Learning surrogate equations for the analysis of an agent-based cancer model

Frontiers in Applied Mathematics and Statistics, Journal Year: 2025, Volume and Issue: 11

Published: May 15, 2025

In this paper, we adapt a two-species agent-based cancer model that describes the interaction between cells and healthy on uniform grid to include with third species—namely immune cells. We run six different scenarios explore competition initial concentration of dynamics. then use coupled equation learning construct population-based reaction for each scenario. show how they can be unified into single surrogate model, whose underlying three ordinary differential equations are much easier analyse than original model. As an example, by finding steady state concentration, able find linear relationship This enables us estimate suitable values reduce substantially without performing additional complex expensive simulations from stochastic

Language: Английский

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Exploring the Potential of Digital Twins in Cancer Treatment: A Narrative Review of Reviews

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(10), P. 3574 - 3574

Published: May 20, 2025

Background: Digital twin (DT) technology, integrated with artificial intelligence (AI) and machine learning (ML), holds significant potential to transform oncology care. By creating dynamic virtual replicas of patients, DTs allow clinicians simulate disease progression treatment responses, offering a personalized approach cancer treatment. Aim: This narrative review aimed synthesize existing studies on the application digital twins in oncology, focusing their benefits, challenges, ethical considerations. Methods: The reviews (NRR) followed structured selection process using standardized checklist. Searches were conducted PubMed Scopus predefined query oncology. Reviews prioritized based synthesis prior studies, focus Studies evaluated quality parameters (clear rationale, research design, methodology, results, conclusions, conflict disclosure). Only scores above prefixed threshold disclosed conflicts interest included final synthesis; seventeen selected. Results Discussion: offer advantages such as enhanced decision-making, optimized regimens, improved clinical trial design. Moreover, economic forecasts suggest that integration into healthcare systems may significantly reduce costs drive growth precision medicine market. However, challenges include data issues, complexity biological modeling, need for robust computational resources. A comparison cutting-edge contributes this direction confirms also legal considerations, particularly concerning AI, privacy, accountability, remain barriers. Conclusions: great promise, but requires careful attention ethical, legal, operational challenges. Multidisciplinary efforts, supported by evolving regulatory frameworks like those EU, are essential ensuring responsible effective implementation improve patient outcomes.

Language: Английский

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Comment on: Antiviral effect of Evusheld in COVID-19 hospitalized patients infected with pre-Omicron or Omicron variants: a modelling analysis of the randomized DisCoVeRy trial

Journal of Antimicrobial Chemotherapy, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 14, 2024

Language: Английский

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Linking spatial drug heterogeneity to microbial growth dynamics in theory and experiment

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 22, 2024

Abstract Diffusion and migration play pivotal roles in microbial communities - shaping, for example, colonization new environments the maintenance of spatial structures biodiversity. While previous research has extensively studied free diffusion, such as range expansion, there remains a gap understanding effects biologically or physically eleterious confined environments. In this study, we examine interplay between drug heterogeneity within an experimental meta-community E. faecalis , Gram-positive opportunistic pathogen. When community is to spatially-extended habitats (‘islands’) bordered by deleterious conditions, find that population level response depends on trade-off growth rate island transfer into regions with harsher phenomenon explore modulating antibiotic concentration island. heterogeneous islands, composed spatially patterned patches support varying levels growth, population’s fate critically specific arrangement these same averaged leads diverging responses. These results are qualitatively captured simple simulations, analytical expressions which derive using first-order perturbation approximations reaction-diffusion models explicit dependence. Among all possible arrangements, our theoretical findings reveal highest rates at center most effectively mitigates decline, while lowest least effective. They thus serve optimal arrangements bounding mixed phase, where outcomes emerge tuning arrangements. Extending approach more complex varied structures, ring-structured community, further validates impact arrangement. Our suggest approaches interpreting clinical when applying identical doses inform optimization spatially-explicit dosing strategies. Author summary develop automated platform experimentally investigate short-term dynamics under heterogeneity. collective can vary significantly, even dose, due different By constructing model, observed simulated closely matches data. Furthermore, aligns well long-term rate, defined largest eigenvalue, system quickly enters equilibrium state. Using concepts from theory, derived relationship boundary diffusion effect, homogeneous effect. highlight habitats, emergent property. The bacterial near equilibrium, suggesting measured ecological scale may be used predict resistance evolutionary behavior.

Language: Английский

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Agent-based modeling reveals impacts of cell adhesion and matrix remodeling on cancer collective cell migration phenotypes

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 23, 2024

Abstract Understanding the phenotypic transitions of cancer cells is crucial for elucidating tumor progression mechanisms, particularly transition from a non-invasive spheroid phenotype to an invasive network phenotype. We developed agent-based model (ABM) using Compucell3D, open-source biological simulation software, investigate how varying biophysical and biochemical parameters influence emerging properties cellular communities, including cell growth, division, migration. Our focus was on cell-cell contact adhesion matrix remodeling effects simplified enzymatic extracellular subsequent enhancements chemotaxis or durotaxis as combined effect localized secretion chemoattractant. By chemoattractant rate energy, we simulated their behavior driving The serves digital twin 3D culture, simulating invasion over 1 week, validated against published data. simulations track emergent morphological collective changes key metrics such circularity invasion. findings indicate that increased enhances invasiveness cells, promoting Additionally, changing energy strong weak affects compactness spheroids, resulting in lower work advances understanding by providing insights into mechanisms behind transitions.

Language: Английский

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