Acute myeloid leukemia (AML), a heterogeneous and aggressive blood cancer, does not respond well to single-drug therapy. A combination of drugs is required to effectively treat this disease. Computational models are critical for combination therapy discovery due to the tens of thousands of two-drug combinations, even with approved drugs. While predicting synergistic drugs is the focus of current methods, few consider drug efficacy and potential toxicity, which are crucial for treatment success. To find effective new drug candidates, we constructed a bipartite network using patient-derived tumor samples and drugs. The network is based on drug-response screening and summarizes all treatment response heterogeneity as drug response weights. This bipartite network is then projected onto the drug part, resulting in the drug similarity network. Distinct drug clusters were identified using community detection methods, each targeting different biological processes and pathways as revealed by enrichment and pathway analysis of the drugs’ protein targets. Four drugs with the highest efficacy and lowest toxicity from each cluster were selected and tested for drug sensitivity using cell viability assays on various samples. Results show that ruxolitinib-ulixertinib and sapanisertib-LY3009120 are the most effective combinations with the least toxicity and the best synergistic effect on blast cells. These findings lay the foundation for personalized and successful AML therapies, ultimately leading to the development of drug combinations that can be used alongside standard first-line AML treatment.

急性髓系白血病 (AML) 是一种异质性侵袭性血癌，对单一药物治疗的反应不佳。需要联合药物才能有效治疗这种疾病。由于存在数以万计的两种药物组合，即使是已批准的药物，计算模型对于联合疗法的发现至关重要。虽然预测协同药物是当前方法的重点，但很少考虑药物疗效和潜在毒性，而这对于治疗成功至关重要。为了寻找有效的新候选药物，我们使用患者来源的肿瘤样本和药物构建了一个二分网络。该网络基于药物反应筛选，并将所有治疗反应异质性总结为药物反应权重。然后将该二分网络投影到药物部分，形成药物相似性网络。使用群落检测方法鉴定了不同的药物簇，每个药物簇都针对不同的生物过程和途径，如药物蛋白质靶点的富集和途径分析所揭示的。从每个簇中选择四种具有最高功效和最低毒性的药物，并使用各种样品的细胞活力测定来测试药物敏感性。结果表明，ruxolitinib-ulixertinib和sapanisertib-LY3009120是最有效的组合，毒性最小，对母细胞的协同作用最好。这些发现为个性化和成功的 AML 治疗奠定了基础，最终导致可与标准一线 AML 治疗一起使用的药物组合的开发。