Current Methods for Quantifying Drug Synergism.

Proteomics & bioinformatics : current research Pub Date : 2019-07-01 Epub Date: 2019-07-22
Jun Ma, Alison Motsinger-Reif
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Abstract

The effectiveness of drug combinations for treatment of a variety of complex diseases is well established. "Drug cocktail" treatments are often prescribed to improve the overall efficacy, decrease toxicity, alter pharmacodynamics, etc in an overall treatment strategy. Specifically, if when combined, drugs interact in some way that causes the total effect to be greater than that predicted by their individual potencies, then drugs are considered synergistic. While there are established ways to quantify the impact of drug combinations clinically, it is an open challenge to quantitatively summarize a synergistic interaction. In this paper, we discuss an overview of the current statistical and mathematical methods for the study of drug combination effects, especially drug synergy quantification (where the interaction effect is not just detected, but quantified according to its magnitude). We first introduce two popular reference models for testing to null hypothesis of non-interaction for a combination, including the Bliss independence model and the Loewe additivity model. Then we discuss several methods for quantifying drug synergism. The advantages and disadvantages with these methods are also provided, and finally, we discuss important next directions in this area.

Abstract Image

Abstract Image

定量药物协同作用的现有方法。
药物联合治疗多种复杂疾病的有效性已得到充分证实。在整体治疗策略中,“鸡尾酒药物”治疗通常是为了提高整体疗效、降低毒性、改变药效学等。具体来说,如果药物联合使用时,以某种方式相互作用,导致总效果大于其单独效力的预测,那么药物被认为是协同作用的。虽然有既定的方法来量化临床药物组合的影响,但量化总结协同相互作用是一个公开的挑战。在本文中,我们概述了目前用于研究药物联合效应的统计和数学方法,特别是药物协同量化(其中不仅检测相互作用效应,而且根据其大小进行量化)。本文首先介绍了两种常用的检验组合非相互作用零假设的参考模型,即Bliss独立模型和Loewe可加性模型。然后讨论了几种量化药物协同作用的方法。并对这些方法的优缺点进行了分析,最后讨论了该领域今后的发展方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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