A drug's free intracellular concentration must be known to accurately predict its effect on an intracellular target. Intracellular drug concentratios are affected by active efflux as well as uptake transporters. The role of these transporters in drug-drug interactions and drug disposition is greatly appreciated. Since it is difficult to experimentally quantitate intracellular drug concentrations, an attractive and powerful alternative is to develop accurate models that predict these concentrations. The overall goal of the proposed work is to develop models that predict unbound intracellular drug concentrations in the presence of efflux as well as uptake transporters. Specifically, we propose to conduct in vitro and in vivo studies to quantitate the effect of transporters on intracellular drug concentration. We further propose to develop mathematical models based on our in vitro and in vivo studies to characterize and predict permeability and transport of drugs in and out of cells. To this end, we propose the following specific aims: 1) Characterize the in vitro disposition properties of a diverse set of 30 drugs. The plasma protein binding, membrane partitioning, permeability, transport, and metabolism for these drugs will be evaluated. These drugs are substrates for P-gp, BCRP, MRP2, and OATP1B1. 2) Characterize the in situ and in vivo disposition properties of a diverse set of 30 drugs. Brain and liver partitioning will be measured by in situ perfusion. In vivo pharmacokinetics will be measured in the rat. Transporter knockout rats will be utilized for in vivo PK studies. IVIVCs will be performed with results from Aims 1 an 2 for both rat and human. 3) Expand our current computational models for drug permeability and transport. More physiological models that incorporate different plasma and intracellular membrane compartments will be developed. These models will be parameterized and tested with the data from Aims 1 and 2. These models are expected to predict the intracellular concentrations of drugs in the presence of transporters. Together, results from the proposed studies will provide, for the first time, integration of in vitro transporter data, in situ transprter-related disposition data, and in vivo PK to predict intracellular concentrations at the target sit. Additionally, models will be interfaced with systemic (plasma) drug concentration-time profiles as input functions to predict intracellular drug concentration profiles. This will result in improed prediction of clearance, distribution, and in vivo drug-drug interactions. Our models will address an unmet critical need for cost-effective drug development by providing novel and useful tools to vastly improve prediction of drug disposition in humans.
A drug's free intracellular concentration must be known in order to accurately predict its effect on an intracellular target. In vitro and in vivo studies wil be used to parameterize mathematical models and predict permeability and transport of drugs in and out of cells. This work will greatly improve our ability to predict in vivo drug disposition, drug-drug interactions, efficacy, and toxicity.
|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) Drug Distribution Part 2. Predicting Volume of Distribution from Plasma Protein Binding and Membrane Partitioning. Pharm Res 34:544-551|
|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|
|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|
|Korzekwa, Ken; Tweedie, Donald; Argikar, Upendra A et al. (2014) A numerical method for analysis of in vitro time-dependent inhibition data. Part 2. Application to experimental data. Drug Metab Dispos 42:1587-95|
|Nagar, Swati; Tucker, Jalia; Weiskircher, Erica A et al. (2014) Compartmental models for apical efflux by P-glycoprotein--part 1: evaluation of model complexity. Pharm Res 31:347-59|
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