Abstract
Recently, the lifecycle management concept for analytical procedures was introduced. It is strongly related to the Quality by Design concept given in the ICH-Q8 guidance. This contrasts with ICH-Q2 recommendations that only focus on the validation step to evaluate the performance of an analytical procedure. ICH-Q2’s well-known check-list approach fails to provide assurance of the quality of future results with respect to the intended use of the procedure.
In this chapter, we propose and evaluate several decision rules to align quality of results to the objective of an analytical procedure using a risk-based approach. The β-expectation tolerance interval on the reportable result is shown to be the best way to assess whether a procedure will deliver quality results while maintaining a reasonable compromise between producer and patient risks. The β-expectation tolerance interval had previously been recognized in several papers as an excellent expression of the uncertainty of measurements. In addition, the accuracy profile is shown to be a simple way to apply a decision rule over the entire dosing range envisaged for the assay or for each potency or concentration level, based on the β-expectation tolerance interval.
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Acknowledgements
The authors would like to thank David Leblond and Stan Altan for their useful comments that significantly increased the quality of this chapter.
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Sondag, P., Lebrun, P., Rozet, E., Boulanger, B. (2016). Assay Validation. In: Zhang, L. (eds) Nonclinical Statistics for Pharmaceutical and Biotechnology Industries. Statistics for Biology and Health. Springer, Cham. https://doi.org/10.1007/978-3-319-23558-5_16
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DOI: https://doi.org/10.1007/978-3-319-23558-5_16
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