AAPS Journal最新文献

Immunogenicity, commonly manifested through the development of anti-drug antibodies (ADAs), is a critical concern for therapeutic antibodies as it can adversely affect pharmacokinetics (PK), efficacy, and safety. Although ADA-related impacts have been closely evaluated for individual antibody drugs, cross-product analyses of approved antibody drugs remain limited. In this study, we examined 92 antibody therapeutics approved by the Japanese regulatory authority as of March 2024, focusing on their review reports and prescribing information, to quantitatively assess the actual clinical impacts of ADA. Among these drugs, ADA-related decreased drug exposure, reduced efficacy, and worsened safety were indicated in the prescribing information of 18.5%, 10.9%, and 5.4%, respectively. Interestingly, ADA-related descriptions of both decreased drug exposure and reduced efficacy were observed in significantly lower proportions among oncology drugs than among non-oncology drugs. Furthermore, humanized antibodies exhibited higher proportions of ADA-related impacts than human antibodies; in particular, decreased exposure was significantly more common with humanized antibodies (27.7%) than with human antibodies (8.6%), supporting the concept that human antibodies have lower immunogenic potential. In addition, our evaluation of review reports indicated that all drugs with ADA-related reduced efficacy had decreased exposure. To the best of our knowledge, this is the first study to quantitatively evaluate the clinical impact of immunogenicity in approved antibody therapeutics in Japan. These results are expected to inform the appropriate clinical use of antibody therapeutics and contribute to a more comprehensive understanding of immunogenicity risk assessments during clinical development.

Short contacts between medical devices and medications that they contain can cause drug sorption or leaching of unwanted compounds which can have clinical consequences. However, the parameters that govern these interactions are still incompletely understood. The objectives of this study were to evaluate the impact of the formulation parameters on migration of 2,4 Di-tert-butylphenol (2,4 DTBP) and sorption of tacrolimus (TAC) in a model micellar ophthalmic drug formulation which is known to interact with silicone elastomers. A design of experiments was established to evaluate the impact of the formulation parameters on 2,4 DTBP leaching and tacrolimus sorption by varying the initial concentrations of TAC (0.04; 0.2 and 1 mg/mL), polyoxyethylenated castor oil (KEL) (32; 80 and 200 mg/mL) and ethanol absolute (EtOH) (10 and 100 mg/mL), at 5°C and 25°C, during static contact between various formulations and silicone valves obtained from an ophthalmic multidose delivery device. Concentrations of 2,4 DTBP and TAC were monitored by liquid chromatography coupled with an UV-visible detector. Under the conditions studied, the amount of 2,4 DTBP leaching out increased during contact with the silicone valve, with increasing TAC concentration being quite interestingly the main factor decreasing its ability to leach out, whilst ethanol increased its leachability. The silicone valve did not cause any significant decrease of TAC concentrations over the duration of the study, regardless of the concentrations of KEL, EtOH, or temperature. This study showed the impact of formulation on the leaching of 2,4 DTBP from a silicone component.

Formation of anti-drug antibodies (ADA) and, in particular, neutralizing antibodies (NAb), is a major risk to the development of biotherapeutics. Cell-based assays, which can reflect the mechanistic interactions among the drug, target, and NAb, are often most suitable for the detection of NAb. We report the development and validation of cell-based platform assays for a class of incretin molecules. An affinity capture elution step was employed to improve drug tolerance of a cell-based cyclic adenosine monophosphate (cAMP) assay. Assay conditions and procedures, including acid elution, cell density, and TAG labeled cAMP (cAMP-TAG) incubation time and concentration, were thoroughly optimized. Delta percent (Δ%) Neutralization was used to reduce assay variability during validation and sample analysis. This platform method has been applied to several incretin molecules and has demonstrated desired sensitivity, drug tolerance, and robustness.

A special panel session at the 2024 NCS Conference in Wiesbaden, Germany, brought together experts to explore the evolving landscape of patient-centric drug product development and specifications. Traditional specifications often rely on manufacturing variability and phase 3 clinical trial data. However, patient-centric specifications shift the focus toward direct clinical relevance, establishing customer-driven acceptance criteria. Discussions covered innovative approaches to defining patient-centric specifications, leveraging prior knowledge, biopharmaceutics, formulation science, regulatory input, and statistical methodologies. The session also highlighted efficient QbD studies, enabling the linkage of Critical Process Parameters (CPPs) and Critical Material Attributes (CMAs) to Chemistry, Manufacturing and Controls (CMC) Critical Quality Attributes (CQAs). While these approaches hold great promise, challenges remain such as cross-disciplinary collaboration, data integration, and the development of robust databases to inform future drug and biologicals development. As industry experience grows, these efforts will pave the way for continuous improvement in nonclinical-clinical linkage designs, enhancing patient outcomes.

QSP models are increasingly being applied to drug development. Calibrating virtual populations (VPops) to clinical data helps explore patient variability, study populations of interest, and predict clinical outcomes for new therapies. In previous work, we have developed the QSP Toolbox, a library of tools and workflows for developing VPops. The aim is to create a VPop that fits clinical data from a variety of sources and with a variety of data types, allowing for differences in the quality of the data. The goodness-of-fit (GOF) of the VPop is given by a scalar function $p$ whose form is inspired by the p-value of Fisher's combined hypothesis test. However, our VPop development workflow has been hampered by the need to perform repeated optimization of "prevalence weights" to maximize $p$ . In this article, we describe how we can speed up our workflow by using proxy GOF functions whose maximization can be reduced to the relatively easy problem of minimizing a convex quadratic objective function. A successful run of this "proxy-guided" workflow generates a VPop with very good $p$ -fit, but without having to continually maximize $p$ throughout the development process. We find that our proxy-guided workflow can calibrate VPops much faster than the original ( $p$ -guided) workflow.

Chronic human immunodeficiency virus (HIV) infection continues to pose a major global health challenge, with an estimated 39.9 M cases and 1.3 M new infections per year. Up to 75%, of people with HIV (PWH) are currently being treated with antiretroviral therapy. The development of effective treatments for HIV requires a detailed understanding of the virus-host interaction. Often, mathematical models are used to inform this understanding as well as to characterize therapeutic response. This work aims to develop a single and fully identifiable population semi-mechanistic pharmacokinetic/pharmacodynamic (popPKPD) model integrating data (drug levels, CD4 + T cells and viral RNA) of five different antiretroviral (ARV) drugs administered in monotherapy: lenacapavir, bictegravir, tenofovir alafenamide, emtricitabine and elvitegravir. Data were obtained from six phase 1 clinical studies and model development was performed using NONMEM 7.5.1. The viral dynamics were best described by expanding the "basic" viral dynamics model with two more populations of infected cells: chronically and latently infected. Obtained death rates values of infected cells & virus were consistent with literature values. Population baseline HIV-RNA was estimated to be 43,460 copies/mL, with an IIV of 141%, the estimated baseline concentrations of CD4 + cells varied largely across the different cell types in the model: 410, 20, 7 and 7 cells/mL for uninfected, infected, chronic and latently infected cells, respectively. The popPKPD model was able to capture key aspects of viral dynamics, drug behaviour, and treatment response. The models developed will serve as a useful tool for further development and optimization of these HIV therapies, especially when evaluating multiple ARVs to be administered in a novel combination setting.

Using pharmacometrics to inform drug discovery and development decisions requires effective communication of models and data to all stakeholders. The new "vachette" visualization method presented here enables modelers and non-modelers to see how a model integrates and represents all data across relevant subgroups, showing how the model "sees" the data when it accounts for covariates. Vachette starts with user-provided model simulations ("curves"), together with observations used in creating (or otherwise relevant to) the model. It automatically produces a single, intuitive plot overlaying all observations onto a user-selected reference curve, accounting for covariate effects and preserving remaining random effects. The method automatically identifies characteristic landmarks (e.g., minima, maxima, and inflection points) which are used to split each curve into segments. A transformation on both x- and y-axes is then applied to each segment and its corresponding observations, accounting for covariate effects by aligning the segments to the reference, allowing intuitive visualization in one plot of covariate effects and of model fit to the data, preserving the distance between model predictions and the observations. Vachette-transformed data can also be used to enhance the utility of model assessments such as visual predictive checks and residual plots. Model visualizations using vachette enable easier and more effective evaluation and communication of the pharmacometric results critical to informing key decisions. Here the vachette method is described and its utility and flexibility are demonstrated through application to multiple types of pharmacometrics models, suggesting that vachette is a useful addition to the pharmacometrician's toolbox.

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.