Journal Article

Cellular Heterogeneity in Drug Uptake Amplifies Pharmacodynamic Variability: A Stochastic PK‐PD Analysis

Do, Tuan Ngoc, Nguyen, Tien Tran‐Nam, Phan, Khanh Quoc, Nguyen, Lap Thi, Duong, Nhung Hong‐Thi

2026

Overview

Traditional pharmacokinetic‐pharmacodynamic models assume cellular homogeneity, yet clinical observations reveal substantial response variability even among patients with similar plasma exposure. We hypothesized that cellular heterogeneity in drug transporter expression, coupled with nonlinear dose–response relationships, can amplify microscopic cellular variability into population‐level outcome variability. Using cobimetinib as an exemplar, we developed a proof‐of‐principle multiscale stochastic framework that couples deterministic systemic pharmacokinetics with cellular‐level stochastic differential equations. In this framework, transporter expression was modeled as log‐normally distributed across cells, generating heterogeneity in intracellular drug concentrations despite identical plasma exposure. Simulations showed that cellular heterogeneity can broaden the distribution of extinction times and produce population‐level outcomes that differ from those predicted by homogeneous or mean‐field formulations. Under the intermittent 21/7 regimen, extinction times were cycle‐structured and, in the extended simulations, were better described by a three‐component mixture than by a unimodal model, indicating schedule‐associated survival cohorts rather than a universal multimodal law. Across the simulations, treatment failure probability increased with population size while the amplification factor remained approximately constant, consistent with an intensive single‐cell property. Sensitivity analyses indicated that the coefficient of variation (CV) of transporter expression was a key determinant of outcome variability across the explored parameter space. These findings support the hypothesis that non‐genetic heterogeneity in drug uptake can contribute to variability in treatment response and apparent resistance. More broadly, this proof‐of‐principle framework highlights the value of stochastic cell‐level modeling for studying therapeutic response distributions when cellular heterogeneity and nonlinear pharmacodynamics are expected to play important roles. Study Highlights What Is the Current Knowledge on the Topic ○Traditional PK‐PD models use population‐averaged approaches that address inter‐patient variability but not intra‐tumor cellular heterogeneity in drug transporter expression. What Question Did This Study Address ○How does cellular‐level heterogeneity in drug transporter expression, coupled with nonlinear pharmacodynamics, affect therapeutic outcomes? What Does This Study Add to Our Knowledge ○Cellular transporter heterogeneity amplifies pharmacodynamic variance up to 1,000‐fold through nonlinear dose–response, creating cycle‐structured extinction time distributions under intermittent dosing and schedule‐associated survival cohorts. Across N = 100–2,000, treatment failure increased with population size while the amplification factor A remained approximately constant, consistent with an intensive single‐cell property. Transporter CV emerged as the strongest predictor of treatment failure across all parameter combinations. How Might This Change Drug Discovery, Development, and/or Therapeutics ○Stochastic cell‐level modeling should be incorporated into PK‐PD frameworks for targeted therapies. Single‐cell measurements of transporter heterogeneity could stratify patients, and combination therapies with uncorrelated transporter dependencies could reduce treatment failures.

• Publisher: Wiley
• Subject: cellular heterogeneity / Computer Simulation / Dose-Response Relationship, Drug / drug transporter variability / Humans / Models, Biological / pharmacokinetic‐pharmacodynamic modeling / Piperidines - administration & dosage / Piperidines - pharmacokinetics / Piperidines - pharmacology / stochastic differential equations / Stochastic Processes / treatment resistance / variance amplification