# Predicting Intracellular Drug Concentrations In The Presence Of Transporters

> **NIH NIH R01** · TEMPLE UNIV OF THE COMMONWEALTH · 2024 · $352,222

## Abstract

Project Summary
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 2018-2022, we have made significant progress in
developing models to predict drug volume of distribution, and models to predict drug absorption. We have used
the basic principles underlying permeability and partitioning to build a new framework for PBPK models
(termed PermQ). This framework now allows us to incorporate permeability-limited distribution, partitioning,
organ blood flow, and active transport into PBPK models with explicit membrane kinetics. We have started to
build upon our current work to develop novel frameworks to predict drug clearance, a new focus of this
renewal. These new modeling paradigms, together with our time- and distance- dependent continuous
absorption models, will provide markedly better predictions of intracellular concentrations in the presence of
drug metabolizing enzymes and transporters, and will address an unmet critical need for cost effective drug
development by providing novel predictive tools for drug pharmacokinetics in humans.
Three specific aims are proposed. 1) New in vitro and mathematical methods will characterize the time-course
of cellular permeability and partitioning, to inform mechanisms underlying drug distribution, absorption, and
intracellular concentrations that drive drug clearance. Experiments in artificial membrane environments at
various pH values will define the pH partitioning – membrane permeability relationship. In vitro microdialysis
and transwell techniques will capture the time-course of drug partitioning into cells including MDCK, Caco-2,
adipocytes, and hepatocytes. Partitioning into erythrocyte glycocalyx will be measured. Resulting data will be
used as inputs to develop mathematical models to predict drug permeability across single vs. multiple
membranes across a cell, and drug partitioning into membranes. 2) Excipient effects on oral absorption will be
predicted in humans and rodents. Effect of excipient dose-dependent (Polysorbate 80 and PEG400) inhibition
of intestinal drug metabolizing enzymes and transporters (DMETs) will be evaluated with a refined rat intestinal
model. A continuous intestinal mouse absorption model will be developed and refined. The human and rat
intestinal models will be interfaced with species-specific PermQ models. 3) New in vitro and mathematical
methods will improve predictions of drug clearance. Rat data will be collected with microfluidics in hepatocytes
and in vivo, with regional drug quantification with MALDI imaging. Three standard liver models – well-stirred
(WSM), parallel-tube (PTM), and dispersion (DM) – will be evaluated within human and rat PermQ. Enzyme
zonation within the liver sinusoid will be modeled with both literature (discretized) and new parti...

## Key facts

- **NIH application ID:** 10894284
- **Project number:** 5R01GM104178-10
- **Recipient organization:** TEMPLE UNIV OF THE COMMONWEALTH
- **Principal Investigator:** Kenneth Ray Korzekwa
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $352,222
- **Award type:** 5
- **Project period:** 2013-01-15 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10894284

## Citation

> US National Institutes of Health, RePORTER application 10894284, Predicting Intracellular Drug Concentrations In The Presence Of Transporters (5R01GM104178-10). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10894284. Licensed CC0.

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