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Systems validation: application to statistical programs.

Rickey E Carter1

  • 1Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA. carterre@musc.edu

BMC Medical Research Methodology
|January 15, 2005
PubMed
Summary
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Biostatisticians can now integrate validation principles into their research using a "Plan, Do, Say" method. This approach ensures statistical programs managing data meet regulatory expectations for system validation.

Area of Science:

  • Biostatistics
  • Regulatory Science
  • Data Management

Background:

  • The US Food and Drug Administration (FDA) guidance on "Part 11" enforcement emphasizes a risk-based approach to system validation.
  • Statistical software manipulates raw data, necessitating critical review for validation requirements.
  • Validation concepts are often underrepresented in biostatistics curricula.

Purpose of the Study:

  • To introduce a practical validation framework for biostatisticians.
  • To bridge the gap between regulatory expectations and biostatistics training.
  • To promote the understanding and implementation of validation principles in research.

Main Methods:

  • Summarizes a "Plan, Do, Say" approach to validation.
  • Integrates validation concepts within the context of the scientific method.

Related Experiment Videos

  • Provides a framework applicable to statistical training.

    • Main Results:

    • The proposed method offers a clear pathway for understanding and implementing validation.
    • Facilitates compliance with regulatory expectations for data management systems.
    • Enhances the rigor of biostatistical research through systematic validation.

    Conclusions:

    • Validation is a crucial, attention-requiring process.
    • The "Plan, Do, Say" approach simplifies validation for biostatisticians.
    • Incorporating validation into training ensures robust and compliant research.