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临床肿瘤学中预测药物反应的建模方法综述

A Review of Modeling Approaches to Predict Drug Response in Clinical Oncology.

作者信息

Park Kyungsoo

机构信息

Department of Pharmacology, Yonsei University College of Medicine, Seoul, Korea.

出版信息

Yonsei Med J. 2017 Jan;58(1):1-8. doi: 10.3349/ymj.2017.58.1.1.

Abstract

Model-based approaches have emerged as important tools for quantitatively understanding temporal relationships between drug dose, concentration, and effect over the course of treatment, and have now become central to optimal drug development and tailored drug treatment. In oncology, the therapeutic index of a chemotherapeutic drug is typically narrow and a full dose-response relationship is not available, often because of treatment failure. Noting the benefits of model-based approaches and the low therapeutic index of oncology drugs, in recent years, modeling approaches have been increasingly used to streamline oncologic drug development through early identification and quantification of dose-response relationships. With this background, this report reviews publications that used model-based approaches to evaluate drug treatment outcome variables in oncology therapeutics, ranging from tumor size dynamics to tumor/biomarker time courses and survival response.

摘要

基于模型的方法已成为定量理解治疗过程中药物剂量、浓度和效应之间时间关系的重要工具,如今已成为优化药物开发和个性化药物治疗的核心。在肿瘤学中,化疗药物的治疗指数通常较窄,而且往往由于治疗失败而无法获得完整的剂量-反应关系。鉴于基于模型的方法的优势以及肿瘤学药物较低的治疗指数,近年来,建模方法越来越多地用于通过早期识别和量化剂量-反应关系来简化肿瘤学药物开发。在此背景下,本报告回顾了使用基于模型的方法评估肿瘤学治疗中药物治疗结果变量的出版物,这些变量涵盖从肿瘤大小动态变化到肿瘤/生物标志物时间进程以及生存反应等方面。

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