When the ICH M10 guideline was adopted in May 2022, it established a harmonized global framework for bioanalytical method validation and study sample analysis. Now fully implemented by major regulatory agencies in North America, Europe, and Asia, M10 has become the international standard for bioanalytical work supporting preclinical and clinical drug development. For scientists, this represents a significant evolution in both technical expectations and regulatory alignment.
The move toward harmonization addresses longstanding inconsistencies among regional guidelines, reducing ambiguity in how assays are developed, validated, and interpreted across borders. While the underlying principles of M10 are familiar to most bioanalytical professionals, the finalized guideline introduces several noteworthy updates that influence day-to-day practice.
Formalizing Method Development
One of the most meaningful shifts in M10 is the formal recognition of bioanalytical method development as a defined phase. Scientists are expected to demonstrate an understanding of the analyte’s characteristics, including its physicochemical properties, mechanism of action, and interactions within biological matrices. These early assessments are critical for designing assays that are both scientifically sound and capable of meeting regulatory standards later in development. M10 emphasizes that method development is not simply preparatory – it is integral to data quality and assay robustness.
Refining Validation and Cross-Validation Practices
The guideline provides more precise boundaries around when to perform full, partial, or cross-validation. Full validation remains essential when introducing a new method for use in pivotal studies, while partial validation is recommended for any modifications to an already validated method. Cross-validation, however, receives new attention. M10 specifies scenarios where it must be applied, such as when combining data from different laboratories or methods across studies. This has particular implications for global studies or programs transitioning between CROs or internal sites.
Importantly, M10 does not dictate strict pass/fail criteria for cross-validation comparisons. Instead, it encourages the use of statistical techniques, such as Bland–Altman analysis or Deming regression, to evaluate the agreement between methods. This added flexibility provides scientists with the room to interpret and manage minor variability in a scientifically defensible manner.
Greater Rigor in Selectivity and Stability Testing
Selectivity assessments are now expected to include multiple sources of biological matrix – six for chromatographic methods and ten for ligand-binding assays. Testing in lipemic and hemolyzed matrices is also recommended when relevant, especially for patient populations with metabolic or inflammatory conditions. These expectations are designed to ensure that assays can accommodate real-world sample variability without compromising data quality and accuracy.
M10 also expands the scope of stability testing. Scientists must now confirm that sample processing, storage, and autosampler conditions do not alter the analyte concentration. This includes stress testing at various timepoints and concentrations. The guideline encourages the use of quality control samples that reflect the dilution factors likely to be applied during sample analysis, particularly in cases where concentrations exceed the upper limit of quantitation.
Incurred Sample Reanalysis (ISR): A Broader Requirement
Incurred sample reanalysis is no longer limited to bioequivalence studies. M10 expands its application to include first-in-human trials, pivotal early-phase patient studies, and special population trials (e.g., hepatic or renal impairment). The guideline outlines the steps for an ISR investigation when failure criteria are met, or even when subtle but systematic discrepancies arise between original and repeat measurements. Scientists are encouraged to interpret ISR results not only as a check on assay reproducibility but as a broader tool for identifying potential issues in sample handling, instrumentation, or method performance.
Clarifying Expectations for Dilutional Linearity
Dilutional linearity studies now follow more standardized criteria. Scientists must demonstrate that high-concentration samples can be accurately measured after dilution by preparing at least three independent dilution series. Mean concentrations must fall within ±20% of nominal values after correction for dilution, with precision not exceeding 20%. These parameters help ensure that samples from high-dose cohorts, or those affected by saturation effects, are accurately quantified throughout a study.
Endogenous Analytes: Four Accepted Approaches
Quantifying endogenous compounds has long been a complex challenge, particularly when distinguishing between baseline physiological levels and drug-derived concentrations. M10 outlines four acceptable strategies for this purpose: the surrogate matrix approach, surrogate analyte approach, standard addition, and background subtraction. Each has specific methodological requirements and limitations, and M10 helps clarify when and how each may be appropriately applied.
For example, the surrogate matrix approach is commonly used in LC-MS-based assays but must be accompanied by parallelism testing to confirm matrix equivalence. The surrogate analyte approach, which utilizes stable isotope-labeled analogs, is a unique feature of mass spectrometry platforms. These strategies are technically demanding and require careful consideration of matrix effects and assay performance characteristics.
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Emphasis on Critical Reagent Control
In immunoassays and other large-molecule platforms, critical reagents, such as capture and detection antibodies, play a central role in determining assay performance. M10 specifies that the identity, batch history, storage, and stability of a reagent must be documented throughout its lifecycle. In cases where a significant change occurs, such as a new production method or supplier, additional validation may be necessary. This level of control aims to reduce variability and improve reproducibility across study phases and global sites.
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Reporting Transparency and Data Completeness
M10 introduces more stringent expectations for study reporting. For LC-MS methods supporting bioavailability and bioequivalence studies, internal standard response plots are now required for each analytical run. Additionally, the guideline recommends reporting all runs, including those that fail the acceptance criteria, to enhance transparency and facilitate regulatory review. While these expectations may lengthen reports, they also improve the traceability of bioanalytical data and support more informed decision-making during inspections or submissions.
Final Thoughts
One notable omission in the ICH M10 guideline is the role of automation in bioanalysis. While many laboratories have embraced automated platforms to improve consistency and throughput, the guideline does not yet provide guidance on validating automated workflows or electronic traceability systems. This gap may become more pressing as the industry continues to modernize, and future updates could address how automation intersects with method validation and data integrity.
In the meantime, scientists must continue to adapt their methods, documentation, and quality systems to reflect the updated expectations under ICH M10. Whether developing new assays or revalidating existing methods, aligning with the guideline is essential for ensuring data reliability, regulatory acceptance, and international consistency.
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As ICH M10 becomes the de facto global standard, scientists are in a position not only to comply with its requirements but also to shape how the industry interprets and applies its principles. The path forward will require collaboration, scientific rigor, and continued dialogue between laboratories and regulators.
Dig deeper into ICH M10’s impacts in our latest whitepaper, ICH M10 Guidance: Harmonization and Modification to Bioanalytical Method Validation.
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