Assessment for statistically-based PPQ sampling plan, including calculating the passing probability, optimizing the baseline and high performance cutoff points, visualizing the PPQ plan and power dynamically. The analytical idea is based on the simulation methods from the textbook Burdick, R. K., LeBlond, D. J., Pfahler, L. B., Quiroz, J., Sidor, L., Vukovinsky, K., & Zhang, L. (2017). Statistical Methods for CMC Applications. In Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry (pp. 227-250). Springer, Cham.
Package details |
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Author | Yalin Zhu [aut, cre] (<https://orcid.org/0000-0003-3830-8660>), Merck & Co., Inc. [cph] |
Maintainer | Yalin Zhu <yalin.zhu@merck.com> |
License | GPL-3 |
Version | 1.1.0 |
URL | https://allenzhuaz.github.io/PPQplan/ https://github.com/allenzhuaz/PPQplan |
Package repository | View on CRAN |
Installation |
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