepatic and retroperitoneal adenopathy May 26, 2017: after 1 PIT cycle Detected efficacy: 83% reduction in tumor metabolic activity (PET CT), liver, lung, lymph nodes and other metastases. Safety detected: Skin reactions Local swelling at the injection site within 48 hours after administration of the vaccine Follow-up: BRC-09 was treated with 5 cycles of PIT vaccine. She felt very well and refused to have a PET CT scan in September 2017. In November she developed symptoms, the PET scan showed progressive disease, but refused all treatments. Also, the oncologist discovered that he had not taken Palbocyclib since the spring / summer. Patient ABC passed away in January 2018. It is likely that the combination of pablocyclib and the personalized vaccine was responsible for the remarkable rapid response observed after administration of the vaccine. Palbocyclib has been shown to enhance the activity of immunotherapies by increasing the presentation of CTA by HLAs and decreasing the proliferation of Tregs: (Goel et al. Nature. 2017:471-475). The PIT vaccine can be used as an adjunct to next-generation therapy for maximum efficacy. Example 17. Breast Cancer Vaccine Design for Large Population and Composition The PEPI3+ test described above was used to design peptides for use in breast cancer vaccines that are effective in a large percentage of patients, considering the heterogeneities of tumor antigens and HLA from patients. Breast cancer CTAs were identified and classified based on the overall expression frequencies of antigens found in breast cancer tumor samples as reported in the peer-reviewed publications (Chen et al. Multiple Cancer / Testis Antigens Are Preferentially Expressed in Hormone-Receptor Negative and High-Grade Breast Cancers. Píos One 2011; 6(3): el7876.; Kanojia et al. Sperm- Associated Antigen 9, a Novel Biomarker for Early Detection of Breast Cancer. Cancer Epidemiol Biomarkers Prev 2009;18(2):630-639.; Saini et al. A Novel Cancer Testis Antigen, A-Kinase Anchor Protein 4 (AKAP4) Is a Potential Biomarker for Breast Cancer. Píos One 2013;8(2):e57095) . For certain CTAs, the PEPI3+ test and model population described in Example 8 were used to identify the 9-mer (PEPI3+) epitopes that are most frequently presented by at least 3HLA of individuals in the model population. We refer to these epitopes herein as "best EPI". An illustrative example of "PEPI3+ hotspot" analysis and identification of best EPIs is shown in Figure 14 for the PRAME antigen. The reported frequency of expression for each CTA (N%) was multiplied by the frequency of PEPI3+ sites of interest in the model population (B%) to identify T cell epitopes (9 mers) that will induce an immune response against CTAs. breast cancer antigens in the largest proportion of individuals (table 30). Then, 15 mers spanning each of the 9 selected mers were selected (Table 30). The 15 mers were selected to bind the greatest number of HLA class II alleles from the majority of subjects, using the process described in Example 22 below. These 15 mers can induce CTL and T helper responses in the largest proportion of subjects. Table 30 List of best PPE to select breast cancer peptide vaccine composition. Ntotal: number of samples analyzed for the expression of the determined antigen; N+: number of individuals expressing the determined antigen; N%: frequency of expression of the determined antigen; B%: frequency of best EPI, that is, the percentage of individuals who have the best EPI within the model population; N%*B%: frequency of expression multiplied by the frequency of bestEPI. Then 31 peptides of 30 mer were designed. Each consists of two fragments of 15 mer optimized, generally from different common CTAs, arranged end-to-end, where each fragment comprises one of the 9 mers (best EPIs) from table 30. Nine of these 30-mer peptides were selected for a panel of peptides, called PolyPEPI915 (table 31). ). The expression frequencies for the 10 PolyPEPI915 target CTAs, individually or in combination, are shown in Figure 15. Table 31 - Selected Breast Cancer Vaccine Peptides for the PolyPEPI915 Panel / Composition * Percentage of individuals who have PEPI3+ specific for CD8+ T cells within the model population (n=433). **Percentage of individuals who have PEPI4+-specific CD4+ T cells within the model population (n=433). Characterization of PolyPEPI915 Tumor heterogeneity can be addressed by including peptide sequences that they target multiple CTAs in an immunotherapy or vaccine regimen. The PolyPEPI915 composition targets 10 different CTAs. Based on the antigen expression rates for these 10 CTAs, the predicted average number of antigens expressed (AG50) and the minimum number of antigens expressed with 95% probability (AG95) on cancer cells were modeled. 95% of individuals expressed a minimum of 4 of the 10 target antigens (AG95=4) as shown by the antigen expression curve in Figure 16. The AG values ​​described above characterize a vaccine regardless of the patient population. They can be used to predict the probability that a specific cancer (eg, breast cancer) will express target antigens of a specific vaccine or immunotherapy composition. AG values ​​are based on known tumor heterogeneity, but do not consider HLA heterogeneity. The HLA heterogeneity of a certain population can be characterized from the point of view of a vaccine composition or immunotherapy by the number of antigens representing PEPI3+. These are the vaccine-specific CTA antigens for which <1 PEPI3+ is predicted, referred to herein as "AP". The average number of antigens with PEPI3+ (AP50) shows how the vaccine can induce an immune response against the target antigens of the composition (breast cancer vaccine-specific immune response). The PolyPEPI915 composition can induce an immune response against an average of 5.3 vaccine antigens (AP5O=5.3O) and 95% of the model population can induce an immune response against at least one vaccine antigen (AP95=1 )(figure 17). Vaccines can be further characterized by AGP values ​​that refer to antigens with PEPI". This parameter is the combination of the two previous parameters: (1) AG depends on the antigen expression frequencies in the specific tumor type but not on the HLA genotype of the individuals in the population, and (2) AP depends on the HLA genotype of the individuals in the population without regard to the frequencies of expression of the antigen AGP depends on the frequencies of expression of the vaccine antigens in the disease and the HLA genotype of individuals in a population. Combining the AP and breast cancer AG data in the model population, the AGP value of PolyPEPI915 representing the probability distribution of vaccine antigens inducing immune responses against antigens expressed in breast tumors was determined. For PolyPEPI915, the AGP50 value in the model population is 3.37. AGP92=1 means that 92% of the subjects in the model population induce immune responses against at least one expressed vaccine antigen (FIG. 18). Example 18 - Selection of Probable Responder Patients Using Companion Diagnostic Tests for Vaccines The probability that a specific patient will have an immune response or a clinical response to treatment with one or more cancer vaccine peptides, for example, as described above, can be determined based on (i) the identification of PEPI3+ within of the vaccine peptides (epitopes of 9 mer capable of binding to at least three HLA of the patient); and / or (ii) a determination of target antigen expression in cancer cells of the patient, eg, as measured in a tumor biopsy. In some cases, ideally both parameters are determined and the optimal combination of vaccine peptides is selected for use in treating the patient. However, PEPI3+ assays can be used only if a determination of expressed tumor antigens, for example by biopsy, is not possible, advisable, or unreliable due to biopsy error (i.e., tissue samples from biopsies taken from a small portion of the tumor or metastatic tumors do not represent the complete repertoire of CTAs expressed in the patient). Example 19 - Comparison of PolyPEPI915 to Competing Breast Cancer Vaccines The in silico clinical trial model described above was used to predict the immune response rates of competing breast cancer vaccines investigated in clinical trials (Table 32). The immune response rate of these products was between 3% and 91%. Peptide vaccines alone were immunogenic in 3%-23% of individuals. By comparison, each of the 30-mer peptides described in Example 18 above (Table 29) were immunogenic in between 44% and 73% of individuals in the same cohorts. This result represents a substantial improvement in the immunogenicity of each peptide of PolyPEPI915. The immune response rates of the competing combination peptide products were between 10-62%. The invented PolyPEPI915 combination products were 96% in the model population and 93% in a breast cancer patient population, representing an improvement in immunogenicity. Table 32. Predicted Immune Response Rates of Competing Breast Cancer Vaccines Another improvement of the use of the PolyPEPI915 vaccine is the reduced possibility of tumor escape. Each 30mer peptide in PolyPEPI915 targets 2 tumor antigens. CTLs against more tumor antigens are more effective against heterologous tumor cells than CTLs against a single tumor antigen. Another improvement of the PolyPEPI915 vaccine is that individuals who are likely to respond to vaccination can be identified based on their HLA genotypes. (sequence) and, optionally, antigen expression on your tumor using the methods described here. Pharmaceutical compositions with the PolyPEPI vaccines will not be administered to individuals whose HLA cannot present any PEPI3 from the vaccines. During clinical trials, correlation will be made between the mAGP or amount of AGP in the PolyPEPI915 regimen and the duration of the individuals' responses. A combination of vaccines with > 1 AGP is more likely to be needed to kill heterologous tumor cells. Example 20 Colorectal Cancer Vaccine Design and Composition Another example is shown for the colorectal cancer vaccine composition using the same design method demonstrated above. The PEPI3+ assay described above was used to design peptides for use in colorectal cancer vaccines that are effective in a large percentage of patients, considering the heterogeneities of patient HLAs and tumor antigens. Colorectal cancer CTAs were identified and classified based on the overall expression frequencies of antigens found in colorectal cancer tumor samples as reported in peer-reviewed publications (Figure 19) (Choi J, Chang H. The expression of MAGE and SSX, and correlation of COX2, VEGF, and survivin in colorectal cancer Anticancer Res 2012. 32(2):559-564 Goossens-Beumer IJ, Zeestraten EC, Benard A, Christen T, Reimers MS, Keijzer R, Sier CF, Liefers GJ, Morreau H, Putter H, Vahrmeijer AL, van de Velde CJ, Kuppen PJ. Clinical prognostic value of combined analysis of Aldhl, Survivin, and EpCAM expression in colorectal cancer. Br .1 Cancer 2014. 110(12):2935 -2944.: Li M, Yuan YH, Han Y, Liu YX, Yan L, Wang Y, Gu J. Expression profile of cancer-testis genes in 121 human colorectal cancer tissue and adjacent normal tissue. Clinical Cancer Res 2005. 11( 5): 1809-1814). For the selection of the most frequently expressed colorectal cancer CTAs, the PEPI3+ test and the model population described in Example 8 were used to identify the "best EPIs". The reported frequency of expression for each CTA (N%) was multiplied by the frequency of PEPI3+ sites of interest in the model population (B%) to identify T cell epitopes (9 mers) that will induce an immune response against CTAs. colorectal cancer antigens in the largest proportion of individuals (Table 33). Then, 15 mers spanning each of the 9 selected mers were selected (Table 33). The 15 mers were selected to bind the greatest number of HLA class II alleles from the majority of subjects, using the process described in Example 22 below. These 15 mers can induce CTL and T helper responses in the largest proportion of subjects. Table 33 List of best PPE to select colorectal cancer peptide vaccine composition. Ntotal: number of biopsy samples (expression of tumor-specific antigen in human colorectal cancer tissues) analyzed for expression of the determined antigen; N+: number of individuals expressing the determined antigen; N%: frequency of expression of the determined antigen; B%: frequency of best EPI, that is, the percentage of individuals who have the best EPI within the model population; N%*B%: frequency of expression multiplied by the frequency of bestEPI. Then 31 peptides of 30 mer were designed. Each consists of two optimized 15-mer fragments, generally of different frequent CTAs, where the 15-mer fragments are arranged end-to-end, where each fragment comprises one of the 9 mers (best EPIs) described above. Nine of these 30mer peptides were selected for a panel of peptide vaccines, designated PolyPEPI1015 (Table 34). The expression frequencies for the 8 PolyPEPI1015 target CTAs, individually or in combination, are shown in Figure 19. Table 34 - Selected Colorectal Cancer Vaccine Peptides for PolyPEPI1015 Composition * Percentage of individuals who have PEPI3+ specific for CD8+ T cells within the model population (n=433). **Percentage of individuals who have PEPI4+-specific CD4+ T cells within the model population (n=433). Characterization of PoliPEPI1015 colorectal cancer vaccine Tumor heterogeneity: The PolyPEPI1015 composition targets 8 different CTAs (FIG. 19). Based on the antigen expression rates for these 8 CTAs, AG50=5.22 and AG95=3 (FIG. 20). Patient heterogeneity: AP50=4.73 and AP95=2 (AP95=2) (figure 21). Tumor and patient heterogeneity: AGP50 = 3.16 and AGP95 = 1 (model population) (figure 22). Example 21 - Comparison of Colorectal Cancer Vaccine Peptides with Competing Colorectal Cancer Vaccines The in silico clinical trial model described above was used to determine the response rate of state-of-the-art T cells and currently developed CRC peptide vaccines and compared to that of polyPEPI1015 (Table 34). The PEPI3 + test demonstrates that competing vaccines can induce immune responses against a tumor antigen in a fraction of subjects (2% - 77%). However, determination of multi-antigen responses (multi-PEPI) for the 2 competing multi-antigen vaccines resulted in no or 2% responders. *E1% Responders is the proportion of subjects in the model population with HLAI 1<PEPI3+ (CD8+ T cell responses) to 1, 2, 3, 4, or 5 antigens of the vaccine compositions. As multi-PEPI responses correlate with tumor vaccine-induced clinical responses, it is unlikely that any of the competing vaccines will demonstrate clinical benefit in 98% of patients. In contrast, multi-PEPI responses were predicted in 95% of subjects, suggesting the likelihood of clinical benefit in most patients. Table 35 Predicted Immune Response Rates of PolyPEPI1015 and Competing Colorectal Cancer Vaccines Example 22. Efficacy of the exemplified design procedure for the PolyPEPIlOl8 colorectal cancer vaccine PolyPEPI1018 (PolyPEPIlOl8) Colorectal Cancer (CRC) Vaccine Composition is a peptide vaccine intended for use as an add-on immunotherapy to current benchmark CRC treatment options in patients identified as potential responders using a test. accompanying in vitro diagnostic (CDx). There are current clinical trials in the United States and Italy to evaluate P0IÍPEPIIOI8 in patients with metastatic colorectal cancer. The product contains 6 peptides (6 of the 30 mer peptides of PolyPEPI1015 described in Examples 18 to 20 mixed with Montanide adjuvant. 6 peptides were selected to induce T cell responses against 12 epitopes of 7 testicular cancer antigens (CTA ) that are most frequently expressed in CRC 6 peptides were optimized to induce durable CRC-specific T cell responses Potentially responsive patients with T cell responses against multiple CTAs expressed in the tumor with an accompanying diagnosis (CDx) can be selected This example establishes the precision process used to design PolyPEPIlOl8 This process can be applied to design vaccines against other cancers and diseases A. Selection of multiple antigen targets The selection of tumor antigens is essential for the safety and efficacy of cancer vaccines. The characteristic of a good antigen is to have a restricted expression in normal tissues to avoid autoimmunity. Several categories of antigens meet this requirement, including uniquely mutated antigens (eg, p53), viral antigens (eg, human papillomavirus antigens in cervical cancer), and differentiation antigens (eg, CD20 in B-cell lymphoma). The inventors selected multiple testicular cancer antigens (CTA) as target antigens since they are expressed on various types of tumor cells and testis cells, but are not expressed on any other normal tissue or somatic cell. CTAs are desirable targets for vaccines for at least the following reasons: • tumors of higher histological grade and later clinical stage tend to have higher frequency of CTA expression • only a subpopulation of tumor cells expresses a certain CTA • different types of cancer are significantly different in its frequency of expression of CTA • tumors that are positive for a CTA usually have simultaneous expression of more than one CTA • None of the CTAs appear to be cell surface antigens, therefore, these are exclusive targets for cancer vaccines (they are not targets for suitable for antibody-based immunotherapies) To identify target CTAs for PolyPEPI1018, the inventors created a CTA expression database. This database contains CTAs that are expressed in CRCs ranked in order of rate of expression. Correlation studies by the inventors (see Example 11) suggest that vaccines that induce CTL responses against multiple antigens that are expressed on tumor cells may benefit patients. Therefore, seven CTAs with high expression rates in CRC were selected for inclusion in the development of PolyPEPI1018. The details are presented in table 36. Table 36 Target CTA in P0IÍPEPIIOI8 CRC Vaccine B. Precise targeting is achieved by PEPI3+ biomarker-based vaccine design As described above, the PEPI3+ biomarker predicts the subject's vaccine-induced T cell responses. The inventors developed and validated a test to accurately identify PEPIs from HLA genotypes and antigen sequences (Examples 1, 2, 3). The PEPI test algorithm was used to identify the dominant PEPIs (best EPIs) of the 7 target CTAs to be included in the PolyPEPI1018 CRC vaccine. Dominant PEPIs identified with the process described herein can induce CTL responses in the highest proportion of subjects: i. Identification of all HLA class I-binding PEPIs of the 7 CTA targets in each of the 433 subjects in the model populationii. Identification of the dominant PEPIs (best EPIs) that are PEPIs present in the largest subpopulation. The 12 dominant PEPIs that are derived from the 7 CTAs in PolyPEPI1018 are presented in the table below. The % PEPI in the model population indicates the proportion of 433 subjects with the indicated PEPI, ie, the proportion of subjects where the indicated PEPI can induce CTL responses. There is a very high variability (18% - 78%) in the dominant PEPIs in inducing CTL responses despite the optimization steps used in the identification process. Table 37 CRC-specific HLA class I-binding dominant PEPIs in PolyPEPI1018 The inventors optimized each dominant PEPT to bind the majority of HLA class II alleles from the majority of subjects. This should improve efficacy as it induces CD4+ T helper cells that can augment CD8+ CTL responses and contributes to long-lasting T cell responses. The example presented in Figure 4 demonstrates that PEPIs that bind to ≥3 alleles of HLA class II most likely activate helper T cells. The 15-mer peptides selected with the process described herein contain dominant HLA class I and class II binding PEPIs. Therefore, these peptides can induce CTL and T helper responses in the highest proportion of subjects. Process: 1. HLA class II genotyping of 400 normal donors*2. Extension of each 9-mer dominant PEPI (Table 33) on both sides with amino acids matching the source antigen3. HLA class II PEPI prediction of 400 normal donors using an IEDB algorithm 4. Selection of 15-mer peptide with the highest proportion of subjects having PEPI binding to HLA class II5. Ensuring the presence of a dominant HLA class II PEPI in each vaccine peptide by linking two 15-mer peptides The 12 optimized 15-mer peptides derived from the 7 CTAs in PolyPEPI1018 are presented in Table 38. These peptides have different HLA class II binding characteristics. There is high variability (0%-100%) in PEPI generating ability (^3 HLA binding) between these peptides despite such optimized custom vaccine design. Table 38 Antigen-specific HLA class II binding PEPI in PolyPEPI1018 30-mer vaccine peptides have the following advantages compared to shorter peptides: (i) Multiple precisely selected tumor-specific immunogens: Each 30-mer contains two precisely selected cancer-specific immunogenic peptides that are capable of inducing CTL and T helper responses in the majority of the relevant population (similar to the model population).(ii) Ensure natural antigen presentation. Long 30-mer polypeptides can be viewed as prodrugs: They are not biologically active by themselves, but are processed into smaller peptides (9 to 15 amino acids in length) that are loaded onto HLA molecules of professional antigen-presenting cells. . Antigen presentation resulting from long peptide vaccination reflects physiological pathways for presentation on HLA class I and class II molecules. Furthermore, the processing of long peptides in cells is much more efficient than that of large intact proteins.(iii) They exclude the induction of tolerant T cell responses. The 9-mer peptides do not require processing by professional antigen-presenting cells and therefore bind exogenously to HLA class I molecules. Thus, the injected short peptides bind in large numbers to HLA class I molecules. HLA class I of all nucleated cells that have surface HLA class I. In contrast, long peptides from >20-mers are processed by antigen-presenting cells prior to binding to HLA class I. Thus, vaccination with long peptides is less likely to lead to tolerance and promote the desired antitumor activity. . (iv) Induce long lasting T cell responses as they can stimulate T helper cell responses by binding to multiple HLA class II molecules(v) Utility. The GMP manufacturing, formulation, quality control and administration of a smaller number of peptides (each with all of the above characteristics) is more feasible than a larger number of peptides that provide different characteristics. Each 30-mer peptide in PolyPEPI1018 consists of 2 dominant HLA class I binding PEPIs and at least one strong HLA class II binding PEPI. Strong-binding PEPIs bind 4 HLA class II alleles in >50% of individuals. Therefore, the vaccine peptides are tailored to both HLA class I and class II alleles of individual subjects in a population. (which is a relevant population for the design of CRC vaccines). As demonstrated above, the high variability of HLA genotype in subjects causes a high variability of T cell responses induced by PolyPEPI1018. This justifies the co-development of a CDx that determines potential responders. The PEPI3+ and >2PEPI3+ biomarkers were able to predict the immune response and clinical responses, respectively, of P0I1PEPIIOI8 vaccinated subjects as detailed in Examples 11 and 12. These biomarkers will be used to co-develop a CDx that predicts potential vaccine responders against PolyPEPIlOL8 CRC. Example 23 - Analysis of the composition and immunogenicity of the PolyPEPIlOl 8 CRC vaccine Selected peptides for the P0IÍPEPIIOI8 composition are shown in Table 39. Table 39 - Selected Colorectal Cancer Vaccine Peptides for the P0IÍPEPIIOI8 Composition * Percentage of individuals who have PEPI3+ specific for CD8+ T cells within the model population (n=433). **Percentage of individuals who have PEPI4+-specific CD4+ T cells among normal donors (n=400). Characterization of immunogenicity The inventors used the PEPI3+ assay to characterize the immunogenicity of PolyPEPI1018 in a cohort of 37 CRC patients with full HLA genotyping data. T cell responses were predicted in each patient against the same 9mer peptides that will be used in clinical trials. These peptides represent the 12 dominant PEPI3+ peptides within P0IÍPEPIIOI8. The 9 mers are shown in table 39. The specificity and sensitivity of PEPI3+ prediction depends on the actual amount of HLA predicted to bind a particular epitope. Specifically, the inventors determined that the probability of an HLA-restricted epitope inducing a T cell response in a subject is typically 4%, which explains the poor sensitivity of state-of-the-art prediction methods based on epitope prediction. HLA-restricted. Applying the PEPI3+ methodology, the inventors determined the probability that the T cell response to each of the dominant PEPI3+-specifics is induced by PolyPEPI1018 in the 37 CRC patients. The results of this analysis are summarized in Table 40. Table 40 Probability of dominant PEPI in the 6 peptides of PolyPEPI1018 in 37 patients with CRC Abbreviations: CRC = colorectal cancer; PEPI = personal epitope Note: Percentages represent the probability of PolyPEPI1018-induced CD8+ T cell responses. Overall, these results show that the most immunogenic peptide in P0IÍPEPIIOI8 is CRC-P8, which is predicted to bind >3 HLA in the majority of patients. The less immunogenic peptide, CRC-P3, binds to >1 HLA in many patients and has a 22% chance of inducing T-cell responses. Because the bioassays used to detect T-cell responses are less precise than PEPI3+, this estimate may be the most accurate characterization of T cell responses in CRC patients. Although MAGE-A8 and SPAG9 were immunogenic in the model population used for vaccine design, MAGE-A8-specific PEPI3+ were absent in all 37 CRC patients, and only one patient (3%) had SPAG9-specific PEPI3+. Characterization of toxicity - immunoBLAST A method was developed that can be performed on any antigen to determine its potential to induce a toxic immune reaction, such as autoimmunity. The method is named in Immunoblast present. Ρ0Ι1ΡΕΡΠΟΙ8 contains six 30-mer polypeptides. Each polypeptide consists of two 15-mer peptide fragments derived from antigens expressed on CRC. Neoepitopes can be generated at the junction region of the two 15-mer peptides and can induce unwanted T cell responses against healthy cells (autoimmunity). This was evaluated using the inventors applied immunoBLAST methodology. A 16-mer peptide was designed for each of the 30-mer components of P0I1PEPIOI8. Each 16-mer contains 8 amino acids from the end of the first 15 residues of the 30-mer and 8 amino acids from the start of the second 15 residues of the 30-mer—precisely thus spanning the joining region of the two 15-mers. These 16-mers are then analyzed to identify cross-reactive regions of local similarity to human sequences using BLAST(https: / / blast.ncbi.nlm.nih.gov / Blast.cgi), which compares the protein sequences with bases of sequence data and calculates the statistical significance of the matches. 8-mers within the 16-mers were selected as the test length as that length represents the minimum length required for a peptide to form an epitope, and is the distance between anchor points during HLA binding. As shown in Figure 23, the amino acid positions in a polypeptide are numbered. The starting positions of the putative HLA-binding and neoepitope-forming 9-mer peptides are the 8 amino acids at positions 8-15. The initial positions of the peptides derived from tumor antigens harbored by the 15-mer that can form the pharmaceutically active epitopes are 7+7=14 amino acids at position 1-7 and 16-22. The proportion of potential peptides generating neoepitopes is 36.4% (8 / 22). The PEPI3+ test was used to identify neoepitopes and neoPEPI among the 9-mer epitopes in the junction region. The risk of P0I1PEPIIOI8 inducing unwanted T cell responses in the 433 subjects in the model population was assessed by determining the proportion of PEPI3+ subjects among the 9-mer in the junction region. The result of the neoepitope / neoPEPI analysis is summarized in Table 41. Across the 433 subjects in the model population, the average predicted number of epitopes that could be generated by intracellular processing was 40.12. Neoepitopes were frequently generated; 11.61 of 40.12 (28.9%) epitopes are neoepitopes. Most of the peptides could be identified as a neoepitope, but the number of subjects presenting neoepitopes varied. The epitopes harbored by P0IÍPEPIIOI8 create an average of 5.21 PEPI3+. These PEPIs can activate T cells in a subject. The number of possible neoPEPIs was much lower than the number of neoepitopes (3.7%). There is a small possibility that these neoPEPIs may compete for T cell activation with PEPIs in some subjects. Importantly, activated neoPEPI-specific T cells did not target healthy tissue. Table 41 - Identification of possible neoepitopes of PolyPEPI1018 Abbreviations: CRC = colorectal cancer; HLA = human leukocyte antigen; PEPI = personal epitope Each of the 30-mer peptides in PolyPEPI1018 were released for clinical development as none of the 8-mer in the binding regions matched any human protein except the target CTAs. Characterization of activity / efficacy The inventors have developed pharmacodynamic biomarkers to predict the activity / effect of vaccines in individual human subjects as well as in populations of human subjects. These biomarkers facilitate more efficient vaccine development and also lower the cost of development. Inventors have the following tools: Antigen Expression Database: The inventors have collected data from experiments published in peer-reviewed scientific journals on tumor antigens expressed by tumor cells and organized by tumor type to create a database of CTA expression levels - database of CTA (CTADB). As of April 2017, the CTADB contained data on 145 CTAs from 41,132 tumor samples, and was organized according to the frequencies of CTA expression in the different cancer types. In silico test populations: The inventors have also collected data on the HLA genotypes of several different model populations. Each individual in the populations has a complete 4-digit HLA genotype and ethnic data. The populations are summarized in Table 42. Table 42 In silico test populations Abbreviations: CRC = colorectal cancer; HLA = human leukocyte antigen Using these tools (or potentially equivalent databases or model populations), the following markers can be assessed: • GA95 - potency of a vaccine: the amount of antigens in a cancer vaccine that a specific tumor type expresses with a 95 % probability. AG95 is an indicator of vaccine potency and is independent of the immunogenicity of the vaccine antigens. AG95 is calculated from tumor antigen expression rate data, which is collected in the CTADB. Technically, AG95 is determined from the CTA binomial distribution, and considers all possible variations and expression rates. In this study, AG95 was calculated by accumulating the probabilities of a given number of expressed antigens, over the widest range of antigens where the sum of probabilities was less than or equal to 95%. The correct value is between 0 (no expression expected with 95% probability) and maximum amount of antigens (all antigens expressed with 95% probability).• PEPI3+ count - immunogenicity of a vaccine in a subject: Vaccine-derived PEPI3+ are signature epitopes that induce T cell responses in a subject. PEPI3+ can be determined using the PEPI3+ test in subjects whose full 4-digit HLA genotype is known. • PA Count - Antigenicity of a Vaccine in a Subject: Amount of PEPI3+ vaccine antigens. Vaccines such as PoliPEPI1018 contain antigen sequences expressed on tumor cells. The PA count is the number of antigens in the vaccine that contain PEPI3+, and the PA count represents the number of antigens in the vaccine that can induce T cell responses in a subject. The AP count characterizes the responses of T cells specific for the subject's vaccine antigen as it depends only on the subject's HLA genotype and is independent of the subject's disease, age, and medication. The correct value is between 0 (no PEPI presented by the antigen) and the maximum number of antigens (all antigens present PEPI). • AP50 - antigenicity of a vaccine in a population: The average amount of vaccine antigens with a PEPI in a population. The AP50 is suitable for the characterization of vaccine antigen-specific T cell responses in a given population since it is dependent on the HLA genotype of subjects in a population. Technically, the PA count was calculated in the model population and the binomial distribution of the result was used to calculate the PA50. • AGP count - efficacy of a vaccine in a subject: amount of vaccine antigens expressed in the tumor with PEPI . The AGP count indicates the amount of tumor antigens that the vaccine recognizes and induces a T-lymphocyte response against them (achieves the target). The AGP count depends on the rate of expression of the vaccinia antigen in the subject's tumor and the subject's HLA genotype. The correct value is between 0 (no PEPI presented by the expressed antigen) and the maximum number of antigens (all antigens are expressed and present a PEPI).• AGP50 - efficacy of a cancer vaccine in a population: the amount Mean number of vaccine antigens expressed in PEPI-indicated tumor (ie, AGP) in a population. The AGP50 indicates the mean amount of tumor antigens that can be recognized by vaccine-induced T cell responses. AGP50 depends on the expression rate of the antigens in the indicated tumor type and the immunogenicity of the antigens in the target population. AGP50 can estimate vaccine efficacy in different populations and can be used to compare different vaccines in the same population. The calculation of AGP50 is similar to that used for AG50, except that expression is weighted by the occurrence of PEPI3+ in the subject at expressed vaccine antigens. In a theoretical population, where each subject has a PEPI of each vaccine antigen, the AGP50 will be equal to AG50. In another theoretical population, where no subject has a PEPI of any vaccine antigen, the AGP50 will be 0. In general, the following statement is valid: 0 > AGP50 > AG50.• mAGP - a candidate biomarker for the selection of potential responders: probability that a cancer vaccine will induce T cell responses against multiple antigens expressed in the indicated tumor. mAGP is calculated from the expression rates of vaccine antigens in CRC and the presence of vaccine-derived PEPI in the subject. Technically, based on the AGP distribution, the mAGP is the sum of the probabilities of the multiple AGPs (<2 AGPs). Application of these markers to evaluate the antigenicity and efficacy of PolyPEPI1018 in individual patients with CRC Table 43 shows the antigenicity and efficacy of PolyPEPIlOl8 in 37 CRC patients using AP and AGP50, respectively. As expected from the high variability of P0IIPPEPIIOI8-specific T cell responses (see Table 41), AP and AGP50 have high variability. The most immunogenic antigen in P0IÍPEPIIOI8 was FOXO39; each patient had a PEPI3+. However, FOXO39 is expressed in only 39% of CRC tumors, suggesting that 61% of patients will have FOXO39-specific T cell responses that do not recognize the tumor. The least immunogenic antigen was MAGE-A8; none of the 37 CRC patients had a PEPI3+ even though the antigen was expressed in 44% of CRC tumors. These results illustrate that both the expression and the immunogenicity of antigens can be considered when determining the efficacy of a cancer vaccine. AGP50 indicates the mean amount of antigens expressed in CRC tumor with PEPI. Patients with higher AGP50 values ​​are more likely to respond to PolyPEPIL 8 as higher AGP50 values ​​indicate that the vaccine may induce T cell responses against more antigens expressed on CRC cells. The last column in Table 43 shows the probability of mAGP (multiple AGP; ie, at least 2 AGP) in each of the 37 CRC patients. The average mAGP in CRC patients is 66%, suggesting that there is a 66% chance that a CRC patient will induce T-cell responses against multiple tumor-expressed antigens. Table 43 - Antigenicity (PA count), efficacy (AGP50 count) and mAGP of PolyPEPIlOl8 in 37 patients with CRC Abbreviations: CRC = colorectal cancer; PEPI = personal epitope; CTA = testicular cancer antigen; AP = antigens expressed with <1 PEPI These biomarkers have immediate utility in vaccine development and routine clinical practice as they do not require invasive biopsies. Antigen expression data can be obtained from the achieved tumor sample and can be organized in databases. 4-digit HLA genotyping can be performed from a saliva sample. It is a validated test performed by certified laboratories around the world for paternity and transplant testing. These evaluations will allow drug developers and clinicians to gain deeper insights into the immunogenicity and activity of the tumor response and the potential emergence of resistance. Application of these markers to assess the antigenicity and efficacy of PolyPEPI1018 in populations Antigenicity of PolyPEPI1018 CRC Vaccine in a General Population The antigenicity of P0IIPPEPIIOI8 in a subject is determined by the AP count, which indicates the amount of vaccine antigens that induce T cell responses in a subject. The P0IÍPEPIIOI8 AP count was determined in each of the 433 subjects in the model population using the PEPI test, and then the AP50 count was calculated for the model population. As shown in Figure 24, the AP50 of P0IÍPEPIIOI8 in the model population is 3.62. Therefore, the mean number of immunogenic antigens (ie, antigens with <1 PEPI) on PolyPEPI1018 in a general population is 3.62. Efficacy of PolyPEPI1018 CRC Vaccine in a General Population Vaccine-induced T cells can recognize and kill tumor cells if the tumor cell presents a PEPI in the vaccine. The amount of AGP (PEPI-expressed antigens) is an indicator of vaccine efficacy in an individual, and depends on the potency and antigenicity of PolyPEPI1018. As shown in Figure 25, the mean number of immunogenic CTAs (ie, APs [antigens expressed with <1 PEPI]) in P0IÍPEPIIOI8 is 2.54 in the model population. The probability that P0I1PEPIIOI8 will induce T-cell responses against multiple antigens in one subject (ie, mAGP) in the model population is 77%. Comparison of PolyPEPI1018 CRC Vaccine Activities in Different Populations Table 44 shows the comparison of the immunogenicity, antigenicity and efficacy of PolyPEPI1018 in different populations. Table 44 - Comparison of immunogenicity, antigenicity and efficacy of P0IÍPEPIIOI8 in different subpopulations Abbreviations: CRC = colorectal cancer; PEPI = personal epitope; SD = standard deviation; AP = antigens expressed with <1 PEPI The average amount of PEPI3+ and the AP results demonstrate that P0IÍPEPIIOI8 is highly immunogenic and antigenic in all populations; P0IIPPEPIIOI8 can induce an average of 3.7-6.0 clones of CRC-specific T cells against 2.9-3.7 CRC antigens. The immunogenicity of PolyPEPI1018 was similar in CRC patients and the average population (p>0.05), this similarity may be due to the small sample size of the CRC population. Additional analyzes suggest that P0IÍPEPIIOI8 is significantly more immunogenic in a Chinese population compared to an Irish population or a general population (p<0.0001). Differences in immunogenicity are also reflected in vaccine efficacy as characterized by AGP50; PolyPEPI1018 is more effective in a Chinese population and less effective in an Irish population. Because a CDx will be used to screen for potential P0IÍPEPIIOI8 responders, ethnic differences will only be reflected in the higher percentage of Chinese individuals who might be eligible for treatment compared to Irish individuals. Example 24 - Personalized immunotherapy composition for the treatment of a patient with metastatic breast cancer in an advanced state. Patient BRC05 was diagnosed with inflammatory breast cancer on the right with extensive carcinomatous lymphangiosis. Inflammatory breast cancer (IBC) is a rare but aggressive form of locally advanced breast cancer. It is called inflammatory breast cancer because its main symptoms are swelling and redness (the breast often looks swollen). Most inflammatory breast cancers are invasive ductal carcinomas (start in the milk ducts). This type of breast cancer is associated with the expression of high-risk human papillomavirus oncoproteins1. In fact, HPV 16 DNA was diagnosed in this patient's tumor. Patient stage in 2011 (6 years before treatment with the PIT vaccine) T4: Tumor of any size with direct extension to the chest wall and / or skin (ulceration or skin nodules) pN3a: Metastasis in < 10 axillary lymph nodes ( at least 1 tumor deposit > 2.0 mm); or metastases to infraclavicular (level III axillary lymph nodes). 14 vaccine peptides were designed and prepared for patient BRC05 (Table 45). Peptides PBRC05-P01-P10 were prepared for this patient based on population expression data. The last 3 peptides in Table 45 (SSX-2, MORC, MAGE-B1) were designed from antigens whose expression was measured directly in the patient's tumor. Table 45 - Vaccine peptides for patient BRC05 Note: bold and red means CD8 PEPI, underlined means best binding CD4 allele. 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Claims

1. A method for predicting the cytotoxic T lymphocyte response rate and / or the helper T lymphocyte response rate of a specific or target human population to the administration of a polypeptide or to the administration of a pharmaceutical composition, kit, or polypeptide panel comprising one or more polypeptides as active ingredients, wherein the method comprises (i) selecting or defining a relevant model human population comprising multiple subjects, each defined by HLA class I genotype and / or HLA class II genotype; (ii) determining for each subject in the model human population whether the polypeptide or polypeptides together comprise (a) at least one amino acid sequence that is a T lymphocyte epitope capable of binding to at least two HLA class I molecules of the subject; and / or (b) at least one amino acid sequence that is a T lymphocyte epitope capable of binding to at least two HLA class II molecules of the subject; and (iii) predicting A.the cytotoxic T lymphocyte response rate of said human population, wherein a higher proportion of the model human population that meets the requirements of step (ii)(a) predicts a higher cytotoxic T lymphocyte response rate in said human population; and / or B. the helper T lymphocyte response rate of said human population, wherein a higher proportion of the model human population that meets the requirements of step (ii)(b) predicts a higher helper T lymphocyte response rate in said human population.

2. A method for predicting the clinical response rate of a specific human population or target to the administration of a pharmaceutical composition, kit, or polypeptide panel comprising one or more polypeptides as active ingredients, wherein the method comprises (i) selecting or defining a relevant model human population comprising multiple subjects, each defined by HLA class I genotype; (ii) determining (a) for each subject in the model human population whether the active ingredient polypeptide(s) together comprise at least two different amino acid sequences, each of which is a T-cell epitope capable of binding to at least two HLA class I molecules of the subject, wherein, optionally, the at least two different amino acid sequences are comprised within the amino acid sequence of two different polypeptide antigens that are targets of the active ingredient polypeptides;(b) in the model population the average amount of target polypeptide antigens comprising at least one amino acid sequence A. that is a T lymphocyte epitope capable of binding to at least three HLA class I molecules of individual subjects in the model population; and B. that is included in the amino acid sequence of the polypeptides of the active ingredient; and / or (c) in the model population the average amount of expressed target polypeptide antigens comprising at least one amino acid sequence A. that is a T lymphocyte epitope capable of binding to at least three HLA class I molecules of individual subjects in the model population; and B. that is included in the amino acid sequence of the polypeptides of the active ingredient;and (iii) predict the clinical response rate of said human population, wherein a higher proportion of the model human population meeting the requirements of step (ii)(a), a higher mean amount of target polypeptides in step (ii)(b), or a higher mean amount of target polypeptides expressed in step (ii)(c) predicts a higher clinical response rate in said human population.

3. The method of claim 1 or claim 2 further comprising repeating the method for one or more additional polypeptides, pharmaceutical compositions, kits or polypeptide panels, and classifying the polypeptides, pharmaceutical compositions, kits or polypeptide panels according to their predicted cytotoxic T lymphocyte, helper T lymphocyte or clinical response rates in said specific human or target population.

4. The method of any one of claims 1 to 3 further comprising selecting or recommending treatment for a subject in need by administering one or more polypeptides or pharmaceutical compositions or the polypeptides from one or more polypeptide kits or panels, based on their predicted response rate or response rate classification.

5. The method of claim 4, wherein (a) a polypeptide, pharmaceutical composition, kit, or polypeptide panel having a high predicted response rate or response rate classification is selected or recommended to induce a therapeutic immune response in the subject; or (b) a polypeptide, pharmaceutical composition, kit, or polypeptide panel having a low predicted response rate or response rate classification is selected or recommended to avoid a toxic immune response.

6. The method of claim 4 or claim 5 further comprising administering one or more of the selected polypeptides or pharmaceutical compositions or the polypeptides from one or more polypeptide kits or panels to the subject.

7. A method of treating a human subject in need thereof, wherein the method comprises administering to the subject one or more polypeptides or pharmaceutical compositions that were selected or recommended for the treatment of the subject using a method according to claim 4 or claim 5. 8.A method for designing or preparing a polypeptide, or a polynucleic acid encoding a polypeptide, for use in a method of inducing an immune response in a subject from a specific human or target population, wherein the method comprises (i) selecting or defining (a) a relevant human model population comprising multiple subjects, each defined by HLA class I genotype and / or HLA class II genotype; or (b) a relevant human model population comprising multiple subjects, each defined by HLA class I genotype and a relevant human model population comprising multiple subjects, each defined by HLA class II genotype; (ii) identifying a fragment of up to 50 consecutive amino acids from a target polypeptide antigen comprising or consisting of A.A. a T lymphocyte epitope capable, in a high percentage of subjects in a model population selected or defined in step (i) that is defined by the HLA class I genotype, of binding to at least three HLA class I molecules from individual subjects; B. a T lymphocyte epitope capable, in a high percentage of subjects in a model population selected or defined in step (i) that is defined by the HLA class II genotype, of binding to at least three HLA class II molecules from individual subjects; or C.a T lymphocyte epitope capable, in a high percentage of subjects from a model population selected or defined in step (i) that is defined by the HLA class I genotype, of binding to at least three HLA class I molecules from individual subjects and a T lymphocyte epitope capable, in a high percentage of subjects from a model population selected or defined in step (i) that is defined by the HLA class TI genotype, of binding to at least three HLA class II molecules from individual subjects; (iii) if the polypeptide fragment selected in step (ii) is an HLA class I binding epitope, optionally selecting a longer fragment of the target polypeptide antigen, wherein the longer fragment comprises or consists of an amino acid sequence that F. comprises the fragment selected in step (ii); and G.is a T lymphocyte epitope that binds to class II HLA molecules capable, in a high percentage of subjects in a selected or defined model population (defined in step (i) by the class II HLA genotype), of binding to at least three or as many class II HLA molecules as possible from individual subjects; and (iv) designing or preparing a polypeptide or polynucleic acid encoding a polypeptide comprising one or more polypeptide fragments identified in step (ii) or step (iii), wherein, optionally, the polypeptide fragment is flanked at the N and / or C end by additional amino acids that are not part of the target polypeptide antigen sequence.

9. The method of claim 8 comprising identifying one or more additional fragments of the same antigen or of one or more different target polypeptide antigens, wherein each polypeptide fragment is a T-cell epitope capable of binding to at least three HLA class I molecules or at least three HLA class II molecules from at least one subject in the model population; and classifying the fragments by (i) the percentage of subjects in the model population expressing at least three HLA class I molecules capable of binding to the fragment; (ii) the percentage of subjects in the model population predicted to express the target polypeptide antigen comprising the fragment and at least three HLA class I molecules capable of binding to the fragment; (iii) the percentage of subjects in the model population expressing at least three HLA class II molecules capable of binding to the fragment;(iv) the percentage of subjects in the model population predicted to express the target polypeptide antigen comprising the fragment and at least three TT class HLA molecules capable of binding to the fragment; (v) the percentage of subjects in the model population expressing at least three class I HLA molecules and at least three class II HLA molecules capable of binding to the fragment; or (iv) the percentage of subjects in the model population predicted to express the target polypeptide antigen comprising the fragment and at least three class I HLA molecules and at least three class II HLA molecules capable of binding to the fragment.

10. The method of claim 9 comprising selecting one or more of the polypeptide fragments based on their classification, and designing or preparing the polypeptide to comprise, or the polynucleic acid to encode, the selected polypeptide fragment(s).

11. The method of any of claims 8 to 10 further comprising designing or preparing a polypeptide, a panel of polypeptides, a pharmaceutical composition or a kit comprising one or more polypeptides as active ingredients for use in a method of inducing an immune response in a subject of the specific human population or target, wherein the polypeptides or polypeptides of the active ingredient comprise at least two polypeptide fragments, optionally between 2 and 15 polypeptide fragments, selected according to the method of claim 8 or claim 10. 12.The method of claim 11, wherein two or more or each of the fragments are from different target polypeptide antigens, optionally different target polypeptide antigens selected from the antigens listed in Tables 2 to 6 and / or different cancer-associated antigens, optionally wherein one or more or each of the cancer-associated antigens are CTA.

13. The method of claim 11 or claim 12, wherein two or more or each of the fragments are arranged in the polypeptide end with end.14.The method of claim 13 further comprising analyzing all neoepitopes formed at the junction between any two of the selected polypeptide fragments arranged end-to-end in a single polypeptide to remove peptides comprising a neoepitope amino acid sequence that (i) corresponds to a fragment of a human polypeptide expressed in healthy cells; (ii) is a T-cell epitope capable of binding, in more than a threshold percentage of human subjects, to at least two HLA class I molecules expressed by individual subjects; (i) meets requirements (i) and (ii).

15. The method of any of claims 8 to 14, wherein the polypeptide(s) were analyzed to remove polypeptides comprising an amino acid sequence that (i) corresponds to a fragment of a human polypeptide expressed in healthy cells; or (ii) corresponds to a fragment of a human polypeptide expressed in healthy cells and is a T-cell epitope capable of binding to at least two subject class I HLA molecules.

16. A method of inducing an immune response in a subject from a specific human or target population, wherein the method comprises designing or preparing a polypeptide, a panel of polypeptides, a polynucleic acid encoding a polypeptide, a pharmaceutical composition, or a kit for use in said specific human or target population according to the method of any of claims 8 to 15 and administering the polypeptides, polynucleic acid, pharmaceutical composition, or the polypeptides of the active ingredient of the kit to the subject. 17.A polypeptide, a polypeptide panel, a polynucleic acid, a pharmaceutical composition, or a kit for use in a method of inducing an immune response in a subject from a specific human population or target, wherein the polypeptide, polypeptide panel, polynucleic acid, pharmaceutical composition, or kit is designed or prepared according to the method of any one of claims 8 to 16 for use in said specific human population or target, and wherein the composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier, or preservative.18.A pharmaceutical composition, polypeptide panel, or kit for use in a method of inducing an immune response in a subject from a specified or target human population, wherein the pharmaceutical composition, polypeptide panel, or kit comprises as active ingredients a first polypeptide and a second polypeptide and, optionally, one or more additional polypeptides, wherein each polypeptide comprises an amino acid sequence that is a T-cell epitope capable of binding to at least three HLA class I molecules from at least 10% of subjects in the specified or target population, wherein the T-cell epitope of the first region, the second region, and, optionally, any additional regions are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier, or preservative.

19. A pharmaceutical composition, polypeptide panel, or kit for use in a method of inducing an immune response in a human subject, wherein the pharmaceutical composition, polypeptide panel, or kit comprises a polypeptide of the active ingredient comprising a first region and a second region and, optionally, one or more additional regions, wherein each region comprises an amino acid sequence that is a T-cell epitope capable of binding to at least three HLA class I molecules from at least 10% of subjects in the specified or target population, wherein the T-cell epitope of the first region, the second region, and, optionally, any additional regions are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier, or preservative. 20.The pharmaceutical composition, polypeptide panel, or kit for use thereof of claim 18 or 19, wherein the amino acid sequence of one or more or each of the T lymphocyte epitopes is from a polypeptide selected from the antigens listed in Tables 2 to 6, or is a cancer-associated antigen, wherein, optionally, one or more or each of the cancer-associated antigens is a CTA.

21. The pharmaceutical composition, polypeptide panel, or kit for use thereof of claims 18 to 20, wherein the amino acid sequence of two or more or each of the T lymphocyte epitopes is from a different polypeptide selected from the antigens listed in Tables 2 to 6, and / or different cancer-associated antigens, wherein, optionally, one or more or each of the cancer-associated antigens is a CTA.22.A pharmaceutical composition, polypeptide panel, or kit for use in a method treating cancer in a subject in need, wherein the pharmaceutical composition, polypeptide panel, or kit comprises as active ingredients a first peptide and a second peptide and, optionally, one or more additional peptides, wherein each peptide comprises an amino acid sequence that is an HLA class I binding T-cell epitope, wherein at least 10% of human subjects having cancer express a tumor-associated antigen selected from the antigens listed in Table 2 comprising said T-cell epitope; and iv.have at least three class I HLA molecules capable of binding to said T lymphocyte epitope; wherein said T lymphocyte epitope of the first peptide, the second peptide and, optionally, any additional peptides are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier or preservative.

23. A pharmaceutical composition, polypeptide panel, or kit for use in a method for treating cancer in a subject in need, wherein the pharmaceutical composition, polypeptide panel, or kit comprises a polypeptide of the active ingredient comprising a first region and a second region and, optionally, one or more additional regions, wherein each region comprises an amino acid sequence that is an HLA class I binding T-cell epitope, wherein at least 10% of human subjects with cancer (a) express a tumor-associated antigen selected from the antigens listed in Table 2 comprising said T-cell epitope; and (b) have at least three HLA class I molecules capable of binding to said T-cell epitope;wherein said T lymphocyte epitope of the first region, the second region and, optionally, any additional region are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier or preservative.

24. A pharmaceutical composition, polypeptide panel, or kit for use in a method for treating selected cancers, including colorectal, breast, ovarian, melanoma, non-melanoma skin cancer, lung, prostate, kidney, bladder, stomach, liver, cervical, esophageal, non-Hodgkin lymphoma, leukemia, pancreatic, uterine, lip, oral cavity, thyroid, brain, nervous system, gallbladder, larynx, pharynx, myeloma, nasopharyngeal cancer, Hodgkin lymphoma, testicular cancer, and Kaposi sarcoma, in a subject in need thereof, wherein the pharmaceutical composition, polypeptide panel, or kit comprises as active ingredients a first polypeptide and a second polypeptide and, optionally, one or more additional polypeptides, wherein each polypeptide comprises an amino acid sequence that is an HLA-binding T-cell epitope of class I,wherein at least 10% of human subjects having said cancer (a) express a tumor-associated antigen selected from the antigens listed in Table 2 comprising said T-cell epitope; and (b) have at least three class I HLA molecules capable of binding to said T-cell epitope; wherein said T-cell epitope of the first peptide, the second peptide, and optionally any additional peptides are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier, or preservative.

25. A pharmaceutical composition, polypeptide panel, or kit for use in a method for treating a selected cancer from colorectal, breast, ovarian, melanoma, non-melanoma skin cancer, lung, prostate, kidney, bladder, stomach, liver, cervical, esophageal, non-Hodgkin lymphoma, leukemia, pancreatic, uterine, lip, oral cavity, thyroid, brain, nervous system, gallbladder, larynx, pharynx, myeloma, nasopharyngeal cancer, Hodgkin lymphoma, testicular cancer, and Kaposi sarcoma in a subject in need thereof, wherein the pharmaceutical composition, polypeptide panel, or kit comprises an active ingredient polypeptide comprising a first region and a second region and, optionally, one or more additional regions, wherein each region comprises an amino acid sequence that is an HLA-binding T-cell epitope of class I,wherein at least 10% of human subjects having said cancer (a) express a tumor-associated antigen selected from the antigens listed in Table 2 comprising said T-cell epitope; and (b) have at least three HLA class I molecules capable of binding to said T-cell epitope; wherein said T-cell epitope of the first polypeptide, the second polypeptide, and optionally any additional polypeptides are different from each other, and wherein the pharmaceutical composition or kit optionally comprises at least one pharmaceutically acceptable diluent, carrier, or preservative.

26. A method of treating a human subject in need thereof, wherein the method comprises administering to the subject a polypeptide, a panel of polypeptides, a pharmaceutical composition, or the polypeptides of the active ingredient of a kit according to any one of claims 17 to 25, wherein the subject is determined to express at least three HLA class I molecules and / or at least three HLA class II molecules capable of binding to the polypeptide or to one or more of the polypeptides of the active ingredient of the pharmaceutical composition or kit.

27. The method of claim 26, wherein the subject is determined to express at least three HLA class I molecules and / or at least three HLA class II molecules capable of binding to a minimum threshold number of T-cell epitopes other than the polypeptide, or the polypeptides of the active ingredient of the pharmaceutical composition or kit. 28.The method of claim 26 or claim 27, wherein it has been determined that the polypeptides of the active ingredient of the pharmaceutical composition, kit, or polypeptide panel together comprise at least two different sequences, each of which is a T-cell epitope capable of binding to at least three subject class I HLA molecules, wherein, optionally, the at least two different amino acid sequences are comprised within the amino acid sequence of two different polypeptide antigens that are targets of the polypeptides of the active ingredient.29.The method of any of claims 26 to 28, wherein the pharmaceutical composition has been determined to have a minimum probability above a threshold of inducing a clinical response in the subject, wherein one or more of the following factors correspond to a higher probability of clinical response: (a) presence in the polypeptides of the active ingredient of a greater number of amino acid sequences and / or different amino acid sequences that are each a T-cell epitope capable of binding to at least three class I HLA of the subject; (b) a greater number of target polypeptide antigens comprising at least one amino acid sequence that A. is comprised in a polypeptide of the active ingredient; and B.is a T lymphocyte epitope capable of binding to at least three class I HLA of the subject; wherein, optionally, the target polypeptide antigens are expressed in the subject, wherein, furthermore, optionally, the target polypeptide antigens are found in one or more samples obtained from the subject; (c) a higher probability of the subject expressing target polypeptide antigens, optionally a threshold amount of the target polypeptide antigens and / or optionally target polypeptide antigens that have been determined to comprise at least one amino acid sequence that A. is comprised in a polypeptide of the active ingredient; and B.is a T-cell epitope capable of binding to at least three class I HLAs of the subject; and / or (d) a greater number of target polypeptide antigens predicted to be expressed by the subject, optionally a greater number of target polypeptide antigens that the subject expresses with a threshold probability, and / or optionally target polypeptide antigens that have been determined to comprise at least one amino acid sequence that A. is comprised in a polypeptide of the active ingredient; and B. is a T-cell epitope capable of binding to at least three class I HLAs of the subject.

30. The method of claim 29, wherein the probability of a clinical response has been determined by a method comprising (i) identifying which target polypeptide antigens of the active ingredient polypeptides comprise an amino acid sequence that A. is comprised in a polypeptide of the active ingredient; and B.(i) is a T-cell epitope capable of binding to at least three class I HLA of the subject; (ii) use population expression data for each antigen identified in step (i) to determine the probability that the subject expresses one or more of the antigens identified in step (i) that together comprise at least two different amino acid sequences from step (i); and (iii) determine the probability that the subject will have a clinical response to the administration of the pharmaceutical composition, kit, or polypeptide panel, wherein a higher probability determined in step (ii) corresponds to a more likely clinical response.

31. A system comprising (a) a storage module configured to store data comprising the HLA class I and / or class II genotypes of each subject in a model population of human subjects; and the amino acid sequence of one or more test polypeptides; wherein the model population is representative of a human target test population; and (b) a computing module configured to identify and / or quantify the amino acid sequences in the test polypeptide(s) that are capable of binding to multiple HLA class T molecules of each subject in the model population and / or the amino acid sequences in the test polypeptide(s) that are capable of binding to multiple HLA class II molecules of each subject in the model population.

32. The system of claim 31 further comprising (c) an output module configured to present (i) a prediction of the cytotoxic T lymphocyte response rate and / or the helper T lymphocyte response rate of the human test target population to the administration of the polypeptide(s), or one or more pharmaceutical compositions comprising the polypeptide(s) as active ingredients; or (ii) a prediction of the clinical response rate of the human test target population to a treatment method comprising the administration of one or more pharmaceutical compositions comprising the polypeptide(s) as active ingredients.