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Activity Number: 522
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract - #304951
Title: Estimating Pharmacokinetics Parameters Using Meta-Analysis and Nonlinear Mixed Effects Model
Author(s): Wijith Prasantha Munasinghe*+ and Balakrishna Hosmane and Rajendra Pradhan and Yi-Lin Chiu
Companies: Abbott Laboratories and Abbott Laboratories and Abbott Laboratories and Abbott Laboratories
Address: 100, Abbott Park Road, Abbott Park, IL, 60064, United States
Keywords: nonlinear mixed models ; intra-and-inter subject variability ; Delta method ; meta-analysis ; pharmacokinetics

During drug development, it is critical to characterize pharmacokinetic profile for the general population, as well as identify covariates that have significant impact on pharmacokinetics. Additional challenges arise as studies are conducted using different dosing strengths, formulations, meal conditions, and variability populations (e.g. age or body weight). In this paper we explored a meta-analysis approach from 5 studies by using nonlinear mixed effects model to estimate an unknown PK profile. Mixed models approach accounts for intra and inter subject variability estimates which were used to construct confidence intervals for the desired PK profile. A nonlinear mixed effects model with categorical covariates to incorporate different study conditions was fitted to describe the relationship between dose and drug exposure. The fitted model then used to estimate the drug exposure for a given dose and corresponding 90% confidence interval for an unknown PK profile. The Delta method approach was used to obtain the standard errors for the estimated drug exposure. The model diagnostics were done using Fisher's F-test and graphical methods.

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