Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
Artikel i vetenskaplig tidskrift, 2019

Purpose: Radiation therapy, whether given alone or in combination with chemical agents, is one of the cornerstones of oncology. We develop a quantitative model that describes tumor growth during and after treatment with radiation and radiosensitizing agents. The model also describes long-term treatment effects including tumor regrowth and eradication. Methods: We challenge the model with data from a xenograft study using a clinically relevant administration schedule and use a mixed-effects approach for model-fitting. We use the calibrated model to predict exposure combinations that result in tumor eradication using Tumor Static Exposure (TSE). Results: The model is able to adequately describe data from all treatment groups, with the parameter estimates taking biologically reasonable values. Using TSE, we predict the total radiation dose necessary for tumor eradication to be 110 Gy, which is reduced to 80 or 30 Gy with co-administration of 25 or 100 mg kg −1 of a radiosensitizer. TSE is also explored via a heat map of different growth and shrinkage rates. Finally, we discuss the translational potential of the model and TSE concept to humans. Conclusions: The new model is capable of describing different tumor dynamics including tumor eradication and tumor regrowth with different rates, and can be calibrated using data from standard xenograft experiments. TSE and related concepts can be used to predict tumor shrinkage and eradication, and have the potential to guide new experiments and support translations from animals to humans.

Translational science



Radiation therapy

Interspecies scaling

Combination therapy

Turnover model


Tim Cardilin

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Joachim Almquist


Mats Jirstrand

Chalmers, Elektroteknik, System- och reglerteknik

Astrid Zimmermann

Merck KGaA

Floriane Lignet

Merck Healthcare KGaA

Samer El Bawab

Merck Healthcare KGaA

Johan Gabrielsson

Sveriges lantbruksuniversitet (SLU)

Cancer Chemotherapy and Pharmacology

0344-5704 (ISSN)

Vol. 83 6 1159-1173


Farmaceutisk vetenskap

Bioinformatik och systembiologi

Cancer och onkologi


Livsvetenskaper och teknik (2010-2018)





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