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Activity Number: 363
Type: Contributed
Date/Time: Tuesday, August 2, 2016 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract #321211
Title: Evaluating In Vivo-In Vitro Correlation Using a Bayesian Approach
Author(s): Junshan Qiu* and Marilyn Martinez and Ram Tiwari
Companies: FDA and FDA and FDA/CDER/OT/OB
Keywords: Bayesian ; IVIVC ; Tolerance intervals ; Matching priors ; Frequentist

A Bayesian approach with frequentist validity has been developed to support inferences derived from a "Level A" in vivo-in vitro correlation (IVIVC). Irrespective of whether the in vivo data reflect in vivo dissolution or absorption, the IVIVC is typically assessed using a linear regression model. There remains an inability to define a range of subject-level drug concentration-time profiles across a population based upon our "Level A" predictions. Thus, there is a need to address not only variability in subject pharmacokinetics but also the variability in the in vivo product performance. The objective of this study is to develop a hierarchical Bayesian method for evaluation of IVIVC, incorporating both the subject and population-level variability; and to use this method to derive Bayesian tolerance intervals with matching priors that have frequentist validity in evaluating an IVIVC.

Authors who are presenting talks have a * after their name.

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