Hernández Rivera, AndrésVelarde, PabloZafra Cabeza, AscensiónMaestre Torreblanca, José María2025-11-042025-11-042025Hernández Rivera, A., Velarde, P., Zafra Cabeza, A. y Maestre Torreblanca, J.M. (2025). Drug dosing for cancer therapy: A stochastic model predictive control perspective. Journal of Theoretical Biology, 615, 112255.https://doi.org/10.1016/j.jtbi.2025.112255.0022-51931095-8541https://hdl.handle.net/11441/178605This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ ).Stochastic Model Predictive Control (SMPC) is an effective decision-making method in applications where uncertainties play a significant role. This work introduces a non-linear formulation of SMPC specifically designed for cancer therapy. The proposed method considers the stochastic nature of tumor growth, non-linear dynamics, and a potential side effect of the treatment. Through one-year simulations, the results showcase the effectiveness of this strategy in controlling drug dosing.application/pdf14 p.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/CancerChemotherapyNon-linear control systemsModel predictive controlStochastic processesinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccesshttps://doi.org/10.1016/j.jtbi.2025.112255