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Model-based evaluation of radiation and radiosensitizing agents in oncology

Journal article
Authors Tim Cardilin
Joachim Almquist
Mats Jirstrand
Astrid Zimmermann
Samer El Bawab
Johan Gabrielsson
Published in CPT: Pharmacometrics and Systems Pharmacology
Volume 7
Issue 1
Pages 51-58
Publication year 2018
Published at Department of Mathematical Sciences
Pages 51-58
Language en
Links doi.org/10.1002/psp4.12268
Subject categories Applied mathematics, Bioinformatics and Systems Biology, Cancer and Oncology

Abstract

© 2017 ASCPT. 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.

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