The overarching goal of the proposed research is to predict the intracellular and extracellular concentration- time profiles using models that include membrane partitioning, membrane permeability, organ blood flow, active transport, and metabolism. In the funding period from 2013-2016, we have made significant progress in incorporating explicit membrane compartments into predictive models, and we have evaluated in depth the impact of various membrane geometries and related factors on intracellular concentration prediction. We are now using the basic principles underlying permeability and partitioning to build a new framework for PBPK models. This will allow us to incorporate permeability-limited distribution, partitioning, organ blood flow, and active transport into PBPK models with explicit membrane kinetics (memPBPK). This new paradigm will provide markedly better predictions of intracellular concentrations, and will address an unmet critical need for cost effective drug development by providing novel predictive tools for drug disposition in humans.
Three specific aims are proposed. 1) Novel biophysical methods will be used to study the cellular kinetics of drug permeability and partitioning. Specifically, novel cell microscopy techniques will be used to evaluate the time-course of cellular distribution and conduct cellular permeability studies in monolayers, and a range of explicit membrane models developed during the current funding period will be evaluated for their ability to quantify the observed membrane, organelle, and cellular distribution kinetics. 2) Develop a new framework for PBPK and hybrid compartmental-PBPK models that incorporate membrane partitioning, permeability-limited diffusion, and organ blood flow (memPBPK). Components include organ-specific models for use in hybrid and full PBPK approaches, and models for absorption using our published convection-diffusion-reaction approach. These models will be used in Aim 3 to incorporate active uptake/efflux transport and metabolism to predict intra- and extracellular concentration-time profiles. 3) In vivo experimental data from rats and humans will be used to expand and validate models to predict the time course of intra- and extracellular drug concentrations. We will focus on modeling the disposition of drugs in the liver and the absorption of drugs from the gastrointestinal tract in the presence of transporters and drug metabolizing enzymes.

Public Health Relevance

The overall goal of this research is to better predict drug efficacy and safety in humans. Biophysical methods, in vitro, in situ, and in vivo data will be used to develop models that incorporate membrane partitioning, permeability-limited diffusion, blood flow, active transport, and metabolism in order to predict intracellular and extracellular drug concentration-time profiles.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Xenobiotic and Nutrient Disposition and Action Study Section (XNDA)
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Okita, Richard T
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Temple University
Schools of Pharmacy
United States
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Guo, Yingying; Chu, Xiaoyan; Parrott, Neil J et al. (2018) Advancing Predictions of Tissue and Intracellular Drug Concentrations Using In Vitro, Imaging and Physiologically Based Pharmacokinetic Modeling Approaches. Clin Pharmacol Ther 104:865-889
Yadav, Jaydeep; Korzekwa, Ken; Nagar, Swati (2018) Improved Predictions of Drug-Drug Interactions Mediated by Time-Dependent Inhibition of CYP3A. Mol Pharm 15:1979-1995
Pham, Chuong; Nagar, Swati; Korzekwa, Ken (2017) Numerical analysis of time dependent inhibition kinetics: comparison between rat liver microsomes and rat hepatocyte data for mechanistic model fitting. Xenobiotica :1-28
Nagar, Swati; Korzekwa, Richard C; Korzekwa, Ken (2017) Continuous Intestinal Absorption Model Based on the Convection-Diffusion Equation. Mol Pharm 14:3069-3086
Nagar, Swati; Korzekwa, Ken (2017) Drug Distribution. Part 1. Models to Predict Membrane Partitioning. Pharm Res 34:535-543
Korzekwa, Ken; Nagar, Swati (2017) On the Nature of Physiologically-Based Pharmacokinetic Models -A Priori or A Posteriori? Mechanistic or Empirical? Pharm Res 34:529-534
Korzekwa, Ken; Nagar, Swati (2017) Drug Distribution Part 2. Predicting Volume of Distribution from Plasma Protein Binding and Membrane Partitioning. Pharm Res 34:544-551
Ye, Min; Nagar, Swati; Korzekwa, Ken (2016) A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding. Biopharm Drug Dispos 37:123-41
Barnaba, Carlo; Yadav, Jaydeep; Nagar, Swati et al. (2016) Mechanism-Based Inhibition of CYP3A4 by Podophyllotoxin: Aging of an Intermediate Is Important for in Vitro/in Vivo Correlations. Mol Pharm 13:2833-43
Kulkarni, Priyanka; Korzekwa, Kenneth; Nagar, Swati (2016) Intracellular Unbound Atorvastatin Concentrations in the Presence of Metabolism and Transport. J Pharmacol Exp Ther 359:26-36

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