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.
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