Abstract
The development of potency assays for Advanced Therapy Medicinal Products (ATMPs) presents significant challenges due to the variability of starting materials and the complex mechanisms of action involved. This article aims to address the following key question: How can we design robust and reliable potency assays for ATMPs that accommodate product-specific challenges and align with evolving regulatory standards? To answer this, we employed a mixed-methods approach, synthesizing data from scientific literature, industry reports, and regulatory guidelines to identify current limitations and innovative solutions for potency assay development. Our methodology integrates a systematic review of academic publications (2018–2024) to capture recent advancements in biotechnology and their applicability to potency testing. We complemented this with an analysis of industry perspectives, drawn from webinars and white papers, as well as a detailed comparison of global regulatory frameworks, including the FDA’s new guidance on potency assurance for Cellular and Gene Therapy Products (CGTs/ATMPs). Additionally, we developed a comprehensive database to analyze potency assays used in approved, rejected, and withdrawn CGT/ATMP products, focusing on technical and regulatory challenges. Based on this multilevel analysis, we propose a product-specific framework for designing, developing, and validating potency assays for different ATMP categories, taking into account their unique technical and regulatory constraints. We also highlight emerging technologies, such as droplet digital polymerase chain reaction and reporter gene assays, as innovative tools for improving the precision and reliability of potency testing. Our findings underscore the need for flexible, risk-based strategies in potency assay development that evolve throughout product development and clinical trial phases. Future recommendations emphasize assay standardization, the definition of acceptable variability, and stronger correlations between in vitro potency data and clinical outcomes.
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