Product quality attribute target range

Abstract

Methods of selecting or rejecting a standard target range of product quality attributes of a pharmaceutical product are described herein. Methods of making pharmaceutical products are described herein. A method of assessing the impact of a product quality attribute of a pharmaceutical product is described herein.

Description

Cross-references to related applications

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 509,688, filed June 22, 2023, which is incorporated herein by reference in its entirety. Technical Field

[0002] The embodiments described herein relate to the target range of product quality attributes for pharmaceutical products, and the achievement of the target range of product quality attributes in the manufacture of pharmaceutical products. Background Technology

[0003] The native structure or chemical properties of biomolecules, such as therapeutic proteins, adapt or change in response to changes within their molecular environment. Other biotherapeutic agents, including nucleic acid-based and cell-based agents, may also undergo changes within their environment. While this flexibility in structure or chemical properties is necessary for the biological functions of most (if not all) biomolecules and cells, it also presents numerous challenges during the development and manufacture of biotherapeutic agents for pharmaceutical applications. For example, therapeutic proteins undergo a variety of conditions in numerous process steps before being finally administered to a patient. These numerous process steps include, for example, one or more of the following: protein production (e.g., recombinant production), harvesting, purification, formulation, filling, packaging, storage, delivery, and final preparation close to patient administration. In each of these steps, the therapeutic protein is placed in one or more environments that may or may not cause changes in its structure or chemical properties. Changes in structure or chemical properties can lead to the formation of different kinds of biotherapeutic agents, resulting in heterogeneous products. While some retain their ability to bind to their targets and thus maintain therapeutic efficacy, others lose their target-binding ability and thus become inactive. In order to maximize and maintain quality control over these biological therapeutics, the biopharmaceutical industry has focused a great deal of effort on understanding why some species lose their activity while others remain active.

[0004] Product quality attributes (which will generally be referred to as "attributes" in this document for brevity) define the physicochemical properties of pharmaceutical products (such as therapeutic biomolecules) and can therefore affect drug safety and efficacy. The level of a product quality attribute, or critical quality attribute (CQA), that is critical to drug quality is clearly defined by a product purity specification that has undergone extensive regulatory review. Summary of the Invention

[0005] The following items are described according to the embodiments herein:

[0006] 1. In some embodiments, a method is provided for selecting or rejecting a standard target range of product quality attributes of a pharmaceutical product. The method includes:

[0007] a) Provide a range of candidate targets for the product quality attributes of the drug product;

[0008] b) Obtain clinical outcome data from subjects who have received the drug product;

[0009] c) Determine the exposure level of the product quality attribute at the time of application;

[0010] d) The clinical outcome data are partitioned based on the exposure level of the product quality attribute, wherein clinical outcome data with exposure to the product quality attribute outside the candidate target range are assigned to the first partition, and clinical outcome data with exposure to the product quality attribute within the candidate target range are assigned to the second partition; and

[0011] e) Determine the incidence of the specified clinical outcome in the first partition and the incidence of the specified clinical outcome in the second partition; and

[0012] f) Any of the following:

[0013] (i) If there is no clinical difference in the incidence of the specified clinical outcome within the partition, then a standard target range for the product quality attribute is selected based on the candidate target range; or

[0014] (ii) If there are clinical differences in the incidence of the specified clinical outcome in the partition, the standard target range is rejected based on the candidate target range.

[0015] 2. In some embodiments of the method, referring to the method described in item 1, the method further includes:

[0016] Repeat a) - e) for at least one additional candidate target range for this product quality attribute, and any of the following:

[0017] (iii) Selecting the standard target range based on the maximum amplitude candidate target range value, where there is no clinical difference in the incidence of the specified clinical outcome among the partitions for the maximum amplitude candidate target range value; or

[0018] (iv) If there is a clinical difference in the incidence of the specified clinical outcome in the partition for each of these candidate target ranges, then the standard target range shall not be determined based on any of these candidate target ranges.

[0019] 3. In some embodiments of the method, referring to the method as described in item 2, if the method includes (iv), the method further includes: repeating the method with an additional candidate target range, the magnitude of which is less than the candidate target range and the at least one additional candidate target range.

[0020] 4. In some embodiments, the method as described in any one of items 1-3 further includes:

[0021] g) Batch manufacturing of the drug product;

[0022] h) Determine the level of the product quality attribute in this batch of drug products; and

[0023] i) Any of the following:

[0024] (i) If the determined level of the product quality attribute is outside the standard target range for that product quality attribute, then the batch shall be rejected; or

[0025] (ii) If the determined level of the product quality attribute is within the standard target range of the product quality attribute, the batch shall be accepted.

[0026] 5. In some embodiments of the method, relating to the method described in item 4, if the batch is rejected, the method further includes marking the batch for investigation.

[0027] 6. In some embodiments of the method, for the method as described in any one of items 1-3, the method further includes developing a manufacturing process for the pharmaceutical product based on a quality target product profile that includes the standard target range.

[0028] 7. In some embodiments, a method of manufacturing a pharmaceutical product is provided. The method includes:

[0029] a) Provide a range of candidate targets for the product quality attributes of the drug product;

[0030] b) Obtain clinical outcome data from subjects who have received the drug product;

[0031] c) Determine the exposure level of the product quality attribute at the time of application;

[0032] d) The clinical outcome data are divided according to the exposure level of the product quality attribute, wherein clinical outcome data with exposure to the product quality attribute outside the candidate target range are assigned to the first partition, and clinical outcome data with exposure to the product quality attribute within the candidate target range are assigned to the second partition.

[0033] e) Determine that there are no clinical differences in the incidence of the specified clinical outcomes among these partitions;

[0034] f) Based on the candidate target range, select a standard target range for the product quality attributes of the drug product; and

[0035] g) Any of the following:

[0036] i) Acceptance criteria are applied to drug product batches that fall within the product quality attribute levels defined by this standard; or

[0037] ii) Reject drug product batches that contain product quality attribute levels outside the scope of this standard's target range.

[0038] 8. In some embodiments, the method described in item 7 further includes:

[0039] h) Repeat a) - e) for at least one additional candidate target range for this product quality attribute.

[0040] Wherein, f) the standard target range for the product quality attribute is selected based on the maximum magnitude candidate target range value, for which there is no clinical difference in the incidence of the specified clinical outcome in the partition.

[0041] 9. In some embodiments, a method is provided for assessing the impact of product quality attributes of a pharmaceutical product. The method includes:

[0042] a) Provide a range of candidate targets for the product quality attributes of the drug product;

[0043] b) Obtain clinical outcome data from subjects who have received the drug product;

[0044] c) Determine the exposure level of the product quality attribute at the time of application;

[0045] d) The clinical outcome data are divided according to the exposure level of the product quality attribute, wherein clinical outcome data with exposure to the product quality attribute outside the candidate target range are assigned to the first partition, and clinical outcome data with exposure to the product quality attribute within the candidate target range are assigned to the second partition.

[0046] e) Determine the incidence of the specified clinical outcome in the first partition and the incidence of the specified clinical outcome in the second partition; and

[0047] f) Any of the following:

[0048] i) If there is no clinical difference in the incidence of the specified clinical outcome within the partition, then the product quality attribute is determined to have no impact on the specified clinical outcome within the candidate target range; or

[0049] ii) If there are clinical differences in the incidence of specified clinical outcomes within the partitions, then determine that the product quality attribute may have an impact on the specified clinical outcome within the target range.

[0050] 10. In some embodiments of the method, the method described in item 9 is repeated for two or more different candidate target ranges.

[0051] 11. In some embodiments, a method for evaluating the injection site effect of a pharmaceutical product is provided. The method includes:

[0052] a) Provide two or more candidate injection sites for the drug product;

[0053] b) Obtain clinical outcome data from subjects who have received the drug product at at least one of the two or more candidate injection sites;

[0054] c) The clinical outcome data are divided according to the injection site, wherein the clinical outcome data of the first injection site is assigned to the first partition and the clinical outcome data of the second injection site is assigned to the second partition.

[0055] e) Determine the incidence of the specified clinical outcome in the first partition and the incidence of the specified clinical outcome in the second partition; and

[0056] f) Any of the following:

[0057] i) If there is no clinical difference in the incidence of the specified clinical outcome within the partition, then it is determined that the injection site has no effect on the specified clinical outcome within the candidate target range; or

[0058] ii) If there are clinical differences in the incidence of the specified clinical outcome within the partition, then determine that the injection site may have an impact on the specified clinical outcome within the target range.

[0059] In some embodiments, the specified clinical outcome is an adverse event, such as an injection site reaction.

[0060] 12. In some embodiments, for any of the methods described herein, these clinical outcome data include at least one of efficacy data or adverse event incidence data.

[0061] 13. In some embodiments, for any of the methods described herein, the designated clinical outcome includes at least one of efficacy outcome or adverse event incidence.

[0062] 14. In some embodiments, for any of the methods described herein, the specified clinical outcome includes the incidence of adverse events.

[0063] 15. In some embodiments of the method, the method of claim 14 includes filtering out any adverse events that occurred prior to the application from the adverse event incidence data before the segmentation.

[0064] 16. In some embodiments, for any of the methods described herein, the clinical difference includes at least one of qualitative difference, statistically significant difference, or quantifiable trend.

[0065] 17. In some embodiments, for any of the methods described herein, assigning clinical outcome data where the product quality attribute is exposed outside the candidate target range to a second partition includes assigning the clinical outcome data to two or more different partitions.

[0066] 18. In some embodiments, for any of the methods described herein, these specified clinical outcome data include two or more different categories or types of clinical outcomes, such as two or more different categories or types of adverse events.

[0067] 19. In some embodiments, for any of the methods described in items 9-18, the method further includes determining whether the exposure level of the product quality attribute is associated or not associated with two or more different categories or types of clinical outcome data.

[0068] 20. In some embodiments, for any of the methods described in items 9-18, the method further includes determining whether there is an association or non-association between the exposure levels of two or more different product quality attributes and at least one category or type of clinical outcome data.

[0069] 21. In some embodiments, for any of the methods described in items 19-20, the method further includes automatically determining whether the exposure level of the product quality attribute is associated or not associated with only some of the two or more different categories of clinical outcomes, and / or

[0070] Specifically, it automatically determines whether there is an association or no association between the exposure levels of two or more different product quality attributes and at least one category or type of clinical outcome data.

[0071] 22. In some embodiments, for any of the methods described herein, the method further includes determining an association or lack thereof between at least one clinical characteristic of a subject in the first partition and the designated clinical outcome.

[0072] 23. In some embodiments, with respect to the method as described in item 22, the at least one clinical characteristic includes one or more of the following: a pre-existing condition, a biomarker, laboratory results, or demographic information.

[0073] 24. In some embodiments, for any of the methods described herein, the clinical outcome data of the pharmaceutical product includes data from two or more different manufacturing batches of the pharmaceutical product.

[0074] 25. In some embodiments, with respect to the method as described in item 24, the two or more different manufacturing batches of the pharmaceutical product comprise manufacturing batches from different manufacturers.

[0075] 26. In some embodiments, for any of the methods described herein, the method is performed on clinical outcome data from two or more different groups, wherein each of the two or more different groups contains clinical outcome data from different manufacturing batches of the drug product.

[0076] 27. In some embodiments, the method described in item 26 further includes comparing a standard target range for each of the two or more different groups of manufacturing batches.

[0077] 28. In some embodiments, with respect to the method as described in any one of items 2-8, 8, or 11-27, the maximum amplitude candidate target range value includes the highest and / or lowest value of the product quality attribute.

[0078] 29. In some embodiments, for any of the methods described herein, determining the exposure level of the product quality attribute includes the following calculations:

[0079]

[0080] Where A t It is an estimated level of product quality attribute exposure at the time of application, summed from the contribution of each batch used at the time of application, where n is the total number of manufacturing batches used at the time of application, and for each manufacturing batch i, %A 0,i It is the percentage of the product's quality attribute at the time of batch release or analytical testing, %A Δ,i It is the percentage change rate of the product's quality attribute level over time under given storage conditions, t. i It is the time stored under the given conditions, and D i This refers to the dosage intensity to be applied.

[0081] 30. In some embodiments, for any of the methods described herein, determining the exposure level of the product quality attribute includes the following calculations:

[0082]

[0083] Among them, %A rel It is the percentage of the product quality attribute exposure relative to the dose level, where A t It is the level of exposure of the product quality attribute calculated using Equation 1 or 2, where D ref It refers to the dose intensity of the active pharmaceutical ingredient in the drug product in terms of quality, associated with each application.

[0084] 31. In some embodiments, for any of the methods described herein, the product quality attribute includes molecular properties, endotoxins, color, clarity, polysorbate, nitrosamines, multiple process-related impurities, one process-related impurity, or pharmaceutical properties, or two or more of the listed items.

[0085] 32. In some embodiments of the method, such as the method described in item 31, the molecular property includes at least one of the following: acidic substance, basic substance, high molecular weight substance, subvisible particle number, visible particle, aggregation, low molecular weight, medium molecular weight, glycosylation (such as non-glycosylated heavy chain or high mannose), glycosylation, sialylation, non-heavy chain and light chain, deamidation, deamination, cyclization, oxidation, sulfation, hydroxylysine, isomerization, fragmentation / shearing, N-terminal and C-terminal variants, signal peptide, reduced substance and partial substance, misfolding, disulfide rearrangement, domain exchange, folded structure, surface hydrophobicity, chemical modification, covalent bond, mutation / misincorporation, C-terminal amino acid motif PARG, C-terminal amino acid motif PAR-amide, drug-antibody ratio (DAR) or peptide-antibody ratio (PAR).

[0086] 33. In some embodiments of the method, such as the method described in item 31 or 32, the process-related impurities include at least one of CHOP, HCP, residual host cell DNA, residual ProA, or process reagent.

[0087] 34. In some embodiments of the method, such as any one of items 31-33, the pharmaceutical characteristic includes impurities; particles; excipients as non-pharmaceutical characteristics; process reagents; extractables; leachables; and / or component characteristics.

[0088] 35. In some embodiments, for any of the methods described herein, the level of the product quality attribute is determined by one or more of the following: mass spectrometry, chromatography, electrophoresis, spectroscopy, optical obscuration, particle methods (such as nanoparticles / visible / micron-scale resonant mass or Brownian motion), analytical centrifugation, imaging or imaging characterization, or immunoassay.

[0089] 36. In some embodiments, for any of the methods described herein, the standard target scope includes action limits, acceptance criteria, or quality targets.

[0090] 37. In some embodiments, for any of the methods described herein, the product quality attribute level outside the candidate or standard target range is (i) a level exceeding the maximum value of the candidate or standard target range, (ii) a level below the minimum value of the candidate or standard target range, or (iii) any one of (i) or (ii).

[0091] 38. In some embodiments, for any of the methods described herein, the pharmaceutical product comprises a biotherapeutic agent, a synthetic molecule, a small molecule, or a nucleic acid.

[0092] 39. In some embodiments of the method, such as in the method described in item 38, the biotherapeutic agent is selected from the group consisting of: antibodies, antigen-binding antibody fragments, antibody protein products, bispecific T-cell connector (BiTE®) molecules, bispecific antibodies, trispecific antibodies, Fc fusion proteins, recombinant proteins, recombinant viruses, recombinant T cells, synthetic peptides, and active fragments of recombinant proteins.

[0093] 40. In some embodiments of the method, such as in the method described in item 38, the pharmaceutical product comprises a synthetic small molecule.

[0094] 41. In some embodiments of the method, such as in the method described in item 38, the nucleic acid comprises siRNA, mRNA, or DNA.

[0095] 42. In some embodiments, such as the method described in any one of items 4-8 or 11-39, the pharmaceutical product comprises a biotherapeutic agent, and manufacturing the pharmaceutical product comprises culturing genetically engineered mammalian host cells containing one or more nucleic acids encoding the biotherapeutic agent. Attached Figure Description

[0096] Figure 1 Schematic diagrams are shown illustrating aspects of methods according to some embodiments herein.

[0097] Figure 2Histograms showing the incidence of adverse events according to some embodiments of the present document are provided. Detailed Implementation

[0098] This article describes methods for assessing the clinical impact of product quality attributes, establishing target ranges for product quality attributes, and manufacturing pharmaceutical products. This article considers that the acceptable range of product quality attributes in a pharmaceutical product can be determined based on whether there is a relationship between the maximum extent of exposure to the product quality attribute in subjects and the development of individual clinical outcomes, such as adverse events. Candidate target ranges for product quality attributes can be provided for assessment. Subjects from clinical studies can be binned based on whether their exposure to the product quality attribute at the time of administration is within or outside (e.g., beyond) the candidate target range. The association (or lack thereof) between attribute exposure outside the candidate target range and a specified clinical outcome, such as adverse events, can then be determined. If there is no association between the clinical outcome (e.g., incidence of adverse events) and the level of the product quality attribute outside the limit of the candidate target range, it can be concluded that clinical exposure to the product quality attribute does not affect the clinical outcome, and the candidate target range can be considered acceptable. Product quality attribute criteria can be based on this acceptable target range. If there is no clinical difference in clinical outcomes between subject bins that received and did not receive product quality attributes outside the target range, it can be concluded that there is no association. Alternatively, if an association exists between clinical outcomes (e.g., adverse event incidence) and levels of product quality attributes exceeding the target range, it may not be possible to conclude that the product quality attribute has no impact on clinical outcomes. Clinical differences between subject boxes that received and did not receive product quality attributes outside the target range can indicate such an association. In such cases, different target ranges can be selected and tested to identify criteria where the range of product quality attributes does not affect clinical outcomes.

[0099] Advantageously, the method described herein uses a binning approach to assess a narrow patient population with the highest amplitude of exposure to a specific attribute, allowing patients at higher risk (in terms of attribute exposure) to receive greater attention. The method described herein involves targeted analysis only on a subgroup of subjects already exposed to a product quality attribute exceeding a specified threshold. Compared to methods that analyze the entire patient population (regardless of attribute exposure level), the method described herein bins subjects into multiple groups based on attribute exposure. The method described herein is envisioned to enhance the sensitivity and likelihood of detecting the clinical impact of product quality attributes, as each subject in the high-amplitude exposure group is examined individually. The method described herein has advantages over other methods that analyze the entire subject population, where statistical averaging may dilute the response of a few individual subjects (who may respond to the product quality attribute), but this response becomes undetectable when combined with the responses of all subjects in the population. Other methods (typically illustrating population-level dynamics) may be diluted by the number of data points being used, compared to the method described herein (targeting top subjects individually to avoid data dilution).

[0100] In other words, the method described in this paper can focus the analysis only on the subject group with the highest amplitude attribute exposure and provide a "worst-case" scenario for the potential impact of high amplitude product quality attribute levels. On the other hand, analyzing the entire subject population (regardless of attribute exposure level) may dilute any impact of the highest amplitude product quality attribute exposure.

[0101] Accordingly, the methods described herein can avoid false negatives when analyzing the impact of product quality attributes of pharmaceutical products on clinical outcomes, such as adverse events. Furthermore, by targeting narrow subgroups rather than searching for patterns across the entire subject population, the methods described herein can be performed quickly with minimal time investment and, if automated, with minimal computational resource usage. The methods described herein can be used to demonstrate product safety to regulators using clinical data. They provide applicability methods and can quickly focus on clinical study subjects exposed to high-amplitude attributes outside the scope of the candidate target (e.g., exceeding it). Aspects of the methods in some embodiments are described below. Figure 1 It is shown schematically in the middle.

[0102] The methods described herein can be used to analyze the impact of candidate target product quality attribute ranges (for pharmaceutical products) on clinical outcomes, such as adverse events or changes in efficacy. Standardized product quality attribute target ranges accepted through the methods described herein can be considered to define a safe and effective level of product quality attributes, as demonstrated by clinical data. Such standardized product quality attribute target ranges can be used for quality target product profiling to guide the development of the pharmaceutical product's manufacturing process. Furthermore, such standardized product quality attribute target ranges can be used as pass / fail criteria for manufacturing batches of the pharmaceutical product. These batches can be evaluated at appropriate stages of manufacturing, such as the active pharmaceutical ingredient (API) stage or the drug product stage.

[0103] Furthermore, the methods described herein can combine results from two or more manufacturing batches to enhance their analytical capabilities. For example, if a specific active pharmaceutical ingredient is manufactured according to two or more different processes, origins, and / or manufacturers, resulting in a wider range of product quality attribute levels, then only the maximum range of product quality attribute exposure levels can be assessed, thereby increasing the likelihood of detecting any impact of product quality attributes.

[0104] Furthermore, patient boxes can be further subdivided or divided into sub-boxes to identify additional ways in which product quality attributes may or may not have a clinical impact. For example, the methods described herein can assess the impact of product quality attributes on patient subgroups with specific clinical characteristics, such as pre-existing conditions, biomarkers, laboratory results, or demographic information. If different impacts of product quality attributes exist, then different doses of the pharmaceutical product (and therefore different levels of product quality attribute exposure) can therefore be provided to subgroups affected by different impacts of product quality attributes.

[0105] It should be understood that pharmaceutical products can be administered at a fixed dose (e.g., mg of the active pharmaceutical ingredient (API)) or a weight-based dose (e.g., mg of API per kg of patient weight). Alternatively, pharmaceutical products can be administered via a stepwise dosing regimen, where the dose depends on the number of administrations received by the subject (e.g., the first injection dose may be lower than subsequent injection doses). However, the standard target range for a product quality attribute can be assessed at the manufacturing batch level, where each batch contains many potential doses of the pharmaceutical product. The standard target range for a product quality attribute in a manufacturing batch can be calculated using gravimetric analysis and clinical dosing based on candidate target ranges for that product quality attribute at the individual patient attribute exposure level to ensure that the target range is expressed in appropriate units in the correct context. For example, if a monoclonal antibody is administered at a fixed dose of 100 mg, and up to 5 mg of the HMW substance candidate target range is not associated with any adverse events (or any loss of potency), then up to 5% (5 mg / 100 mg) of the HMW substance standard target range can be determined to be reasonable and acceptable in the manufacturing batch. However, it will be further understood that some product quality attributes (such as subvisible particles) are not typically expressed in units of mass. Given this disclosure, those skilled in the art will be able to readily apply and (where necessary) convert applicable units between standard target ranges for product quality attributes, target ranges for candidate product quality attributes, and attribute exposure levels in clinical studies. By performing an applicable unit conversion (a conversion between units of clinical attribute exposure and acceptable attribute ranges in batches of pharmaceutical products (including active pharmaceutical ingredients or pharmaceutical products), those skilled in the art can derive a standard target range for product quality attributes “based on” the candidate target range. It will be further understood that a standard target range for product quality attributes “based on” the candidate target range may include adjustments based on practical factors (such as significant figures based on the sensitivity of relevant analytical assays) and practical considerations. For example, negative values ​​for product quality attribute parameters may not have practical meaning, so for a range of “less than X” or “less than or equal to X”, zero (0) will be understood as its substantive lower limit.

[0106] Typically, a “high amplitude” or “maximum amplitude” product quality attribute level will be an exponentially higher level than the maximum value of the candidate target range for that product quality attribute. For example, high molecular weight (HMW) substances in biotherapeutic agents may be associated with immunogenicity and / or loss of efficacy. Accordingly, for the analysis of the effect of HMW substances on efficacy, those skilled in the art will understand that HMW substances exceeding the maximum level of the candidate target range will indicate whether HMW substances outside that range may have an impact on clinical outcomes, including adverse events and / or changes in efficacy. However, it should be further understood that for some product quality attributes, such as medium molecular weight (MMW) substances, values ​​below the minimum value of the candidate target range may also have potential clinical effects. For each product quality attribute, given this disclosure and available prior knowledge, those skilled in the art can readily determine the relevant analysis for a given product quality attribute outside the candidate target range, which will refer to a product quality attribute level exceeding the maximum level, below the minimum level, or both. Thus, in some embodiments, a product quality attribute level outside the standard target range is (i) a level exceeding the maximum value of the standard target range. In some embodiments, a product quality attribute level outside the standard target range is (ii) a level below the minimum value of the standard target range. In some embodiments, the level of product quality attributes outside the standard target range is (i) a level that exceeds the maximum value of the standard target range, or (ii) a level that is below the minimum value of the standard target range.

[0107] Product quality attributes

[0108] "Product quality attributes" and variations thereof have their common and conventional meaning as would be understood by one of ordinary skill in the art in light of this disclosure. It refers to the physical or chemical properties of a pharmaceutical product other than the skeleton or core structure of the active pharmaceutical ingredient itself. Examples of product quality attributes include molecular properties, endotoxins, color, clarity, polysorbates, nitrosamines, process-related impurities, active pharmaceutical ingredient characteristics, pharmaceutical properties, or any combination of two or more of the listed items.

[0109] The term "molecular property" and variations thereof have their common and conventional meaning as will be understood by one of ordinary skill in the art in light of this disclosure. A "molecular property" refers to the structure of a macromolecule (such as a protein or nucleic acid) with chemical or physical changes and can be characterized by its chemical identity or property type and its position in the sequence of the macromolecule (e.g., the amino acid position where the property occurs). For example, asparagine and glutamine residues readily undergo deamidation. Deamidated asparagine at position 10 of the amino acid sequence of a therapeutic protein is an example of a property. Exemplary types of molecular properties are described herein. For brevity, molecular properties may be simply referred to as "properties" herein. The level of a drug quality-critical property, or critical quality attribute (CQA), can be clearly defined by product purity standards. These standards are typically subject to extensive regulatory scrutiny. In some embodiments, standards may set permissible levels of one or more molecular properties in the manufacture of biotherapeutic agents.

[0110] In some embodiments, the molecular properties include or consist of one or more of the following: acidic substances, basic substances, high molecular weight substances, particle number (visible and / or subvisible particles), low molecular weight, medium molecular weight, glycosylation (such as non-glycosylated heavy chains or high mannose), non-heavy chains and light chains, deamidation, deamination, saccharification, sialylation, sulfation, hydroxylation, misassembled molecules, mutation, cyclization, oxidation, isomerization, fragmentation / splicing, N-terminal and C-terminal variants, reduced and partially reduced substances, folded structures, surface hydrophobicity, chemical modification, covalent bonds, C-terminal amino acid motif PARG, C-terminal amino acid motif PAR-amide, drug-antibody ratio (DAR), or peptide-antibody ratio (PAR). In some embodiments, the molecular properties include or consist of at least one of the following: acidic substances, basic substances, high molecular weight substances, amino acid isomers, or subvisible particle number. PARG is an alternative C-terminal variant of the antibody, which may arise due to alternative splicing. It represents four amino acids (proline, alanine, arginine, and glycine), with the "AR" genetically inserted into the canonical IgG2 C-terminal sequence. PAR-amide is another C-terminal variant produced by further processing PARG. It refers to the cleavage of the C-terminal glycine from the PARG-terminated antibody, leaving an amide group on the C-terminal arginine.

[0111] "Process-related impurities" and variations thereof have their common and conventional meaning as would be understood by one of ordinary skill in the art in light of this disclosure. It refers to substances other than any specified excipients that may be present in the intact active pharmaceutical ingredient and pharmaceutical product. Examples of process-related impurities include host cell proteins (HCPs), unfiltered process materials, Chinese hamster ovary protein (CHOP), residual host cell DNA, residual protein A (ProA) and / or protein L (ProL), process reagents, or any combination of two or more of the listed items.

[0112] The term "pharmaceutical characteristics" and variations thereof have their common and conventional meanings as will be understood by one of ordinary skill in the art in light of this disclosure. Pharmaceutical characteristics may include impurities, particles (visible and / or subvisible), excipients, and non-pharmaceutical features. Examples of non-pharmaceutical features include materials used in a type of application device (such as a syringe) (e.g., metallic components), components used in the application device, and / or components used in plastics. Pharmaceutical characteristics may also include process reagents, extractables and leachables (such as plastic and / or metal ions from a reaction vessel), and component features (such as silicone oils and / or excipients).

[0113] Technology for detecting product quality attribute levels

[0114] Any suitable analytical technique for detecting product quality attribute levels can be used in conjunction with the methods described herein. It should be understood that pharmaceutical products have corresponding active pharmaceutical ingredients (APIs), and pharmaceutical properties can be evaluated in such APIs. Thus, product quality attributes as described herein can be determined in the pharmaceutical product or API (if applicable). Those skilled in the art will understand the methods used to appropriately validate analytical techniques, utilize appropriate standards and controls where applicable, and the appropriate detection limits for each analytical technique. Techniques for detecting product quality attributes include, but are not limited to, mass spectrometry, chromatography, electrophoresis, spectroscopy, optical obscuration, particle methods (nanoparticles / visible / micron-scale resonant mass or Brownian motion), analytical centrifugation, imaging and imaging characterization, and immunoassays.

[0115] Exemplary techniques for detecting product quality attributes include reducing and non-reducing peptide mapping analysis (which can detect chemical modifications), chromatography (such as size exclusion chromatography (SEC), ion exchange chromatography (IEX) such as cation exchange chromatography (CEX), hydrophobic interaction chromatography (HIC), affinity chromatography such as protein A-column chromatography or reversed-phase (RP) chromatography), capillary isoelectric focusing (cIEF), capillary zone electrophoresis (CZE), field flow separation (FFF) or ultracentrifugation (UC), HIAC (such as for detecting subvisible particle counts), MFI (such as for detecting subvisible particle counts and morphology), visual inspection (visible particles), SDS-PAGE (such as for detecting fragments, covalent aggregates), and color analysis (Trp). Ox), rCE-SDS and nrCE-SDS (such as for detecting fragments as part of a molecule), nanoparticle size determination, spectroscopic methods (such as FTIR, CD, intrinsic fluorescence or ANS dye binding), Ellman assay (free thiol), SEC-MALS, hydrophilic interaction liquid chromatography (HILIC) (glycan mapping), ELISA (such as for detecting HCP) or mass spectrometry.

[0116] pharmaceutical products

[0117] As used herein, “pharmaceutical product” and variations thereof have their common and conventional meaning as will be understood by one of ordinary skill in the art in light of this disclosure. It refers to a therapeutic product containing an active pharmaceutical ingredient (API). A pharmaceutical product may further contain additional substances, such as carriers or excipients. In some embodiments, a pharmaceutical product is subject to regulatory and premarket approval by a government regulatory agency, such as the Food and Drug Administration (FDA) or the European Medicines Agency (EMA). In some embodiments, a pharmaceutical product is authorized by such a government regulatory agency for administration to human subjects. Examples of pharmaceutical products include biologics, small molecules, synthetic molecules, and nucleic acids (such as small interfering RNA (siRNA) and DNA). In some embodiments, a pharmaceutical product is intended for medical use. In some embodiments, a pharmaceutical product is intended for medical use in human subjects.

[0118] As used herein, “biothermal agent” and variations thereof have their common and conventional meaning as would be understood by one of ordinary skill in the art in light of this disclosure. “Biothermal agent” means a therapeutic composition comprising a biological macromolecule, such as a gene therapy agent, a therapeutic protein, a nucleic acid, a virus, or a cell or a portion thereof.

[0119] In the methods described herein, the biotherapeutic agent may be selected from the group consisting of: antibodies, antigen-binding antibody fragments, antibody protein products, bispecific T-cell connector (BiTE®) molecules, bispecific antibodies, trispecific antibodies, Fc fusion proteins, recombinant proteins, functional protein fragments, recombinant viruses, recombinant T cells, synthetic peptides, deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and active fragments of recombinant proteins.

[0120] The term "antibody" has its usual and common meaning, as understood by one of ordinary skill in the art in light of this disclosure. It refers to any isotype of immunoglobulin that specifically binds to a target antigen, and includes, for example, chimeric antibodies, humanized antibodies, and fully human antibodies. For example, an antibody can be a monoclonal antibody. For example, a human antibody can be any isotype of human antibody, including IgG (including IgG1, IgG2, IgG3, and IgG4 subtypes). Human IgG antibodies typically contain two full-length heavy chains and two full-length light chains. Antibodies may be derived from a single source or may be "chimeric" antibodies, meaning that different portions of the antibody may be derived from two or more different antibodies of the same or different species. It should be understood that once an antibody is obtained from its source, it can be further engineered, for example, to enhance stability and folding. Accordingly, it should be understood that "human" antibodies can be obtained from a source and can undergo further engineering, such as engineering in the Fc region. Engineered antibodies can still be referred to as a type of human antibody. Similarly, variants of human antibodies, such as those that have undergone affinity maturation, will also be understood as “human antibodies” unless otherwise stated. In some embodiments, an antibody comprises, is substantially composed of, or is composed of: a human antibody, a humanized antibody, or a chimeric monoclonal antibody.

[0121] In several respects, biotherapeutic agents are antibody protein products. As used herein, the term "antibody protein product" refers to any of several antibody substitutes based on an antibody architecture but not found in nature, in various contexts. In some respects, the molecular weight of the antibody protein product is in the range of at least about 12-150 kDa. In some respects, the antibody protein product has a valence (n) range from monomer (n = 1) to dimer (n = 2), to trimer (n = 3), to tetramer (n = 4), if not higher valences. In some respects, the antibody protein product is based on those that are part of the complete antibody structure and / or mimics those antibody fragments that retain the complete antigen-binding ability, such as scFv, Fab, and VHH / VH (discussed below). Small antigen-binding antibody fragments that retain the complete antigen-binding site are Fv fragments, which consist entirely of variable (V) regions. To stabilize the molecule, the V region is linked to the scFv fragment (a variable single-chain fragment) using a soluble, flexible amino acid peptide linker, or a constant (C) domain is added to the V region to produce a Fab fragment (an antigen-binding fragment). Both scFv and Fab fragments can be readily produced in host cells, such as prokaryotic host cells. Other antibody protein products include disulfide-stabilized scFv (ds-scFv), single-chain Fab (scFab), and dimer and polymeric antibody forms, such as bifunctional, trifunctional, and tetrafunctional antibodies, or various forms of mini-antibodies (miniAbs) comprising scFvs linked to oligomeric domains. The smallest fragments are the VHH / VH of camel heavy chain Abs and single-domain Abs (sdAbs). Structural units frequently used to construct antibody forms include VH domains (e.g., for fragments containing or based on heavy chain-only molecules), or single-chain variable (V) domain antibody fragments (scFvs) containing V domains (VH and VL domains) from the heavy and light chains linked by peptide linkers of approximately 15 amino acid residues. Peptibody, or peptide-Fc fusion, is another type of antibody protein product. The structure of a peptibody consists of a bioactive peptide grafted onto an Fc domain. Peptibody is well described in the art. See, for example, Shimamoto et al., mAbs [Monoclonal Antibodies] 4(5): 586-591 (2012).

[0122] Biological therapeutic agents suitable for the methods described herein may include peptides, including those that bind to one or more of the following: these include CD proteins, including CD3, CD4, CD8, CD19, CD20, CD22, CD30, and CD34; including those that interfere with receptor binding; HER receptor family proteins, including HER2, HER3, HER4, and EGF receptors; and cell adhesion molecules, such as LFA-I, MoI, p150, 95, VLA-4, ICAM-I, VCAM, and αv / β3 integrin. Growth factors, such as vascular endothelial growth factor (“VEGF”), growth hormone, thyroid-stimulating hormone, follicle-stimulating hormone, luteinizing hormone, growth hormone-releasing factor, parathyroid hormone, Müllerian-inhibiting substance, human macrophage inflammatory protein (MIP-1α), erythropoietin (EPO), nerve growth factor (such as NGF-β), platelet-derived growth factor (PDGF), fibroblast growth factor (including, for example, aFGF and bFGF), epidermal growth factor (EGF), transforming growth factor (TGF) (especially including TGF-α and TGF-β, including TGF-β1, TGF-β2, TGF-β3, TGF-β4 or TGF-β5), insulin-like growth factor-I and insulin-like growth factor-II (IGF-I and IGF-II), des(l-3)-IGF-I (brain IGF-I) and bone-inducing factor. Insulin and insulin-related proteins, including insulin, insulin A chain, insulin B chain, proinsulin, and insulin-like growth factor binding proteins. Coagulation proteins and coagulation-related proteins, especially factors such as factor VIII, tissue factor, von Willebrands factor, protein C, α-1-antitrypsin, plasminogen activators (such as urokinase and tissue plasminogen activator (“t-PA”)), bombazine, thrombin, and thrombopoietin; (vii) other blood and serum proteins, including but not limited to albumin, IgE, and blood group antigens. Colony-stimulating factors and their receptors, especially including M-CSF, GM-CSF, and G-CSF and their receptors, such as the CSF-1 receptor (c-fms). Receptors and receptor-related proteins, including, for example, flk2 / flt3 receptors, obesity (OB) receptors, LDL receptors, growth hormone receptors, thrombopoietin receptors (“TPO-R”, “c-mpl”), glucagon receptors, interleukin receptors, interferon receptors, T-cell receptors, stem cell factor receptors (such as c-Kit), and other receptors. Receptor ligands, including, for example, OX40L, which is a ligand for the OX40 receptor.Neurotrophic factors, including bone-derived neurotrophic factor (BDNF) and neurotrophin-3, neurotrophin-4, neurotrophin-5, or neurotrophin-6 (NT-3, NT-4, NT-5, or NT-6). Relaxin A chain, relaxin B chain, and pro-relaxin; interferons and interferon receptors, including, for example, interferon-α, interferon-β, and interferon-γ and their receptors. Interleukins and interleukin receptors, particularly IL-1 to IL-33 and IL-1 to IL-33 receptors, such as the IL-8 receptor. Viral antigens, including AIDS enveloped virus antigens. Lipoproteins, calcitonin, glucagon, atrial natriuretic factor, pulmonary surfactant, tumor necrosis factor-α and tumor necrosis factor-β, enkephalins, RANTES (activating regulatory proteins expressed and secreted by normal T cells), mouse gonadotropin-related peptide, DNases, inhibin, and activin. Integrins, protein A or D, rheumatoid factor, immunotoxins, bone morphogenetic protein (BMP), superoxide dismutase, surface membrane proteins, decay accelerator factor (DAF), HIV envelope, transport proteins, homing receptors, addressins, regulatory proteins, immunoadhesins, antibodies. Myostatin, TALL proteins (including TALL-I), amyloid proteins (including but not limited to amyloid β protein), thymic stromal lymphopoietin (“TSLP”), RANK ligands (“RANKL” or “OPGL”), c-kit, TNF receptors (including TNF receptor type 1), TRAIL-R2, angiopoietin, and any of the above-mentioned bioactive fragments or analogues or variants.

[0123] Examples of biological therapeutic agents suitable for the methods described herein include antibodies such as infliximab, bevacizumab, cetuximab, ranibizumab, palivizumab, abagovomab, abciximab, actoxumab, adalimumab, afelimomab, afutuzumab, alacizumab, pegol, ald518, alemtuzumab, alicurumab, attumomab, amatuximab, and anatumomab. mafenatox, anrukinzumab, apolizumab, arcitumomab, acelizumab, altinumab, atlizumab, atorolimiumab, tocilizumab, bapineuzumab, basiliximab, bavituxim ab), bectumomab, belimumab, bemarituzumab, beralizumab, bertilimumab, besilesomab, bevacizumab, bezlotoxumab, biciromab, bivatuzumab, mor-bivatuzumab Mertansine, blinatumomab, blosozumab, brentuximab vedotin, briakinumab, brodalumab, canakinumab, cantuzumab mertansine, cantuzumabMertansine, caplacizumab, capromab pendetide, carlumab, catumaxomab, CC49, cedelizumab, certolizumab pegol, cetuximab, citatuzumab bogatox, cixutumab, clazakizumab, clenoliximab, clivatuzumab tetraxetan, conatumumab, crenezumab, CR6261, dacetuzumab, daclizumab, dalotuzumab, daratumumab, demcizumab, denosumab, detumomab, dorlimomabaritox, drozitum ab), duligotumab, dupilumab, ecromeximab, eculizumab, edobacomab, edrecolomab, efalizumab, efungumab, elotuzumab, elsilimomab, enavatuzumab, enlimomabpegol, enokizumab, enoticumab, ensituximab, epitumomabcituxetan, epratuzumab, erenumab, erlizumab, ertumaxomab, etaracizumab, etrolizumab, evolocumab, exbivirumab, fanolesomab, faralimomab, farletuzumab, farsinumab ab), fbta05, felvizumab, fezakinumab, ficlatuzumab, figitumumab, flanvotumab, fontolizumab, foralumab, foravirumab, fresolimumab, fulranumab, futuximab, galiximab, ganitumab, gantenerumab, gavilimomab, gemtuzumab (Ozomicin) ozogamicin, gevokizumab, girentuximab, glembatumumab vedotin, golimumab, gomiliximab, GS6624, ibalizumab, ibritumomab tiuxetan, icrucumab, igovomab, imciromab, imgatuzumab, inclacumab, indatuximab ravtansine, infliximab, intetumumab, ininolimomab, inotuzumabozogamicin, ipilimumab, iratumumab, itolizumab, ixekizumab, keliximab, labetuzumab, lebrikizumab, lemalesomab, lerdelimumab, lexatumumab, libivirumab, ligelizumab, lintuzumab, lirilumab, lorvotuzumab Mertansine, Lucatumumab, Lumiliximab, Mapatumumab, Maslimomab, Mavrilimumab, Matuzumab, Mepolizumab, Metelimumab, Milatuzumab, Minretumomab, Mitumomab, Mogamulizumab, Morolimumab, Motavizumab, Moxetumomab Pasudotox, Muromonab-CD3, Nacolomab Tafenatox, Namilumab, Naaptumomab Esafenatox, Narnatumab, Natalizumab, Nebacumab, Necitumumab, Nerelimomab, Nesvacumab, Nimotuzumab, Nivolumab, NofetumomabMerpentan, Ocaratuzumab, Ocrelizumab, Odulimomab, Ofatumumab, Olaratumab, Olokizumab, Omalizumab, Onartuzumab, Oportuzumab Monatox, Oregomab, Orticumab, Otelixizumab, Oxelumab, Ozanezumab, Ozoralizumab, Pagibaximab, Palivizumab, Panitumumab, Panobacumab, Parsatuzumab, Pascolizumab umab), pateclizumab, patritumab, pemtumomab, perakizumab, pertuzumab, pexelizumab, pidilizumab, pintumomab, placulumab, ponezumab, priliximab, pritumumab, PRO140. Quilizumab, Racotumomab, Radretumab, Rafivirumab, Ramucirumab, Ranibizumab, Raxibacumab, Regavirumab, Reslizumab, Rilotumumab, Rituximab, Robatumumab, Roledumab, Romosozumab, Rontalizumab, Rovelizumab, Ruplizumab, Samalizumab, Sarilumab, Satumomab Pendetide, secukinumab, sevirumab, sibrotuzumab, sifalimumab, siltuximab, simtuzumab, siplizumab, sirukumab, solanezumab, solitomab, solitomab, sonetuzumab, stamulumab, sulesomab, suvizumab, tabalumab, tacatuzumab tetraxetan, tadocizumab, talizumab, tanezumab, taplitumomab paptox, tarlatamab, tefibazumab, telimomabaritox, tetiramomab, tefibazumab, teneliximab, teplizumab, teprotumumab, tezepelumab, TGN1412, tremelimumab, ticilimumab, tildrakizumab, tigatuzumab, TNX-650, tocilizumab, toralizumab, tositumomab, tralokinumab, trastuzumab, TRBS07, tregalizumab, tucotuzumab celmoleukin, tuvirumab, ublituximab, urelumab, urtoxazumab, ustekinumab, vapaliximab, vatelizumab, vedolizumab, veltuzumab, vepalimomab, vesencumab, visilizumab, volociximab, vorsetuzumab mafodotin, votumumab, zalutumumab, zanolimumab, zatuximab, ziralimumab, or zolimomab aritox).

[0124] In some embodiments, the biotherapeutic agent is a BiTE® molecule. BiTE® molecules are engineered bispecific antigen-binding constructs that guide the cytotoxic activity of T cells against cancer cells. They are fusions of two single-chain variable fragments (scFvs) of different antibodies or amino acid sequences from four different genes on a single peptide chain of approximately 55 kDa. One scFv binds to T cells via a CD3 receptor, while the other binds to tumor cells via a tumor-specific molecule. Blincyto® is an example of a CD19-specific BiTE® molecule. Modified BiTE® molecules (such as those modified to extend their half-life) may also be used in the disclosed methods. In various aspects, the polypeptide is an antigen-binding protein, such as a BiTE® molecule. In some embodiments, the antibody protein product comprises a BiTE® molecule.

[0125] In some embodiments, the biotherapeutic agent is contained in a formulation. This formulation may be pharmaceutically acceptable. The formulation may comprise the biotherapeutic agent together with pharmaceutically acceptable diluents, carriers, solubilizers, emulsifiers, preservatives, and / or adjuvants.

[0126] Acceptable formulation substances for use as described herein are preferably non-toxic to the recipient at the doses and concentrations used. In some embodiments, the pharmaceutical composition may contain formulation materials for altering, maintaining, or preserving, for example, the composition's pH, osmotic pressure, viscosity, transparency, color, isotonicity, odor, sterility, stability, dissolution or release rate, adsorption, or penetration. In such embodiments, suitable formulation materials include, but are not limited to, amino acids (such as glycine, glutamine, asparagine, arginine, or lysine); antimicrobial agents; antioxidants (such as ascorbic acid, sodium sulfite, or sodium bisulfite); buffers (such as borates, bicarbonates, Tris-HCl, citrates, phosphates, or other organic acids); leavening agents (such as mannitol or glycine); chelating agents (such as ethylenediaminetetraacetic acid (EDTA)); complexing agents (such as caffeine, polyvinylpyrrolidone, β-cyclodextrin, or hydroxypropyl-β-cyclodextrin); fillers; monosaccharides; disaccharides; and other carbohydrates (such as glucose, sucrose, mannose, or dextrin); proteins (such as serum albumin, gelatin, or immunoglobulins); colorants, flavoring agents, and diluents; emulsifiers; hydrophilic polymers (such as polyvinylpyrrolidone); and low molecular weight peptides. Salt-forming counterions (such as sodium); preservatives (such as benzalkonium chloride, benzoic acid, salicylic acid, thimerosal, phenethyl alcohol, methylparaben, propylparaben, chlorhexidine, sorbic acid, or hydrogen peroxide); solvents (such as glycerol, propylene glycol, or polyethylene glycol); sugar alcohols (such as mannitol or sorbitol); suspending agents; surfactants or wetting agents (such as pluronics, PEG, dehydrated sorbitol esters, polysorbate esters (such as polysorbate 20, polysorbate esters), triton, tromethamine, lecithin, cholesterol, tyloxapal); stability enhancers (such as sucrose or sorbitol); tension enhancers (such as alkali metal halides (preferably sodium chloride or potassium chloride), mannitol, sorbitol); delivery media; diluents; excipients and / or pharmaceutical adjuvants. See, for example, REMINGTON'S PHARMACEUTICALSCIENCES, 18th edition, (edited by AR Genrmo), 1990, Mack Publishing Company.

[0127] Suitable mediators or carriers for this formulation may be water for injection, physiological saline, or artificial cerebrospinal fluid, possibly supplemented with other substances commonly used in parenteral administration. Neutral buffered saline or saline mixed with serum albumin are other exemplary mediators. In certain embodiments, the pharmaceutical composition comprises a Tris buffer at about pH 7.0-8.5 or an acetate buffer at about pH 4.0-5.5, and may further comprise sorbitol or a suitable alternative thereof.

[0128] Product quality attributes exposed

[0129] It should be understood that the level of product quality attributes in pharmaceutical products may change over time. For example, the level of some product quality attributes may increase as the pharmaceutical product is stored for a period of time. This paper envisions that, for the method described herein, it is advantageous to determine the level of product quality attributes when administering the pharmaceutical product to subjects, which would improve the accuracy of attribute effect determination.

[0130] For example, drug exposure can be calculated using gravimetric analysis to determine product quality attribute exposure, and the maximum standard dose (MSD) of an attribute can be calculated based on the maximum permissible dose. MSD is an example of a target range limit for a candidate product quality attribute. It should be understood that some product quality attributes (such as subvisible particles) are not typically measured in units of mass; therefore, attribute exposure can be calculated proportionally to dose, but not necessarily using gravimetric analysis. The difference between product quality attribute exposure and MSD can be calculated.

[0131] In some embodiments, the exposure level of a product quality attribute includes the following calculations:

[0132]

[0133] [Equation 1]

[0134] Where A t It is an estimated level of product quality attribute exposure at the time of application, summed from the contribution of each batch used at the time of application, where n is the total number of manufacturing batches used at the time of application, and for each manufacturing batch i: %A 0,i It is a percentage of product quality attributes at the time of batch release or analytical testing, %A Δ,i It is the percentage change rate of a product quality attribute level over time under given storage conditions, t. i It is the time stored under the given conditions, and D i This refers to the administered dose intensity. In some embodiments, D i This refers to the dose when n = i = 1, or the component dose when n > 1.

[0135] In some embodiments, determining the exposure level of a product quality attribute includes the following calculations:

[0136] [Equation 2]

[0137] Among them, %A rel It is the percentage of the product quality attribute exposure relative to the dose level, where A t It is the level of exposure of the product quality attribute calculated using Equation 1 or 2, where D ref It refers to the dose intensity of the active pharmaceutical ingredient in a drug product in terms of quality, which is associated with each application.

[0138] A particular batch (such as pharmaceuticals) is expected to be stored under different conditions (such as different temperatures). In this case, the exposure level of product quality attributes can be calculated using the following methods:

[0139] [Equation 3]

[0140] The variables are defined according to the equation, and hj is a condition (e.g., temperature), with a maximum of k conditions.

[0141] In some embodiments, the exposure level of a product quality attribute is calculated based on the release criteria, stability criteria, and time elapsed until the release of the clinical batch. Based on the dosage of the drug product, a weighted analysis can be used to convert the relative attribute level to the attribute exposure level (and vice versa), using the same units for candidate target ranges and product quality attribute exposures in the clinical dataset.

[0142] Optionally, clinical outcome data can be preprocessed along with the calculation of attribute exposures. Exposures and clinical outcomes (such as adverse events) can be labeled according to logical rules. For example, exposures exceeding the MSD and / or clinical outcomes occurring only after exposure can be labeled. For example, clinical outcomes can be clustered by subject and event date. This analysis can identify clinical outcomes associated with the administration of the drug product, rather than human or coincidental events.

[0143] Methods for selecting or rejecting standard target ranges of product quality attributes

[0144] This article describes a method for selecting or rejecting a standard target range for a product quality attribute. Advantageously, the method described herein can select a standard target range for a product quality attribute based on the highest magnitude of attribute exposure in clinical studies, thereby reducing the likelihood of dilution of the impact of high-magnitude attribute exposure (which may occur if subjects with high-magnitude attribute exposure are averaged in a large population). Therefore, the method described herein has enhanced sensitivity to potential attribute effects and can be flexibly implemented with fewer computational resources. The method may include a) providing candidate target ranges for the product quality attribute of the pharmaceutical product. The method may further include b) obtaining clinical outcome data from subjects who have received administration of the pharmaceutical product. The method may further include c) determining the exposure level of the product quality attribute at the time of administration. The method may further include d) partitioning the clinical outcome data according to the exposure level of the product quality attribute, wherein clinical outcome data with exposure to the product quality attribute outside the candidate target range are assigned to a first partition, and clinical outcome data with exposure to the product quality attribute within the candidate target range are assigned to a second partition. The method may further include e) determining the incidence rate of a specified clinical outcome in the first partition and the incidence rate of a specified clinical outcome in the second partition. The method may further include f) either: (i) selecting a standard target range for the product quality attribute based on the candidate target range if there is no clinical difference between the incidence rates of the specified clinical outcome in the partitions; or (ii) rejecting the determination of the standard target range based on the candidate target range if there is a clinical difference between the incidence rates of the specified clinical outcome in the partitions. For example, a specified clinical outcome may be an adverse event incidence rate. For example, a candidate target range may refer to a threshold, and exposure of a product quality attribute within the candidate target range may refer to an exposure level below the threshold, while exposure of a product quality attribute outside the candidate target range may refer to an exposure level above the threshold.

[0145] As used herein, “clinical difference” has its usual and common meaning, as understood by one of those skilled in the art in light of this disclosure. It refers to a difference that is qualitatively significant in the context of one or more applicable clinical outcomes. For example, clinical difference can refer to a qualitative difference in clinical outcomes, a statistically significant difference in clinical outcomes, or a quantifiable trend. It should be understood that not every numerical difference is a clinical difference. For example, some clinical outcome parameters may have numerical differences at a certain granularity level, but this does not represent a qualitatively significant difference (e.g., two numerical parameters are slightly different, but within the detection error of the relevant measurement). However, clinical difference refers to a difference that represents a qualitatively different clinical condition in the context of a clinical situation and a specific clinical outcome, such as different incidence rates of adverse events that would be identified as different clinical conditions. In some embodiments of the methods, clinical difference includes at least one of qualitative difference, statistically significant difference, or quantifiable trend.

[0146] The term "candidate target range" for a product quality attribute has its common and conventional meaning, as would be understood by one of ordinary skill in the art in light of this disclosure. It refers to the range of product quality attribute levels of a pharmaceutical product that, when administered at a clinically relevant dose of the pharmaceutical product, can be used to assess the potential impact of product quality attributes within or outside this range. Candidate target ranges may be based on, for example, prior knowledge, in vitro or animal model data, or pharmacokinetic modeling.

[0147] The “standard target range” for a product quality attribute has its common and conventional meaning, as would be understood by one of ordinary skill in the art in light of this disclosure. It refers to a specified target range for the level of a product quality attribute of a pharmaceutical product, for which it has been determined that, when the pharmaceutical product is administered at a clinically relevant dose, the level of that product quality attribute is not associated with undesirable clinical outcomes. The standard target range may be included in a quality target product profile, which may be used to develop a method of manufacturing the pharmaceutical product. The standard target range may be included in release criteria for a batch of the pharmaceutical product being manufactured (including active pharmaceutical ingredient or drug product batch, if applicable). For any of the methods described herein, the standard target range may include action or rejection limits, acceptance criteria, or quality objectives.

[0148] Optionally, the method can be repeated for at least one additional candidate target range. It is envisioned that two or more distinct candidate target ranges can be selected based on prior knowledge or for hypothesis testing purposes. The largest target range from which no product quality attribute influences (no association between clinical outcomes and attribute exposures outside the target range) can then be selected, for example, to improve manufacturing efficiency by avoiding unnecessary rejection of clinically acceptable batches of pharmaceutical products. Example 2 illustrates the method described herein, wherein the method is performed for multiple candidate target ranges.

[0149] For some of the methods described herein for selecting or rejecting a standard target range, these methods further include repeating a)-e) for at least one additional candidate target range for a product quality attribute, and any of the following: (iii) selecting the standard target range based on a maximum amplitude candidate target range value for which there is no clinical difference between the incidence rates of the specified clinical outcome in the partitions; or (iv) rejecting the determination of the standard target range based on any of these candidate target ranges if there is a clinical difference between the incidence rates of the specified clinical outcome in the partitions for each of these candidate target ranges. Optionally, if the method includes (iv), the method may further include repeating the method with an additional candidate target range that has a lower amplitude than other candidate target ranges (e.g., the candidate target range and the at least one additional candidate target range).

[0150] Some of these methods can be used to inform the selection or rejection of a pharmaceutical product manufacturing batch. For example, some methods for selecting or rejecting the standard target range as described herein may further include g) manufacturing the pharmaceutical product in the batch; and h) determining the level of the product quality attribute in the batch of pharmaceutical product. The method may further include i) either: (i) rejecting the batch if the determined level of the product quality attribute is outside the standard target range for that product quality attribute; or (ii) accepting the batch if the determined level of the product quality attribute is within the standard target range for that product quality attribute. Optionally, if the batch is rejected, the method may further include marking the batch for investigation. This investigation may assess, for example, batch history, raw materials, and / or the suitability of the standard target range for further manufacturing.

[0151] Some of these methods can be used to develop manufacturing processes for pharmaceutical products based on a quality target product profile that includes a standard target range. For example, a standard target range can be used to define a quality target product profile, and manufacturing parameters, equipment selection, raw material selection, etc., can be selected to develop a manufacturing process that can produce a pharmaceutical product that is reasonably acceptable according to that quality target product profile.

[0152] Methods for manufacturing pharmaceutical products

[0153] This article describes methods for manufacturing pharmaceutical products. These methods ensure that the product quality attributes of the pharmaceutical product are within ranges relevant to acceptable clinical impact. For example, these methods can select a standard target range for product quality attributes based on candidate target ranges that are unrelated to undesirable clinical outcomes, such as adverse events or loss of efficacy. A batch of the pharmaceutical product can be accepted or rejected based on whether the level of the product quality attributes is within the standard target range.

[0154] A method of manufacturing a pharmaceutical product may include a) providing a candidate target range of product quality attributes for the pharmaceutical product. The method may further include b) obtaining clinical outcome data of subjects who have received administration of the pharmaceutical product. The method may further include c) determining the exposure level of the product quality attribute at the time of administration. The method may further include d) partitioning the clinical outcome data according to the exposure level of the product quality attribute, wherein clinical outcome data with exposure to the product quality attribute outside the candidate target range are assigned to a first partition, and clinical outcome data with exposure to the product quality attribute within the candidate target range are assigned to a second partition. The method may further include e) determining that there is no clinical difference in the incidence of the specified clinical outcome among these partitions. The method may further include f) selecting a standard target range of the product quality attribute for the pharmaceutical product based on the candidate target range. The method may further include g) either i) accepting batches of pharmaceutical products containing product quality attribute levels within the standard target range; or ii) rejecting batches of pharmaceutical products containing product quality attribute levels outside the standard target range.

[0155] Optionally, the method can be repeated for two or more different candidate target ranges. For example, a method of manufacturing a pharmaceutical product may include h) repeating a) - e) for at least one additional candidate target range for a product quality attribute. In such a method, f) selecting a standard target range for the product quality attribute may be based on a maximum magnitude candidate target range value for which there is no clinical difference in the incidence of the specified clinical outcome across different partitions.

[0156] Methods for assessing the impact of product quality attributes of pharmaceutical products

[0157] This article describes methods for assessing the impact of product quality attributes on pharmaceutical products. These methods can assess the impact of one or more product quality attributes on one or more specified clinical outcomes, such as adverse events. These methods can be used, for example, to inform the design of manufacturing processes, assess the impact of clinical attributes in real-world datasets, or evaluate the clinical acceptability of manufacturing processes or batches with certain ranges of product quality attributes.

[0158] Methods for assessing the impact of product quality attributes of a pharmaceutical product may include a) providing a candidate target range for the product quality attributes of the pharmaceutical product. The method may further include b) obtaining clinical outcome data from subjects who have received administration of the pharmaceutical product. The method may further include c) determining the exposure level of the product quality attribute at the time of administration. The method may further include d) partitioning the clinical outcome data according to the exposure level of the product quality attribute. Clinical outcome data where the exposure to the product quality attribute is outside the candidate target range may be assigned to a first partition, and clinical outcome data where the exposure to the product quality attribute is within the candidate target range may be assigned to a second partition. Optionally, clinical outcome data within the candidate target range may be assigned to two or more different sub-partitions, for example, based on the clinical characteristics of the subjects or a sub-range of the product quality attribute. The method may further include e) determining the incidence rate of the specified clinical outcome in the first partition and the incidence rate of the specified clinical outcome in the second partition. The method may further include f) either: (i) determining that the product quality attribute has no effect on the specified clinical outcome within the candidate target range if there is no clinical difference in the incidence of the specified clinical outcome within the partitions; or (ii) determining that the product quality attribute may have an effect on the specified clinical outcome within the target range if there are clinical differences in the incidence of the specified clinical outcome within the partitions. Optionally, the method may be repeated for two or more different candidate target ranges.

[0159] It should be further understood that the methods described herein can determine the impact of drug delivery methods and strategies (such as injection sites) on specified clinical outcomes (such as adverse events). Accordingly, for any of the methods described herein, "delivery method" or "injection site" can replace "product quality attribute". Thus, the method may include partitioning clinical outcome data according to delivery method (e.g., injection site), wherein clinical outcome data for a first delivery method (e.g., injection site) is assigned to a first partition, and clinical outcome data for a second delivery method (e.g., injection site) is assigned to a second partition. Such a method may further include determining the incidence of a specified clinical outcome in the first partition and the incidence of a specified clinical outcome in the second partition. A specified clinical outcome may include an injection site reaction. For such a method, if (i) there is no clinical difference between the incidence rates of the specified clinical outcome in the partitions, it can be determined that the delivery method (e.g., injection site) has no effect on the specified clinical outcome within the candidate target range. Or, (ii) if there is a clinical difference between the incidence rates of the specified clinical outcome in the partitions, it can be determined that the delivery method (e.g., injection site) may have an effect on the specified clinical outcome. Optionally, the method can be repeated for two or more different injection sites.

[0160] Additional options

[0161] For any of the methods described herein, including methods for selecting or rejecting standard target ranges of product quality attributes, methods for manufacturing pharmaceutical products, or methods for assessing the impact of product quality attributes of pharmaceutical products, the following additional options apply according to some embodiments:

[0162] For any of the methods described herein, clinical outcome data may include at least one of efficacy data or adverse event incidence data. In some embodiments of the method, clinical outcome data includes or consists of adverse event incidence data.

[0163] For any of the methods described herein, specifying a clinical outcome may include at least one of efficacy outcome or adverse event incidence. In some embodiments of the method, specifying a clinical outcome includes adverse event incidence. In some embodiments of the method, specifying a clinical outcome consists of adverse event incidence. Adverse event incidence may be expressed as a ratio or absolute value applicable to a particular method. Furthermore, in addition to occurrence, adverse events may also include a classification of severity or grade.

[0164] For any of the methods described herein, the method may further include filtering out any scientifically inapplicable clinical outcomes from the clinical outcome data prior to segmentation, such as adverse events clearly related to an unrelated disease state (e.g., if a subject acquires an unrelated viral infection), or clinical outcomes reflecting symptoms of a disease state being treated, or clinical outcomes occurring before administration of the drug product. For any of the methods described herein, wherein a specified clinical outcome includes or consists of an adverse event incidence rate, the method may further include filtering out any scientifically inapplicable adverse events from the adverse event incidence rate data prior to segmentation, such as adverse events occurring before administration of the drug product. The removal of such “isolated adverse events” occurring before administration is expected to enhance the accuracy of determining the association (or lack thereof) between product quality attributes and adverse events, as such isolated adverse events could lead to false positives or false negatives (depending on the patient group in which they occur) in determining the association or lack thereof between product quality attributes and adverse events. For any of the methods described herein, the method may further include identifying the first occurrence of this type of clinical outcome event for each subject (e.g., if the clinical outcome is an adverse event, the method may include identifying the first headache experienced by an individual, even if those individuals may have experienced multiple headaches during the clinical study). For some methods, repeated adverse events of the same type in the same individual may be counted as a single instance for the purpose of determining association or lack thereof.

[0165] For any of the methods described herein, multiple partitions may be used, such as at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 partitions. For any of the methods described herein, assigning clinical outcome data where the product quality attribute is exposed outside the candidate target range to the second partition includes assigning the clinical outcome data to two or more distinct partitions. For example, assigning clinical outcome data where the product quality attribute is exposed outside the candidate target range to the second partition may include assigning the clinical outcome data to two or more sub-partitions. For example, sub-partitions may be based on the clinical characteristics of the patient group, the type of clinical outcome (e.g., the type of adverse event), or the level of exposure to the product quality attribute.

[0166] For any of the methods described herein, the specified clinical outcome data may include two or more different categories or types of clinical outcomes, such as two or more different categories or types of adverse events. For any of the methods described herein, the category or type of clinical outcome used as the specified clinical outcome may be based on the incidence of these clinical outcomes. For example, the most common clinical outcome type or category may be the specified clinical outcome. For instance, a histogram listing the incidence of each type of adverse event may be prepared (see...). Figure 2The most common adverse events (e.g., the top 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 most common adverse events) can be selected as the designated clinical outcome.

[0167] For any of the methods described herein, the method may further include determining whether there is an association or lack thereof between the exposure level of a product quality attribute and clinical outcome data of two or more different categories or types. For any of the methods described herein, the method may further include determining whether there is an association or lack thereof between the exposure level of two or more different product quality attributes and clinical outcome data of at least one category or type. Optionally, for any of the methods described herein, the association or lack thereof between the exposure level of two or more different product quality attributes and clinical outcome data of at least one category or type may be determined automatically. Optionally, for any of the methods described herein, the association or lack thereof between the exposure level of a product quality attribute and only some of two or more different categories of clinical outcomes may be determined automatically.

[0168] For any of the methods described herein, the method may further include determining an association or lack thereof between at least one clinical characteristic of a subject in the first partition and a specified clinical outcome. Examples of “clinical characteristics” include pre-existing conditions, biomarkers, laboratory results, or demographic information, or a combination of two or more of the listed items.

[0169] For any of the methods described herein, clinical outcome data for a pharmaceutical product includes data from two or more different manufacturing batches of the pharmaceutical product. For example, these two batches may be manufactured using different processes, different raw materials, at different locations, and / or by different manufacturers (e.g., two different manufacturers of products with the same generic name). It is conceivable that combining data from two or more different batches can increase the diversity of product quality ranges and thus enhance the analytical capabilities used to identify the association (or lack thereof) between product quality attributes and clinical outcomes. In some embodiments, the two or more different manufacturing batches of the pharmaceutical product include manufacturing batches from different manufacturers.

[0170] Furthermore, it is envisioned that some of the methods described herein can combine the results of two or more clinical studies. For any of the methods described herein, the method can be performed on clinical outcome data from two or more different groups, each of which contains clinical outcome data from different manufacturing batches of the drug product. Optionally, the method may further include comparing a standardized target range for each manufacturing batch within the manufacturing batches of the two or more different groups of clinical outcome data.

[0171] As used herein, a “maximum magnitude candidate target range value” refers to a target range value that has the largest absolute difference from a baseline or null case (i.e., the core API without any changes or modifications) for a particular product quality attribute. For most product quality attributes, the maximum magnitude candidate target range value will be the candidate target range value with the highest value. However, for some product quality attributes (such as MMW substances), where a lower incidence of the product quality attribute indicates a more significant deviation from the baseline, the maximum magnitude candidate target range value will be the candidate target range value with the lowest value. For any of the methods described herein, the maximum magnitude candidate target range value includes the highest and / or lowest values ​​of the product quality attribute.

[0172] It should be understood that a product quality attribute level outside the candidate or standard target range will generally be a level exceeding the maximum value of the standard target, but may also be a value below the minimum value of the standard target range (e.g., in the case of MMW substances). It should be understood that for a product quality attribute where the standard target range is defined as a threshold, a product quality attribute level exceeding that threshold will be outside the range (e.g., if the target range is for a product quality attribute level ≤ X, then a product quality attribute level > X is outside the target range). For any of the methods described herein, a product quality attribute level outside the candidate or standard target range may be (i) a level exceeding the maximum value of the candidate or standard target range, (ii) a level below the minimum value of the candidate or standard target range, or (iii) any one of (i) or (ii). Example

[0173] Example 1: Establishing the target scope of product quality attribute standards for mAb 1

[0174] Using the methods described herein, safe clinical exposure was demonstrated for seven product quality attributes (CEX acid peak, CEX main peak, CEX basic peak, CEX basic peak 3, SE-UHPLC HMW, SE-UHPLC main peak, and rCE-SDS non-HC+LC) within the target range of candidate product quality attributes provided by mAb 1. mAb 1 is a therapeutic humanized IgG2 monoclonal antibody. Since mAb 1 is intended for clinical use at a fixed dose (mg), percentage values ​​for each product quality attribute were converted to mg of the fixed dose using gravimetric analysis.

[0175] Product quality attribute exposures were determined based on completed clinical studies of mAb 1, where clinical outcome data, including adverse event incidence data, were available. Dosing in this study was weight-based (mg / kg), and attribute exposures were calculated using weight-based drug exposure analysis. Drug batches were documented in the clinical data, and batch lineage was traced to track individual drug batches. For each drug batch, batch data was retrieved from the stability database to find the product quality attribute level associated with each batch. The product quality attribute level at administration to subjects was estimated by extrapolating batch release attribute data against weight-based DP weight exposures documented in the clinical trials. Accordingly, product quality attribute exposures at administration were determined for each subject in the clinical studies. For each product quality attribute, clinical outcome data included product quality attribute exposure levels exceeding the provided candidate target range (candidate stability criteria). The provided candidate product quality attribute target ranges and calculated clinical study attribute exposures are shown in Table 1.1.

[0176] Table 1.1

[0177]

[0178] a The release and stability standards for rCE-SDS HC+LC are ≥ 97.5% and ≥ 96.4%, respectively. Therefore, the relevant non-HC+LC rCE-SDS substances are ≤ 2.5% and ≤ 3.6%, respectively.

[0179] Next, exposure to product quality attributes beyond the provided candidate target range was correlated with the incidence of adverse events from the clinical study dataset. Only adverse events following exposure to mAb 1 and that product quality attribute were considered. That is, “isolated adverse events” occurring before mAb 1 administration were filtered out, as these were not expected to provide information about the impact of the mAb 1 product quality attribute. Additionally, the first occurrence of this type of adverse event for each subject was recorded (e.g., the first headache experienced by an individual, even if he or she may have experienced multiple headaches during the clinical study).

[0180] Although data on injection site reactions (ISRs) were also obtained, they could not be isolated from the influence of injection rate during clinical studies and were therefore not included in the analysis. Specifically, ISRs occurred in 12 subjects, 9 of whom received >3 injections. Adverse event data are shown in Table 1.2. In the FIH study, no hypersensitivity reactions or autoimmune disorders were observed in any subject at any DP exposure level. ADAs were found in up to 6 subjects (22% at N = 27), compared to the reported clinical immunogenicity rate (18.1%).

[0181] Table 1.2

[0182]

[0183] No hypersensitivity reactions or autoimmune disorders occurred in this analysis. Furthermore, the incidence of ADA was comparable to the known clinical immunogenicity rate. Accordingly, no clinical difference was found between the incidence of adverse events at and outside the target criterion for property exposure. Moreover, a strong safety assessment can be given because the exposures to several maximum product quality properties significantly exceeded the proposed target levels (based on clinical fixed doses and provided stability criteria).

[0184] Accordingly, the provided target range for candidate product quality attributes can serve as the acceptable basis for the target range of product quality attribute standards. Based on the known fixed dose of mAb 1, attribute exposure (in units of mass) can be converted into percentage attribute content through gravimetric analysis. Accordingly, for each batch of mAb 1, the target range for product quality attribute standards can be expressed as the acceptable % target range for product quality attributes. This product quality attribute standard can be used as the release standard for mAb 1.

[0185] Example 2: Establishing the target scope of product quality attribute standards for protein 1

[0186] Using the methods described herein, the safety of clinical exposure to the product quality attribute (host cell protein - HCP) is demonstrated for protein 1 based on the provided product quality attribute stability criteria.

[0187] For multiple batches of Protein 1 manufactured using a method that produces relatively high HCP, their HCP levels were measured using an SF-ELISA HCP assay. Clinical studies containing batches manufactured using this method (and therefore expected to have high HCP) of Protein 1 were identified: Study A and Study B. Clinical outcome data, including adverse event incidence data, were obtained from these clinical studies (Study A and Study B). The study-related HCP levels, measured by the SF-ELISA HCP assay, were obtained and are shown in Table 2.1. Data on relatively high HCP exposure were determined for these clinical studies.

[0188] Table 2.1

[0189]

[0190] Three candidate target ranges for HCP levels of Protein 1 products (Candidate Target Ranges 1-3) are provided, including two proposed release criteria and one proposed rejection criterion. Clinically relevant values ​​(in μg) for the candidate target ranges were calculated by extrapolating the candidate target range HCP levels (ng / mg) to DP weight exposures recorded in clinical trials based on weight analysis. Maximum clinical exposure exceeding the calculated maximum standard level (based on the maximum candidate target range (MSD)) was calculated based on (weight analysis of drug exposure). HCP standard) and (MSD) The HCP standard was used for calculation. The highest HCP level in the two clinical studies was 397% of the maximum value of the lowest HCP candidate target range. These data are shown in Table 2.2.

[0191] Table 2.2

[0192]

[0193] Identify product quality attributes (HCP) levels outside the candidate target ranges and correlate them with adverse event incidence data from clinical studies. Evaluate the safety evidence for each of candidate target range 1 (up to 632 ng / mg HCP), candidate target range 2 (up to 924 ng / mg HCP), and candidate target range 3 (up to 1765 ng / mg HCP).

[0194] Four major adverse event categories were analyzed from the clinical outcome dataset: anti-drug antibodies (ADA), pure red cell aplasia (PRCA), hypertension, and allergic reactions. No cases of ADA or PRCA were reported regardless of protein 1 exposure level. These data are shown in Table 2.3.

[0195] Table 2.3

[0196]

[0197] At each candidate target range, the incidence of all adverse events above the MSD level was comparable to or lower than that below the MSD level. ADA and PRCA were not reported in any subject regardless of the attribute exposure level. At all candidate target range levels (candidate target ranges 1–3), the levels of hypertension and allergic reactions above the MSD level were comparable to or lower than those below the MSD level. Accordingly, it was concluded that HCP target ranges based on any one of candidate target ranges 1–3 were acceptable. Candidate target range 3 (which includes the largest HCP level range, ≤ 1765 ng / ml) was selected as the acceptable target range.

[0198] General description

[0199] All references cited in this article (including publications, patent applications, and patents) are hereby incorporated by reference as if each reference were individually and explicitly indicated to be incorporated by reference and presented in its entirety in this article.

[0200] Unless otherwise indicated herein or the context clearly contradicts it, the use of the terms “a / an” and “the” and similar indicators in the context of describing this disclosure (particularly in the context of the following claims) shall be regarded as covering both the singular and the plural. Unless otherwise noted, the terms “comprising,” “having,” “including,” and “containing” shall be understood as open-ended terms (i.e., meaning “including (but not limited to)”).

[0201] The terms "patient" and "subject" are used interchangeably herein. Generally, these terms should be understood to refer to a person. In some embodiments of the methods, the patient or subject is a person.

[0202] Unless otherwise indicated herein, the statements in this document regarding the range of values ​​are intended only as a shorthand for individually referring to each individual value falling within that range and each endpoint, and each individual value and endpoint is incorporated into this specification as if it were stated individually herein.

[0203] Unless otherwise indicated herein or otherwise obviously contradicted by the context, all methods described herein may be performed in any suitable order. Unless otherwise stated, the use of any and all instances or exemplary language (e.g., “such as”) provided herein is intended only to better describe this disclosure and not to limit its scope. The language in the specification should not be construed as indicating that any unclaimed element is necessary to practice this disclosure.

[0204] This document describes preferred embodiments of the present disclosure, including the best mode known to the inventors for carrying out the disclosure. Variations of those preferred embodiments will become apparent to those skilled in the art upon reading the above description. The inventors intend that those skilled in the art will adopt such variations as appropriate, and the inventors intend to carry out the disclosure in ways other than those specifically described herein. Accordingly, this disclosure includes all modifications and equivalents of the subject matter set forth in the appended claims that are permitted by applicable law. Furthermore, unless otherwise indicated herein or clearly contradicted by the context, this disclosure covers any combination of all possible variations of the elements described herein.

Claims

1. A method for selecting or rejecting a standard target range of product quality attributes for a pharmaceutical product, the method comprising: a) Provide a range of candidate targets for the product quality attributes of the drug product; b) Obtain clinical outcome data from subjects who have received the drug product; c) Determine the exposure level of the product quality attribute at the time of application; d) The clinical outcome data are divided according to the exposure level of the product quality attribute, wherein clinical outcome data with exposure to the product quality attribute outside the candidate target range are assigned to the first partition, and clinical outcome data with exposure to the product quality attribute within the candidate target range are assigned to the second partition. as well as e) Determine the incidence of the specified clinical outcome in the first partition and the incidence of the specified clinical outcome in the second partition; and f) Any of the following: (i) If there is no clinical difference in the incidence of the specified clinical outcome within the partition, then a standard target range for the product quality attribute is selected based on the candidate target range; or (ii) If there are clinical differences in the incidence of the specified clinical outcome in the partition, the standard target range is rejected based on the candidate target range.

2. The method of claim 1, further comprising: Repeat a) - e) for at least one additional candidate target range for this product quality attribute, and any of the following: (iii) Selecting the standard target range based on the maximum amplitude candidate target range value, where there is no clinical difference in the incidence of the specified clinical outcome among the partitions for the maximum amplitude candidate target range value; or (iv) If there is a clinical difference in the incidence of the specified clinical outcome in the partition for each of these candidate target ranges, then the standard target range shall not be determined based on any of these candidate target ranges.

3. The method of claim 2, wherein if the method includes (iv), the method further includes repeating the method with an additional candidate target range that is smaller than the candidate target range and the at least one additional candidate target range.

4. The method according to any one of claims 1-3, further comprising: g) Batch manufacturing of the drug product; h) Determine the level of the product quality attribute in this batch of drug products; as well as i) Any of the following: (i) If the determined level of the product quality attribute is outside the standard target range for that product quality attribute, then the batch shall be rejected; or (ii) If the determined level of the product quality attribute is within the standard target range of the product quality attribute, the batch shall be accepted.

5. The method of claim 4, wherein if the batch is rejected, the method further includes marking the batch for investigation.

6. The method of any one of claims 1-3, further comprising developing a manufacturing process for the pharmaceutical product based on a quality target product profile that includes the standard target range.

7. A method for manufacturing a pharmaceutical product, the method comprising: a) Provide a range of candidate targets for the product quality attributes of the drug product; b) Obtain clinical outcome data from subjects who have received the drug product; c) Determine the exposure level of the product quality attribute at the time of application; d) The clinical outcome data are divided according to the exposure level of the product quality attribute, wherein clinical outcome data with exposure to the product quality attribute outside the candidate target range are assigned to the first partition, and clinical outcome data with exposure to the product quality attribute within the candidate target range are assigned to the second partition. e) Determine that there are no clinical differences in the incidence of the specified clinical outcomes among these partitions; f) Based on the candidate target range, select a standard target range for the product quality attributes of the drug product; and g) Any of the following: i) Acceptance criteria are applied to drug product batches that fall within the product quality attribute levels defined by this standard; or ii) Reject drug product batches that contain product quality attribute levels outside the scope of this standard's target range.

8. The method of claim 7, further comprising: h) Repeat a) - e) for at least one additional candidate target range for this product quality attribute. Wherein, f) the standard target range for the product quality attribute is selected based on the maximum magnitude candidate target range value, for which there is no clinical difference in the incidence of the specified clinical outcome in the partition.

9. A method for assessing the impact of product quality attributes of a pharmaceutical product, the method comprising: a) Provide a range of candidate targets for the product quality attributes of the drug product; b) Obtain clinical outcome data from subjects who have received the drug product; c) Determine the exposure level of the product quality attribute at the time of application; d) The clinical outcome data are divided according to the exposure level of the product quality attribute, wherein clinical outcome data with exposure to the product quality attribute outside the candidate target range are assigned to the first partition, and clinical outcome data with exposure to the product quality attribute within the candidate target range are assigned to the second partition. e) Determine the incidence of the specified clinical outcome in the first partition and the incidence of the specified clinical outcome in the second partition; as well as f) Any of the following: i) If there is no clinical difference in the incidence of the specified clinical outcome within the partition, then the product quality attribute is determined to have no impact on the specified clinical outcome within the candidate target range; or ii) If there are clinical differences in the incidence of the specified clinical outcome within the partition, then determine that the product quality attribute may have an impact on the specified clinical outcome within the target range.

10. The method of claim 9, wherein the method is repeated for two or more different candidate target ranges.

11. A method for assessing the effects of a drug product on the injection site, the method comprising: a) Provide two or more candidate injection sites for the drug product; b) Obtain clinical outcome data from subjects who have received the drug product at at least one of the two or more candidate injection sites; c) The clinical outcome data are divided according to the injection site, wherein the clinical outcome data of the first injection site is assigned to the first partition and the clinical outcome data of the second injection site is assigned to the second partition. e) Determine the incidence (such as the incidence of adverse events) of the specified clinical outcome in the first partition and the incidence of the specified clinical outcome in the second partition; and f) Any of the following: i) If there is no clinical difference in the incidence of the specified clinical outcome within the said partition, then it is determined that the injection site has no effect on the specified clinical outcome within the candidate target range; or ii) If there are clinical differences in the incidence of the specified clinical outcome within the partition, then determine that the injection site may have an impact on the specified clinical outcome within the target range.

12. The method as described in any of the preceding claims, wherein the clinical outcome data comprises at least one of efficacy data or adverse event incidence data.

13. The method as described in any of the preceding claims, wherein the designated clinical outcome comprises at least one of efficacy outcome or adverse event incidence.

14. The method as described in any of the preceding claims, wherein the specified clinical outcome includes the incidence of adverse events.

15. The method of claim 14, further comprising filtering out any adverse events that occurred prior to the application from the adverse event incidence data before the segmentation.

16. The method as described in any of the preceding claims, wherein the clinical difference comprises at least one of qualitative difference, statistically significant difference, or quantifiable trend.

17. The method of any of the preceding claims, wherein allocating clinical outcome data that exposes the product quality attribute outside the candidate target range to the second partition includes allocating the clinical outcome data to two or more different partitions.

18. The method as described in any of the preceding claims, wherein the specified clinical outcome data comprises two or more different categories or types of clinical outcomes, such as two or more different categories or types of adverse events.

19. The method of any one of claims 9-18, further comprising determining whether the exposure level of the product quality attribute is associated or not associated with two or more different categories or types of clinical outcome data.

20. The method of any one of claims 9-18, further comprising determining whether there is an association or non-association between the exposure levels of two or more different product quality attributes and at least one category or type of clinical outcome data.

21. The method of claim 19 or 20, wherein the association or lack thereof between the exposure level of the product quality attribute and only some of the two or more different categories of clinical outcomes is automatically determined, and / or in, Automatically determine whether there is an association or no association between the exposure levels of two or more different product quality attributes and at least one category or type of clinical outcome data.

22. The method as described in any of the preceding claims, further comprising determining whether at least one clinical characteristic of a subject in the first partition is associated with or lacks an association with the designated clinical outcome.

23. The method of claim 22, wherein the at least one clinical characteristic comprises one or more of the following: a pre-existing condition, a biomarker, a laboratory result, or demographic information.

24. The method as described in any of the preceding claims, wherein the clinical outcome data of the pharmaceutical product comprises data from two or more different manufacturing batches of the pharmaceutical product.

25. The method of claim 24, wherein the two or more different manufacturing batches of the pharmaceutical product comprise manufacturing batches from different manufacturers.

26. The method of any one of claims 1-23, wherein the method is performed on clinical outcome data from two or more different groups, wherein each of the two or more different groups comprises clinical outcome data from different manufacturing batches of the pharmaceutical product.

27. The method of claim 26, further comprising comparing a standard target range for each of the two or more different groups of manufacturing batches.

28. The method of any one of claims 2-8, 8 or 11-27, wherein the maximum amplitude candidate target range value includes the highest and / or lowest value of the product quality attribute.

29. The method as described in any of the preceding claims, wherein determining the exposure level of the product quality attribute comprises the following calculations: Where A t It is an estimated level of product quality attribute exposure at the time of application, summed from the contribution of each batch used at the time of application, where n is the total number of manufacturing batches used at the time of application, and for each manufacturing batch i, %A 0,i It is the percentage of the product's quality attribute at the time of batch release or analytical testing, %A Δ,i It is the percentage change rate of the product's quality attribute level over time under given storage conditions, t. i It is the time stored under the given conditions, and D i This refers to the dosage intensity to be applied.

30. The method as described in any of the preceding claims, wherein determining the exposure level of the product quality attribute comprises the following calculations: Among them, %A rel It is the percentage of the product quality attribute exposure relative to the dose level, where A t It is the level of exposure of the product quality attribute calculated using Equation 1 or 2, where D ref It refers to the dose intensity of the active pharmaceutical ingredient in the drug product in terms of quality, associated with each application.

31. The method as described in any of the preceding claims, wherein the product quality attributes include molecular attributes, endotoxins, color, clarity, polysorbate, nitrosamines, a variety of process-related impurities, one process-related impurity, or pharmaceutical properties, or two or more of the listed items.

32. The method of claim 31, wherein the molecular property comprises at least one of the following: acidic substance, basic substance, high molecular weight substance, subvisible particle number, visible particle, aggregation, low molecular weight, medium molecular weight, glycosylation (such as non-glycosylated heavy chain or high mannose), glycosylation, sialylation, non-heavy chain and light chain, deamidation, deamination, cyclization, oxidation, sulfation, hydroxylysine, isomerization, fragmentation / shearing, N-terminal and C-terminal variants, signal peptide, reduced substance and partial substance, misfolding, disulfide rearrangement, domain exchange, folded structure, surface hydrophobicity, chemical modification, covalent bond, mutation / misincorporation, C-terminal amino acid motif PARG, C-terminal amino acid motif PAR-amide, drug-antibody ratio (DAR) or peptide-antibody ratio (PAR).

33. The method of claim 31 or 32, wherein the process-related impurities comprise at least one of CHOP, HCP, residual host cell DNA, residual ProA, or process reagents.

34. The method of any one of claims 31-34, wherein the pharmaceutical characteristic comprises impurities; particles; excipients as non-pharmaceutical characteristics; process reagents; extractables; leachables; and / or component characteristics.

35. The method of any of the preceding claims, wherein the level of the product quality attribute is determined by one or more of the following: mass spectrometry, chromatography, electrophoresis, spectroscopy, optical obscuration, particle methods (such as nanoparticles / visible / micron-scale resonant mass or Brownian motion), analytical centrifugation, imaging or imaging characterization, or immunoassay.

36. The method as described in any of the preceding claims, wherein the standard target scope includes action limits, acceptance criteria, or quality targets.

37. The method of any of the preceding claims, wherein the product quality attribute level outside the candidate or standard target range is (i) a level exceeding the maximum value of the candidate or standard target range, (ii) a level below the minimum value of the candidate or standard target range, or (iii) any one of (i) or (ii).

38. The method as described in any of the preceding claims, wherein the pharmaceutical product comprises a biotherapeutic agent, a synthetic molecule, a small molecule, or a nucleic acid.

39. The method of claim 38, wherein the biotherapeutic agent is selected from the group consisting of: antibodies, antigen-binding antibody fragments, antibody protein products, bispecific T-cell connector (BiTE®) molecules, bispecific antibodies, trispecific antibodies, Fc fusion proteins, recombinant proteins, recombinant viruses, recombinant T cells, synthetic peptides, and active fragments of recombinant proteins.

40. The method of claim 38, wherein the pharmaceutical product comprises a synthetic small molecule.

41. The method of claim 38, wherein the nucleic acid comprises siRNA, mRNA, or DNA.

42. The method of any one of claims 4-8 or 11-39, wherein the pharmaceutical product comprises a biotherapeutic agent, and wherein manufacturing the pharmaceutical product comprises culturing genetically engineered mammalian host cells containing one or more nucleic acids encoding the biotherapeutic agent.

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