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

Area of Science:

• Pharmacology
• Mathematical Biology
• Systems Biology

Background:

• Traditional pharmacokinetic-pharmacodynamic (PK/PD) models assume cellular homogeneity, failing to explain clinical response variability.
• Patient outcomes often differ despite similar drug plasma concentrations, suggesting underlying biological heterogeneity.

Purpose of the Study:

• To develop and validate a multiscale stochastic framework explaining how cellular heterogeneity amplifies drug response variability.
• To investigate the role of drug transporter expression variability in patient treatment outcomes using cobimetinib as a model.

Main Methods:

• Coupled deterministic systemic pharmacokinetics with cellular-level stochastic differential equations.
• Modeled log-normal distribution of transporter expression across cells to simulate intracellular drug concentration heterogeneity.
• Utilized simulations to analyze extinction times and population-level outcomes under an intermittent dosing regimen.

Main Results:

• Cellular heterogeneity broadened extinction time distributions and altered population-level outcomes compared to homogeneous models.
• Intermittent dosing (21/7) resulted in cycle-structured extinction times, suggesting schedule-associated survival cohorts.
• Treatment failure probability increased with population size, while the amplification factor remained constant, indicating a single-cell property.

Conclusions:

• Non-genetic heterogeneity in drug uptake significantly contributes to variable treatment responses and apparent drug resistance.
• Stochastic cell-level modeling is valuable for studying therapeutic response distributions when cellular heterogeneity and nonlinear pharmacodynamics are present.