A Bayesian Approach to Robust Parameter Estimation of Physiologically Based Pharmacokinetics Model with Drug Dissolution Model

Abstract

Physiologically based pharmacokinetics (PBPK) model can predict absorption, degradation, execration and metabolism in drug delivery system. Thus, it can be useful for regulating dose and estimating drug concentration at a particular time during the clinical demonstration. While PBPK model is generally expressed as a set of ordinary differential equations with a large number of parameters, in-vivo experimental data are often noisy and sparse. This makes it difficult to estimate parameters with conventional least squares approaches. Therefore, maximum a posteriori method from Bayesian approach that is the robust parameter estimation technique can be used to estimate parameters of PBPK model. However, the scheme of maximum a posteriori method by using Markov Chain Monte Carlo sampling is hard to use for parameter estimation of PBPK model because of the large number of parameters. This work introduces the Bayesian approach estimation method for parameter estimation of PBPK model. In addition, a scheme of maximum a posteriori method is proposed to find maximum of the posterior distribution without using Markov Chain Monte Carlo sampling.\\

To regulate the concentration of drug and prevent side effect, the studies of drug dosage form are developed. However, since PBPK models and drug dissolution models are studied independently, there is no consideration of the drug dissolution dynamics in PBPK model. Therefore, accurate description of oral administrated drug delivery system requires an improved PBPK model. This work proposes a PBPK model that can describe orally administrated drug dissolution model by combining the drug dissolution model and PBPK model.\\

This thesis simulates parameter estimation of PBPK model to compare the performance of least squares method and maximum a posteriori method. In addition, the case study for Tegafur delivery system is conducted with in-vivo data and drug dissolution model included PBPK model to predict concentration profile of Tegafur, and to evaluate the proposed PBPK model.