A Consensus Framework Unifies Multi-Drug Synergy Metrics

A Consensus Framework Unifies Multi-Drug Synergy Metrics
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统一多药协同指标的共识框架

DOI:
10.1101/683433
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发表时间:
2019
期刊:
bioRxiv
影响因子:
--
通讯作者:
Carlos F. Lopez
Carlos F. Lopez
中科院分区:
--
文献类型:
--
作者:
David J. Wooten;Christian T. Meyer;V. Quaranta;Carlos F. Lopez

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药物组合的发现依赖于可靠的协同作用指标;然而,没有共识存在于适当的协同作用模型,以优先考虑领先的候选人。该领域的分散状态混淆了组合的分析、再现性和临床转化。在这里,我们提出了一个大规模的行动为基础的形式主义,以准确地衡量药物组合的协同作用。在这项工作中,我们澄清了占主导地位的药物协同作用的原则之间的关系,并显示如何出现偏见,由于内在的假设,阻碍了其广泛的适用性。我们进一步提出了一个映射到一个统一的协同景观,它确定了影响协同发现工作的解释基本问题的常用框架。具体来说,我们推断传统的指标如何掩盖相应的协同作用,并包含依赖于希尔斜率和最大效果的单一药物的偏见。我们展示了这些偏见如何系统地影响大组合筛选误导发现工作的协同分类。所提出的方法有可能加速药物协同作用研究的可翻译性和再现性,通过弥合药物混合物的治疗潜力和研究复杂性之间的差距。
Drug combination discovery depends on reliable synergy metrics; however, no consensus exists on the appropriate synergy model to prioritize lead candidates. The fragmented state of the field confounds analysis, reproducibility, and clinical translation of combinations. Here we present a mass-action based formalism to accurately measure the synergy of drug combinations. In this work, we clarify the relationship between the dominant drug synergy principles and show how biases emerge due to intrinsic assumptions which hinder their broad applicability. We further present a mapping of commonly used frameworks onto a unified synergy landscape, which identifies fundamental issues impacting the interpretation of synergy in discovery efforts. Specifically, we infer how traditional metrics mask consequential synergistic interactions, and contain biases dependent on the Hill-slope and maximal effect of single-drugs. We show how these biases systematically impact the classification of synergy in large combination screens misleading discovery efforts. The proposed approach has potential to accelerate the translatability and reproducibility of drug-synergy studies, by bridging the gap between the curative potential of drug mixtures and the complexity in their study.
DOI: --
发表时间: 1995-06
影响因子: 21.1
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影响因子: 14.8
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DOI: 10.1016/j.cels.2019.01.003
发表时间: 2019-02-27
期刊: CELL SYSTEMS
影响因子: 9.3
作者:
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发表时间: 1981-01-01
期刊: EUROPEAN JOURNAL OF BIOCHEMISTRY
影响因子: --
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