PhysiBoSS

Integration of stochastic Boolean modelling in an agent-based modelling framework as an add-on

Institution:

Research Group:

BSC Group: Computational Biology - Life Sciences

Researcher/s:

Miguel Ponce de Leon, Arnau Montagud, Gerard Pradas, Annika Meert, Alfonso Valencia, Vincent Noel, Laurence Calzone, Gaelle Letort, Emmanuel Barillot

Description:

PhysiBoSS couples an agent-based tissue simulator (PhysiCell) with stochastic Boolean signalling (MaBoSS), letting each in-silico cell carry its own regulatory network. This enables simulating patient-size “virtual tumours” that respond to drugs in silico.

PhysiBoSS is a multi-scale, HPC-ready digital-twin engine. GPU kernels, clinical-grade packaging and organoid validation will position it as a decision-support layer for adaptive oncology and complex-tissue pharmacology.

Value Proposition:

Simulate tomorrow's biopsy before you treat

Aplication areas:

Drug treatment, drug repurposing, oncology, digital twin, virtual clinical trials, personalised medicine

Target market:

Pharmaceutical; Software as a Medical Device

Technology Readiness Level (1-9): 4

Protection:

BSD License (Version 3.0)

More information

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