Prediction of multidimensional drug dose responses based on measurements of drug pairs
Prediction of multidimensional drug dose responses based on measurements of drug pairs
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DOI：
10.1073/pnas.1606301113
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发表时间：
2016-09-13
影响因子：
11.1
通讯作者：
Alon, Uri
中科院分区：
文献类型：
--
作者：
Zimmer, Anat;Katzir, Itay;Alon, Uri
寻找对抗癌症和感染的有效多药组合是一项紧迫的治疗挑战；然而，筛选所有组合是困难的，因为实验数量随着药物数量和剂量的增加而呈指数级增长。为了解决这个问题，我们提出了一个数学模型，它只基于对几个剂量的药物对的测量，而不需要机械信息，就可以预测三种或更多抗生素或抗癌药物在所有剂量下的效果。该模型对抗生素组合的现有数据以及对三种抗癌药物的反应矩阵(每种药物八剂)的实验提供了准确的预测。这种方法提供了一种使用少量实验来搜索有效的多药组合的方法。
Finding potent multidrug combinations against cancer and infections is a pressing therapeutic challenge; however, screening all combinations is difficult because the number of experiments grows exponentially with the number of drugs and doses. To address this, we present a mathematical model that predicts the effects of three or more antibiotics or anticancer drugs at all doses based only on measurements of drug pairs at a few doses, without need for mechanistic information. The model provides accurate predictions on available data for antibiotic combinations, and on experiments presented here on the response matrix of three cancer drugs at eight doses per drug. This approach offers a way to search for effective multidrug combinations using a small number of experiments.