Fillinger Lucas, Walter Samuel, Ley Matthias, Kęska-Izworska Kinga, Dehkordi Leily Ghasemi, Kratochwill Klaus, Perco Paul
Delta4 GmbH, Vienna, Austria.
Delta4 GmbH, Vienna, Austria.
Drug Discov Today. 2025 May;30(5):104345. doi: 10.1016/j.drudis.2025.104345. Epub 2025 Mar 28.
Drug combinations offer several advantages over monotherapies, but identifying effective drug combinations while avoiding adverse effects is a major challenge. Computational network models are particularly useful for identifying mechanistically compatible drug combinations and generating hypotheses about their mechanisms of action. Here, we discuss the advantages and challenges of in silico discovery approaches for drug combinations. Obtaining regulatory approval during later stages of product development can be more complex for drug combinations than for single drugs. The regulatory pathway is mainly determined by the approval status of the individual compounds included in a combination. We provide an overview of the regulatory guidelines for drug combination development and discuss trends from previous approvals.
与单一疗法相比,联合用药具有多个优势,但在避免不良反应的同时识别有效的联合用药方案是一项重大挑战。计算网络模型对于识别机制上兼容的联合用药方案并生成其作用机制的假设尤为有用。在此,我们讨论用于联合用药的计算机模拟发现方法的优势和挑战。在产品开发的后期阶段,联合用药获得监管批准可能比单一药物更为复杂。监管途径主要由联合用药中所含各个化合物的批准状态决定。我们概述了联合用药开发的监管指南,并讨论了以往批准情况的趋势。