Due to the heap of data sets available for drug discovery, modern drug discovery has taken the shape of big data. Usage of Artificial intelligence (AI) can help to modify drug discovery based on big data to precised, knowledgeable data. The pharmaceutical companies have already geared their departments for this and started a race to search for new novel drugs. The AI helps to predict the molecular structure of the compound and its in-vivo vs. in-vitro characteristics without hampering life, thus saving time and economic loss. Clinical studies, electronic records, and images act as a helping hand for the development. The data mining and curation techniques help explore the data with a single click. AI in big data analysis has paved the red carpet for future rational drug development and optimization. This review's objective is to familiarise readers with various advances in the AI field concerning software, firms, and other tools working in easing out the labor of the drug discovery journey.

中文翻译：

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人工智能在药物发现中的应用。

由于可用于药物发现的大量数据集，现代药物发现已采用大数据的形式。人工智能 (AI) 的使用可以帮助将基于大数据的药物发现修改为精确的、知识渊博的数据。制药公司已经为此调整了他们的部门，并开始了寻找新药的竞赛。人工智能有助于在不影响生命的情况下预测化合物的分子结构及其体内与体外特性，从而节省时间和经济损失。临床研究、电子记录和图像为开发提供了帮助。数据挖掘和管理技术有助于通过一次单击探索数据。大数据分析中的人工智能为未来的合理药物开发和优化铺平了红地毯。这篇评论'