Malheiro Vera, Santos Beatriz, Figueiras Ana, Mascarenhas-Melo Filipa
Laboratory of Drug Development and Technologies, Faculty of Pharmacy, University of Coimbra, 3000-548 Coimbra, Portugal.
REQUIMTE/LAQV, Group of Pharmaceutical Technology, University of Coimbra, 3000-548 Coimbra, Portugal.
Pharmaceuticals (Basel). 2025 May 25;18(6):788. doi: 10.3390/ph18060788.
Artificial intelligence (AI) is a subfield of computer science focused on developing systems that can execute tasks traditionally associated with human intelligence. AI systems work through algorithms based on rules or instructions that enable the machine to make decisions. With the advancement of science, more sophisticated AI techniques, such as machine learning and deep learning, have been developed, allowing machines to learn from large amounts of data and improve their performance over time. The pharmaceutical industry has greatly benefited from the development of this technology. AI has revolutionized drug discovery and development by enabling rapid and effective analysis of vast volumes of biological and chemical data during the identification of new therapeutic compounds. The algorithms developed can predict the efficacy, toxicity, and possible adverse effects of new drugs, optimize the steps involved in clinical trials, reduce associated time and costs, and facilitate the implementation of innovative drugs in the market, making it easier to develop precise therapies tailored to the individual genetic profile of patients. Despite significant advancements, there are still gaps in the application of AI, particularly due to the lack of comprehensive regulation. The constant evolution of this technology requires ongoing and in-depth legislative oversight to ensure its use remains safe, ethical, and free from bias. This review explores the role of AI in drug development, assessing its potential to enhance formulation, accelerate discovery, and repurpose existing medications. It highlights AI's impact across all stages, from initial research to clinical trials, emphasizing its ability to optimize processes, drive innovation, and improve therapeutic outcomes.
人工智能（AI）是计算机科学的一个子领域，专注于开发能够执行传统上与人类智能相关任务的系统。人工智能系统通过基于规则或指令的算法运行，这些规则或指令使机器能够做出决策。随着科学的进步，已经开发出了更复杂的人工智能技术，如机器学习和深度学习，使机器能够从大量数据中学习并随着时间的推移提高其性能。制药行业从这项技术的发展中受益匪浅。人工智能通过在新治疗化合物的识别过程中对大量生物和化学数据进行快速有效的分析，彻底改变了药物发现和开发。所开发的算法可以预测新药的疗效、毒性和可能的不良反应，优化临床试验中涉及的步骤，减少相关时间和成本，并促进创新药物在市场上的应用，从而更容易开发针对患者个体基因特征的精准疗法。尽管取得了重大进展，但人工智能的应用仍存在差距，特别是由于缺乏全面监管。这项技术的不断发展需要持续深入的立法监督，以确保其使用仍然安全、符合道德且无偏见。本综述探讨了人工智能在药物开发中的作用，评估了其在改进制剂、加速发现和重新利用现有药物方面的潜力。它强调了人工智能在从初步研究到临床试验的所有阶段的影响，强调了其优化流程、推动创新和改善治疗结果的能力。
