Drug combinations are a promising strategy to overcome the compensatory mechanisms and unwanted off-target effects that limit the utility of many potential drugs. However, enthusiasm for this approach is tempered by concerns that the therapeutic synergy of a combination will be accompanied by synergistic side effects. Using large scale simulations of bacterial metabolism and 94,110 multi-dose experiments relevant to diverse diseases, we provide evidence that synergistic drug combinations are generally more specific to particular cellular contexts than are single agent activities. We highlight six combinations whose selective synergy depends on multitarget drug activity. For one anti-inflammatory example, we show how such selectivity is achieved through differential expression of the drugs' targets in cell types associated with therapeutic, but not toxic, effects and validate its therapeutic relevance in a rat model of asthma. The context specificity of synergistic combinations creates many opportunities for therapeutically relevant selectivity and enables improved control of complex biological systems.
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The authors are grateful to many people at CombinatoRx who provided technical materials for this paper. We also thank T. Golub and F. Roth for comments on the manuscript. The simulations were performed using Boston University's computing facilities. Antiviral research was conducted in collaboration with CombinatoRx Singapore, funded by the Singapore Economic Development Board. Anthrax studies were funded through the National Institutes of Health/National Institute of Allergy and Infectious Diseases under grant U01 AI61345. Cardiovascular screens were done in collaboration with Angiotech. Huntington's disease experiments were done in collaboration with and funded by the CHDI Foundation. MM.1R and MM.1S were kindly provided by S. Rosen, Northwestern University.
All of the authors are currently, or were previously, employed by CombinatoRx, Inc.
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