机器学习在癌症药物联合治疗中的应用。
Machine Learning for Cancer Drug Combination.
机构信息
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
出版信息
Clin Pharmacol Ther. 2020 Apr;107(4):749-752. doi: 10.1002/cpt.1773. Epub 2020 Feb 11.
Abstract
When treating multiple complex diseases, such as cancer, polytherapy may demonstrate efficiency than monotherapy. However, due to the multiplicative relationship between the number of drugs and cell lines vs. the number of combinations, it is impractical to test all drug combinations using high-throughput preclinical approaches. An alternative to experimental tests is predicting drug synergy through computational models. Here, we summarize recent computational approaches for predicting drug synergy, discuss current limitations, and propose future directions.
摘要
在治疗多种复杂疾病（如癌症）时，联合治疗可能比单药治疗更有效。然而，由于药物数量与细胞系数量与组合数量之间呈乘法关系，使用高通量临床前方法测试所有药物组合是不切实际的。实验测试的替代方法是通过计算模型预测药物协同作用。在这里，我们总结了最近用于预测药物协同作用的计算方法，讨论了当前的局限性，并提出了未来的方向。
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