Use of immunologic efficacy or clinical relative immunologic efficacy in assessing the strength of a vaccine response in a subject

Abstract

The present application provides an immune efficacy ε or a clinical relative immune efficacy ε * The application belongs to the field of biomedical technology and is used in evaluating the strength of a vaccine response of a subject. The present application selects a clinical index capable of detecting immune efficacy and predicting the strength of a vaccine response by comprehensively considering the core signal pathway involved in human immune response, the in vivo circulation of lymphocytes and cytokines, and the dynamic process of innate and adaptive immune response of the host to the antigen, and proposes a method for evaluating the immune efficacy ε or the clinical relative immune efficacy ε * The immune efficacy ε is the immune efficacy ε of the immune system in killing infected cells k The immune efficacy ε is the immune efficacy ε of the immune system in killing infected cells c The immune efficacy ε is the immune efficacy ε of the immune system in killing infected cells The present application also relates to a method, system and kit for evaluating the immunity of a subject after vaccination by using the clinical index.

Description

[0001] This application is a divisional application of the invention entitled "Application of Immunovalidation or Clinical Relative Immunovalidation in Evaluating the Intensity of Vaccine Response in Subjects", filed on June 14, 2022, with application number CN202210667994.7. Technical Field

[0002] This invention belongs to the field of biomedical technology, specifically relating to immunogenicity ε or clinical relative immunogenicity ε. * Application in evaluating the strength of vaccine response in subjects. Background Technology

[0003] Individuals with weakened immune systems, particularly those with impaired type I interferon (IFN) responses and reduced HLA-II expression levels, are more likely to experience severe symptoms after infection with the novel coronavirus. These symptoms include lymphopenia and cytokine release syndrome (also known as cytokine storm), accompanied by elevated levels of the pro-inflammatory cytokine IL-6.

[0004] Numerous clinical trials and antiviral treatments for COVID-19 (SARS-CoV-2) patients have been reported. Currently, 33 COVID-19 vaccines are used in different countries, with protection rates ranging from 50% to 95%. In clinical practice, virus-specific neutralizing antibody levels are now used as a universal indicator of vaccine efficacy to reflect vaccine effectiveness.

[0005] In fact, the human immune system is a complex defense system involving dozens of different cell types and hundreds of interactions. In the last decade of the 20th century, mathematical modeling was developed for clinical data on HIV, HBV, and HCV infections. In a 2007 influenza virus infection model, the anti-infection capacity of interferon-induced respiratory epithelial cells and the ability of effector cells to remove infected cells were used as indicators of innate immunity, while virus-specific antibodies were used as indicators of adaptive immunity. This model consisted of 10 ordinary differential equations with 27 parameters, used to characterize the rates of various processes leading to disease progression (doi: https: / / doi.org / 10.1016 / j.jtbi.2006.12.015). However, this model did not consider multiple cell types and cytokines, and the clinical indicators were incomplete; therefore, a unified indicator for measuring the strength of immunity was not obtained. Summary of the Invention

[0006] In view of this, the object of the present invention is to provide immunogenicity ε or clinical relative immunogenicity ε. * In evaluating the strength of a subject's vaccine response, this invention provides a unified index for measuring the strength of a subject's immunity.

[0007] This invention provides immunogenicity ε or clinical relative immunogenicity ε. * Application in evaluating the strength of vaccine response in subjects,

[0008] The immunogenicity ε is calculated according to Equation 1:

[0009] ε=ε k ·ε c Formula 1;

[0010] The immunogenicity ε* is calculated according to Equation 4:

[0011]

[0012] Wherein, the ε k To enhance the immunogenicity of the immune system in killing infected cells, the ε c The immunogenicity of the immune system in killing infecting viruses; The relative immunogenicity of the immune system in killing infected cells, the The relative immunogenicity of the immune system in killing infecting viruses;

[0013] The ε k Calculated according to Equation 2:

[0014]

[0015] The ε c Calculated according to Equation 3:

[0016]

[0017] In Equations 2 and 3, [Mphi], [Neut], [NK], [CTL], and [CD8+T] are used. M The cell counts of the subjects are as follows: macrophages, neutrophils, natural killer cells, virus-specific cytotoxic T cells, and virus-specific CD8+ memory T cells; [nAb] represents the level of virus-specific neutralizing antibodies in peripheral blood; k Mphi k NK , The rates at which the macrophages, natural killer cells, virus-specific cytotoxic T cells, and virus-specific CD8+ memory T cells kill infected cells are respectively; d If c represents the rate of apoptosis in infected cells. Mphi as well as The rates at which the macrophages and neutrophils clear the virus, respectively. The rate at which the peripheral blood virus-specific neutralizing antibody neutralizes viral particles;

[0018] Among them, the as well as The following formulas are used to calculate the following: (Formulas 5-6 and 8-14)

[0019]

[0020]

[0021]

[0022]

[0023]

[0024]

[0025]

[0026]

[0027]

[0028] In Equations 5-6 and 8-14, [Mono] represents the percentage or count of peripheral blood mononuclear cells in the subject, [T] represents the cell count of cells releasing IFN-γ after antigen stimulation in the subject's peripheral blood, [Neut] represents the percentage or count of peripheral blood neutrophils in the subject, [nAb] represents the level of virus-specific neutralizing antibodies in the subject's peripheral blood / the level of total antibodies in the peripheral blood, [B] represents the percentage or count of peripheral blood neutrophils in the subject's peripheral blood, [NAb] represents the level of virus-specific neutralizing antibodies in the subject's peripheral blood / the level of total peripheral blood antibodies, [B] represents the percentage or count of peripheral blood neutrophils in the subject's peripheral blood, [NAb ... M [ ] represents the count of virus-specific memory B cells in the peripheral blood of the subject; Mono% represents the percentage of mononuclear cells in the peripheral blood of the subject; Neut% represents the percentage of neutrophils in the peripheral blood of the subject; and Lym% represents the percentage of lymphocytes in the peripheral blood of the subject.

[0029] Preferably, the vaccine comprises a viral vaccine; preferably, the virus comprises a respiratory virus; preferably, the respiratory virus comprises an influenza virus or a coronavirus; preferably, the influenza virus is an influenza A virus or an influenza B virus; preferably, the coronavirus is SARS, MERS, or SARS-CoV-2.

[0030] This invention also provides a method for detecting the immunogenicity or clinical relative immunogenicity of a subject, comprising: measuring the subject's clinical indicators:

[0031] The clinical indicators are selected from the first clinical indicator, the second clinical indicator, the third clinical indicator, the fourth clinical indicator, the fifth clinical indicator, or the sixth clinical indicator;

[0032] The first clinical indicator includes: the peripheral blood immune cell count and the peripheral blood virus-specific neutralizing antibody level of the subject; the immune cells include: macrophages, neutrophils, natural killer cells, virus-specific cytotoxic T cells and virus-specific CD8+ memory T cells;

[0033] The second clinical indicator includes: the percentage or count of peripheral blood mononuclear cells in the subject, the concentration of interferon-gamma in peripheral blood after antigen stimulation, the background level of IFN-γ, the percentage or count of peripheral blood neutrophils, and the level of virus-specific neutralizing antibodies or total antibodies in peripheral blood.

[0034] The third clinical indicator includes: the level of virus-specific neutralizing antibodies or total antibodies in the peripheral blood of the subject, the concentration of interferon-gamma in the peripheral blood after antigen stimulation, and the background level of IFN-γ.

[0035] The fourth clinical indicator includes: the percentage or count of peripheral blood mononuclear cells in the subject, the concentration of interferon-gamma in peripheral blood after antigen stimulation, the IFN-γ background level, the percentage or count of peripheral blood neutrophils, and the count of virus-specific memory B cells in peripheral blood.

[0036] The fifth clinical indicator includes: the percentage of peripheral blood mononuclear cells, the percentage of peripheral blood neutrophils, and the percentage of peripheral blood lymphocytes in the subject;

[0037] The sixth clinical indicator includes: the percentage of neutrophils and lymphocytes in the subject's peripheral blood;

[0038] When the clinical indicator is the first clinical indicator, the measurement result of the first clinical indicator is substituted into the formulas shown in Equations 1 to 3 to obtain the immunogenicity.

[0039] Immunovalidity c is calculated according to Equation 1:

[0040] ε=ε k ·ε c Formula 1;

[0041] In Equation 1, the ε k To enhance the immunogenicity of the immune system in killing infected cells, the ε c The ε refers to the immunogenicity of the immune system in killing infectious viruses; k The ε is calculated using the formula described in Equation 2; c The formula described in Equation 3 is used for calculation.

[0042]

[0043]

[0044] In Equations 2 and 3, [Mphi], [Neut], [NK], [CTL], and [CD8+T] M [nAb] represents the peripheral blood immune cell counts of the subject as follows: macrophages, neutrophils, natural killer cells, virus-specific cytotoxic T cells, and virus-specific CD8+ memory T cells; [nAb] represents the peripheral blood virus-specific neutralizing antibody level.

[0045] In Equation 2, 0.24 × 10 -6 mL / day ≤ k Mphi ≤0.98×10 -6 mL / day, 0.25×10 -6 mL / day ≤ k NK ≤1×10 -6 mL / day, d If =0.4 / day;

[0046] In Equation 3, 0.18 × 10 -6 mL·day -1 ≤CM phi ≤1.3×10 -6 mL·day -1 , and

[0047] The strength of a subject's response to a vaccine can be predicted based on this immunogenicity. In this regard, the present invention also provides a method for detecting the strength of a subject's response to a vaccine, comprising: measuring the subject's clinical indicators; said clinical indicators are those described in the above-described scheme;

[0048] When the clinical indicator is the first clinical indicator, the measurement result of the first clinical indicator is substituted into the formulas shown in Equations 1 to 3 in the above scheme to obtain the immunogenicity ε.

[0049] The viral release amount N1 of the virus corresponding to the viral vaccine is measured, and the virulence γ of the virus is calculated according to Equation 15.

[0050] γ=N1d If k infect [H0] Equation 15;

[0051] In Equation 15, d If =0.4 / day, k infect =0.00012×10 -6 mL / day, H0 = 50 × 10 6 / mL;

[0052] The immunogenicity ε of the subject is compared with the virulence γ. When ε is greater than the virulence γ, the subject is determined to have obtained a sufficient vaccine response strength.

[0053] When the clinical indicator is the second clinical indicator, the measurement result of the second clinical indicator is substituted into the formulas shown in Equations 4 to 7 to obtain the clinical relative immunogenicity.

[0054]

[0055] In Equation 4, ε* represents the clinical relative immunogenicity. The relative immunogenicity of the immune system in killing infected cells. The relative immunogenicity of the immune system in killing infecting viruses;

[0056] The The result is obtained according to Equation 5. This is calculated according to Equation 6;

[0057]

[0058]

[0059] In Formula 5, [Mono] represents the percentage or count of peripheral blood mononuclear cells in the subject, and [T] represents the cell count of cells in the subject's peripheral blood that release IFN-γ after antigen stimulation.

[0060] In Formula 6, [Neut] represents the percentage or count of neutrophils in the peripheral blood of the subject, and [nAb] represents the level of virus-specific neutralizing antibodies in the peripheral blood of the subject / the level of total antibodies in the peripheral blood.

[0061] The [T] is calculated according to the following formula 7;

[0062] [T]=[IFN-γ] / [IFN-γ]0-1 Formula 7;

[0063] In Formula 7, [IFN-γ] is the concentration of interferon-γ in the peripheral blood of the subject after antigen stimulation; [IFN-γ]0 is the background level of IFN-γ in the subject.

[0064] When the clinical indicator is the third clinical indicator, the measurement result of the third clinical indicator is substituted into the formulas shown in Equations 4, 7, 8 and 9 to obtain the clinical relative immunogenicity.

[0065]

[0066]

[0067] In Formula 8, [T] is the cell count of cells that release IFN-γ after antigen stimulation in the peripheral blood of the subject; in Formula 9, [nAb] is the level of virus-specific neutralizing antibody in the peripheral blood of the subject / the level of total antibody in the peripheral blood.

[0068] When the clinical indicator is the fourth clinical indicator, the measurement result of the fourth clinical indicator is substituted into the formulas shown in Equations 4, 5, 7 and 10 to obtain the clinical relative immunogenicity.

[0069]

[0070] In Formula 10, [Neut] represents the percentage or count of neutrophils in the peripheral blood of the subject, [B] represents the percentage or count of neutrophils in the peripheral blood of the subject. M The number of virus-specific memory B cells in the peripheral blood of the subject;

[0071] When the clinical indicator is the fifth clinical indicator, the measurement result of the fifth clinical indicator is substituted into the formulas shown in Equations 4, 11 and 12 to obtain the clinical relative immunogenicity.

[0072]

[0073]

[0074] In Formula 11, Lym% represents the percentage of peripheral blood lymphocytes in the subject; in Formula 12, Neut% represents the percentage of peripheral blood neutrophils in the subject; and in both Formulas 11 and 12, Mono% represents the percentage of peripheral blood mononuclear cells in the subject.

[0075] When the clinical indicator is the sixth clinical indicator, the measurement result of the sixth clinical indicator is substituted into the formulas shown in Equations 4, 13 and 14 to obtain the clinical relative immunogenicity.

[0076]

[0077]

[0078] In Formula 13, Lym% is the percentage of peripheral blood lymphocytes in the subject; in Formula 14, Neut% is the percentage of peripheral blood neutrophils in the subject.

[0079] The present invention also provides a method for detecting the strength of a subject's response to a vaccine, comprising: measuring the subject's clinical indicators; wherein the clinical indicators are those described in the above-described scheme;

[0080] When the clinical indicator is the first clinical indicator, the measurement result of the first clinical indicator is substituted into the formulas shown in Equations 1 to 3 in the above scheme to obtain the immunogenicity ε.

[0081] The viral release amount N1 of the virus corresponding to the viral vaccine is measured, and the virulence γ of the virus is calculated according to Equation 15.

[0082] γ=N1d If k infect [H0] Equation 15,

[0083] In Equation 15, d If =0.4 / day, k infect =0.00012×10 -6 mL / day, H0 = 50 × 10 6 / mL;

[0084] The immunogenicity ε of the subject is compared with the virulence γ. When ε is greater than the virulence γ, the subject is determined to have obtained a sufficient vaccine response strength.

[0085] When the clinical indicator is a second clinical indicator, the measurement result of the second clinical indicator is substituted into the formulas shown in Equations 5 to 7 in the above scheme to obtain... and

[0086] When the clinical indicator is the third clinical indicator, the measurement result of the third clinical indicator is substituted into the formulas shown in Equations 7 to 9 in the above scheme to obtain... and

[0087] When the clinical indicator is the fourth clinical indicator, the measurement result of the fourth clinical indicator is substituted into the formulas shown in Equations 5, 7 and 10 in the above scheme to obtain... and

[0088] When the clinical indicator is the fifth clinical indicator, the measurement result of the fifth clinical indicator is substituted into the formulas shown in Equations 11 and 12 in the above scheme to obtain... and

[0089] When the clinical indicator is the sixth clinical indicator, the measurement result of the sixth clinical indicator is substituted into the formulas shown in Equations 13 and 14 in the above scheme to obtain... and

[0090] get and Then, according to the formulas described in Equations 16 to 18, the combined distribution f of the immunogenicity index of the immune system killing the infecting virus and the immunogenicity index of the immune system killing infected cells in the vaccinated population is calculated. m (x, y):

[0091]

[0092]

[0093]

[0094] In Equation 18, μ x and σ x These are respectively the vaccinated population The mean and standard deviation, μ y and σ y These are respectively the vaccinated population The mean and standard deviation;

[0095] Calculate the relative toxicity index γ / k according to Equation 19. v :

[0096]

[0097] In Equation 19, E represents the protection rate of the viral vaccine;

[0098] The relative toxicity index γ / k v and and When comparing, At that time, it was determined that the subject had obtained a sufficient strength of vaccine response.

[0099] Preferably, the vaccine comprises a viral vaccine; preferably, the virus comprises a respiratory virus; preferably, the respiratory virus comprises an influenza virus or a coronavirus; preferably, the influenza virus is an influenza A virus or an influenza B virus; preferably, the coronavirus is SARS, MERS, or SARS-CoV-2.

[0100] The present invention also provides a system for evaluating the intensity of a subject's viral vaccine response, the system comprising: a subject module, a viral virulence module, and a calculation module;

[0101] When the clinical indicator is the first clinical indicator described in the above scheme, the subject module is used to collect the subject's clinical indicators and calculate the immunogenicity ε of the subject's immune system in killing infected cells according to the formulas shown in Equations 2 and 3 in the method described in the above scheme. k And the immunogenicity ε of the immune system in killing infected viruses. c ;

[0102] The virus virulence module is used to obtain the virus release amount N1 and calculate the virulence γ of the virus according to Equation 15 in the method described above.

[0103] The calculation module is used to process the ε obtained by the subject module. k and ε c Compared with viral virulence γ, when ε k ·ε c When the value is greater than γ, the result is output indicating that the subject has achieved a sufficient vaccine response strength;

[0104] When the clinical indicator is the second, third, fourth, fifth, or sixth clinical indicator described in the above protocol, the subject module is used to collect the clinical indicators of the subject to be evaluated and calculate them according to the method described in the above protocol. and The formula was used to calculate the subject's and

[0105] The viral virulence module is used to collect clinical indicators from the vaccinated population and calculate them according to the method described in the above protocol. and The formula is used to calculate the vaccinated population. The mean and standard deviation The mean and standard deviation, and the relative virulence index γ / k of the vaccinated population calculated according to formulas 16 to 19 in the method described above. v :

[0106] The calculation module is used to calculate the relative virulence γ / k obtained by the virus virulence module. v The subject obtained by the subject module as well as When comparing, At that time, the results showing that the subject has obtained a sufficient strength of vaccine response are output.

[0107] The present invention also provides a kit for evaluating the strength of a subject's vaccine response, comprising a first reagent, a second reagent, or a third reagent:

[0108] The first reagent includes reagents for detecting peripheral blood macrophage counts, neutrophil counts, natural killer cell counts, virus-specific cytotoxic T cell counts, and virus-specific CD8+ memory T cell counts, and reagents for detecting peripheral blood virus-specific neutralizing antibody levels;

[0109] The second reagent includes a reagent for detecting the cell count of cells that release IFN-γ after antigen stimulation in peripheral blood, a reagent for detecting the level of virus-specific neutralizing antibodies in peripheral blood or the count of virus-specific memory B cells in peripheral blood, a reagent for detecting the percentage or count of neutrophils in peripheral blood, a reagent for detecting the level of total antibodies in peripheral blood, and a reagent for detecting the percentage or count of monocytes in peripheral blood.

[0110] The third reagent includes reagents for detecting the percentage of neutrophils in peripheral blood, reagents for detecting the percentage of lymphocytes in peripheral blood, and reagents for detecting the percentage of monocytes in peripheral blood.

[0111] Preferably, the reagent used to detect the cell count of cells releasing IFN-γ after antigen stimulation in peripheral blood is a reagent used to detect the concentration of interferon-γ in peripheral blood after antigen stimulation.

[0112] Beneficial effects: This invention provides immunogenicity ε or clinical relative immunogenicity ε. * Application in evaluating the strength of vaccine responses in subjects. The immune system is a complex system by which the human body protects itself from invading viruses and bacteria. Due to the complexity of the immune system and the variability between populations, although many detection technologies are currently available to measure various immune indicators in human peripheral blood, it is difficult to correlate these indicators with an individual's immune response to a virus without a global model. For example, existing technologies can be used to determine whether antibodies are produced after vaccination or whether the white blood cell count exceeds the normal range. However, these measurements are insufficient to determine whether the protective effect produced after vaccination is adequate, especially whether infection will still occur after vaccination, and whether severe illness will develop after infection.

[0113] In this invention, based on immunological principles, we comprehensively consider the core signaling pathways involved in the human immune response and the in vivo circulation of lymphocytes and cytokines to construct a multi-compartment kinetic model to describe the dynamic process of the innate and adaptive immune responses against viral attacks. The model consists of 32 ordinary differential equations with 32 variables and 161 parameters. These parameters are derived from published experimental data or reasonable estimates and are used to characterize the rates of various processes in the immune response. First, we use this model to recreate the course of the host's immune response to SARS-CoV-2 at the time of initial infection. Based on the kinetic characteristics of viral load and immune response, we study the dynamic process of the immune response in different populations. This model, based on individual immune responses to SARS-CoV-2, explains individual differences in the disease, thus providing effective guidance for treatment and vaccination strategies.

[0114] Unlike previously disclosed models that only describe primary infection, the model of this invention can also be used to describe the dynamic process of host adaptive immunity under vaccine protection, particularly how memory cells in cellular and humoral immunity synergistically prevent SARS-CoV-2 infection. According to embodiments of the invention, the protective effect of a vaccine against SARS-CoV-2 infection can be characterized by immunogenicity based on memory T cells and immunogenicity based on killing the infecting virus. The model of this invention shows that an individual's vaccine protection ε includes cellular immune response efficacy ε. k With humoral immune response validity ε c Two dimensions, and the two have a multiplicative relationship (ε = ε). k ·ε c Therefore, the multiplicative relationship between cellular immunity and humoral immunity can be used as a quantitative indicator of an individual's immune system efficacy. Clinically, relative immunogenicity can also be used to characterize the strength of the immune efficacy of a subject or a subject population. In this regard, the commonly used clinical measurements currently involve detecting different lymphocyte counts, cytokine concentrations, and antibody concentrations in peripheral blood. However, there is a significant difference between the actual number of lymphocytes at the site of inflammation and the number in peripheral blood in many diseases. A major characteristic of severe pneumonia caused by COVID-19 infection is peripheral blood lymphopenia. In reality, lymphocytes move dynamically throughout the body, and the number of infiltrating lymphocytes at the site of inflammation may actually increase. Therefore, without correction, peripheral blood lymphocyte counts cannot directly reflect the levels of immune cells and cytokines at the site of infection (e.g., the lungs). According to the model of the present invention, for peripheral blood clinical indicators, the concentrations of immune cells and cytokines at the site of infection are taken into account through parameter fitting, making the results more quantitative and accurate in clinical practice.

[0115] Furthermore, evaluating the protective ability of vaccines against emerging mutant strains remains a pressing issue in the face of numerous new variants. Although many studies have explained the differences between mutant strains and the original strain at the molecular and genetic levels, a simple indicator is still lacking to measure the risk of the viral strain (compared to the original strain). In the model of this invention, the patient's disease progression and recovery time are correlated with virulence γ and the individual's vaccine protective efficacy ε. γ and ε can be compared to assess the protective ability of vaccine-produced antibodies against the viral strain in the subject's body.

[0116] The clinical indicators of this invention, as well as the methods, systems, and kits based on this invention, are also applicable to assessing adaptive immunity against other respiratory viruses, such as severe acute respiratory syndrome virus (SARS), Middle East respiratory syndrome virus (MERS), and influenza virus. Attached Figure Description

[0117] Figure 1This diagram illustrates the immune system response network against SARS-CoV-2 infection. In the model of this invention, A represents the immune system response network comprising five modules: a virus infection module, an innate immunity module, a cellular immunity module, a humoral immunity module, and an immunosuppression module. Each module contains complex and nonlinear interactions between immune cells and cytokines; these interactions can be activation (→) or inhibition. B provides an overview of the interactions between the five modules;

[0118] Figure 2 This diagram illustrates the protection of immune memory and its prediction of vaccine efficacy. Figure A shows the change in antibody levels over time after vaccination. After vaccination, the cellular immunity in the recipient reaches homeostasis rapidly, while antibody levels decline slowly over time. When memory cells (BM and CD8+TM) reach homeostasis, antibody levels exhibit three typical states over time: homeostasis (ss), intermediate state, and exponential decline state (exp). In the ss state, the immunogenicity produced by the vaccine activates a certain level of BM, and the release of BM and antibody degradation reach equilibrium, maintaining antibody levels at a constant value. In the exp state, the immunogenicity produced by the vaccine does not activate BM, and antibodies produced by adaptive immunization decrease to zero after a sufficiently long period. The intermediate state is between two extreme states: antibody... Antibody levels decrease over time, but due to the presence of BM cells, the decline in antibody levels is not exponential; they eventually reach a stable level determined by BM cells. B represents a numerical simulation of the disease progression from initial infection (dashed line) to no infection after vaccination (light gray solid line) / infection cases (black solid line). Initial infection represents the absence of BM and TM. The light gray evolutionary trajectory represents fully protected individuals whose viral load decreases monotonically due to their strong adaptive immunity, resulting in no clinical infection. The dark gray evolutionary trajectory represents individuals infected due to insufficient immunogenicity. All samples are in the SS state. The initial CD8+TM and Ab levels of the samples were obtained through uniform random sampling. The interval of the black solid line represents the mean ± standard deviation. C represents the initial CD8+TM and Ab (t=t*) levels in space. Figure 3 The results of individual sampling for B are shown in the left and right figures, representing the exp and ss states, respectively. The solid and dashed lines correspond to the boundaries of complete protection in the exp and ss states, respectively. When an individual's immunogenicity is to the right of the boundary, they are immune to infection (light gray). The initial t = t* represents the time of virus exposure. D represents the projection of the average protective efficacy of all individuals in the exp and ss states onto ε. c -ε k The plane, solid line and dashed line correspond to the fully protected boundary in the exp state and ss state, respectively. The slopes of the two protection lines in the double logarithmic coordinates are close to -1.

[0119] Figure 3The model according to the present invention is used to predict the protection level of different types of vaccines against mutant strains; wherein, A is the combined distribution of immune indicators and the protection line against mutant strains in the vaccinated population, the top two figures are the combined distribution of immune indicators in CoronaVac and SputnikV vaccinated individuals, and the bottom two figures are the combined distribution of immune indicators in ChAdOx1 and BNT162b2 vaccinated individuals; B is a comparison of the predicted protection rate and clinical protection rate of various vaccines against each mutant strain.

[0120] Figure 4 The diagram illustrates the distribution of lymphocytes in patients with varying disease severity using a circulatory model according to the present invention. A represents the circulatory model comprising four compartments: pulmonary lymph nodes, distal lymph nodes and spleen, peripheral blood, and lungs; chemokines / chemokine receptors regulate the localization and migration of immune cells within the same compartment. B represents the number of lymphocytes in secondary lymphoid organs, peripheral blood, and lungs calculated based on the model.

[0121] Figure 5 The model according to this invention is used to fit the immunogenicity and viral load data; where A represents the infection data and immunogenicity fitting results of two COVID-19 patients in Singapore; and B represents the relationship between recovery time and immunogenicity of COVID-19 patients in Singapore, Germany, South Korea, and France. Detailed Implementation

[0122] The immune system is a complex system that protects the human body from invading viruses and bacteria. Targeting the multi-level regulatory mechanisms between viruses and the human immune system, we conducted interdisciplinary research in medicine and biophysics. Using systems biology methods, we established quantitative mathematical models to study the immune system response to the novel coronavirus and the time-varying dynamics of cytokine storms (corresponding to the disease's development), providing a reference for understanding the disease's progression. In this invention, based on the overall function of the immune system, we proposed quantitative standards for evaluating the effectiveness of individual vaccines, providing quantitative indicators and quantitative efficacy predictions for clinical treatment.

[0123] Immunovalidity ε and relative immunovalidity ε ＊ Calculation

[0124] In this invention, we propose a quantitative index ε that reflects an individual's immunity after vaccination, wherein the immunogenicity ε is calculated according to Equation 1:

[0125] ε=ε k ·ε c Formula 1;

[0126] In Equation 1, the ε k To enhance the immunogenicity of the immune system in killing infected cells, the ε cThe immunogenicity of the immune system in killing infectious viruses. Due to the role of ε in vaccine response and protection... k It is mainly associated with memory T cells, ε c ε is primarily associated with memory B cells and antibody levels; therefore, in the context of discussing the vaccine protection process, ε will also be considered. k This is called cellular immunogenicity, and ε is... c This is called humoral immune efficacy.

[0127] In some implementations, the ε k To calculate according to Equation 20, the ε c To calculate according to Equation 21:

[0128]

[0129]

[0130] In Equations 20 and 21, the clinical indicator [APC] l [APC] u [Neut], [NK], [CTL], and [CD8+T] M [A] represents the cell counts of the subject's cells as follows: antigen-presenting cells bound to the antigen, antigen-presenting cells not bound to the antigen, neutrophils, natural killer cells, virus-specific cytotoxic T cells, and virus-specific CD8+ memory T cells; [Ab] represents the subject's peripheral blood antibody concentration. In Equation 20, the parameters... as well as The values ​​represent the killing rates of antigen-activated APCs on virus-infected cells, the killing rates of non-antigen-activated APCs on infected cells, the killing rates of NK cells on virus-infected cells, the killing rates of CTL cells on virus-infected cells, and the killing rates of memory CD8+ T cells on virus-infected cells, respectively, with their respective ranges being... as well as d If The cell mortality rate due to viral infection is preferably 0.4 / day. In Equation 21, the parameter... A represents the rates at which antigen-activated APCs clear SARS-CoV-2 viral particles via phagocytosis, the rates at which non-antigen-activated APCs clear SARS-CoV-2 viral particles via phagocytosis, the rates at which neutrophils clear SARS-CoV-2 viral particles via NETs, ​​the rates at which antibodies clear SARS-CoV-2 viral particles, and the affinity of antibodies for antigens, respectively, with their value ranges being [missing values]. And 0 < A < 1. The parameters in Equations 20 and 21 and Calculated according to equations 22 and 23:

[0131]

[0132]

[0133] In Equations 22-23, the clinical indicators [IFN-γ] are the concentrations of interferon-gamma after antigen stimulation, [TNF-α] are the concentrations of tumor necrosis factor-α after antigen stimulation, and [IL-2] are the concentrations of interleukin-2 after antigen stimulation. [IFN-γ], [TNF-α], and [IL-2] can all be obtained by measuring peripheral blood of the subjects using commercially available kits. [D] is the concentration of dead cells, which can be expressed as the percentage of shadow area in a lung CT scan multiplied by 100. Parameters parameter

[0134] In clinical practice, clinical indicators [APC] of subjects can be monitored. l [APC] u ], [Neut], [NK], [CTL], [CD8+T M [Ab] and D were measured, and the immunogenicity ε of the immune system killing infected cells was calculated based on Equations 20-23. k And the immunogenicity ε of the immune system in killing infected viruses. c .

[0135] For the purpose of facilitating clinical measurement, in some implementations, the types of APC in Equations 20-21 are not distinguished, and a fixed value is taken based on the model results. and In such implementations, ε k ε is obtained from Equation 2. c The result is obtained according to Equation 3:

[0136]

[0137]

[0138] In Equations 2 and 3, [Mphi], [Neut], [NK], [CTL], and [CD8+T] are used. M The cell counts of the subjects are as follows: macrophages, neutrophils, natural killer cells, virus-specific cytotoxic T cells, and virus-specific CD8+ memory T cells; [nAb] represents the level of virus-specific neutralizing antibodies in peripheral blood. Without being limited by theory, [Mphi] = [APC] l ]+[APC u]; parameter k Mphi k NK , and The parameters d respectively reflect the ability of the corresponding cells to kill infected cells. If The apoptosis rate of infected cells; parameter c Mphi and These are the parameters representing the ability of the corresponding cells to clear viruses. This refers to the ability of antibodies to neutralize viral particles. In a preferred embodiment, in Formula 2, k Mphi k NK , as well as The value range is 0.24 × 10. -6 mL / day ≤ k Mphi ≤0.98×10 -6 mL / day, 0.25×10 - 6 mL / day ≤ k NK ≤1×10 -6 mL / day, as well as d If =0.4 / day; In Equation 3, c Mphi , as well as The range of values ​​for are respectively as well as

[0139] In some implementation methods, clinical relative immunogenicity ε may be used. * Compare the strength of vaccine response among different subjects or subject groups. Similar to immunogenicity ε, clinical relative immunogenicity ε... * It reflects the relative immunogenicity of the subjects' immune system in killing the infecting virus. and the relative immunogenicity of the immune system in killing infected cells The multiplicative relation, that is

[0140] In some implementations... This is calculated according to Equation 5. The result is obtained according to Equation 6:

[0141]

[0142]

[0143] Wherein, [Mono] is the percentage or count of peripheral blood mononuclear cells in the subject, [T] is the cell count of cells that release IFN-γ after antigen stimulation in the subject's peripheral blood, [Neut] is the percentage or count of peripheral blood neutrophils in the subject, and [nAb] is the level of virus-specific neutralizing antibodies in the subject's peripheral blood / the level of total antibodies in the subject's peripheral blood.

[0144] In such implementations, It can also be calculated according to Equation 10:

[0145]

[0146] [B M The number of virus-specific memory B cells in the peripheral blood of the subject is [number].

[0147] In some implementations... This is calculated according to Equation 8. The result is obtained according to Equation 9:

[0148]

[0149]

[0150] Wherein, [7] is the cell count of cells releasing IFN-γ after antigen stimulation in the peripheral blood of the subject, and [nAb] is the level of virus-specific neutralizing antibody in the peripheral blood of the subject / the level of total antibody in the peripheral blood. In a preferred embodiment, the concentration of memory T cells can be characterized by the level of interferon-γ after stimulation by the novel coronavirus, that is, [T] is calculated according to Equation 7:

[0151] [T]=[IFN-γ] / [IFN-γ]0-1 Formula 7;

[0152] Wherein, [IFN-γ] is the concentration of interferon-gamma after antigen stimulation; [IFN-γ]0 is the baseline IFN-γ level of the subject. To avoid being limited by theory, in order to correlate the clinical parameter [IFN-γ] with [T], the steady-state level needs to be subtracted; the difference is proportional to the actual number of activated T cells.

[0153] In some implementations... This is calculated according to Equation 11. The result is obtained according to Equation 12:

[0154]

[0155]

[0156] Wherein, Mono% is the percentage of peripheral blood mononuclear cells in the subject, Neut% is the percentage of peripheral blood neutrophils in the subject, and Lym% is the percentage of peripheral blood lymphocytes in the subject.

[0157] In this type of implementation, it can also be calculated according to Equation 13. Calculated according to Equation 14

[0158]

[0159]

[0160] Neut% represents the percentage of neutrophils in the peripheral blood of the subject, and Lym% represents the percentage of lymphocytes in the peripheral blood of the subject.

[0161] Although this invention discloses various methods for calculating ε * The method, however, can be applied as long as the same method is used when calculating toxicity to assess the ε of the subjects to be evaluated. * Quantitative comparison with toxicity γ.

[0162] The methods for measuring clinical indicators such as peripheral blood macrophage count, neutrophil count, neutrophil percentage, natural killer cell count, virus-specific cytotoxic T cell count, virus-specific CD8+ memory T cell count, monocyte percentage, monocyte count, cell count of cells releasing IFN-γ after antigen stimulation, lymphocyte percentage, virus-specific memory B cell count, and virus-specific neutralizing antibody level are well known in the art. For example, commercially available kits in Table 1 can be used to measure each clinical indicator.

[0163] Table 1. Kits for measuring specific immune cells, antibodies, and cytokines.

[0164]

[0165] Peripheral blood neutrophil count, neutrophil percentage, monocyte percentage, monocyte count, lymphocyte percentage, and lymphocyte count can be obtained using a complete blood count analyzer.

[0166] Virus-specific cytotoxic T cells (CTLs) can be measured using the following method: First, a peripheral blood sample is obtained from the subject, and the cytotoxic T cell count is measured and recorded as the baseline value. Then, the corresponding antigen (e.g., viral surface protein) is added to the peripheral blood sample for activation. After one day of culture, the cytotoxic T cell count in the sample is measured again and recorded as the activation value. Virus-specific cytotoxic T cell count = activation value - baseline value. The same method can be used to measure the virus-specific CD8+ memory T cell count and the virus-specific memory B cell count.

[0167] Viral virulence γ and relative virulence index γ / k v Calculation

[0168] To date, numerous laboratory and clinical studies have been reported on the mechanisms of SARS-CoV-2 infection, treatment of infected individuals, and protection of susceptible populations. However, further integration of these clinical and laboratory data, and systematic research on the immune responses to viral infection and vaccine protection, remains needed. In particular, suitable models are currently lacking to explain the individual differences in immune responses to SARS-CoV-2 and its mutant strains, the immunogenicity and efficacy of vaccines, and the risk to susceptible populations.

[0169] We proposed quantitative indicators of viral virulence for different mutant strains.

[0170] According to the model of the present invention, the virulence γ of the virus can be calculated according to Equation 15:

[0171] γ=N1d If k infect [H0] Equation 15

[0172] Wherein, parameter d If =0.4 / day, k infect =0.00012×10 -6 mL / day, H0 = 50 × 10 6 / mL. The clinical indicator N1 is the viral burst size, which is the number of viral particles produced by a single infected cell. The viral burst size of a virus or mutant strain can be determined using methods known in the art, such as inoculating the virus into isolated cells or directly introducing the viral sequence into isolated cells, followed by quantitative competitive RT-PCR or in situ hybridization image analysis of the infected or transformed cells (https: / / doi.org / 10.1073 / pnas.0707449104).

[0173] In some implementations, viral virulence γ can be calculated based on the immunogenicity of the vaccinated population:

[0174] First, obtain the relative immunogenicity of the immune system in the vaccinated population in killing the infecting virus. and the relative immunogenicity of the immune system in killing infected cells And the protection rate E of the vaccine;

[0175] Subsequently, the combined distribution f of the immunogenicity index of the immune system killing the infecting virus and the immunogenicity index of the immune system killing infected cells in the vaccinated population was calculated according to Equations 16-18. m (x, y):

[0176]

[0177]

[0178]

[0179] In Equation 18, μ x and σ x These are respectively the vaccinated population The mean and standard deviation, μ y and σ y These are respectively the vaccinated population The mean and standard deviation;

[0180] Finally, the relative toxicity index γ / k is calculated according to Equation 19. v :

[0181]

[0182] In Equation 19, E represents the protection rate of the vaccine.

[0183] To avoid being limited by theory, x and y in Equations 16-19 are merely distinctions between different variables. This also allows... and

[0184] The relative immunogenicity of the immune system in vaccinated individuals in killing the infecting virus Relative immune efficacy of the immune system in killing infected cells Furthermore, vaccine protection rate (E) data are generally disclosed in the clinical trial section of the vaccine marketing authorization materials. As mentioned earlier, as long as the formulas used to calculate the relative immunogenicity of the subjects to be evaluated are the same as those used to calculate the immunogenicity, the protective efficacy of the subjects after vaccination can be quantitatively evaluated. For example, when the vaccine marketing authorization materials include the level of virus-specific neutralizing antibodies in peripheral blood and the cell count [T] of cells releasing IFN-γ after antigen stimulation in peripheral blood, these two clinical indicators of the subjects to be evaluated can be measured, and the protective efficacy of each recipient in the subjects to be evaluated and the vaccinated population can be calculated using Equations 7 and 8, respectively. and Therefore, the relative immunogenicity ε after vaccination in the subjects was assessed. * Comparison with toxicity γ. Preferably, the subject's... as well as The γ / k calculated using Equation 18 v When comparing, At that time, the subjects were evaluated as having achieved a sufficient strength of vaccine response. In this respect, the uses and methods of the present invention are compatible with public data from different sources, making it possible to quantitatively compare immunity between different individuals and between individuals and groups.

[0185] In this invention, the following counts of peripheral blood immune cells and the level of virus-specific neutralizing antibodies in the subject are defined as the first clinical indicators. The peripheral blood immune cells of the subject include: macrophages, neutrophils, natural killer cells, virus-specific cytotoxic T cells, and virus-specific CD8+ memory T cells. Based on Equations 1-3, the immunogenicity ε of the subject, the immunogenicity ε of the immune system killing infected cells, and the immunogenicity ε of the immune system killing the infected virus can be calculated. c In this type of implementation, the virulence γ of the viral strain can be calculated using Equation 15, and the immunogenicity ε of the subject can be compared with the virulence γ. When ε is greater than the virulence γ, it is determined that the subject has obtained a sufficient strength of vaccine response.

[0186] In this invention, the percentage or count of peripheral blood mononuclear cells, the concentration of interferon-gamma in peripheral blood after antigen stimulation, the IFN-γ background level, the percentage or count of peripheral blood neutrophils, and the level of virus-specific neutralizing antibodies or total antibodies in peripheral blood are also defined as the second clinical indicator. Based on Equations 4-7, the clinical relative immunogenicity ε of the subject can be calculated. * The relative immunogenicity of the immune system in killing infected cells and the relative immunogenicity of the immune system in killing infecting viruses. In this type of implementation, the relative virulence index γ / k of the viral strain can be calculated using Equations 16-19. v and the relative toxicity index γ / k v and and When comparing, At that time, it was determined that the subject had obtained a sufficient strength of vaccine response.

[0187] In this invention, the level of virus-specific neutralizing antibodies or total antibodies in the peripheral blood of the subject, the concentration of interferon-gamma in the peripheral blood after antigen stimulation, and the background level of IFN-γ are also defined as the third clinical indicator. Based on Equations 4 and 7-9, the clinical relative immunogenicity ε* and the relative immunogenicity of the immune system in killing infected cells can be calculated. and the relative immunogenicity of the immune system in killing infecting viruses. In this type of implementation, the relative virulence index γ / k of the viral strain can be calculated using Equations 16-19. v and the relative toxicity index γ / k v and and When comparing, At that time, it was determined that the subject had obtained a sufficient strength of vaccine response.

[0188] In this invention, the percentage or count of peripheral blood mononuclear cells, the concentration of interferon-gamma in peripheral blood after antigen stimulation, the IFN-γ background level, the percentage or count of peripheral blood neutrophils, and the count of virus-specific memory B cells in peripheral blood are also defined as the fourth clinical indicator. The clinical relative immunogenicity ε of the subject can be calculated based on Equations 4, 5, 7, and 10. * The relative immunogenicity of the immune system in killing infected cells and the relative immunogenicity of the immune system in killing infecting viruses. In this type of implementation, the relative virulence index γ / k of the viral strain can be calculated using Equations 16-19. v and the relative toxicity index γ / k v and and When comparing, At that time, it was determined that the subject had obtained a sufficient strength of vaccine response.

[0189] In this invention, the percentage of peripheral blood mononuclear cells, the percentage of peripheral blood neutrophils, and the percentage of peripheral blood lymphocytes in the subject are also defined as the fifth clinical indicator. The clinical relative immunogenicity ε of the subject can be calculated based on Equations 4 and 11-12. *The relative immunogenicity of the immune system in killing infected cells and the relative immunogenicity of the immune system in killing infecting viruses. In this type of implementation, the relative virulence index γ / k of the viral strain can be calculated using Equations 16-19. v and the relative toxicity index γ / k v and and When comparing, At that time, it was determined that the subject had obtained a sufficient strength of vaccine response.

[0190] In this invention, the percentage of neutrophils and lymphocytes in the peripheral blood of the subjects are also defined as the sixth clinical indicator. The clinical relative immunogenicity ε of the subjects can be calculated based on Equations 4 and 13-14. * The relative immunogenicity of the immune system in killing infected cells and the relative immunogenicity of the immune system in killing infecting viruses. In this type of implementation, the relative virulence index γ / k of the viral strain can be calculated using Equations 16-19. v and the relative toxicity index γ / k v and and When comparing, At that time, it was determined that the subject had obtained a sufficient strength of vaccine response.

[0191] Systems and kits for evaluating the strength of viral vaccine responses in subjects.

[0192] The present invention also provides a system for evaluating the intensity of a subject's viral vaccine response, the system comprising: a subject module, a viral virulence module, and a calculation module.

[0193] In one implementation, the subject module is used to collect the subject's first clinical indicators and calculate ε based on the clinical indicators. k and ε c The viral virulence module is used to obtain the viral release amount N1 and calculate the viral virulence γ according to Equation 15 in the method described above; the calculation module is used to convert the ε obtained by the subject module into the viral virulence γ. k and ε c Compared with viral virulence γ, when ε k ·ε c When the value is greater than γ, the result is output indicating that the subject has achieved a sufficient vaccine response strength.

[0194] In some implementations, the subject module is used to collect a second, third, fourth, fifth, or sixth clinical indicator from the subject, and to calculate based on the clinical indicators. as well as

[0195] The viral virulence module is used to collect clinical indicators from the vaccinated population and calculate them using the same method as that used in the subject module. and Obtain the vaccinated population The mean and standard deviation, and The mean and standard deviation of the values ​​were used to calculate the relative virulence index γ / k of the vaccinated population according to formulas 16 to 19. v :

[0196] The calculation module is used to calculate the relative virulence γ / k obtained by the virus virulence module. v The subject obtained by the subject module as well as When comparing, At that time, the results showing that the subject has obtained a sufficient strength of vaccine response are output.

[0197] The present invention also provides a kit for evaluating the strength of a subject's vaccine response, comprising a first reagent, a second reagent, or a third reagent:

[0198] The first reagent includes reagents for detecting peripheral blood macrophage counts, neutrophil counts, natural killer cell counts, virus-specific cytotoxic T cell counts, and virus-specific CD8+ memory T cell counts, and reagents for detecting peripheral blood virus-specific neutralizing antibody levels;

[0199] The second reagent includes a reagent for detecting the cell count of cells that release IFN-γ after antigen stimulation in peripheral blood, a reagent for detecting the level of virus-specific neutralizing antibodies in peripheral blood or the count of virus-specific memory B cells in peripheral blood, a reagent for detecting the percentage or count of neutrophils in peripheral blood, a reagent for detecting the level of total antibodies in peripheral blood, and a reagent for detecting the percentage or count of monocytes in peripheral blood.

[0200] The third reagent includes reagents for detecting the percentage of neutrophils in peripheral blood, reagents for detecting the percentage of lymphocytes in peripheral blood, and reagents for detecting the percentage of monocytes in peripheral blood.

[0201] In this invention, the reagent for detecting the cell count of cells that release IFN-γ after antigen stimulation in peripheral blood is preferably a reagent for detecting the concentration of interferon-γ in peripheral blood after antigen stimulation.

[0202] Unless otherwise specified, the present invention does not have special requirements on the source of raw materials used, and commercially available products well known to those skilled in the art can be used.

[0203] the term

[0204] As used herein, the term "subject" refers to any animal useful for evoking an immune response. The subject can be a wild animal, a domesticated animal, a commercial animal, or a companion animal, such as a bird or a mammal. The subject can be a human. Although in one embodiment of the invention, the uses, methods, systems, and kits disclosed herein are contemplated to be suitable for human evaluation, they are also applicable to mammals (such as non-human primates, rodents) and non-mammals (such as chickens, ducks, or turkeys).

[0205] As used in this article, the term "antigen" or "immunogen" refers to any substance that promotes an immune response against it, such as a virus or viral fragment.

[0206] As used herein, the term "vaccine" refers to an immunogenic agent capable of inducing protective immunity in a recipient, such as a human or animal recipient. In terms of efficacy, a vaccine can induce immunity in a partially immunized population, while some individuals may fail to elicit a robust or protective immune response, or in some cases, no immune response at all. This failure to elicit an immune response may stem from the recipient's genetic background, or from an immunodeficiency state (a deficiency in acquired or innate immunity) or immunosuppression (e.g., due to chemotherapy or the use of immunosuppressive drugs), and the efficacy of the vaccine can be evaluated using the methods of this invention. Vaccines suitable for the evaluation methods of this invention include, but are not limited to, inactivated vaccines, live attenuated vaccines, recombinant protein vaccines, viral vector vaccines, and mRNA vaccines.

[0207] As used in this article, "immune cells" refers to any cell capable of releasing cytokines, chemokines, or antibodies in response to direct or indirect antigenic stimulation. "Immune cells" encompass lymphocytes, including natural killer (NK) cells, T cells (CD4+ and / or CD8+ cells), B cells, macrophages; leukocytes; dendritic cells; mast cells; monocytes; and any other cells capable of producing cytokine or chemokine molecules in response to direct or indirect antigenic stimulation.

[0208] The term "subject vaccine response strength" used in this article refers to the immunity against the immunogen generated in a subject after vaccination, which is the immunogenicity ε of the subject's immune system in killing infected cells. k Immunoprotective efficacy ε of the immune system in killing infectious viruses cThe product is calculated. After vaccination, a sufficient vaccine response means that the vaccine can provide complete protection against the virus. The adaptive immunity of the subject leads to a monotonic decrease in viral load, clinically manifested as no infection.

[0209] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments thereof.

[0210] Example 1: Construction of a virus-immune system interaction network model

[0211] We have analyzed the signaling pathways, different cell types, and key cytokines involved in the human immune response against viruses, constructing a virus-immune system interaction network. This network can be used to understand the dynamic process of viral infection. Figure 1 As shown, the network includes a virus infection module, an innate immunity module, a cellular immunity module, a humoral immunity module, and an immunosuppression module.

[0212] For coronaviruses, respiratory epithelial cells are the target cells for infection. Healthy epithelial cells (H) become infected cells (If) after infection and are detected by innate immune cells such as antigen-presenting cells (APCs), natural killer cells (NKs), and neutrophils (Neuts). Innate immune cells activate CD4+ and CD8+ T lymphocytes and B lymphocytes through the secretion of inflammatory cytokines and, more importantly, antigen-presenting pathways—that is, downstream adaptive immunity is activated by innate immunity. These activated lymphocytes proliferate and perform corresponding effector functions. Cytotoxic T cells (CTLs) kill infected cells, while antibodies (Abs) secreted by plasma cells (PBs) clear the virus. In addition, regulatory T cells (Tregs) play a negative regulatory role in immunity by releasing anti-inflammatory cytokines. During this process, some activated lymphocytes transform into a memory phenotype, responding more rapidly upon re-exposure to the same antigen. For B cells, germinal center B cells (GC B) differentiate into plasma cells and memory B cells. The former can secrete antibodies, while the latter can rapidly respond to antigen-like stimuli by reforming germinal centers. For T cells, activated CD8+ T cells (CD8+ T T cells) A They differentiate into effector memory T cells with cytotoxic functions, or into central memory T cells. Central memory T cells can rapidly proliferate and differentiate into CD8+ T cells. A ; while memory CD4+ T cells (CD4+ T cells) M These cells can rapidly differentiate into activated CD4+ T cells (CD4+ T cells) upon antigen stimulation. A ).exist Figure 1In the diagram, the black text above the arrow indicates cytokines or factors that promote the process; conversely, the gray text below the arrow indicates cytokines or factors that inhibit the process.

[0213] based on Figure 1 Based on the detailed network of A in the diagram, we established a system of 32 ordinary differential equations to describe the dynamic process of the immune response triggered by SARS-CoV-2 infection. The equations and parameters are detailed in the Methods section.

[0214]

[0215]

[0216]

[0217] Equations 24–26 describe the kinetics of viral infection of lung epithelial cells. Equation 24 describes the kinetics of SARS-CoV-2. Specifically, viral particles spread from the lung epithelial cells at a rate of N1d... If [If] is generated and released in infected cells (If), where N1 is the average number of viral particles released upon rupture of a single infected cell, and d If It is the mortality rate of infected cells. This corresponds to the clearance rate of mucosal immunity. The clearance rate of viral particles under the combined action of innate immunity and antibodies; in this invention, it is defined as...

[0218]

[0219] This allows the immune system's ability to clear viral particles to be simplified as ε. c ·[nCoV]. Here, This indicates the enhancement of APC effector function by cytokines and inflammatory signals (e.g., interferon-gamma, damage-related molecules); A represents antibody affinity, which gradually increases as infection progresses.

[0220] Equation 25 describes the dynamics of infected cells. Where, k infect [nXoV][H] represents the rate at which healthy epithelial cells (H) are infected by viral particles and transform into infected cells; d If [If] represents the mortality rate of infected cells; the third term is the rate at which innate and cellular immune cells clear infected cells. Similar to ε. c The immune system's ability to clear infected cells (ε) k ) can be defined as

[0221]

[0222] Equation 26 describes the dynamics of healthy epithelial cells. Epithelial cells regenerate at a constant rate r. H Regeneration, at the rate of natural apoptosis d H [H] Apoptosis, therefore the concentration at steady state or before infection is r. H / d H .

[0223] Substituting equations 20 and 21 back into equations 24 and 25, we get...

[0224]

[0225]

[0226] When infected cells reach steady state (d[If] / dt = 0), and the rate of virus clearance by innate and humoral immunity is much greater than that by mucosal immunity, Equation 27 can be simplified to:

[0227]

[0228] Among them, we will ε c ·ε k Defined as immunogenicity ε, it is correlated with various indicators of innate immunity, cellular immunity, and humoral immunity; viral virulence γ is defined as γ≡N1d. If k infect ·[H]0, which is related to the characteristics of the virus. As mentioned above, from Equation 26, the initial concentration of healthy cells can be derived as [H]0 = r H / d H As can be seen from the above equations, if we can maintain... Viral mutation rate The viral load gradually decreases and is eventually cleared. In the initial state, the vaccinated individual has just been exposed to the virus but has not yet become infected; at this time, [H] = [H]0. If the individual's immunogenicity is greater than the viral virulence (ε > γ), infection can be prevented; if ε < γ, the virus will proliferate, i.e., infection will occur. Therefore, the relationship between immunogenicity and viral virulence determines whether viral infection will occur and whether the immune system can clear the virus. For the same viral strain (with unchanged virulence), immunogenicity can quantitatively evaluate the strength of immunity in different individuals. Furthermore, because ε c and ε k These are indicators of humoral immunity and cellular immunity, respectively. According to our model, the product of cellular immunity and humoral immunity (i.e., immunogenicity) determines the strength of the body's immunity.

[0229] In summary, starting from the dynamics of the SARS-CoV-2 virus and infected cells, we analyzed and deduced how to predict whether infection will occur upon exposure to the virus based on immune indicators, and theoretically derived how the immune system protects vaccine recipients from SARS-CoV-2 infection. This immune indicator is immunogenicity ε, which includes humoral immunity ε. k and cellular immunity ε c It consists of two parts, which are multiplicative.

[0230] Example 2: Numerical simulation of the virus-immune system interaction network

[0231] Example 1 can be used to perform numerical simulations of the viral infection process, taking into account individual differences in innate and adaptive immunity, to verify the roles of cellular and humoral immunity in vaccine protection and the reliability of using immunogenicity as an indicator of immune strength. As mentioned above, immunogenicity is defined as... (Equation 1), where ε c and ε k The definition is given in Equations 20 and 21.

[0232] Following vaccination, the immune system responds to antigen stimulation, activating the proliferation of antigen-specific cells and antibody secretion. Among these, memory cells and specific antibodies, among other immune markers, can maintain their protective effect against infection for a relatively long time. Other immune markers return to pre-infection levels after approximately two weeks. We discuss the initial memory CD8+ T cell count ([CD8+T...)) through numerical simulation. M The relationship between the levels of neutralizing antibodies ([Ab]) and infection.

[0233] For the same recipient (with unchanged parameters), differences in vaccine type, vaccination strategy, or the timing of post-vaccination exposure to the virus will lead to variations in the levels of memory CD8+ T cells and neutralizing antibodies upon encountering the virus (i.e., different immunogenicity). On the other hand, for different individuals, detecting antibody levels at a certain point after vaccination (…) Figure 2 At time A (0), even if antibody levels are the same, subsequent antibody changes will differ due to variations in the levels of antibody-secreting cells such as long-lived B cells. Based on these differences in immunogenicity caused by vaccines, antibody kinetics can be categorized into three types: steady state (ss), exponential decline (exp), and an intermediate state between the two. The exponential decline state corresponds to the absence of memory B cells (B... M Antibody levels rapidly decline and approach zero. Steady state corresponds to a certain level of B... M Cells continuously produce antibodies, maintaining stable antibody levels in the body. This intermediate state corresponds to B. MThe antibody levels produced by the cells decrease slowly, and the final antibody level in this state is lower than the antibody level at steady state. For a given initial antibody level, the antibody concentration typically evolves into an intermediate state. Steady state and exponential decline are the limiting cases, with the intermediate state falling between the two. Therefore, we subsequently perform numerical simulations under both limiting cases.

[0234] In the numerical simulation, the initial viral load was set to 10. 4 / ml, and independently of the initial CD4+T M Sampling CD8+T M The antibody levels were evenly distributed. Specifically, in the exp state, B was... M Set the level to 0 and the initial antibody level at the time of virus exposure (t*) to Ab. In ss state, set B... M Let Ab(t) be a constant. Figure 2 The solid line B in the diagram illustrates the infection dynamics trajectory in the ss state. For vaccinated individuals, depending on their antibody and memory T cell levels upon viral exposure, they face two scenarios: increased viral load leading to immune escape and infection (dark gray); or low viral load allowing direct clearance by the recipient's immune system (light gray), resulting in no infection and complete protection. The dynamic trajectory of primary infection in the same recipient who has never been vaccinated (with zero memory T cell and antibody levels) is shown below. Figure 1 The dashed line B in the diagram shows that immunogenicity can also be broken down into innate immunity (ε). i ) and adaptive immunity (ε a The sum of ) according to Figure 1 The innate immune module and cellular immune module in B, ε i and ε a They are respectively

[0235]

[0236]

[0237] according to Figure 2 In equation B, when adaptive immunity is higher in the initial state, infection can be avoided; if immunity falls below a certain level, infection will occur. According to equations 30 and 31, the adaptive immunity term is included in ε. α In the middle, ε i Determined by innate immunity. Clinical studies have shown that adaptive immunity after vaccination is much greater than innate immunity; therefore, the strength of adaptive immunity can be used as a measure of immunogenicity (ε≈ε). α It is evident that whether a recipient will become infected with the virus depends on the level of immunogenicity ε at the time of viral exposure, and immunogenicity can quantitatively assess the strength of immunity. The infection dynamics trajectory in the Exp state is similar to that in the ss state.

[0238] We further analyzed how cellular and humoral immunity in adaptive immunity synergistically protect vaccine recipients from infection. The sampling results of the ss and exp states were projected onto ε. c -ε k (based on antibody concentration and initial CD8+T) M (Calculation) Plane. For example... Figure 2 As shown in Figure C, the immune indicator space is divided into two regions: infection and non-infection (protection). The boundary between these two regions is called the protection line. Infection will not occur if the subject's immune indicators are above the protection line. Figure 2 As shown in D, under a double logarithmic coordinate system, the slope of the protection line is close to -1, indicating that the concentration of memory T cells and the level of antibodies jointly determine whether infection will occur upon exposure to the virus. From a quantitative perspective, when the immunogenicity of a vaccine recipient satisfies Equation 32, that is, when the immunogenicity is greater than a certain threshold c, it can protect the recipient from infection.

[0239] log 10 ε c +log 10 ε k =log 10 (ε c ·ε k ) = log 10 (ε)>c Equation 32

[0240] This conclusion holds true in both the ss state (dashed line) and the exp state (solid line). The above numerical simulation results are consistent with the theoretical derivation, further demonstrating that the product of cellular immunity and humoral immunity upon viral exposure determines whether infection occurs, and that immunogenicity is a quantitative indicator for evaluating immunity.

[0241] In the case of complete immunity, the viral load decreases monotonically over time, i.e., the viral replication rate R... t The value remains less than 1. Since healthy target cells [H] ≤ [H] 0, and the immune system is functioning, immunogenicity increases after infection, according to Equation 33. In other words, the sufficient condition for complete protection after vaccination is ε. k ε c | t＝t* >γ, i.e., ε| t＝t* >γ. Therefore, this invention can also be used to evaluate vaccine-induced immune responses. In current clinical practice, antibody levels are commonly used as an indicator of immune protection. Our research shows that cellular immunity (characterized by memory T cells) and humoral immunity (antibodies) work together, and their product determines whether the adaptive immunity generated by vaccination can protect the recipient from viral infection.

[0242] Example 3: Calculation of virulence γ using vaccine clinical trial data

[0243] In the two embodiments described above, we have theoretically demonstrated the feasibility of immunogenicity in evaluating immunity and introduced how to calculate immunogenicity using clinical immunological indicators. Next, we will explain how to calculate viral virulence γ using clinical data from vaccine trials, and how to infer infection risk by comparing the relationship between virulence and immunogenicity, thereby predicting vaccine efficacy.

[0244] As mentioned above, the parameter ε in c Proportional to antibody levels, parameter ε k Proportional to CD8+ T cells. In an individual ε c ·ε k Under virulence γ, complete protection can be achieved. Therefore, immunogenicity data can be extracted from vaccine clinical data and compared with the virulence of different mutant strains to infer the protective efficacy of different types of vaccines against mutant strains. In this regard, we collected population-level clinical data of Sinovac (CoronaVac), Sputnik V, Oxford-AstraZeneca (ChAdOx1), and Pfizer (BNT162b2) vaccines (data sources are shown in Table 3). Due to the limitations of vaccine manufacturers' clinical trials, the recorded data only include a few immune indicators. Therefore, in this embodiment, the immunogenicity ε of each recipient in the population is calculated based on two immune indicators: the level of SARS-CoV-2-specific neutralizing antibody titer and the response of SARS-CoV-2-specific memory T cells (γ-gamma interferon, IFN-γ). Regarding antibody data, we standardized it using the average level of SARS-CoV-2-infected patients to allow for comparison of the trial results of different vaccines, and took the logarithm to obtain the corresponding data "log". 10 (Antibody)". For memory T cells, we used the following treatment method to obtain "log 10 The "(T cells)" data corresponds to the level of COVID-19-specific memory T cells:

[0245] log 10 (T) = log 10 ([IFN-γ] / [IFN-γ]0-1)

[0246] Wherein, [IFN-γ] represents the IFN-γ concentration after viral stimulation, corresponding to the specific memory T cell response; [IFN-γ]0 represents the basal IFN-γ level before viral stimulation, corresponding to the IFN-γ released by non-COVID-19 specific immune cells. In the vaccine recipient population, "log 10 (antibody) and "log 10Under the assumption that the levels of "(T cells)" all follow a normal distribution and are mutually independent, for a certain vaccine m, the joint distribution f of the immune indicators of the vaccinated population can be obtained by combining the mean μ and standard deviation σ of antibody and T cell data from clinical trials. m (x, y):

[0247]

[0248] Where x is "log 10 (antibody)"; y is "log 10 (T cells)”; μ and σ are the mean and standard deviation of the corresponding immune indicators. Figure 3 Figure A shows the combined distribution of immune indicators from different vaccines.

[0249] By utilizing the vaccine protection rate obtained from clinical trials and the protection conditions derived from models, the virulence of the virus can be calculated for subsequent evaluation of immunity and prediction of risk. In this embodiment, the formula for calculating immunogenicity can be specified as ε = k v ×T cells × neutralizing antibodies, where parameter k v Characterizes antibody affinity and T-cell cytotoxicity, etc. For example... Figure 3 As shown in A, the protection line is

[0250] log 10 (T cells) + log 10 (Neutralizing antibody) = log 10 (γ / k v )

[0251] For a vaccine to produce sufficient immunogenicity to prevent infection, its immunogenicity must exceed its virulence, i.e., it must be above the protective threshold. Furthermore, the proportion of the population with immunogenicity above the protective threshold can be calculated and used as the expected value E of the vaccine's protective rate.

[0252]

[0253] The expected protection rate of this vaccine is usually found in the vaccine application materials. We can use this expected value to fit the viral virulence-related parameters (γ / k) of different strains. v ), and draw the protective line ( Figure 3 (The gray line in A). For example... Figure 3 As shown in A, for the original SARS-CoV-2 strain (WT), γ / k v With a mean square error of 0.15, our root mean square error (RMSE) for predicting the efficacy of Sinovac and Sputnik vaccines against WT is 2.7%. The γ / k ratio of the alpha variant (B.1.1.7) is... vWith a value of 0.51, our predicted RMSE for the efficacy of Pfizer and Oxford-AstraZeneca vaccines against the B.1.1.7 variant is 3.5%. The γ / k ratio for the Delta variant (B.1.617.2) is... v The RMSE is 0.72. Our projected RMSE for the efficacy of the Russian Sputnik vaccine against the B.1.617.2 variant is 5.8%. Figure 3 In case B, the predicted protection rate was consistent with the clinical protection rate, indicating that for the same strain (γ / k) v (Similarly), given the population distribution of the vaccine's immunization indicators, its protection rate can be predicted, and the quality of the vaccine can be evaluated. Furthermore, for vaccine recipients, only the individual's immunogenicity and virulence (γ / k) need to be known. v By understanding the relationship between k and other pathogens, we can assess the strength of their immunity and the risk of infection. Therefore, according to our model, for a specific strain, k... v With γ as a constant, γ / k v It can serve as the sole parameter for determining the effectiveness of a vaccine against a specific strain, which is of great clinical significance.

[0254] Example 4: Dynamics of SARS-CoV-2 mutant strains: Competition between viral virulence γ and immunogenicity ε

[0255] While humans are implementing community-based public health control through vaccination, the novel coronavirus itself is also mutating. In the competition among mutant strains, Alpha, Delta, and Omega-Jon strains have successively become the dominant circulating strains. Some mutant strains possess higher immune evasion and target cell affinity, thus leading to increased viral load, more severe symptoms, breach of vaccine protection, and / or increased infectivity in patients. In a further model, we consider the interaction between mutants and the immune system and discuss how mutations affect epidemiological characteristics at both the individual and population levels.

[0256] According to the latest research, compared to the original strain, mutant strains may possess one or more of the following characteristics: evading existing neutralizing antibodies through S protein mutations; increasing viral affinity for angiotensin-converting enzyme 2 (ACE2); and accelerating replication. Therefore, our model was modified as follows: reducing antibody affinity; increasing infectivity. infect The target cell abundance [H]0; and the increase in the average number of viral particles released per infected cell N1. k infect [H]0 and N1 are all parameters related to toxicity γ. Since it is difficult to directly calculate the first term N1d in Equation 15... If k infect ·[H]0, therefore we used the method of Example 3 to integrate clinical antibody affinity and vaccine protective efficacy data for each mutant strain, and used k vThe virulence Y of each mutant strain was assessed using the protective condition of T·Ab>γ. Based on the model, the virulence Y of the alpha strain was estimated. α = 4.8 days -2 (4.5-5.1 days) -2 The virulence of the delta strain γ δ = 9.1 days -2 (6.0-11.5 days) -2 The virulence of the original WT strain γ WT = 3.6 days -2 .

[0257] The viral replication rate (Rt) and the course of infection within the host depend on both the host's individual immune efficacy (ε) and viral virulence (γ). When the patient's immune response is activated, ε increases, helping to clear the virus and kill infected cells, thus promoting recovery. Conversely, higher γ leads to more rapid disease progression. Numerical simulations of the dynamic changes in disease progression after infection with different mutant strains showed that a higher γ indicates faster disease progression, explaining the higher viral load observed in patients with the delta variant compared to those with the original strain. At the population level, regardless of whether complete protection was maintained, infection with more virulent variants increased the rate of severe illness among infected individuals.

[0258] Example 5: Predicting cells and cytokines at the site of infection based on a circulation model and peripheral blood data.

[0259] In a further model, we take into account the distribution of immune cells and cytokines within organs. For SARS-CoV-2 infection, we consider the infection site (lungs), peripheral blood, and lymphoid organs (lymph nodes and spleen), and establish a set of quantitative ordinary differential equations that include immune responses, inter-compartmental lymphocyte circulation and migration, and cytokine diffusion.

[0260] like Figure 4 As shown in A, the compartment dynamics model in this embodiment focuses on pulmonary infection and immunity, while also considering bacterial infection. Specifically, damage molecules produced at the site of infection (lungs) activate macrophages and antigen-presenting cells, and macrophages release pro-inflammatory cytokines and chemokines into the bloodstream. In this way, the immune response at the site of inflammation can be linked to the peripheral blood. By comparing clinical data (doi.org / 10.1186 / s12879-021-06899-7, https: / / doi.org / 10.1038 / s41598-021-93519-8, etc.) with parameter values ​​in the steady-state cellular level estimation model, the main differences or concerns between different types of patients are identified, and the associated parameters of major changes are found.

[0261] By fitting peripheral blood test results from patients at multiple time points, and using measurements from a healthy state as a steady-state control, a model estimate of the immune status is obtained, thus providing the calculated results for the site of inflammation. Multi-parameter fitting can employ a temperature-parallel Monte Carlo method, limiting the parameters to a reasonable range and combining measurement results to provide parameter estimates, preventing unreasonable results and fit failures. Through compartmental modeling, peripheral blood and the site of inflammation can be correlated. Figure 4 As shown in B, the proportion of lymphocytes in patients with different degrees of COVID-19 infection varies. In mild cases, lymphocytes in the blood chemotaxis towards the lungs in the early stages of infection, leading to a decrease in peripheral blood lymphocytes. Later, the number of lymphocytes in the peripheral blood recovers as inflammation subsides. In critically ill patients, lymphocyte chemotaxis towards the lungs also occurs in the early stages of infection, but in the later stages, due to persistent viral infection and co-infection with bacteria, the proportion of lymphocytes in the peripheral blood remains low, while the proportion of lymphocytes in the lungs remains high. Table 2 shows the ratio of infection site concentration to peripheral blood immune cell concentration in patients with different disease severities.

[0262] Table 2: Ratio of immune cell concentrations at the site of infection to those in peripheral blood in patients with different disease severities

[0263] neutrophils ≈1 1.5～5 1～2 Monocytes ≈20 10～100 10～20 NK cells ≈5 20～100 5～150 T lymphocytes ≈5 20～70 5～50 B lymphocytes ≈5 30～80 5～60

[0264] Example 6: Fitting Clinical Data on Virus Shedding

[0265] Based on Equations 25-27, we analyzed viral shedding data from nasopharyngeal swabs and sputum samples of 171 subjects mentioned in three recently published articles (doi: 10.1126 / sciadv.abc7112, doi: 10.1016 / S1473-3099(20)30232-2, doi: 10.1073 / pnas.2017962118). Data for each clinical case were replicated more than three times. This analysis ignored the mucosal immunity term ε. v After infection, viral load enters an ascending phase, meaning the viral load gradually rises to its peak. For cases in the ascending phase (24 cases), the ascending phase ε is defined. c =1, change parameter ε k The value is chosen such that the model prediction matches the data, resulting in ε. k Level. After the viral load reaches its peak, it enters a decline phase. For cases in the decline phase (171 cases), the decline phase ε is set. k =3, change parameter ε c The value is chosen such that the model prediction matches the data, resulting in ε. c Level; and calculate the immunogenicity ε for each period according to Equation 1. Figure 5 Figure A shows the fit of ε for two cases. Furthermore, we use the patient's maximum viral load as an indicator of the patient's condition. Analysis of 24 groups of data including the rising phase revealed a negative correlation between maximum viral load and immunogenicity (Pearson correlation coefficient p = -0.42), further indicating that weaker immunity in the early stages of infection worsens the patient's condition. Parameters Y (e.g., viral load and patient susceptibility) also affect maximum viral load. On the other hand, immunogenicity during the declining phase determines the duration of viral shedding; the power law of the immunogenicity-shedding time relationship curve is -1.1 (…). Figure 5 (B) Older patients are more likely to experience slower viral clearance and recovery. Analysis of data from Neant et al. (doi: 10.1073 / pnas.2017962118) showed that older patients were more likely to experience slower viral clearance and recovery (Whitney-Mann U test p = 0.22 for the rising phase, p = 0.17 for the falling phase), due to relatively insufficient adaptive immunity. A prolonged viral shedding period can lead to severe lymphopenia, lung damage, and bacterial infections. Therefore, older adults and patients with immunosuppressive diseases are more likely to develop severe symptoms.

[0266] During viral infection, the human immune system responds through a coordinated effort across the entire system, including innate immunity, antigen presentation, and adaptive immunity; and works in conjunction with other systems in the body to produce effects. Currently, most measurements are performed using single-indicator methods, then establishing a link between the indicator and various physiological processes. This method, by combining the required measurement indicators into a comprehensive indicator (e.g., immunogenicity), will significantly improve the sensitivity and accuracy of the indicator in monitoring subjects; using a single reagent kit to complete the expected multi-indicator measurements saves subjects' time and economic costs, enabling the measurement of multiple indicators with a single blood sample, reducing blood volume and medical waste.

[0267] Furthermore, by establishing a compartmental circulation scheme to estimate the condition of the inflamed site, compared with the traditional peripheral sampling compartment, more information on the immune response can be incorporated (when performing data fitting), thus providing a clearer picture of the inflamed site and offering quantitative indicators for more accurate diagnosis and treatment.

[0268] 1. Parameter Sampling Method

[0269] When faced with COVID-19 infection or other infectious diseases, individuals exhibit significant differences in their immune responses and the treatments they receive. These differences correspond to variations in virus-immune system interaction parameters within the model. To identify representative parameter sets that reflect the dynamics of the COVID-19 infection process, we need to explore the model's parameter space, i.e., sample and screen the parameters.

[0270] First, given the 32 variables and 161 parameters in the model, to reduce the dimensionality and size of the parameter space and improve sampling efficiency, we fixed all dissociation constants (Hill coefficients), which determine the system's dynamic characteristics. These dissociation constants include the rate of immune cell apoptosis, the rate of cytokine production and degradation, and virus-related parameters (infection rate, infected cell death rate, and the number of viruses released by infected cells) (Table 3). Next, we sampled intercellular interaction parameters, including the size of the CD4+ and CD8+ T cell pools. The sampling method was Latin hypercube sampling, with a uniform distribution in logarithmic space, and the sampling range is shown in Table 3. Furthermore, numerical simulations were performed on each set of sampled parameters. The initial values ​​(see Table 4) were fixed, and the ordinary differential equations were solved numerically using the Scipy library in Python. The initial conditions were set as follows: the initial viral load was 0.01 × 10⁻⁶. 6 (cells / mL); the initial number of infected cells was 0; the initial antigen-specific naive CD4+ and CD8+ T cells were sampling parameters (see Table 3); the initial values ​​of other variables were all at steady-state levels. Finally, based on publicly available data, we required the simulation results to meet clinical standards, i.e., to have physiological significance, and took the mean of all parameters that met this condition as the representative parameter group for subsequent simulation studies.

[0271] 2. Simulation of the vaccine protection process

[0272] The vaccine protection process is defined as the process of viral infection after vaccination and the immune system clearing the virus. In the simulation of the vaccine protection process, we changed the initial conditions of variables related to immune memory. Among them, we modified the initial conditions of antigen-specific memory CD8+ T cells (CD8+ T cells). M Initial values ​​of antibodies (Ab) and antibody levels were uniformly sampled, with a sampling range of 0–0.5 × 10⁻⁶. 5 0-1200 micrograms per milliliter; antigen-specific memory CD4+ T cells (CD4+ T cells) M The initial value of ) is fixed at 0.2 × 10 5 Each milliliter; antibody affinity is fixed at 1. We divide the vaccine protection process into the exp state and the ss state (see Example 2 for details), and their initial conditions are distinguished by antigen-specific memory B cells (B cells). M The initial values ​​are different: in the exp state, the initial level is 0; in the ss state, it is assumed that the antibody level has reached equilibrium, that is, the rate of antibody change is 0.

[0273]

[0274] The initial value of memory B cells can be calculated based on the initial antibody level, using the following formula:

[0275]

[0276] Among them, [IL-4] ss The target level for interleukin-4 was set; other parameters are defined in Table 3. The initial viral load was 0.01 × 10⁻⁶. 6 (cells / mL); initial antigen-specific naive CD4+ and CD8+ T cells were half of the original parameters; other variables were initialized to steady-state levels.

[0277] 3. Methods for predicting protection rates and calculating viral virulence γ based on vaccine data

[0278] Refer to Example 3 for the method of predicting protection rates based on vaccine data. After the above processing, the composite parameters (γ / k) of different strains can be obtained. v The virulence γ of different strains of the virus can be calculated based on this parameter. The specific steps are described below using Example 3 as an example.

[0279] Example 3 shows that the (γ / k) of Alpha and Delta v The levels were 3.4 times and 4.8 times that of the original strain, respectively. The calculation process is as follows:

[0280]

[0281]

[0282] Here, subscripts refer to different strains: WT (original strain), Alpha, and Delta. Meanwhile, from publicly available data (references 1-2), the difference in antibody affinity for mutant strains and original strains can be obtained, i.e., the k values ​​for different mutant strains in the formula. v The differences are as follows. Specifically, compared to the original strain, the antibody's affinity for the alpha strain decreased by 2.4 to 2.7 times, and its affinity for the delta strain decreased by 1.5 to 2.9 times. In the model, we assume that the virulence γ of the original strain is different. wT It takes 3.6 days -2 Alpha toxicity γ can be calculated. Alpha Between 4.5 and 5.1 days -2 Between, Delta toxicity γ Delta Between 6.0 and 11.5 days -2 The calculation process is as follows: If we take k... v，WT / k v，Delta =1.5, the virulence γ of the delta strain can be calculated. Delta for:

[0283]

[0284] References on changes in affinity:

[0285] 1. Liu, C. et al. Reduced neutralization of SARS-CoV-2 B.1.617 by vaccine and convalescent serum. Cell 184, 4220-4236.e4213, doi: https: / / doi.org / 10.1016 / j.cell.2021.06.020(2021).

[0286] 2. Lustig, Y. et al. Neutralising capacity against Delta (B.1.617.2) and other variants of concern following Comirnaty (BNT162b2, BioNTech / Pfizer) vaccination in health care workers, Israel. Euro surveillance: bulletin Europeensur les maladies transmissibles=European communicabledisease bulletin 26, doi: 10.2807 / 1560-7917.Es.2021.26.26.2100557(2021).

[0287] Complete model formula

[0288] For ease of writing, square brackets [·] in the equations represent cell number (particle number) density or concentration. For the core virus infection module...

[0289] 1.) Virus dynamics

[0290]

[0291]

[0292]

[0293] ε=ε k (ε c +ε v )

[0294]

[0295]

[0296]

[0297]

[0298]

[0299]

[0300]

[0301]

[0302] 2.) Leukocyte dynamics

[0303]

[0304]

[0305]

[0306]

[0307]

[0308]

[0309]

[0310]

[0311]

[0312]

[0313]

[0314]

[0315]

[0316]

[0317]

[0318]

[0319]

[0320]

[0321]

[0322]

[0323] [APC0]=Constant, [NK0]=Constant, [Neut0]=Constant, [B0]=Constant

[0324]

[0325]

[0326]

[0327]

[0328]

[0329]

[0330]

[0331] 3.) Cytokine and Antibody Kinetics

[0332]

[0333]

[0334]

[0335]

[0336]

[0337]

[0338]

[0339] Table 3. Parameter Description and Value Range

[0340]

[0341]

[0342]

[0343]

[0344]

[0345] Table 4. All variable names, descriptions, initial values, and units

[0346]

[0347]

[0348] Table 5: Vaccine Data Sources

[0349]

[0350]

[0351] Although the above embodiments have provided a detailed description of the present invention, they are only some embodiments of the present invention and not all embodiments. People can obtain other embodiments based on these embodiments without creative effort, and these embodiments all fall within the protection scope of the present invention.

Claims

1. A system for evaluating the intensity of a subject's vaccine response, characterized in that, The system is used to calculate clinical relative immunogenicity. ; The clinical relative immunogenicity Calculated according to Equation 4: Equation 4; Among them, the The relative immunogenicity of the immune system in killing infected cells, the The relative immunogenicity of the immune system in killing infecting viruses; Among them, the as well as The following formulas are used to calculate the following: = Formula 5; Formula 6; = Formula 8; Equation 9; Formula 10; = Formula 11; Equation 12; = Equation 13; Equation 14; In Equations 5-6 and 8-14, [Mono] represents the percentage or count of peripheral blood mononuclear cells in the subject, [T] represents the cell count of cells releasing IFN-γ after antigen stimulation in the subject's peripheral blood, and [Neut] represents the percentage or count of peripheral blood neutrophils in the subject. The value represents the ratio of the peripheral blood virus-specific neutralizing antibody level to the total peripheral blood antibody level of the subject. The count of virus-specific memory B cells in the peripheral blood of the subject is given; Mono% is the percentage of monocytes in the peripheral blood of the subject; Neut% is the percentage of neutrophils in the peripheral blood of the subject; and Lym% is the percentage of lymphocytes in the peripheral blood of the subject. The vaccine is a vaccine against a respiratory virus; the respiratory virus is either an influenza virus or a coronavirus.

2. The system according to claim 1, characterized in that, The influenza virus in question is either type A or type B influenza virus.

3. The system according to claim 1, characterized in that, The coronavirus mentioned is SARS, MERS, or SARS-CoV-2.

4. A system for evaluating the immunogenicity or clinical relative immunogenicity of subjects, comprising: Measure the clinical indicators of the subjects; The clinical indicators are selected from the second, third, fourth, fifth, or sixth clinical indicators. The second clinical indicator includes: the percentage or count of peripheral blood mononuclear cells in the subject, and the concentration of gamma interferon in peripheral blood after antigen stimulation. IFN-γ Background level, percentage of neutrophils or neutrophil count in peripheral blood, and level of virus-specific neutralizing antibodies or total antibodies in peripheral blood; The third clinical indicator includes: the level of virus-specific neutralizing antibodies or total antibodies in the subject's peripheral blood, and the concentration of interferon-gamma in the peripheral blood after antigen stimulation. IFN-γ Baseline level; The fourth clinical indicator includes: the percentage or count of peripheral blood mononuclear cells in the subject, and the concentration of gamma interferon in peripheral blood after antigen stimulation. IFN-γ Background level, percentage or count of neutrophils in peripheral blood, and count of virus-specific memory B cells in peripheral blood; The fifth clinical indicator includes: the percentage of peripheral blood mononuclear cells, the percentage of peripheral blood neutrophils, and the percentage of peripheral blood lymphocytes in the subject; The sixth clinical indicator includes: the percentage of neutrophils and the percentage of lymphocytes in the subject's peripheral blood; When the clinical indicator is the second clinical indicator, the measurement result of the second clinical indicator is substituted into the formulas shown in Equations 4 to 7 to obtain the clinical relative immunogenicity. Equation 4; In Equation 4, For clinical relative immunogenicity, The relative immunogenicity of the immune system in killing infected cells. The relative immunogenicity of the immune system in killing infecting viruses; The The result is obtained according to Equation 5. This is calculated according to Equation 6; = Formula 5; Formula 6; In Equation 5, [ Mono [This refers to the percentage or count of peripheral blood mononuclear cells in the subject.] T [This refers to the cell count of cells in the peripheral blood of the subject that release IFN-γ after antigen stimulation;] In Equation 6, [ Neut The percentage or count of neutrophils in the peripheral blood of the subject. nAb The value represents the peripheral blood virus-specific neutralizing antibody level / peripheral blood total antibody level of the subject. The [ T The result is calculated according to Equation 7 below; Formula 7; In Equation 7, [ IFN-γ [This refers to the concentration of gamma interferon in the peripheral blood of the subject after antigen stimulation;] IFN-γ ]0 is the subject IFN-γ Baseline level; When the clinical indicator is the third clinical indicator, the measurement result of the third clinical indicator is substituted into the formulas shown in Equations 4, 7, 8 and 9 to obtain the clinical relative immunogenicity. = Formula 8; Equation 9; In Equation 8, [ T [ ] is the cell count of cells that release IFN-γ after antigen stimulation in the peripheral blood of the subject; in Formula 9, [ nAb The value represents the peripheral blood virus-specific neutralizing antibody level / peripheral blood total antibody level of the subject. When the clinical indicator is the fourth clinical indicator, the measurement result of the fourth clinical indicator is substituted into the formulas shown in Equations 4, 5, 7 and 10 to obtain the clinical relative immunogenicity. Formula 10; In Equation 10, [ Neut The percentage or count of neutrophils in the peripheral blood of the subject. B M The number of virus-specific memory B cells in the peripheral blood of the subject; When the clinical indicator is the fifth clinical indicator, the measurement result of the fifth clinical indicator is substituted into the formulas shown in Equations 4, 11 and 12 to obtain the clinical relative immunogenicity. = Formula 11; Equation 12; In Equation 11, Lym % represents the percentage of peripheral blood lymphocytes in the subject; in Formula 12, Neut % represents the percentage of neutrophils in the peripheral blood of the subject; in Formulas 11 and 12, Mono% represents the percentage of mononuclear cells in the peripheral blood of the subject; When the clinical indicator is the sixth clinical indicator, the measurement result of the sixth clinical indicator is substituted into the formulas shown in Equations 4, 13 and 14 to obtain the clinical relative immunogenicity. = Equation 13; Equation 14; In Equation 13, Lym % represents the percentage of peripheral blood lymphocytes in the subject; in Formula 14 Neut % represents the percentage of peripheral blood neutrophils in the subject.

5. A system for evaluating the intensity of a subject's vaccine response, characterized in that, include: The clinical indicators of the subjects are measured; the clinical indicators are the second, third, fourth, fifth or sixth clinical indicators as described in claim 4. When the clinical indicator is a second clinical indicator, the measurement result of the second clinical indicator is substituted into the formulas shown in Equations 5 to 7 of claim 4 to obtain... and ; When the clinical indicator is a third clinical indicator, the measurement result of the third clinical indicator is substituted into the formulas shown in Equations 7 to 9 of claim 4 to obtain the result. and ; When the clinical indicator is the fourth clinical indicator, the measurement result of the fourth clinical indicator is substituted into the formulas shown in Equations 5, 7 and 10 of claim 4 to obtain the result. and ; When the clinical indicator is the fifth clinical indicator, the measurement result of the fifth clinical indicator is substituted into the formulas shown in Equations 11 and 12 in claim 4 to obtain... and ; When the clinical indicator is the sixth clinical indicator, the measurement result of the sixth clinical indicator is substituted into the formulas shown in Equations 13 and 14 of claim 4 to obtain... and ; The above and Then, the combined distribution of the immunogenicity of the immune system in killing the infecting virus and the immunogenicity index of the immune system in killing infected cells in the vaccinated population was calculated according to the formulas described in Equations 16 to 18. : Formula 16; Equation 17; Formula 18; In Equation 18, μ x and σ x These are respectively the vaccinated population The mean and standard deviation, μ y and σ y These are respectively the vaccinated population The mean and standard deviation; Calculate the relative toxicity index according to Equation 19. : Formula 19, In Equation 19, E The protection rate of the vaccine against the virus; The relative toxicity index and and When comparing, + At that time, it was determined that the subject had obtained a sufficient strength of vaccine response; The vaccine is a vaccine against a respiratory virus; the respiratory virus is either an influenza virus or a coronavirus.

6. The system according to claim 5, characterized in that, The influenza virus in question is either type A or type B influenza virus.

7. The system according to claim 5, characterized in that, The coronavirus mentioned is SARS, MERS, or SARS-CoV-2.

8. The system according to claim 5, characterized in that, The vaccine is an inactivated vaccine, a live attenuated vaccine, a recombinant protein vaccine, a viral vector vaccine, or an mRNA vaccine.

9. A system for evaluating the intensity of a subject's viral vaccine response, the system comprising: Subject module, viral virulence module, and calculation module; When the clinical indicator is the second, third, fourth, fifth, or sixth clinical indicator as described in claim 4, the subject module is used to collect the clinical indicators of the subject to be evaluated and calculate them according to the method described in claim 4. and The formula was used to calculate the subject's and ; The viral virulence module is used to collect clinical indicators from the vaccinated population and calculate them according to the system described in claim 4. and The formula is used to calculate the vaccinated population. The mean and standard deviation The mean and standard deviation are calculated, and the relative virulence index of the vaccinated population is calculated according to the formulas 16 to 19 in the system described in claim 5. : The calculation module is used to process the relative virulence obtained by the virus virulence module. The subject obtained by the subject module as well as When comparing, + At that time, the result is output showing that the subject has obtained a sufficient strength of vaccine response; The virus in question is a respiratory virus vaccine, which may be an influenza virus or a coronavirus.

Images