Your browser doesn't support javascript.
loading
Setting the control limit at release for stability assurance.
Chen, X Gregory; van der Vaart, A W.
Afiliación
  • Chen XG; Biostatistics and Research Decision Sciences, MSD, Zurich, Switzerland.
  • van der Vaart AW; Delft Institute of Applied Mathematics, TU Delft, Delft, The Netherlands.
Pharm Stat ; 22(1): 45-63, 2023 01.
Article en En | MEDLINE | ID: mdl-36637243
A common task in quality control is to determine a control limit for a product at the time of release that incorporates its risk of degradation over time. Such a limit for a given quality measurement will be based on empirical stability data, the intended shelf life of the product and the stability specification. The task is particularly important when the registered specifications for release and stability are equal. We discuss two relevant formulations and their implementations in both a frequentist and Bayesian framework. The first ensures that the risk of a batch failing the specification is comparable at release and at the end of shelf life. The second is to screen out batches at release time that are at high risk of failing the stability specification at the end of their shelf life. Although the second formulation seems more natural from a quality assurance perspective, it usually renders a control limit that is too stringent. In this paper we provide theoretical insight in this phenomenon, and introduce a heat-map visualisation that may help practitioners to assess the feasibility of implementing a limit under the second formulation. We also suggest a solution when infeasible. In addition, the current industrial benchmark is reviewed and contrasted to the two formulations. Computational algorithms for both formulations are laid out in detail, and illustrated on a dataset.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Teorema de Bayes Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Pharm Stat Asunto de la revista: FARMACOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Teorema de Bayes Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Pharm Stat Asunto de la revista: FARMACOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido