In recent years there has been a paradigm shift in how data is being used to progress early drug discovery campaigns from hit identification to candidate selection. Significant developments in data mining methods and the accessibility of tools for research scientists have been instrumental in reducing drug discovery timelines and in increasing the likelihood of a chemical entity achieving drug development milestones. KNIME, the Konstanz Information Miner, is a leading open source data analytics platform and has supported drug discovery endeavours for over a decade. KNIME provides a rich palette of tools supported by an extensive community of contributors to enable ligandand structure-based drug design. This review will examine recent developments within the KNIME platform to support small-molecule drug design and provide a perspective on the challenges and future developments within this field.

近年来，在如何使用数据来进行早期药物发现活动方面，从命中识别到候选人选择发生了范式转变。数据挖掘方法的显着发展以及研究科学家工具的可访问性在减少药物发现时间表和增加化学实体实现药物开发里程碑的可能性方面发挥了作用。Konstanz Information Miner KNIME是领先的开源数据分析平台，在过去十年中一直支持药物发现工作。KNIME提供了丰富的工具面板，并得到了广泛的贡献者社区的支持，以实现基于配体和结构的药物设计。