Curve Ball (Sorger)

New approaches, surprising results challenge fundamental principle of drug discovery

After analyzing hundreds of interactions between cancer drugs and cancer cells using information theory and advanced modeling techniques, Harvard Medical School researchers have found that a standard model for predicting drug effectiveness is incomplete and potentially misleading.

The findings, published recently in Nature Chemical Biology, could have implications for directing billions of dollars of drug research in a way that will rule out drugs unlikely to be effective in the clinic and highlight potentially useful drugs that the traditional standard would miss. The techniques suggested by the findings could also potentially help identify combination therapies that would boost the performance of under-achieving drugs and help clinicians maximize effectiveness without undue side effects.

“The results of this study are a small but significant step toward a new understanding of therapeutics,” said senior author Peter Sorger, the Otto Krayer Professor of Systems Pharmacology and head of the HMS Program in Therapeutic Science.