Hypoxia-activated prodrugs offer a promising strategy for targeting oxygen-deficient regions in solid tumors, which are often resistant to conventional therapies. However, modeling their behavior is challenging because of the complex interplay between oxygen availability, drug activation, and cell survival. In this work, we developed a multi-scale and mixed-dimensional model that coupled spatially resolved drug and oxygen transport with pharmacokinetics and pharmacodynamics to simulate the cellular response. The model integrated blood flow, oxygen diffusion, and consumption, drug delivery, and metabolism. To reduce computational cost, we mitigated the global nonlinearity by coupling the multi-scale and mixed-dimensional models one-way with a reduced 0D model for drug metabolization. The global sensitivity analysis was then used to identify key parameters influencing drug activation and therapeutic outcome. This approach enabled efficient simulation and supports the design of optimized therapies targeting hypoxia.
Mathematical modeling and sensitivity analysis of hypoxia-activated drugs / Coclite, Alessandro; Eccher, Riccardo Montanelli; Possenti, Luca; Vitullo, Piermario; Zunino, Paolo. - In: AIMS MATHEMATICS. - ISSN 2473-6988. - ELETTRONICO. - 10:11(2025), pp. 25504-25544. [10.3934/math.20251130]
Mathematical modeling and sensitivity analysis of hypoxia-activated drugs
Coclite, AlessandroMembro del Collaboration Group
;
2025
Abstract
Hypoxia-activated prodrugs offer a promising strategy for targeting oxygen-deficient regions in solid tumors, which are often resistant to conventional therapies. However, modeling their behavior is challenging because of the complex interplay between oxygen availability, drug activation, and cell survival. In this work, we developed a multi-scale and mixed-dimensional model that coupled spatially resolved drug and oxygen transport with pharmacokinetics and pharmacodynamics to simulate the cellular response. The model integrated blood flow, oxygen diffusion, and consumption, drug delivery, and metabolism. To reduce computational cost, we mitigated the global nonlinearity by coupling the multi-scale and mixed-dimensional models one-way with a reduced 0D model for drug metabolization. The global sensitivity analysis was then used to identify key parameters influencing drug activation and therapeutic outcome. This approach enabled efficient simulation and supports the design of optimized therapies targeting hypoxia.| File | Dimensione | Formato | |
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