AI Article Synopsis
- * Cross-validation is crucial to ensure data comparability when different methods or labs participate, but the lack of explicit acceptance criteria in ICH M10 complicates this process for many labs.
- * The editorial suggests that bioanalytical labs need to adopt effective statistical methods and collaborate closely with clinical pharmacology and biostatistics departments for successful cross-validation of PK assays post-ICH M10.
Article 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.
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| http://dx.doi.org/10.1080/17576180.2024.2418284 | DOI Listing |
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