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Updated: Oct 18, 2025

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Deep learning in retrosynthesis planning: datasets, models and tools
Jingxin Dong1, Mingyi Zhao2, Yuansheng Liu1
1College of Information Science and Engineering, Hunan University, 2 Lushan S Rd, Yuelu District, 410086, Hunan, China.
Abstract:
In recent years, synthesizing drugs powered by artificial intelligence has brought great convenience to society. Since retrosynthetic analysis occupies an essential position in synthetic chemistry, it has received broad attention from researchers. In this review, we comprehensively summarize the development process of retrosynthesis in the context of deep learning. This review covers all aspects of retrosynthesis, including datasets, models and tools. Specifically, we report representative models from academia, in addition to a detailed description of the available and stable platforms in the industry. We also discuss the disadvantages of the existing models and provide potential future trends, so that more abecedarians will quickly understand and participate in the family of retrosynthesis planning.
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