Speaker
Description
This talk explores how we move from models toward clinically useful digital twins in biomedicine. It focuses on three pillars: multiscale integration of intracellular signalling with agent-based cell simulations \cite{Estragues} , personalisation using patient-specific omics \cite{Montagud}, and community standards for model validation \cite{Ntiniakou}.
We present PhysiBoSS1, a tool that couples stochastic Boolean network simulations with agent-based multicellular dynamics, demonstrating applications in drug screening and in predicting synergies in cancer treatments. Crucially, this modular architecture enables independent evolution of biological components, such as signalling logic and cell properties, supporting long-term maintainability and scalability. We will highlight that realistic tumour simulations will require better-curated data, novel algorithms and computer architectures, and, more importantly, careful methods to bridge very different temporal and spatial scales \cite{Ponce}.
A community benchmarking effort across several major agent-based tools shows that, despite similar core features, differences in underlying mathematics and numerics affect results, underscoring the need for shared interfaces, metrics, and open dissemination \cite{Ntiniakou}. Finally, we show that patient-specific Boolean models, parameterised with genomic and transcriptomic data in breast and prostate cancer, can suggest actionable drug targets and are experimentally validated in cell lines, illustrating the potential of predictive, personalised digital twins \cite{Montagud}.
Bibliography
@ARTICLE{Estragues,
title = "A novel scalable high performance diffusion solver for
multiscale cell simulations",
author = "Estragues-Mu{\~n}oz, Jose-Luis and Alvarez, Carlos and
Montagud, Arnau and Jimenez-Gonzalez, Daniel and Valencia,
Alfonso",
month = feb,
year = 2026,
archivePrefix = "arXiv",
primaryClass = "cs.DC",
eprint = "2602.05017"
}
@ARTICLE{Montagud,
title = "Patient-specific Boolean models of signalling networks guide
personalised treatments",
author = "Montagud, Arnau and B{\'e}al, Jonas and Tobalina, Luis and
Traynard, Pauline and Subramanian, Vigneshwari and Szalai, Bence
and Alf{\"o}ldi, R{\'o}bert and Pusk{\'a}s, L{\'a}szl{\'o} and
Valencia, Alfonso and Barillot, Emmanuel and Saez-Rodriguez,
Julio and Calzone, Laurence",
journal = "Elife",
publisher = "eLife Sciences Publications, Ltd",
volume = 11,
number = "e72626",
month = feb,
year = 2022,
}
@UNPUBLISHED{Ntiniakou,
title = "Open benchmarking for cell-based multiscale models: Lessons from
a community initiative",
author = "Ntiniakou, Thaleia and Osborne, James and Zhao, Jieling and
Dichamp, Jules and Cogno, Nicol{`o} and Heiland, Randy and
Amponsah, Kwabena and Pesek, Jiri and Duswald, Tobias and
Hayoun-Mya, Othmane and Jennings, Jack and Pedrazzi, Matteo and
Bournes, Ryan and Ruscone, Marco and Cooper, Fergus and
No{\"e}l, Vincent and Leach, Matthew I and Madrid-Valiente,
Alejandro and Estragu{\'e}s-Mu{\~n}oz, Jose and Smelko, Adam and
Aliyev, Taghi and Manca, Marco and Pitt-Francis, Joe and Mirams,
Gary and Macklin, Paul and Fletcher, Alexander G and Vavourakis,
Vasileios and Hoehme, Stefan and Carbonell-Caballero, Jose and
Bauer, Roman and Paul Liedekerke, Van and Drasdo, Dirk and
Valencia, Alfonso and Montagud, Arnau",
journal = "bioRxiv",
month = jul,
year = 2025,
}
@ARTICLE{Ponce,
title = "{PhysiBoSS} 2.0: a sustainable integration of stochastic Boolean
and agent-based modelling frameworks",
author = "Ponce-de-Leon, Miguel and Montagud, Arnau and No{\"e}l, Vincent
and Meert, Annika and Pradas, Gerard and Barillot, Emmanuel and
Calzone, Laurence and Valencia, Alfonso",
journal = "NPJ Syst. Biol. Appl.",
publisher = "Springer Science and Business Media LLC",
volume = 9,
number = 1,
pages = "54",
month = oct,
year = 2023,
}
