Systematic Modeling of Pharmacokinetics Based on Multi-Scale Imaging

Abstract

Cancer research has achieved dramatic advances in recent years with modern techniques and aroused extensive efforts to discover effective therapeutic drugs. As complement to time and resource intensive traditional drug development methods, application of computational models for drug pharmacokinetics and pharmacodynamics research has become increasingly popular because of its high efficiency and flexibility. Our work provides a well-designed integrated mechanistic model for developing cancer drugs by incorporating new techniques like PET, CT, and intravital microscopy. This model studies drug distribution and therapeutic effects from a systematic viewpoint at three different yet highly related levels. Firstly, a macro-scale model was established to study time course drug distributions in different organs especially in blood which circulates in whole body and delivers drug to targeted tumor. At the intratumoral level, a coupled 3D tumor growth and angiogenesis model was proposed to elaborately simulate neovasculature formation and calculate regional variations in drug distribution inside solid tumor. The third part focuses on how regional variations in drug distribution affect tumor cell death/proliferation rate by linking therapeutic response to intracellular signaling pathway blockade or alteration, which provides us a high-resolution overview of drug action in the targeted tumor cell. Hence, the first two modules which target the organ level and intratumoral microenvironment are directly coupled to pharmacokinetics analysis which is linked to the last component of the model that analyzes the pharmacodynamic effects at the cellular level. Experimental data for calibrating computational model, like drug distribution, tumor vasculature, drug penetration rate etc., were measured using PET, CT, and high resolution intravital microscopy. We perform simulations to investigate the delivery efficiency and drug efficacy of free drug and nanotherapeutics. Our model successfully predicted optimal drug property and therapy strategy. Finally, model effectiveness was validated by in vivo experimental data.