Borau, C. orcid.org/0000-0002-3784-1140, Chisholm, R. orcid.org/0000-0003-3379-9042 and Richmond, P. orcid.org/0000-0002-4657-5518 (2026) Cellfoundry: A GPU-accelerated, multi-physics ABM framework for cellular microenvironment and organoid-scale studies. Array, 31. 101107. ISSN: 2590-0056
Abstract
Advanced in vitro systems such as organoids and microfluidic organ-on-a-chip platforms enable physiologically richer experimentation, but their complexity creates large parameter spaces and makes it difficult to disentangle the mechanistic roles of transport, mechanics, and extracellular microstructure. Agent-based modelling provides a natural computational counterpart by representing cells as discrete entities coupled through rules and environmental fields. However, microenvironment models often remain limited by scalability, simplified extracellular matrix representations, and the practical difficulty of calibrating large numbers of parameters. Here we present Cellfoundry, a GPU-accelerated computational framework built on FLAMEGPU2 for simulating cellular microenvironments. Its principal novelty is the integration, within a single modular architecture, of explicit fibrous extracellular matrix mechanics and remodelling, agent-resolved focal adhesions, multispecies extracellular transport, and parameter-calibration workflows. The framework supports multiple cell types and couples mechanically resolved cell–cell and cell–matrix interactions with biochemical fields regulating metabolism, migration, and cell-cycle progression. To support reproducible model development and calibration, the framework includes a fibre-network generation module, automated performance benchmarking workflows, post-processing and reporting utilities, and an Optuna-based Bayesian optimization pipeline with configurable single- and multi-objective targets. Two showcase examples illustrate these capabilities: a migration assay calibrated against fibroblast motility descriptors and a multi-objective organoid growth scenario reproducing target population composition and expansion dynamics over time. Together, these examples demonstrate how Cellfoundry can be used to build, calibrate, and extend mechanistically interpretable models of coupled biochemical and mechanical dynamics in advanced in vitro systems.
Metadata
| Item Type: | Article |
|---|---|
| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/). |
| Keywords: | Agent-based modelling; GPU computing; Mechanobiology; Extracellular matrix; Focal adhesions; FLAMEGPU2 |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
| Date Deposited: | 14 Sep 2026 13:28 |
| Last Modified: | 14 Sep 2026 13:28 |
| Status: | Published |
| Publisher: | Elsevier BV |
| Refereed: | Yes |
| Identification Number: | 10.1016/j.array.2026.101107 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:245411 |
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