Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Sci Transl Med. 2013 Oct 9;5(206):206ra140. doi: 10.1126/scitranslmed.3006548.
Drugs are designed for therapy, but medication-related adverse events are common, and risk/benefit analysis is critical for determining clinical use. Rosiglitazone, an efficacious antidiabetic drug, is associated with increased myocardial infarctions (MIs), thus limiting its usage. Because diabetic patients are often prescribed multiple drugs, we searched for usage of a second drug ("drug B") in the Food and Drug Administration's Adverse Event Reporting System (FAERS) that could mitigate the risk of rosiglitazone ("drug A")-associated MI. In FAERS, rosiglitazone usage is associated with increased occurrence of MI, but its combination with exenatide significantly reduces rosiglitazone-associated MI. Clinical data from the Mount Sinai Data Warehouse support the observations from FAERS. Analysis for confounding factors using logistic regression showed that they were not responsible for the observed effect. Using cell biological networks, we predicted that the mitigating effect of exenatide on rosiglitazone-associated MI could occur through clotting regulation. Data we obtained from the db/db mouse model agreed with the network prediction. To determine whether polypharmacology could generally be a basis for adverse event mitigation, we analyzed the FAERS database for other drug combinations wherein drug B reduced serious adverse events reported with drug A usage such as anaphylactic shock and suicidality. This analysis revealed 19,133 combinations that could be further studied. We conclude that this type of crowdsourced approach of using databases like FAERS can help to identify drugs that could potentially be repurposed for mitigation of serious adverse events.
药物旨在治疗疾病，但药物相关的不良反应很常见，风险/效益分析对于确定临床应用至关重要。罗格列酮是一种有效的抗糖尿病药物，但与心肌梗死（MI）风险增加有关，因此限制了其应用。由于糖尿病患者常同时服用多种药物，我们在食品和药物管理局的不良事件报告系统（FAERS）中搜索了一种可降低罗格列酮（“药物 A”）相关 MI 风险的第二种药物（“药物 B”）的使用情况。在 FAERS 中，罗格列酮的使用与 MI 发生率的增加有关，但与艾塞那肽联合使用可显著降低罗格列酮相关的 MI。西奈山数据仓库的临床数据支持 FAERS 的观察结果。使用逻辑回归进行混杂因素分析表明，这些因素不是导致观察到的效果的原因。使用细胞生物学网络，我们预测艾塞那肽对罗格列酮相关 MI 的缓解作用可能是通过凝血调节发生的。我们从 db/db 小鼠模型获得的数据与网络预测一致。为了确定多药理学是否可以作为减轻不良反应的一般基础，我们分析了 FAERS 数据库中其他药物组合，其中药物 B 降低了与药物 A 一起使用时报告的严重不良事件，如过敏反应和自杀倾向。这项分析揭示了 19,133 种可能进一步研究的组合。我们得出结论，这种使用 FAERS 等数据库的众包方法可以帮助识别可能被重新用于减轻严重不良反应的药物。
