Department of Pharmaceutics, St. John Institute of Pharmacy and Research, Palghar, Maharashtra, 401404, India.
Department of Pharmaceutical Technology, Faculty of Pharmacy, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
Comput Biol Med. 2024 Aug;178:108702. doi: 10.1016/j.compbiomed.2024.108702. Epub 2024 Jun 7.
Artificial intelligence (AI) has emerged as a powerful tool to revolutionize the healthcare sector, including drug delivery and development. This review explores the current and future applications of AI in the pharmaceutical industry, focusing on drug delivery and development. It covers various aspects such as smart drug delivery networks, sensors, drug repurposing, statistical modeling, and simulation of biotechnological and biological systems. The integration of AI with nanotechnologies and nanomedicines is also examined. AI offers significant advancements in drug discovery by efficiently identifying compounds, validating drug targets, streamlining drug structures, and prioritizing response templates. Techniques like data mining, multitask learning, and high-throughput screening contribute to better drug discovery and development innovations. The review discusses AI applications in drug formulation and delivery, clinical trials, drug safety, and pharmacovigilance. It addresses regulatory considerations and challenges associated with AI in pharmaceuticals, including privacy, data security, and interpretability of AI models. The review concludes with future perspectives, highlighting emerging trends, addressing limitations and biases in AI models, and emphasizing the importance of collaboration and knowledge sharing. It provides a comprehensive overview of AI's potential to transform the pharmaceutical industry and improve patient care while identifying further research and development areas.
人工智能 (AI) 已成为颠覆医疗保健领域（包括药物输送和开发）的强大工具。本综述探讨了人工智能在制药行业中的当前和未来应用，重点关注药物输送和开发。它涵盖了智能药物输送网络、传感器、药物再利用、统计建模以及生物技术和生物系统的模拟等各个方面。还研究了人工智能与纳米技术和纳米医学的集成。人工智能通过有效识别化合物、验证药物靶点、简化药物结构以及优先考虑响应模板，在药物发现方面取得了重大进展。数据挖掘、多任务学习和高通量筛选等技术有助于推动药物发现和开发创新。本文讨论了人工智能在药物配方和输送、临床试验、药物安全性和药物警戒方面的应用。它还讨论了与制药领域人工智能相关的监管考虑因素和挑战，包括隐私、数据安全和人工智能模型的可解释性。最后，本文提出了未来展望，强调了人工智能在改善患者护理方面的潜力，同时也强调了合作和知识共享的重要性。本文全面概述了人工智能在改变制药行业和改善患者护理方面的潜力，同时也确定了进一步的研究和发展领域。
