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脑出血M10后药代动力学检测的交叉验证并非通过/失败标准。

Cross-validation of pharmacokinetic assays post-ICH M10 is not a pass/fail criterion.

作者信息

Fjording Marianne Scheel, Goodman Joanne, Briscoe Chad

机构信息

Biolyzr, Vaerloese, DK-3500, Denmark.

Bioanalytical Services,Celerion, Lincoln, NE 68502, USA.

出版信息

Bioanalysis. 2025 Jan;17(1):1-5. doi: 10.1080/17576180.2024.2418284. Epub 2024 Nov 6.

Abstract

The ICH M10 guideline establishes global standards for bioanalytical method validation for pharmacokinetic assays, focusing on data reliability and accuracy across studies. A significant component is cross-validation, which should be performed to ensure data comparability when multiple methods or laboratories are involved in a single study or across studies where comparison will be performed. However, ICH M10 does not specify acceptance criteria for cross-validation, creating challenges for the industry because traditionally many laboratories have always utilized acceptance criteria to "pass" or "fail" the study. This editorial discusses how bioanalytical labs should conduct cross-validation for PK assays post-ICH M10, highlighting the role of statistical methods and the need for close collaboration with clinical pharmacology and biostatistics departments. Proper implementation and strategic focus on relevant studies are essential for effective cross-validation.

摘要

国际人用药品注册技术协调会(ICH)M10指南为药代动力学分析的生物分析方法验证确立了全球标准,重点关注各项研究数据的可靠性和准确性。一个重要组成部分是交叉验证,当单个研究涉及多种方法或多个实验室,或者在将进行比较的跨研究中,应进行交叉验证以确保数据的可比性。然而,ICH M10并未规定交叉验证的接受标准,这给行业带来了挑战,因为传统上许多实验室一直使用接受标准来判定研究“通过”或“不通过”。本社论讨论了生物分析实验室应如何在ICH M10发布后对药代动力学分析进行交叉验证,强调了统计方法的作用以及与临床药理学和生物统计学部门密切合作的必要性。有效实施交叉验证并对相关研究进行战略聚焦至关重要。

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