用 T 细胞制造药物:工程化 T 细胞疗法的定量药理学

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Daniel C. Kirouac, Cole Zmurchok, Denise Morris
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引用次数: 0

摘要

工程 T 细胞已成为治疗血液肿瘤的高效疗法。目前正在开展数百项临床计划,努力扩大这种免疫治疗方式的疗效、安全性和应用范围。开发这些 "活体药物 "的一个主要挑战是其药理学的复杂性,因为药物产品会增殖、分化、在组织间流动,并通过与患者免疫系统的相互作用而演变。利用公开的嵌合抗原受体(CAR)T 细胞临床数据,我们展示了如何利用数学模型来量化产品特性、患者生理学、药代动力学和临床结果之间的关系。在科学家们开发下一代细胞疗法产品的过程中,数学模型将成为数据背景化和促进产品设计转化为临床策略不可或缺的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Making drugs from T cells: The quantitative pharmacology of engineered T cell therapeutics

Making drugs from T cells: The quantitative pharmacology of engineered T cell therapeutics

Engineered T cells have emerged as highly effective treatments for hematological cancers. Hundreds of clinical programs are underway in efforts to expand the efficacy, safety, and applications of this immuno-therapeutic modality. A primary challenge in developing these “living drugs” is the complexity of their pharmacology, as the drug product proliferates, differentiates, traffics between tissues, and evolves through interactions with patient immune systems. Using publicly available clinical data from Chimeric Antigen Receptor (CAR) T cells, we demonstrate how mathematical models can be used to quantify the relationships between product characteristics, patient physiology, pharmacokinetics and clinical outcomes. As scientists work to develop next-generation cell therapy products, mathematical models will be integral for contextualizing data and facilitating the translation of product designs to clinical strategy.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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