Continuous Method Validation: Beyond One-Time Studies to Characterize Analytical Methods

References

• Ando, T. (2010), Bayesian Model Selection and Statistical Modeling, Boca Raton, FL: Chapman and Hall/CRC Press.
   Google Scholar
• Banbeta, A., van Rosmalen, J., Dejardin, D., and Lesaffre, E. (2019), “Modified Power Prior with Multiple Historical Trials for Binary Endpoints,” Statistics in Medicine, 38, 1147–1169. DOI: 10.1002/sim.8019.
   PubMed Web of Science ®Google Scholar
• Bennett, M., White, S., Best, N., and Mander, A. (2021), “A Novel Equivalence Probability Weighted Power Prior for Using Historical Control Data in an Adaptive Clinical Trial Design: A Comparison To Standard Methods,” Pharmaceutical Statistics, 20, 462–484. DOI: 10.1002/pst.2088.
   PubMed Web of Science ®Google Scholar
• Boulanger, B., Chiap, P., Dewe, W., Crommen, J., and Hubert, P. (2003), “An Analysis of the SFSTP Guide on Validation of Chromatographic Bioanalytical Methods: Progresses and Limitations,” Journal of Pharmaceutical and Biomedical Analysis, 32, 753–765. DOI: 10.1016/S0731-7085(03)00182-1.
   PubMed Web of Science ®Google Scholar
• Chatfield, M. J. (2018), “Uncertainty of Variance Estimators in Analytical and Process Variability Studies,” Doctoral dissertation, University of Southampton, available at https://eprints.soton.ac.uk/422240/.
   Google Scholar
• Claeskens, G., and Hjort, N. L. (2008), Model Selection and Model Averaging, Cambridge: Cambridge University Press.
   Google Scholar
• DeSilva, B., Smith, W., Weiner, R., Kelley, M., Smolec, J., Lee, B., Khan, M., Tacey, R., Hill, H., and Celniker, A. (2003), “Recommendations for the Bioanalytical Method Validation of Ligand-Binding Assays to Support Pharmacokinetic Assessments of Macromolecules,” Pharmaceutical Research, 20, 1885–1900. DOI: 10.1023/B:PHAM.0000003390.51761.3d.
   PubMed Web of Science ®Google Scholar
• Duan, Y., Smith, E. P., and Ye, K. (2006a), “Using Power Priors to Improve the Binomial Test of Water Quality,” Journal of Agricultural, Biological, and Environmental Statistics, 11, 151–168. DOI: 10.1198/108571106X110919.
   Web of Science ®Google Scholar
• Duan, Y., Ye, K., and Smith, E. P. (2006b), “Evaluating Water Quality Using Power Priors to Incorporate Historical Information,” Environmetrics, 17, 95–106. DOI: 10.1002/env.752.
   Web of Science ®Google Scholar
• Eudey, T. L. (2007), “Pharmaceutical and Medical Device Validation by Experimental Design,” in Designing Experiments for Validation of Quantitative Methods, eds. L. D. Torbeck, pp. 1–46, Boca Raton, FL: Chapman and Hall/CRC Press.
   Google Scholar
• Evans, M., and Moshonov, H. (2006), “Checking for Prior-Data Conflict,” Bayesian Analysis, 1, 893–914. DOI: 10.1214/06-BA129.
   Web of Science ®Google Scholar
• Faya, P., Seaman, J. W., Jr., and Stamey, J. D. (2017), “Bayesian Assurance and Sample Size Determination in the Process Validation Life-cycle,” Journal of Biopharmaceutical Statistics, 27, 159–174. DOI: 10.1080/10543406.2016.1148717.
   PubMed Web of Science ®Google Scholar
• Faya, P., Seaman, J. W., Jr., and Stamey, J. D. (2018), “Using Accelerated Drug Stability Results to Inform Long-Term Studies in Shelf Life Determination,” Statistics in Medicine, 37, 2599–2615. DOI: 10.1002/sim.7663.
   PubMed Web of Science ®Google Scholar
• Faya, P., Seaman, J. W., Jr., and Stamey, J. D. (2020b), “Power Priors for Sample Size Determination in the Process Validation Life Cycle,” in Bayesian Applications in Pharmaceutical Development, eds. M. Lakshminarayanan and F. Natanegara, pp. 287–306, Boca Raton: Chapman and Hall/CRC Press.
   Google Scholar
• Faya, P., Sondag, P., Novick, S., Banton, D., Seaman, J. W., Jr, Stamey, J. D., and Boulanger, B. (2020a), “The Current State of Bayesian Methods in Nonclinical Pharmaceutical Statistics: Survey Results and Recommendations from the DIA/ASA-BIOP Nonclinical Bayesian Working Group,” Pharmaceutical Statistics, 20, 245–255. DOI: 10.1002/pst.2072.
   PubMed Web of Science ®Google Scholar
• FDA (2010), “Guidance for the use of Bayesian Statistics in Medical Device Clinical Trials, Center for Devices and Radiological Health,” available at https://www.fda.gov/media/71512/download.
   Google Scholar
• FDA (2011), “Guidance for Industry: Process Validation: General Principles and Practices,” available at https://www.fda.gov/files/drugs/published/Process-Validation–General-Principles-and-Practices.pdf.
   Google Scholar
• Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. (2014), Bayesian Data Analysis (3rd ed.), Boca Raton: Chapman and Hall/CRC Press.
   Google Scholar
• González, A. G., Herrador, M. A., and Asuero, A. G. (2005), “Practical Digest for Evaluating the Uncertainty of Analytical Assays from Validation Data According to the LGC/VAM Protocol,” Talanta, 65, 1022–1030. DOI: 10.1016/j.talanta.2004.08.038.
   PubMed Web of Science ®Google Scholar
• Gravestock, I., Held, L, and COMBACTE-Net consortium. (2017), “Adaptive Power Priors with Empirical Bayes for Clinical Trials,” Pharmaceutical Statistics, 16, 349–360. DOI: 10.1002/pst.1814.
   PubMed Web of Science ®Google Scholar
• Graybill, F. A. (1976), Theory and Application of the Linear Model, North Scituate, MA: Duxbury Press.
   Google Scholar
• Hobbs, B. P., Carlin, B. P., Mandrekar, S. J., and Sargent, D. J. (2011), “Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials,” Biometrics, 67, 1047–1056. DOI: 10.1111/j.1541-0420.2011.01564.x.
   PubMed Web of Science ®Google Scholar
• Hobbs, B. P., Sargent, D. J., and Carlin, B. P. (2012), “Commensurate Priors for Incorporating Historical Information in Clinical Trials Using General and Generalized Linear Models,” Bayesian Analysis, 7, 639–674. DOI: 10.1214/12-BA722.
   PubMed Web of Science ®Google Scholar
• Hubert, P., Nguyen-Huu, J. J., Laurentie, M., Mercier, N., and Muzard, G. (2003), “Validation des Procédures Analytiques Quantitatives Harmonisation des Démarches,” STP Pharma Pratiques, 13, 101–138.
   Google Scholar
• Ibrahim, J. G., and Chen, M. H. (2000), “Power Prior Distributions for Regression Models,” Statistical Science, 15, 46–60.
   Web of Science ®Google Scholar
• Ibrahim, J. G., Chen, M. H., Gwon, Y., and Chen, F. (2015), “The Power Prior: Theory and Applications,” Statistics in Medicine, 34, 3724–3749. DOI: 10.1002/sim.6728.
   PubMed Web of Science ®Google Scholar
• Lebrun, P., and Rozet, E. (2020), “Analytical Method and Essay,” in Bayesian Methods in Pharmaceutical Research, eds. E. Lesaffre, G. Baio, and B. Boulanger, pp. 369–390, Boca Raton: Chapman and Hall/CRC.
   Google Scholar
• Morita, S., Thall, P. F., and Müller, P. (2008), “Determining the Effective Sample Size of a Parametric Prior,” Biometrics, 64, 595–602. DOI: 10.1111/j.1541-0420.2007.00888.x.
   PubMed Web of Science ®Google Scholar
• Morita, S., Thall, P. F., and Müller, P. (2012), “Prior Effective Sample Size un Conditionally Independent Hierarchical Models,” Bayesian Analysis, 7, 591–614.
   Web of Science ®Google Scholar
• Neuenschwander, B., Branson, M., and Spiegelhalter, D. J. (2009), “A Note on the Power Prior,” Statistics in Medicine, 28, 3562–3566. DOI: 10.1002/sim.3722.
   PubMed Web of Science ®Google Scholar
• Nikolakopoulos, S., van der Tweel, I., and Roes, K. C. (2018), “Dynamic Borrowing Through Empirical Power Priors that Control Type I Error,” Biometrics, 74, 874–880. DOI: 10.1111/biom.12835.
   PubMed Web of Science ®Google Scholar
• Novick, S. J., Christian, E., Farmer, E., and Tejada, M. (2020), “A Bayesian Statistical Approach to Continuous Qualification of a Bioassay,” PDA Journal of Pharmaceutical Science and Technology, 75, 8–23. DOI: 10.5731/pdajpst.2019.011221.
   PubMedGoogle Scholar
• Ollier, A., Morita, S., Ursino, M., and Zohar, S. (2020), “An Adaptive Power Prior for Sequential Clinical Trials–Application to Bridging Studies,” Statistical Methods in Medical Research, 29, 2282–2294. DOI: 10.1177/0962280219886609.
   PubMed Web of Science ®Google Scholar
• Peterson, J. (2020), “Process Development and Validation,” in Bayesian Methods in Pharmaceutical Research, eds. E. Lesaffre, G. Baio, and B. Boulanger, pp. 357–368, Boca Raton: Chapman and Hall/CRC.
   Google Scholar
• Press, J. S. (2003), Subjective and Objective Bayesian Statistics (2nd ed.), New York: Wiley.
   Google Scholar
• Rambla-Alegre, M., Esteve-Romero, J., and Carda-Broch, S. (2012), “Is it Really Necessary to Validate an Analytical Method or Not? That is the Question,” Journal of Chromatography. A, 1232, 101–109. DOI: 10.1016/j.chroma.2011.10.050.
   PubMed Web of Science ®Google Scholar
• Schofield, T. (2016), “Lifecycle Approach to Bioassay,” in Nonclinical Statistics for Pharmaceutical and Biotechnology Industries, ed. E. Zhang, pp. 433–460, Cham: Springer.
   Google Scholar
• Seaman, J. W., III, Seaman, J. W., Jr., and Stamey, J. D. (2012), “Hidden Dangers of Specifying Noninformative Priors,” The American Statistician, 66, 77–84. DOI: 10.1080/00031305.2012.695938.
   Web of Science ®Google Scholar
• Song, G., Zhong, J., Lindborg, S., and Han, B. (2020), “Practical Considerations for Building Priors for Confirmatory Studies,” in Bayesian Applications in Pharmaceutical Development, eds. M. Lakshminarayanan and F. Natanegara, pp. 49–60, Boca Raton: Chapman and Hall/CRC Press.
   Google Scholar
• Tan, C. (2005), “RSD and Other Variability Measures of the Lognormal Distribution,” Pharmacopeial Forum, 31, 653–655.
   Google Scholar
• van Rosmalen, J., Dejardin, D., van Norden, Y., Löwenberg, B., and Lesaffre, E. (2018), “Including Historical Data in the Analysis of Clinical Trials: Is it Worth the Effort?,” Statistical Methods in Medical Research, 27, 3167–3182. DOI: 10.1177/0962280217694506.
   PubMed Web of Science ®Google Scholar
• Viele, K., Berry, S., Neuenschwander, B., Amzal, B., Chen, F., Enas, N., Hobbs, B., Ibrahim, J., Kinnersley, N., Lindborg, S., Micallef, S., Roychoudhury, S., and Thompson, L. (2014), “Use of Historical Control Data for Assessing Treatment Effects in Clinical Trials,” Pharmaceutical Statistics, 13, 41–54. DOI: 10.1002/pst.1589.
   PubMed Web of Science ®Google Scholar
• Yuan, Y., and Xia, J. (2017), “A Calibrated Power Prior Approach to Borrow Information from Historical Data with Application to Biosimilar Clinical Trials,” Journal of the Royal Statistical Society, Series C, 66, 979–996. DOI: 10.1111/rssc.12204.
   Web of Science ®Google Scholar