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<p>The ICH Guideline M10, adopted by the EMA in July 2022 and implemented in January 2023, recommends that stability testing of quality controls (QCs) should match actual sample analyte concentrations, prompting adjustments in QC levels when samples exceed analytical ranges. Laboratories continue long-term stability (LTS) testing on ultra-high concentration quality controls (UHQCs) which are often defined by multiples of the upper limit of quantification (ULOQ) rather than observed maximum concentrations (Cmax). Based on recommendations for implementation of the M10 Guideline regarding Phase 3 clinical trials, we questioned the need for further LTS testing at UHQC levels beyond Phase 2. To address LTS timeline challenges, incurred sample reproducibility (ISR) data from clinical studies were compiled, evaluating their relevance to Cmax and utilizing a Random Intercept Model (RIM) as a tool for establishing stability profiles for drug analytes. Analysis showed most UHQCs estimated using simple ULOQ multiples may not accurately reflect Cmax. Clinical ISR data provided evidence of stability across analyte concentrations within patient matrices with a high degree of confidence. Predictive tools based on ISR data were proposed as a practical approach to demonstrate stability. ISR data can support claims of analyte stability including at ultra-high concentrations, consistent with the M10 guideline and established LTS from validation testing. Using ISR from clinical reports reduces reliance on lengthy LTS testing, offering a robust, efficient method for establishing stability profiles from real-world samples to accomplish regulatory expectations while optimizing workflows.</p> Graphical Abstract <p></p>

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Use of Incurred Sample Reproducibility Data to Support Long Term Stability of Therapeutic Antibodies in Clinical Bioanalytical Methods

  • 期刊论文

  • 发表日期：

    2026年2月24日

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  • Catherine L. Brockus,
  • Likitha Venkatesh

摘要

The ICH Guideline M10, adopted by the EMA in July 2022 and implemented in January 2023, recommends that stability testing of quality controls (QCs) should match actual sample analyte concentrations, prompting adjustments in QC levels when samples exceed analytical ranges. Laboratories continue long-term stability (LTS) testing on ultra-high concentration quality controls (UHQCs) which are often defined by multiples of the upper limit of quantification (ULOQ) rather than observed maximum concentrations (Cmax). Based on recommendations for implementation of the M10 Guideline regarding Phase 3 clinical trials, we questioned the need for further LTS testing at UHQC levels beyond Phase 2. To address LTS timeline challenges, incurred sample reproducibility (ISR) data from clinical studies were compiled, evaluating their relevance to Cmax and utilizing a Random Intercept Model (RIM) as a tool for establishing stability profiles for drug analytes. Analysis showed most UHQCs estimated using simple ULOQ multiples may not accurately reflect Cmax. Clinical ISR data provided evidence of stability across analyte concentrations within patient matrices with a high degree of confidence. Predictive tools based on ISR data were proposed as a practical approach to demonstrate stability. ISR data can support claims of analyte stability including at ultra-high concentrations, consistent with the M10 guideline and established LTS from validation testing. Using ISR from clinical reports reduces reliance on lengthy LTS testing, offering a robust, efficient method for establishing stability profiles from real-world samples to accomplish regulatory expectations while optimizing workflows.

Graphical Abstract