Itay Katzir - Poster of BC2 .pdf

Finding potent multi-drug combinations against cancer and bacterial 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 recently developed a mathematical model which predicts the effects of three or more antibiotics or anti-cancer 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 previous data for up to four antibiotic combinations, and on experiments on the response matrix of three cancer drugs at eight doses per drug.

To further test the model beyond four drugs and for clinically relevant pathogens, we performed experiments on drug combinations at multiple doses in two organisms: E. coli and M. tuberculosis. We measured all 45 pair combinations of ten drugs in E. coli and M. tuberculosis, and tested predictions for combinations of three to five drugs. We find that the dose model works well in both E. coli and M. tuberculosis. We also use the model to find new synergistic combinations of three to five drugs for M. tuberculosis.