Serrano Dolores R, Luciano Francis C, Anaya Brayan J, Ongoren Baris, Kara Aytug, Molina Gracia, Ramirez Bianca I, Sánchez-Guirales Sergio A, Simon Jesus A, Tomietto Greta, Rapti Chrysi, Ruiz Helga K, Rawat Satyavati, Kumar Dinesh, Lalatsa Aikaterini
Department of Pharmaceutics and Food Science, School of Pharmacy, Complutense University of Madrid, 28040 Madrid, Spain.
Instituto Universitario de Farmacia Industrial, 28040 Madrid, Spain.
Pharmaceutics. 2024 Oct 14;16(10):1328. doi: 10.3390/pharmaceutics16101328.
Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep learning, and other advanced computational methods. These innovations have unlocked unprecedented opportunities for the acceleration of drug discovery and delivery, the optimization of treatment regimens, and the improvement of patient outcomes. AI is swiftly transforming the pharmaceutical industry, revolutionizing everything from drug development and discovery to personalized medicine, including target identification and validation, selection of excipients, prediction of the synthetic route, supply chain optimization, monitoring during continuous manufacturing processes, or predictive maintenance, among others. While the integration of AI promises to enhance efficiency, reduce costs, and improve both medicines and patient health, it also raises important questions from a regulatory point of view. In this review article, we will present a comprehensive overview of AI's applications in the pharmaceutical industry, covering areas such as drug discovery, target optimization, personalized medicine, drug safety, and more. By analyzing current research trends and case studies, we aim to shed light on AI's transformative impact on the pharmaceutical industry and its broader implications for healthcare.
人工智能（AI）涵盖了制药公司已经使用了数十年的广泛技术，包括机器学习、深度学习和其他先进的计算方法。这些创新为加速药物发现和交付、优化治疗方案以及改善患者预后带来了前所未有的机遇。人工智能正在迅速改变制药行业，彻底变革从药物研发到个性化医疗的方方面面，包括靶点识别与验证、辅料选择、合成路线预测、供应链优化、连续生产过程中的监测或预测性维护等等。虽然人工智能的整合有望提高效率、降低成本并改善药物和患者健康，但从监管角度来看，它也引发了重要问题。在这篇综述文章中，我们将全面概述人工智能在制药行业的应用，涵盖药物发现、靶点优化、个性化医疗、药物安全等领域。通过分析当前的研究趋势和案例研究，我们旨在阐明人工智能对制药行业的变革性影响及其对医疗保健的更广泛影响。
