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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.

作者:Anat, Zimmer;Itay, Katzir;Erez, Dekel;Avraham E, Mayo;Uri, Alon

来源:Proceedings of the National Academy of Sciences of the United States of America 2016 年 113卷 37期

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作者:
Anat, Zimmer;Itay, Katzir;Erez, Dekel;Avraham E, Mayo;Uri, Alon
来源:
Proceedings of the National Academy of Sciences of the United States of America 2016 年 113卷 37期
标签:
cancer treatment drug cocktails drug combinations mechanism-free formula predictive formula
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.