Abbas M K G, Rassam Abrar, Karamshahi Fatima, Abunora Rehab, Abouseada Maha
Center for Advanced Materials, Qatar University, P.O. Box, 2713, Doha, Qatar.
Secondary Education, Educational Sciences, Qatar University, P.O. Box, 2713, Doha, Qatar.
Chembiochem. 2024 Jul 15;25(14):e202300816. doi: 10.1002/cbic.202300816. Epub 2024 Jun 26.
The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in pharmaceutical research, blending sophisticated computational techniques with conventional scientific exploration to break through enduring obstacles. This review paper elucidates the multifaceted applications of AI across various stages of drug development, highlighting significant advancements and methodologies. It delves into AI's instrumental role in drug design, polypharmacology, chemical synthesis, drug repurposing, and the prediction of drug properties such as toxicity, bioactivity, and physicochemical characteristics. Despite AI's promising advancements, the paper also addresses the challenges and limitations encountered in the field, including data quality, generalizability, computational demands, and ethical considerations. By offering a comprehensive overview of AI's role in drug discovery, this paper underscores the technology's potential to significantly enhance drug development, while also acknowledging the hurdles that must be overcome to fully realize its benefits.
人工智能(AI)在药物发现领域的出现标志着制药研究的一个关键转变,它将复杂的计算技术与传统科学探索相结合,以突破长期存在的障碍。这篇综述文章阐明了AI在药物开发各个阶段的多方面应用,突出了重大进展和方法。它深入探讨了AI在药物设计、多药理学、化学合成、药物再利用以及药物性质预测(如毒性、生物活性和物理化学特性)中的重要作用。尽管AI取得了令人鼓舞的进展,但本文也讨论了该领域遇到的挑战和局限性,包括数据质量、通用性、计算需求和伦理考量。通过全面概述AI在药物发现中的作用,本文强调了该技术显著增强药物开发的潜力,同时也认识到要充分实现其益处必须克服的障碍。