AAPS Journal最新文献

Data integrity is necessary to help ensure the accuracy, consistency, validity and completeness of data. Data can be untraceably manipulated when it lacks adequate integrity. The FDA identified data integrity concerns with the pharmacokinetic data of a bioequivalence (BE) study for rivaroxaban 20 mg tablets, which was conducted by a contract research organization (CRO) in support of an abbreviated new drug application (ANDA) submission. The hypothesis was that samples from the late cohort of the study might have been substituted or manipulated to allow an otherwise failing study to meet the BE endpoint. To test this hypothesis FDA investigators collected 2,392 plasma samples from the BE study at the CRO's clinical site. FDA laboratory then developed and validated a bioanalytical method and re-analyzed the BE study plasma samples. Comparison of the data generated by the CRO and FDA suggested that the study was manipulated by altering the volume of plasma samples used for bioanalysis. This manipulation was likely done to achieve a lower than actual maximum plasma concentration test/reference (C_max T/R) ratio.

Physiologically based pharmacokinetic (PBPK) modeling has emerged as a valuable tool in model-informed drug development (MIDD). This approach enables the integration of diverse experimental data to predict pharmacokinetics (PK) and dosing regimens and facilitates understanding of mechanism of action (MoA) and pharmacodynamics (PD). In this article we provide a landscape analysis of PBPK submissions at the U.S. Food and Drug Administration, Center for Biologics Evaluation and Research (CBER). We summarize CBER's experience on PBPK modeling and simulation (M&S) for therapeutic proteins, cell and gene therapy products. We discuss specific case studies that illustrate the use of PBPK for dose selection of therapeutic proteins, highlight recent progress and provide our perspectives on potential application of PBPK for adeno-associated virus (AAV)-based gene therapies and messenger RNA (mRNA) therapeutics. For cell and gene therapy products, PBPK M&S is emerging as MIDD approaches to support clinical trial design, dose selection, predicting PK/PD, and facilitate quantitative understanding of safety and efficacy. As the field continues to evolve, PBPK modeling is well positioned to provide supportive evidence to facilitate the development of safe and effective biological products.

The current paradigm for detection of anti-drug antibodies (ADA) recommends a tiered strategy in which samples are tested in consecutive screening and confirmatory assays to ensure high sensitivity and specificity of detection. In each tier individual responses are compared against a statistically determined cut point to make positive/negative classifications and advance the sample to the next testing tier. This manuscript argues that the idea of cut point is scientifically flawed and not suitable for making positive/negative ADA classifications. Cut point set at the ≥ 95th percentile of the population responses does not reduce the number of false negatives; on the contrary, it reduces the ability to detect ADA in 95% of the population with lower responses. Likewise, ADA classification of individual study samples should not be predicated by responses of other individuals used to determine the assay cut points. Experimental conditions used during cut point determination often differ from those encountered during testing of study samples (e.g. drug-naïve vs treated subjects, different disease state before and after treatment) and therefore a cut point may not be suitable for testing of post-baseline samples. Since cut point cannot be trusted to make ADA classifications, it is proposed to discard its use together with tiered testing and instead base the detection of ADA on post-baseline signal changes and their relationship to pharmacokinetics, pharmacodynamics, efficacy and safety. Discarding both cut point and tiered strategy is expected not only to significantly reduce the workload dedicated by bioanalytical laboratories to immunogenicity testing but also to improve data analysis and interpretation.

Physiologically based pharmacokinetic (PBPK) models are commonly used in human drug discovery and development and human health risk assessment of environmental chemicals. One emerging application of PBPK models is to predict tissue residues and withdrawal times of drugs in food animals, which is important for human food safety assessment of animal-derived food products, such as meat, milk, and eggs. This review summarizes existing guidelines to establish the regulatory agency approved label withdrawal period and available pharmacometric methods to predict extralabel withdrawal times, with a focus on PBPK modeling. We conducted a comprehensive literature search on existing PBPK models in food animals. Two hundred thirteen PBPK models in different food animal species (e.g., cattle, swine, sheep, goats, and chickens) from 113 publications were identified. The general procedure to build a PBPK model for a drug in food animals to predict withdrawal times is summarized. Differences in PBPK modeling between humans and food animals and between different food animal species are discussed. Novel uses of PBPK models to predict extralabel withdrawal times are illustrated with recent case studies from the Food Animal Residue Avoidance Databank (FARAD). Recent advances and challenges in PBPK modeling in food animals are discussed, followed by our future perspectives on how to develop more robust PBPK models for food animals to address the safety assessment of animal-derived food products.

It is important to understand the key factors affecting the pharmacokinetics (PK), pharmacological response and toxicity of a drug to ensure clinical therapeutic efficacy and safety across disease populations. Traditionally, label dose-adjustment recommendations for patient populations are based on drug plasma concentrations. However, plasma PK may not be an appropriate surrogate for response and/or toxicity for drugs like statins with intracellular targets and tissue distribution influenced by membrane transporters. This study presents the integration of a physiologically-based pharmacokinetic model with a quantitative systems pharmacology and toxicology (PBPK-QSP-TOX) model for statins in patients with normal kidney function and in different stages of chronic kidney disease (CKD). The QSP model was informed by 2753 measurements of circulating LDL concentrations in 1147 patients (NCT00654537). The TOX model was informed by a meta-analysis of creatine kinase elevation incidence per statin dose in 30 clinical studies (49,284 patients). The CKD populations accounted for disease related changes to 1) anatomy and physiology, 2) drug enzymes and transporters expression and 3) lipoprotein metabolism. This study provides a qualified PBPK-QSP-TOX model for statins that accurately describe plasma concentration-time profiles, lipid-lowering effect and myotoxicity risk over investigated dose range for patients with normal kidney function and varying degree of CKD.

Recycling antibodies can enhance therapeutic efficacy by enabling efficient antigen removal through pH-dependent binding mechanisms enabling antibody recycling, but the optimal targets for this strategy remain unclear. This work employs a mathematical modeling approach using a minimal PBPK model, along with global and local sensitivity analyses, to explore how target turnover rates influence the suitability of recycling antibodies. We applied this approach to a scenario featuring a soluble antigen with high baseline levels (1000 nM) that necessitates treatment with an antibody with a high intravenous dosing regimen. Our findings indicate that the recycling strategy is most effective for target antigens expressed at high levels, and particularly for those with half-lives of 10 to 30 h. In contrast, for antigens expressed at sufficiently low levels, where the antibody can be present in significant excess, further optimization of conventional antibodies to achieve higher antigen-binding affinity at neutral pH can be beneficial. While optimizing the off-rate at acidic pH is often the primary focus in the engineering of recycling antibodies, our analysis indicates that the on-rate at pH 6 is also an important parameter, albeit to a lesser extent. Therefore, the equilibrium dissociation constant (K_D) at pH 6 can be used as a composite parameter for effective design of recycling antibodies. For the soluble antigen embodied in the scenario described in this work, a pool of randomly selected antibodies, engineered to undergo recycling, reach half of their maximum antigen reduction capacity at a mean pH 6 K_D of 520 nM and 180 nM for targets with half-lives of 10 and 30 h, respectively.

The efficient review and approval of chemistry, manufacturing and control (CMC) post-approval changes by global health authorities remains a critical aspect toward ensuring medical product commercial supply chains and patient access. The recent and growing implementation of innovative regulatory frameworks such as ICH Q12, large molecule statistical analysis of stability data, and global reliance has provided a positive impact on the health authority approval of CMC post-approval changes. This case study presents a large molecule multi-product post-approval change management protocol (PACMP) and the review/approval by a WHO-Listed Authority (WLA). The regulatory approval of this PACMP exemplifies how the principles of ICH Q12 combined with large molecule statistical stability analysis accelerates the implementation of a drug product aseptic filling line supporting the production of 5 globally approved products by 7 months. This accelerated approval by a WLA leads to the faster submission of the required approval letter/module 3 documentation to global national regulatory authorities leveraging WHO Good Reliance Procedures to improve rest-of-world regulatory review/approval timelines.

Bispecific antibodies (BsAbs) have emerged as a promising class of therapeutics to treat complex diseases, offering advantages in dual targeting simultaneously compared to monospecific antibodies. However, BsAbs often require advanced engineering, and the novel formats present challenges for the development of clinical anti-drug antibody (ADA) assays. Immunogenicity evaluation is a required study endpoint during the clinical development of biotherapeutics, and bridging immunoassay is a common method for developing clinical ADA assays. However, in two of our BsAb programs, the traditional bridging enzyme-linked immunosorbent assay (ELISA) was unable to detect surrogate ADAs directed against the arm containing multivalent domains. Further investigations revealed that the surrogate ADAs to the multivalent binding domain of the two BsAbs predominantly form 1:1 complexes with the drug, even in the presence of a significant excess of the BsAbs. To overcome the limitations of traditional bridging ELISA, we explored alternative assay approaches and developed fit-for-purpose ADA assays tailored to supporting multivalent BsAbs. Here, we present two case studies of multivalent BsAb analyzed using a stepwise ELISA format, where the drug is used for capture and a recombinant human high affinity Fc gamma receptor 1A (FcγRIa) is used for detection of the ADAs, leveraging the LALAPG attenuated effector function mutations present in both BsAbs. This work highlights the complexity of bioanalytical challenges in developing advanced therapeutic modalities and showcases the innovative solutions required to support the rapidly evolving field of BsAb therapeutics.