Virtual Populations for Quantitative Systems Pharmacology Models

Abstract

Quantitative systems pharmacology (QSP) places an emphasis on dynamic systems modeling, incorporating considerations from systems biology modeling and pharmacodynamics. The goal of QSP is often to quantitatively predict the effects of clinical therapeutics, their combinations, and their doses on clinical biomarkers and endpoints. In order to achieve this goal, strategies for incorporating clinical data into model calibration are critical. Virtual population (VPop) approaches facilitate model calibration while faced with challenges encountered in QSP model application, including modeling a breadth of clinical therapies, biomarkers, endpoints, utilizing data of varying structure and source, capturing observed clinical variability, and simulating with models that may require more substantial computational time and resources than often found in pharmacometrics applications. VPops are frequently developed in a process that may involve parameterization of isolated pathway models, integration into a larger QSP model, incorporation of clinical data, calibration, and quantitative validation that the model with the accompanying, calibrated VPop is suitable to address the intended question or help with the intended decision. Here, we introduce previous strategies for developing VPops in the context of a variety of therapeutic and safety areas: metabolic disorders, drug-induced liver injury, auto-immune diseases, and cancer. We introduce methodological considerations, prior work for sensitivity analysis and VPop algorithm design, and potential areas for future advancement. Finally, we give a more detailed application example of a VPop calibration algorithm that illustrates recent progress and many of the methodological considerations. In conclusion, although methodologies have varied, VPop strategies have been successfully applied to give valid clinical insights and predictions with the assistance of carefully defined and designed calibration and validation strategies. While a uniform VPop approach for all potential QSP applications may be challenging given the heterogeneity in use considerations, we anticipate continued innovation will help to drive VPop application for more challenging cases of greater scale while developing new rigorous methodologies and metrics.

Development of a minimal PBPK-QSP modeling platform for LNP-mRNA based therapeutics to study tissue disposition and protein expression dynamics

“…A powerful application of QSP modeling is the ability to generate virtual populations and perform trial simulations in silico (Cheng et al, 2022). We examined how treatment efficacy would change for the same virtual animal cohort under different dosing regimens.…”

Quantitative systems pharmacology modeling of tumor heterogeneity in response to BH3‐mimetics using virtual tumors calibrated with cell viability assays

“…In this study, a new approach is proposed to explore intra‐tumoral heterogeneity and both innate and acquired drug resistance in multiple drug target combinations. In a manner analogous to simulating virtual patients that are gathered into virtual populations in classical QSP workflows, 38 the proposed method simulates virtual cells (VCs) that are combined into virtual tumors (VTs), with VCs calibrated to reproduce multiple drug perturbation cell viability assays. Potential uses of calibrated VTs were explored, including cell heterogeneity descriptions to characterize the impact of each drug in a combination regimen and the integration of VTs inside an ABM approach to enable in vitro to in vivo bridging.…”