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Commentary: Multiplex dPCR and SV-AUC are Promising Assays to Robustly Monitor the Critical Quality Attribute of AAV Drug Product Integrity

多路复用 计算生物学 数字聚合酶链反应 衣壳 计算机科学 医学 生物 病毒学 生物信息学 基因 病毒 聚合酶链反应 遗传学
作者
David Hayes,David Dobnik
出处
期刊:Journal of Pharmaceutical Sciences [Elsevier]
卷期号:111 (8): 2143-2148 被引量:6
标识
DOI:10.1016/j.xphs.2022.04.010
摘要

Adeno-associated viral (AAV) capsids are an emerging vector technology for a number of novel gene therapy modalities (including transgene delivery and CRISPR gene editing). In this commentary, the proper approach to managing uncertainty (described by Rosenberg et al., 2012) when determining critical quality attributes is stated and applied retrospectively to Peginesatide and prospectively to AAV drug product integrity. With Peginesatide, the omission of advanced analytical techniques (for particles) led to a severe safety risk that appeared post marketing. Peginesatide was withdrawn from the market. One of the critical quality attributes of AAV capsid products is drug product integrity. Drug product integrity is critical because it is related to measuring the active dose of product and because the effects of empty, aggregated, particulate, and partial capsids on efficacy and safety are uncertain. The dose of an AAV capsid vector is typically measured as genomes per milliliter. Regulatory agencies have already recommended digital PCR (dPCR) methods because traditional real-time PCR methods were not precise enough for drug product characterization. However, even with dPCR methods, the practice of characterizing AAV product with a simple empty-full ratio is problematic because simplex dPCR methods count partial genomes as full genomes. The proper management of uncertainty requires a robust quantitative measurement of AAV drug product integrity to ensure control of efficacy and safety. Multiplex dPCR and SV-AUC are promising technologies that together have the potential to enable the development of assays fit for the purpose of measuring AAV drug product integrity more precisely.
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