Unifying principles of multi-drug resistance
Drugs combinations are commonly employed in the treatment of severe infections. Unfortunately, it is generally impossible to infer the net effect of a multi-drug combination directly from the effects of individual drugs. We are combining experiments with tools from statistical physics to explore how drug interactions accumulate as the number of drugs increases. Surprisingly, we have found that the effects of drug pairs are sufficient to predict the effects of larger drug combinations on growth in E. coli and S. aureus. This work was published in PNAS. We are currently extending this approach to multiple types of human cancer cells and plan to explore its utility for the systematic development of potent multi-drug therapies.
This project is the work of former postdoctoral fellow Kevin Wood, in collaboration with Satoshi Nishida. Rotation student Bryan Weinstein is extending this general approach to multi-cellular tumors.