An Integrated Multiscale Mechanistic Model for Cancer Drug Therapy

Daniel Y Lee,King C Li,De-Shuang Huang,Xiaobo Zhou,Lei Tang,Jing Su

doi:10.5402/2012/818492

Daniel Y Lee, King C Li + Show 4 more

Open Access

https://doi.org/10.5402/2012/818492

Copy DOI

Abstract

In this paper, we established a multiscale mechanistic model for studying drug delivery, biodistribution, and therapeutic effects of cancer drug therapy in order to identify optimal treatment strategies. Due to the specific characteristics of cancer, our proposed model focuses on drug effects on malignant solid tumor and specific internal organs as well as the intratumoral and regional extracellular microenvironments. At the organ level, we quantified drug delivery based on a multicompartmental model. This model will facilitate the analysis and prediction of organ toxicity and provide important pharmacokinetic information with regard to drug clearance rates. For the analysis of intratumoral microenvironment which is directly related to blood drug concentrations and tumor properties, we constructed a drug distribution model using diffusion-convection solute transport to study temporal/spatial variations of drug concentration. With this information, our model incorporates signaling pathways for the analysis of antitumor response with drug combinations at the extracellular level. Moreover, changes in tumor size, cellular proliferation, and apoptosis induced by different drug treatment conditions are studied. Therefore, the proposed multi-scale model could be used to understand drug clinical actions, study drug therapy-antitumor effects, and potentially identify optimal combination drug therapy. Numerical simulations demonstrate the proposed system's effectiveness.

Highlights

Cancer disease remains a leading cause of high morbidity and mortality in both adults and children
One of the most important changes is the application of computational modeling for pharmacokinetics/pharmacodynamics (PK/PD) analysis [1, 2]
PD models focus on time course of drug effects at the site of action (Figure 1)

Summary

Introduction

Cancer disease remains a leading cause of high morbidity and mortality in both adults and children. Cancer research has undergone dramatic changes recently. One of the most important changes is the application of computational modeling for pharmacokinetics/pharmacodynamics (PK/PD) analysis [1, 2]. PD models focus on time course of drug effects at the site of action (Figure 1). These models have been playing increasingly important roles in contemporary drug research [3]. Some pharmaceutical companies like SimCYP and Entelos have been implementing the combined mathematical models to assist drug R&D works. The SimCYP developed a Virtual-population-based Simulator which streamlines drug development through the modelling and simulation of pharmacokinetics and pharmacodynamics analysis [4].

Objectives

Methods

Conclusion