生物分析
药代动力学
食品药品监督管理局
结合
转化式学习
单克隆抗体
药理学
抗体-药物偶联物
药品
分析物
化学
医学
计算生物学
药物发现
计算机科学
双特异性抗体
药物开发
药品审批
临床实习
小分子
从长凳到床边
风险分析(工程)
共轭体系
制药工业
人类使用
药物输送
抗体
生化工程
作者
Weifeng Xu,Linlin Luo,Murali K. Matta,Roy Helmy,Faye Vazvaei-Smith
出处
期刊:Bioanalysis
[Future Science Ltd]
日期:2026-01-22
卷期号:18 (2): 179-188
标识
DOI:10.1080/17576180.2026.2631640
摘要
Antibody-drug conjugates (ADCs) have reemerged as a transformative therapeutic modality, with over a dozen approvals and hundreds of candidates in clinical development. Historically, ADC pharmacokinetic (PK) evaluation required measuring all constituent components - total antibody (TAb), conjugated antibody (ADC), or conjugated payload, free payload, and major metabolites. This comprehensive approach led to a significantly higher bioanalytical (BA) investment, increased patient blood volume requirements, and far more resources than those needed for monoclonal antibody (mAb) therapeutics or small molecule drugs. In 2024, the US Food and Drug Administration (FDA) issued guidance encouraging a more streamlined, data-driven approach to ADC PK assessment in clinical development, including the potential to omit certain analytes when scientifically justified. While this guidance represents a pivotal shift, adoption across the industry has been slow, and few examples of successful assay reduction have been publicly shared. In this perspective, we examine the scientific and regulatory rationale for simplifying ADC PK strategies. We also propose a pragmatic framework for reducing assays - grounded in clinical relevance, early-phase data, and platform knowledge - that seeks to reduce complexity without compromising patient safety or data integrity.
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