Over the last decade, increasing interest has been attracted towards the application of artificial intelligence (AI) technology for analyzing and interpreting the biological or genetic information, accelerated drug discovery, and identification of the selective small-molecule modulators or rare molecules and prediction of their behavior. Application of the automated workflows and databases for rapid analysis of the huge amounts of data and artificial neural networks (ANNs) for development of the novel hypotheses and treatment strategies, prediction of disease progression, and evaluation of the pharmacological profiles of drug candidates may significantly improve treatment outcomes. Target fishing (TF) by rapid prediction or identification of the biological targets might be of great help for linking targets to the novel compounds. AI and TF methods in association with human expertise may indeed revolutionize the current theranostic strategies, meanwhile, validation approaches are necessary to overcome the potential challenges and ensure higher accuracy. In this review, the significance of AI and TF in the development of drugs and delivery systems and the potential challenging issues have been highlighted.

在过去的十年中，越来越多的兴趣吸引着人工智能（AI）技术用于分析和解释生物或遗传信息，加速药物发现以及选择性小分子调节剂或稀有分子的鉴定及其预测的兴趣。行为。自动化工作流程和数据库用于大量数据的快速分析的应用以及人工神经网络（ANN）用于开发新的假设和治疗策略，预测疾病进展以及评估候选药物的药理学特征的应用可能会大大改善治疗结果。通过快速预测或鉴定生物靶标进行靶标捕捞（TF），可能对将靶标与新型化合物联系起来有很大帮助。AI和TF与人类专业知识相结合的方法确实可能会彻底改变当前的诊断方法，同时，验证方法对于克服潜在的挑战并确保更高的准确性是必不可少的。在这篇综述中，强调了AI和TF在药物和给药系统开发中的重要性以及潜在的挑战性问题。