Pharmacokinetics of Anti-VEGF Agent Aflibercept in Cancer Predicted by Data-Driven, Molecular-Detailed Model

CPT: Pharmacometrics & Systems Pharmacology
Stacey D FinleyAleksander S Popel

Abstract

Mathematical models can support the drug development process by predicting the pharmacokinetic (PK) properties of the drug and optimal dosing regimens. We have developed a pharmacokinetic model that includes a biochemical molecular interaction network linked to a whole-body compartment model. We applied the model to study the PK of the anti-vascular endothelial growth factor (VEGF) cancer therapeutic agent, aflibercept. Clinical data is used to infer model parameters using a Bayesian approach, enabling a quantitative estimation of the contributions of specific transport processes and molecular interactions of the drug that cannot be examined in other PK modeling, and insight into the mechanisms of aflibercept's antiangiogenic action. Additionally, we predict the plasma and tissue concentrations of unbound and VEGF-bound aflibercept. Thus, we present a computational framework that can serve as a valuable tool for drug development efforts.

References

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Citations

Apr 25, 2017·Integrative Biology : Quantitative Biosciences From Nano to Macro·Jared C Weddell, Princess I Imoukhuede
Apr 7, 2018·Integrative Biology : Quantitative Biosciences From Nano to Macro·Ding Li, Stacey D Finley
Dec 22, 2017·NPJ Systems Biology and Applications·Jared C WeddellP I Imoukhuede
Feb 18, 2016·Annals of Biomedical Engineering·Colleen E ClancyDavid M Eckmann
Jun 27, 2019·The AAPS Journal·Mohammad JafarnejadAleksander S Popel
Aug 8, 2020·Frontiers in Physiology·Yingye FangP I Imoukhuede
Sep 4, 2020·Scientific Reports·Spencer B MamerP I Imoukhuede
Jan 1, 2016·NPJ Systems Biology and Applications·Jennifer A RohrsStacey D Finley

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Methods Mentioned

BETA
flow cytometry

Software Mentioned

Sundials
MATLAB
SimBiology
Pi4U

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