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Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs
Bulletin of Mathematical Biology, Volume: 83, Issue: 10
Swansea University Authors: SARA HAMIS, Gibin Powathil
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DOI (Published version): 10.1007/s11538-021-00935-y
Abstract
We combine a systems pharmacology approach with an agent-based modelling approach to simulate LoVo cells subjected to AZD6738, an ATR (ataxia–telangiectasia-mutated and rad3-related kinase) inhibiting anti-cancer drug that can hinder tumour proliferation by targeting cellular DNA damage responses. T...
Published in: | Bulletin of Mathematical Biology |
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ISSN: | 0092-8240 1522-9602 |
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Springer Science and Business Media LLC
2021
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URI: | https://cronfa.swan.ac.uk/Record/cronfa57780 |
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2022-10-27T11:29:51.9703191 v2 57780 2021-09-06 Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs 12e5602e8f55d1da67bf35a0a8a51236 SARA HAMIS SARA HAMIS true false f23646a94239f673e2a43ebe7397aabd 0000-0002-8372-7349 Gibin Powathil Gibin Powathil true false 2021-09-06 We combine a systems pharmacology approach with an agent-based modelling approach to simulate LoVo cells subjected to AZD6738, an ATR (ataxia–telangiectasia-mutated and rad3-related kinase) inhibiting anti-cancer drug that can hinder tumour proliferation by targeting cellular DNA damage responses. The agent-based model used in this study is governed by a set of empirically observable rules. By adjusting only the rules when moving between monolayer and multi-cellular tumour spheroid simulations, whilst keeping the fundamental mathematical model and parameters intact, the agent-based model is first parameterised by monolayer in vitro data and is thereafter used to simulate treatment responses in in vitro tumour spheroids subjected to dynamic drug delivery. Spheroid simulations are subsequently compared to in vivo data from xenografts in mice. The spheroid simulations are able to capture the dynamics of in vivo tumour growth and regression for approximately 8 days post-tumour injection. Translating quantitative information between in vitro and in vivo research remains a scientifically and financially challenging step in preclinical drug development processes. However, well-developed in silico tools can be used to facilitate this in vitro to in vivo translation, and in this article, we exemplify how data-driven, agent-based models can be used to bridge the gap between in vitro and in vivo research. We further highlight how agent-based models, that are currently underutilised in pharmaceutical contexts, can be used in preclinical drug development. Journal Article Bulletin of Mathematical Biology 83 10 Springer Science and Business Media LLC 0092-8240 1522-9602 DNA damage response inhibition; Agent-based model; Mathematical oncology; AZD6738 30 8 2021 2021-08-30 10.1007/s11538-021-00935-y COLLEGE NANME COLLEGE CODE Swansea University Other 2022-10-27T11:29:51.9703191 2021-09-06T16:10:48.3808851 Faculty of Science and Engineering School of Mathematics and Computer Science - Mathematics SARA HAMIS 1 James Yates 2 Mark A. J. Chaplain 3 Gibin Powathil 0000-0002-8372-7349 4 57780__20971__2ba9c390591b4c7da96a86464d74b427.pdf 57780.pdf 2021-09-22T16:21:52.3583566 Output 1362268 application/pdf Version of Record true © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License true eng https://creativecommons.org/licenses/by/4.0/ |
title |
Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs |
spellingShingle |
Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs SARA HAMIS Gibin Powathil |
title_short |
Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs |
title_full |
Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs |
title_fullStr |
Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs |
title_full_unstemmed |
Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs |
title_sort |
Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs |
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author |
SARA HAMIS Gibin Powathil |
author2 |
SARA HAMIS James Yates Mark A. J. Chaplain Gibin Powathil |
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Springer Science and Business Media LLC |
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We combine a systems pharmacology approach with an agent-based modelling approach to simulate LoVo cells subjected to AZD6738, an ATR (ataxia–telangiectasia-mutated and rad3-related kinase) inhibiting anti-cancer drug that can hinder tumour proliferation by targeting cellular DNA damage responses. The agent-based model used in this study is governed by a set of empirically observable rules. By adjusting only the rules when moving between monolayer and multi-cellular tumour spheroid simulations, whilst keeping the fundamental mathematical model and parameters intact, the agent-based model is first parameterised by monolayer in vitro data and is thereafter used to simulate treatment responses in in vitro tumour spheroids subjected to dynamic drug delivery. Spheroid simulations are subsequently compared to in vivo data from xenografts in mice. The spheroid simulations are able to capture the dynamics of in vivo tumour growth and regression for approximately 8 days post-tumour injection. Translating quantitative information between in vitro and in vivo research remains a scientifically and financially challenging step in preclinical drug development processes. However, well-developed in silico tools can be used to facilitate this in vitro to in vivo translation, and in this article, we exemplify how data-driven, agent-based models can be used to bridge the gap between in vitro and in vivo research. We further highlight how agent-based models, that are currently underutilised in pharmaceutical contexts, can be used in preclinical drug development. |
published_date |
2021-08-30T20:16:49Z |
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11.047609 |