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Systems validation: application to statistical programs

BACKGROUND: In 2003, the United States Food and Drug Administration (FDA) released a guidance document on the scope of "Part 11" enforcement. In this guidance document, the FDA indicates an expectation of a risk-based approach to determining which systems should undergo validation. Since s...

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Detalles Bibliográficos
Autor principal: Carter, Rickey E
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC545946/
https://www.ncbi.nlm.nih.gov/pubmed/15649319
http://dx.doi.org/10.1186/1471-2288-5-3
Descripción
Sumario:BACKGROUND: In 2003, the United States Food and Drug Administration (FDA) released a guidance document on the scope of "Part 11" enforcement. In this guidance document, the FDA indicates an expectation of a risk-based approach to determining which systems should undergo validation. Since statistical programs manage and manipulate raw data, their implementation should be critically reviewed to determine whether or not they should undergo validation. However, the concepts of validation are not often discussed in biostatistics curriculum. DISCUSSION: This paper summarizes a "Plan, Do, Say" approach to validation that can be incorporated into statistical training so that biostatisticians can understand and implement validation principles in their research. SUMMARY: Validation is a process that requires dedicated attention. The process of validation can be easily understood in the context of the scientific method.