Model-based evaluation of radiation and radiosensitizing agents in oncology
Journal article, 2018

Radiotherapy is one of the major therapy forms in oncology, and combination therapies involving radiation and chemical compounds can yield highly effective tumor eradication. In this paper, we develop a tumor growth inhibition model for combination therapy with radiation and radiosensitizing agents. Moreover, we extend previous analyses of drug combinations by introducing the tumor static exposure (TSE) curve. The TSE curve for radiation and radiosensitizer visualizes exposure combinations sufficient for tumor regression. The model and TSE analysis are then tested on xenograft data. The calibrated model indicates that the highest dose of combination therapy increases the time until tumor regrowth 10-fold. The TSE curve shows that with an average radiosensitizer concentration of 1.0μg/mL the radiation dose can be decreased from 2.2 Gy to 0.7 Gy. Finally, we successfully predict the effect of a clinically relevant treatment schedule, which contributes to validating both the model and the TSE concept.


Tim Cardilin

University of Gothenburg

Chalmers, Mathematical Sciences

Joachim Almquist

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Mats Jirstrand

Chalmers, Electrical Engineering, Systems and control, Automatic Control

A. Zimmermann

Merck KGaA

S. El Bawab

Merck KGaA

J. Gabrielsson

Swedish University of Agricultural Sciences (SLU)

CPT: Pharmacometrics and Systems Pharmacology

2163-8306 (ISSN)

Vol. 7 1 51-58

Subject Categories

Computational Mathematics

Bioinformatics and Systems Biology

Cancer and Oncology

Areas of Advance

Life Science Engineering (2010-2018)



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