Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs.
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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DOI：
10.1007/s11538-021-00935-y
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发表时间：
2021-08-30
影响因子：
3.5
通讯作者：
Powathil GG
中科院分区：
文献类型：
--
作者：
Hamis S;Yates J;Chaplain MAJ;Powathil GG
我们将系统药理学方法与基于代理的建模方法相结合，模拟接受 AZD6738 处理的 LoVo 细胞，AZD6738 是一种 ATR（共济失调毛细血管扩张突变和 rad3 相关激酶）抑制抗癌药物，可通过靶向细胞 DNA 损伤反应来阻碍肿瘤增殖。本研究中使用的基于主体的模型受一组经验可观察规则的约束。通过仅调整在单层和多细胞肿瘤球体模拟之间移动时的规则，同时保持基本数学模型和参数完整，基于代理的模型首先通过单层体外数据进行参数化，然后用于模拟动态药物递送的体外肿瘤球体中的治疗反应。随后将球体模拟与小鼠异种移植物的体内数据进行比较。球体模拟能够捕捉肿瘤注射后约 8 天的体内肿瘤生长和消退的动态。在体外和体内研究之间转换定量信息仍然是临床前药物开发过程中在科学和经济上具有挑战性的一步。然而，成熟的计算机工具可用于促进体外到体内的转化，在本文中，我们举例说明了如何使用数据驱动、基于代理的模型来弥合体外和体内研究之间的差距。我们进一步强调了目前在制药领域尚未充分利用的基于代理的模型如何用于临床前药物开发。在线版本补充材料可在 10.1007/s11538-021-00935-y 获取。
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. The online version supplementary material available at 10.1007/s11538-021-00935-y.
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DOI：
10.1098/rsif.2017.0681
发表时间：
2018-01
期刊：
Journal of the Royal Society, Interface
影响因子：
--
作者：
Brüningk S;Powathil G;Ziegenhein P;Ijaz J;Rivens I;Nill S;Chaplain M;Oelfke U;Ter Haar G
通讯作者：
Ter Haar G
影响因子：
4.6
作者：
Checkley, Stephen;MacCallum, Linda;Bendtsen, Claus
通讯作者：
Bendtsen, Claus
影响因子：
7.3
作者：
Foote, Kevin M.;Nissink, J. Willem M.;Jewsbury, Philip J.
通讯作者：
Jewsbury, Philip J.
影响因子：
16.6
作者：
Brady-Nicholls, Renee;Nagy, John D.;Enderling, Heiko
通讯作者：
Enderling, Heiko
影响因子：
4.3
作者：
Hamis, Sara;Kohandel, Mohammad;Powathil, Gibin G.
通讯作者：
Powathil, Gibin G.