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早期药物研发中安全风险量化的系统建模:以分岔分析和基于主体的建模为例

Systems Modeling to Quantify Safety Risks in Early Drug Development: Using Bifurcation Analysis and Agent-Based Modeling as Examples.

作者信息

Pin Carmen, Collins Teresa, Gibbs Megan, Kimko Holly

机构信息

Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge Science Park, Milton Road, Cambridge, UK.

Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Gaithersburg, Maryland, USA.

出版信息

AAPS J. 2021 May 20;23(4):77. doi: 10.1208/s12248-021-00580-2.

Abstract

Quantitative Systems Toxicology (QST) models, recapitulating pharmacokinetics and mechanism of action together with the organic response at multiple levels of biological organization, can provide predictions on the magnitude of injury and recovery dynamics to support study design and decision-making during drug development. Here, we highlight the application of QST models to predict toxicities of cancer treatments, such as cytopenia(s) and gastrointestinal adverse effects, where narrow therapeutic indexes need to be actively managed. The importance of bifurcation analysis is demonstrated in QST models of hematologic toxicity to understand how different regions of the parameter space generate different behaviors following cancer treatment, which results in asymptotically stable predictions, yet highly irregular for specific schedules, or oscillating predictions of blood cell levels. In addition, an agent-based model of the intestinal crypt was used to simulate how the spatial location of the injury within the crypt affects the villus disruption severity. We discuss the value of QST modeling approaches to support drug development and how they align with technological advances impacting trial design including patient selection, dose/regimen selection, and ultimately patient safety.

摘要

定量系统毒理学(QST)模型能够概括药物动力学和作用机制,以及生物组织多个层面的机体反应,可预测损伤程度和恢复动态,以支持药物研发过程中的研究设计和决策制定。在此,我们重点介绍QST模型在预测癌症治疗毒性方面的应用,如血细胞减少和胃肠道不良反应,对于这些情况需要积极管理狭窄的治疗指数。在血液学毒性的QST模型中,通过分叉分析来理解参数空间的不同区域在癌症治疗后如何产生不同的行为,这会导致渐近稳定的预测,但对于特定方案来说却极不规则,或者会产生血细胞水平的振荡预测。此外,还使用了基于主体的肠隐窝模型来模拟隐窝内损伤的空间位置如何影响绒毛破坏的严重程度。我们讨论了QST建模方法对支持药物研发的价值,以及它们如何与影响试验设计的技术进步保持一致,这些技术进步包括患者选择、剂量/方案选择以及最终的患者安全。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1572/8137611/58f0017b6229/12248_2021_580_Fig1_HTML.jpg

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