In drug-drug interaction (DDI) research, to fully understand multiple drugs'pharmacokinetics and their interactions, a physiologically based pharmacokinetic model (PBPK) is the only viable means of investigating and quantifying all the interacting factors (active sites or organs). A PBPK model is known for its model identification problem because of its complex structure;hence, it usually borrows prior physiological information to make the model identifiable. However, conventional DDI researches based on deterministic PBPK models ignore population variations in PK parameters, experimental noise and uncertainties in prior knowledge, which in turn leads to subjective conclusions with unknown reliability. This grant application proposes a system of Bayesian tools to meet these pharmacological, statistical and computational challenges of PBPK models by exploring three aims.
In Aim 1, individual drug's PBPK models of the inhibitor-substrate combination is established based on their published animal, in-vitro, and in-vivo data;the strategy of starting a simple model with limited information to a complex model with rich knowledge is systematically discussed;and Bayesian meta-analysis methods are proposed.
In Aim 2, based on clinical DDI studies, a two-stage Bayesian method for a joint inhibitor-substrate PBPK model is developed;a predictive false negative rate is proposed to evaluate the DDI prediction;and Bayesian model selection procedures are implemented to select the best PBPK model among competitive ones.
In Aim 3, all the prescribed Bayesian tools are implemented in R, a statistical and computational freeware;and its web-based application is developed to facilitate its usage for general research scientists. In this grant application, we realize the fact that the DDI is enzyme-dependent. Hence, a CYP3A specific inhibitor-substrate combination, ketoconazole-midazolam, is chosen as a starting example. It will serve as a building block for multi-enzyme and multi-drug based DDI PBPK models.
|Schelleman, H; Han, X; Brensinger, C M et al. (2014) Pharmacoepidemiologic and in vitro evaluation of potential drug-drug interactions of sulfonylureas with fibrates and statins. Br J Clin Pharmacol 78:639-48|
|Kim, Seongho; Li, Lang (2014) Statistical identifiability and convergence evaluation for nonlinear pharmacokinetic models with particle swarm optimization. Comput Methods Programs Biomed 113:413-32|
|Wu, Heng-Yi; Chiang, Chien-Wei; Li, Lang (2014) Text mining for drug-drug interaction. Methods Mol Biol 1159:47-75|
|Wu, Heng-Yi; Karnik, Shreyas; Subhadarshini, Abhinita et al. (2013) An integrated pharmacokinetics ontology and corpus for text mining. BMC Bioinformatics 14:35|
|Jiang, Guanglong; Chakraborty, Arindom; Wang, Zhiping et al. (2013) New aQTL SNPs for the CYP2D6 identified by a novel mediation analysis of genome-wide SNP arrays, gene expression arrays, and CYP2D6 activity. Biomed Res Int 2013:493019|
|Chakraborty, Arindom; Jiang, Guanglong; Boustani, Malaz et al. (2013) Simultaneous inferences based on empirical Bayes methods and false discovery rates ineQTL data analysis. BMC Genomics 14 Suppl 8:S8|
|Xu, Cong; Quinney, Sara K; Guo, Yingying et al. (2013) CYP2B6 pharmacogenetics-based in vitro-in vivo extrapolation of efavirenz clearance by physiologically based pharmacokinetic modeling. Drug Metab Dispos 41:2004-11|
|Quinney, Sara K; Knopp, Shawn; Chang, Chien et al. (2013) Integration of in vitro binding mechanism into the semiphysiologically based pharmacokinetic interaction model between ketoconazole and midazolam. CPT Pharmacometrics Syst Pharmacol 2:e75|
|Wu, Heng-Yi; Zheng, Pengyue; Jiang, Guanglong et al. (2012) A modulator based regulatory network for ERýý signaling pathway. BMC Genomics 13 Suppl 6:S6|
|Quinney, S K; Mohamed, A N; Hebert, M F et al. (2012) A Semi-Mechanistic Metabolism Model of CYP3A Substrates in Pregnancy: Predicting Changes in Midazolam and Nifedipine Pharmacokinetics. CPT Pharmacometrics Syst Pharmacol 1:e2|
Showing the most recent 10 out of 28 publications