Network Biology & Drug Discovery Department, Pharnext, 11 rue René Jacques, 92130 Issy-les-Moulineaux, France.
Data Science Department, Pharnext, 11 rue René Jacques, 92130 Issy-les-Moulineaux, France.
Curr Opin Pharmacol. 2020 Apr;51:78-92. doi: 10.1016/j.coph.2019.12.004. Epub 2020 Jan 22.
Drug repurposing has attracted increased attention, especially in the context of drug discovery rates that remain too low despite a recent wave of approvals for biological therapeutics (e.g. gene therapy). These new biological entities-based treatments have high costs that are difficult to justify for small markets that include rare diseases. Drug repurposing, involving the identification of single or combinations of existing drugs based on human genetics data and network biology approaches represents a next-generation approach that has the potential to increase the speed of drug discovery at a lower cost. This Pharmacological Perspective reviews progress and perspectives in combining human genetics, especially genome-wide association studies, with network biology to drive drug repurposing for rare and common diseases with monogenic or polygenic etiologies. Also, highlighted here are important features of this next generation approach to drug repurposing, which can be combined with machine learning methods to meet the challenges of personalized medicine.
药物重定位引起了越来越多的关注，特别是在药物发现率仍然很低的情况下，尽管最近批准了许多生物疗法（例如基因疗法）。这些基于新生物实体的治疗方法成本高昂，对于包括罕见病在内的小市场来说，难以证明其合理性。药物重定位涉及根据人类遗传学数据和网络生物学方法识别单个或组合现有药物，代表了一种下一代方法，有可能以更低的成本提高药物发现的速度。本药理学观点综述了将人类遗传学（特别是全基因组关联研究）与网络生物学相结合以推动单基因或多基因病因的罕见和常见疾病药物重定位的进展和观点。此外，这里还突出了这种下一代药物重定位方法的重要特征，它可以与机器学习方法相结合，以应对个性化医疗的挑战。
