Follow-on drugs represent the majority of new drug introductions and show improved properties to the pioneer drug. In order to fast-follow, R&D needs to be able to quickly generate a library of analogues that can then be screened for desired properties. Here we have designed a hybrid machine-assisted approach which makes use of both multi-step continuous flow processing and robotic microwave reactors to generate a library of indoles over two technology steps (four reaction steps; diazotization, reduction, unmasking of the hydrazine and Fischer indole reaction). This ‘machine’ is then used to prepare a small library of hitherto unreported analogues of the 5-HT agonist Zolmitriptan in good yields, thus demonstrating that the integration and use of machines is a powerful tool to expedite drug discovery.

中文翻译：

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一种机器辅助方法，用于制备后续药物化合物库†

后续药物代表了大多数新药物的引进，并显示出对先驱药物的改良特性。为了快速跟进，R＆D需要能够快速生成类似物库，然后可以针对所需性质对其进行筛选。在这里，我们设计了一种混合的机器辅助方法，该方法利用多步连续流处理和机器人微波反应器，通过两个技术步骤（四个反应步骤；重氮化，还原，肼和费歇尔的掩蔽）生成吲哚库。吲哚反应）。然后，该“机器”用于以良好的产率制备5-HT激动剂佐米曲普坦迄今未报道的类似物的小文库，从而证明了机器的集成和使用是加快药物发现的强大工具。