Mechanism-based pharmacokinetic and pharmacodynamic modeling for bispecific antibodies: challenges and opportunities

药物开发 双特异性抗体 机制(生物学) 药品 计算生物学 医学 药效学 药物发现 计算机科学 药代动力学 药理学 抗体 生物信息学 免疫学 生物 单克隆抗体 认识论 哲学
作者
Jin Niu,Weirong Wang,Danièle Ouellet
出处
期刊:Expert Review of Clinical Pharmacology [Taylor & Francis]
卷期号:16 (10): 977-990 被引量:3
标识
DOI:10.1080/17512433.2023.2257136
摘要

ABSTRACTIntroduction Unlike conventional antibodies, bispecific antibodies (bsAbs) are engineered antibody- or antibody fragment-based molecules that can simultaneously recognize two different epitopes or antigens. Over the past decade, there has been an explosion of bsAbs being developed across therapeutic areas. Development of bsAbs presents unique challenges and mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) modeling has served as a powerful tool to optimize their development and realize their clinical utility.Areas covered In this review, the guiding principles and case examples of how fit-for-purpose, mechanism-based PK/PD models have been applied to answer questions commonly encountered in bsAb development are presented. Such models characterize the key pharmacological elements of bsAbs, and they can be utilized for model-informed drug development. We also include the discussion of challenges, knowledge gaps and future direction for such models.Expert opinion Mechanistic PK/PD modeling is a powerful tool to support the development of bsAbs. These models can be extrapolated to predict treatment outcomes based on mechanisms of action (MoA) and clinical observations to form positive learn-and-confirm cycles during drug development, due to their abilities to differentiate system- and drug-specific parameters. Meanwhile, the models should keep being adapted according to novel drug design and MoA, providing continuous opportunities for model-informed drug development.KEYWORDS: PK/PDmodel-informed drug developmentbispecific antibodyT-cell engagertarget-mediated drug disposition (TMDD) Article highlights Bispecific antibodies (BsAbs) targeting two differnt antigens or epitopes can carry out novel biological functions with specific therapeutic mechanism, and potentially achieve better efficacy and lower off-target toxicity because of the dual-targeting feature.Types of bsAbs include T cell redirecting bsAbs (or T cell engagers), dual-targeting bsAbs, and those with special functions such as piggyback (one of the binding arms to alter the biodistribution of the bsAb) or half-life extension (one of the binding arms to extend the half-life by binding to albumin).Model-informed drug development has been adopted at various stages of R&D for bsAbs from molecular design to clinical dose selection.Mechanism-based PK/PD models have been developed to describe bsAb PK, target binding/complex formation, and downstream PD responses. They are powerful tools that can be extrapolated across doses, drugs or diseases, to answer common questions in bsAb drug development, such as optimizing drug design, predicting first-in-human dose, and selecting efficacious safe dosing regimen.Knowledge gaps in the understanding of the exact pharmacological mechanism(s) of action, especially in target expression at the site of drug action, will present challenges for mechanism-based PK/PD model development and hinder bsAb development in general.It is expected that the use and impact of mechanism-based PK/PD models in bsAb development will increase in the future, to cover new types of bsAbs or newly discovered biological mechanisms and to find the optimal dose for patients.Declaration of interestAll authors are employees of Janssen Research and Development LLC (Johnson & Johnson) and may own stocks. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.Reviewer disclosuresPeer reviewers on this manuscript have no relevant financial or other relationships to disclose.Additional informationFundingThis paper was not funded.
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