Research

A multi-compartment pharmacokinetic model of the interaction between paclitaxel and doxorubicin

¹ Department of Physics and Astronomy, University of Lethbridge, 4401 University Drive, Lethbridge, T1K 3M4, Canada
² Department of Physics, University of Alberta, Edmonton, T6G 2J1, Canada
³ Department of Engineering, Mathematics and Physics, Fayoum University, Fayoum, Egypt
⁴ Department of Oncology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, T6G 2J1, Canada

^* e-mail: jack.tuszynski@gmail.com

Received: 12 June 2014
Accepted: 5 September 2014
Published online: 5 November 2014

Abstract

Background

In this paper the interactions between paclitaxel, doxorubicin and the metabolic enzyme CYP3A4 are studied using computational models. The obtained results are compared with those of available clinical data sets. Analysis of the drug-enzyme interactions leads to a recommendation of an optimized paclitaxel-doxorubicin drug regime for chemotherapy treatment.

Methods

A saturable multi-compartment pharmacokinetic model for the multidrug treatment of cancer using paclitaxel and doxorubicin in a combination is developed. The model’s kinetic equations are then solved using standard numerical methods for solving systems of nonlinear differential equations. The parameters were adjusted by fitting to available clinical data. In addition, we studied the interaction of each drug with the metabolic enzyme CYP3A4 through blind docking simulations to demonstrate that these drugs compete for the same metabolic enzyme and to show their molecular mode of binding. This provides a molecular-level justification for the introduction of interaction terms in the kinetic model.

Results

Using docking simulations we compared the relative binding affinities for the metabolic enzyme of the two chemotherapy drugs. Since paclitaxel binds more strongly to CYP3A4 than doxorubicin, an explanation is given why doxorubicin has no apparent influence upon paclitaxel, while paclitaxel has a profound effect upon doxorubicin. Finally, we studied different time sequences of paclitaxel and doxorubicin concentrations and calculated their AUCs.

Conclusions

We have found excellent agreement between our model and available empirical clinical data for the drug combination studied here. To support the kinetic model at a molecular level, we built an atomistic three-dimensional model of the ligands interacting with the metabolic enzyme and elucidated the binding modes of paclitaxel and doxorubicin within CYP3A4. Blind docking simulations provided estimates of the corresponding binding energies. The paper is concluded with clinical implications for the administration of the two drugs in combination.