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Updated: Dec 10, 2025
Author Spotlight: Establishing a Murine Non-Small Cell Lung Cancer Model for Developing Nanoformulations of Anticancer Drugs
Published on: May 10, 2024
Advanced Non-linear Mathematical Model for the Prediction of the Activity of a Putative Anticancer Agent in
Sotirios G Liliopoulos1, George S Stavrakakis1, Konstantinos S Dimas2
1School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece.
Background/Aim:
Mathematical models have long been considered as important tools in cancer biology and therapy. Herein, we present an advanced non-linear mathematical model that can predict accurately the effect of an anticancer agent on the growth of a solid tumor.
Materials And Methods:
Advanced non-linear mathematical optimization techniques and human-to-mouse experimental data were used to develop a tumor growth inhibition (TGI) estimation model.
Results:
Using this mathematical model, we could accurately predict the tumor mass in a human-to-mouse pancreatic ductal adenocarcinoma (PDAC) xenograft under gemcitabine treatment up to five time periods (points) ahead of the last treatment.
Conclusion:
The ability of the identified TGI dynamic model to perform satisfactory short-term predictions of the tumor growth for up to five time periods ahead was investigated, evaluated and validated for the first time. Such a prediction model could not only assist the pre-clinical testing of putative anticancer agents, but also the early modification of a chemotherapy schedule towards increased efficacy.
