Suppr超能文献

支持免疫肿瘤学中药理学治疗开发的定量机制建模。

Quantitative Mechanistic Modeling in Support of Pharmacological Therapeutics Development in Immuno-Oncology.

机构信息

M&S Decisions, Moscow, Russia.

Computational Oncology Group, I.M. Sechenov First Moscow State Medical University of the Russian Ministry of Health, Moscow, Russia.

出版信息

Front Immunol. 2019 Apr 30;10:924. doi: 10.3389/fimmu.2019.00924. eCollection 2019.

Abstract

Following the approval, in recent years, of the first immune checkpoint inhibitor, there has been an explosion in the development of immuno-modulating pharmacological modalities for the treatment of various cancers. From the discovery phase to late-stage clinical testing and regulatory approval, challenges in the development of immuno-oncology (IO) drugs are multi-fold and complex. In the preclinical setting, the multiplicity of potential drug targets around immune checkpoints, the growing list of immuno-modulatory molecular and cellular forces in the tumor microenvironment-with additional opportunities for IO drug targets, the emergence of exploratory biomarkers, and the unleashed potential of modality combinations all have necessitated the development of quantitative, mechanistically-oriented systems models which incorporate key biology and patho-physiology aspects of immuno-oncology and the pharmacokinetics of IO-modulating agents. In the clinical setting, the qualification of surrogate biomarkers predictive of IO treatment efficacy or outcome, and the corresponding optimization of IO trial design have become major challenges. This mini-review focuses on the evolution and state-of-the-art of quantitative systems models describing the tumor vs. immune system interplay, and their merging with quantitative pharmacology models of IO-modulating agents, as companion tools to support the addressing of these challenges.

摘要

近年来,随着首个免疫检查点抑制剂的批准,用于治疗各种癌症的免疫调节药理模式的发展呈爆炸式增长。从发现阶段到晚期临床测试和监管批准,免疫肿瘤学 (IO) 药物的开发面临着多方面的挑战,这些挑战既复杂又多样。在临床前环境中,免疫检查点周围潜在药物靶点的多样性、肿瘤微环境中不断增加的免疫调节分子和细胞力量——为 IO 药物靶点提供了更多机会、探索性生物标志物的出现以及各种模式组合的潜力释放,都需要开发定量、基于机制的系统模型,这些模型纳入了免疫肿瘤学的关键生物学和病理生理学方面以及 IO 调节药物的药代动力学。在临床环境中,预测 IO 治疗疗效或结果的替代生物标志物的资格认证,以及 IO 试验设计的相应优化,已成为主要挑战。本篇迷你综述重点介绍了描述肿瘤与免疫系统相互作用的定量系统模型的演变和最新进展,以及它们与 IO 调节药物的定量药理学模型的融合,作为支持解决这些挑战的辅助工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eba1/6524731/b775c9997441/fimmu-10-00924-g0001.jpg

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