Combinatorial drug treatment strategies perturb biological networks synergistically to achieve therapeutic effects and represent major opportunities to develop advanced treatments across a variety of human disease areas. However, the discovery of new combinatorial treatments is challenged by the sheer scale of combinatorial chemical space. Here, we report a high-throughput system for nanoliter-scale phenotypic screening that formulates a chemical library in nanoliter droplet emulsions and automates the construction of chemical combinations en masse using parallel droplet processing. We applied this system to predict synergy between more than 4,000 investigational and approved drugs and a panel of 10 antibiotics against Escherichia coli, a model gram-negative pathogen. We found a range of drugs not previously indicated for infectious disease that synergize with antibiotics. Our validated hits include drugs that synergize with the antibiotics vancomycin, erythromycin, and novobiocin, which are used against gram-positive bacteria but are not effective by themselves to resolve gram-negative infections.

组合药物治疗策略可协同干扰生物网络以实现治疗效果，并为开发跨多种人类疾病领域的先进治疗方法提供了重大机遇。然而，新的组合疗法的发现受到组合化学空间的巨大规模的挑战。在这里，我们报告了一种用于纳升级表型筛选的高通量系统，该系统可在纳升微滴乳剂中配制化学文库，并使用并行微滴处理技术自动构建大量化学组合。我们应用该系统预测了4,000多种研究和批准的药物与10种针对大肠杆菌的抗生素之间的协同作用，是一种革兰氏阴性病原体。我们发现了以前没有针对感染性疾病的与抗生素协同作用的一系列药物。我们经过验证的热门产品包括与万古霉素，红霉素和新霉素等抗生素协同作用的药物，这些药物可用于革兰氏阳性细菌，但本身不能有效解决革兰氏阴性感染。