Speaker
Description
Deciphering intratumor spatial configuration of cell communities is fundamental for mechanistically understanding how heterogeneity in tumor phenotypes impacts the effectiveness of treatments. Such dynamic interplay in the tumor microenvironment determines a continuum of transition stages, having different levels of compliance to therapy \cite{prunella2025pharmacometric}. Scheduling and sequencing of two or more treatments starting from routinely available H&E-stained Whole Slide Images could hence be improved by considering also longitudinal interactions between cancerous and immune cells. Agent-based modeling is a computational modeling framework that deploys dynamic cell-to-cell inter-actions within a drug-modulated selective environment, and can provide a time-resolved quantitative approach for more informed and adaptive treatment \cite{kather2017silico} selection. The temporal dimension of the model allows not only simulating under fixed behavioral rules, but also includes the cumulative effects of drug exposure over time \cite{surendran2023agent}. This enables the representation of plastic interactions between cells and therapeutic agents, whereby cellular behavior can dynamically change as a function of prior treatment history. Such a framework allows the simulation of clinically relevant phenomena frequently observed in oncology, including the emergence and selection of therapy-resistant clones.
Bibliography
@article{kather2017silico,
title={In silico modeling of immunotherapy and stroma-targeting therapies in human colorectal cancer},
author={Kather, Jakob Nikolas and Poleszczuk, Jan and Suarez-Carmona, Meggy and Krisam, Johannes and Charoentong, Pornpimol and Valous, Nektarios A and Weis, Cleo-Aron and Tavernar, Luca and Leiss, Florian and Herpel, Esther and others},
journal={Cancer research},
volume={77},
number={22},
pages={6442--6452},
year={2017},
publisher={American Association for Cancer Research}
}
@article{prunella2025pharmacometric,
title={Pharmacometric and Digital Twin modeling for adaptive scheduling of combination therapy in advanced gastric cancer},
author={Prunella, Michela and Altini, Nicola and D’Alessandro, Rosalba and Schirizzi, Annalisa and Ricci, Angela Dalia and Lotesoriere, Claudio and Scarabaggio, Paolo and Carli, Raffaele and Dotoli, Mariagrazia and Giannelli, Gianluigi and others},
journal={Computer Methods and Programs in Biomedicine},
volume={270},
pages={108919},
year={2025},
publisher={Elsevier}
}
@article{surendran2023agent,
title={Agent-based modelling reveals the role of the tumor microenvironment on the short-term success of combination temozolomide/immune checkpoint blockade to treat glioblastoma},
author={Surendran, Anudeep and Jenner, Adrianne L and Karimi, Elham and Fiset, Benoit and Quail, Daniela F and Walsh, Logan A and Craig, Morgan},
journal={The Journal of Pharmacology and Experimental Therapeutics},
volume={387},
number={1},
pages={66--77},
year={2023},
publisher={Elsevier}
}
