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Method validation in the bioanalytical laboratory.

A R Buick1, M V Doig, S C Jeal

  • 1Department of Bioanalytical Sciences, Wellcome Research Laboratories, Beckenham, Kent, UK.

Journal of Pharmaceutical and Biomedical Analysis
|January 1, 1990
PubMed
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Bioanalytical method validation ensures reliable results using techniques like chromatography and mass spectrometry. Key criteria include stability, accuracy, and precision, with validation extent depending on application and data use.

Area of Science:

  • Analytical Chemistry
  • Pharmacology
  • Biotechnology

Background:

  • Bioanalytical methods are crucial for generating reliable data in drug development and clinical diagnostics.
  • Various physico-chemical and biological techniques, including chromatography, immunoassay, and mass spectrometry, are employed.
  • Method validation is essential before and during use to ensure data integrity.

Purpose of the Study:

  • To outline the fundamental criteria for validating bioanalytical methods.
  • To emphasize the importance of method validation for ensuring data reliability and confidence.
  • To discuss factors influencing the extent of validation required.

Main Methods:

  • Evaluation of drug and analyte stability.
  • Assessment of selectivity, limits of quantification and detection, accuracy, precision, linearity, and recovery.

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  • Consideration of specific validation needs based on analytical techniques (e.g., antibody-binding, matrix effects).

    • Main Results:

    • Established fundamental validation criteria for bioanalytical methods.
    • Highlighted the dependency of validation extent on prospective use, sample size, and data application.
    • Recommended cross-validation with specific detectors like mass spectrometry and ongoing performance monitoring with quality control standards.

    Conclusions:

    • Rigorous validation of bioanalytical methods is paramount for scientific and clinical applications.
    • A comprehensive approach to validation, including ongoing monitoring, ensures sustained method reliability.
    • Tailoring validation to specific assay requirements and intended use is critical for data quality.