Dolores R Serrano, Francis C Luciano, Brayan J Anaya, Baris Ongoren, Aytug Kara, Gracia Molina, Bianca I Ramirez, Sergio A Sánchez-Guirales, Jesus A Simon, Greta Tomietto, Chrysi Rapti, Helga K Ruiz, Satyavati Rawat, Dinesh Kumar, Aikaterini Lalatsa
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引用次数: 0
Abstract
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.
PharmaceuticsPharmacology, Toxicology and Pharmaceutics-Pharmaceutical Science
CiteScore
7.90
自引率
11.10%
发文量
2379
审稿时长
16.41 days
期刊介绍:
Pharmaceutics (ISSN 1999-4923) is an open access journal which provides an advanced forum for the science and technology of pharmaceutics and biopharmaceutics. It publishes reviews, regular research papers, communications, and short notes. Covered topics include pharmacokinetics, toxicokinetics, pharmacodynamics, pharmacogenetics and pharmacogenomics, and pharmaceutical formulation. Our aim is to encourage scientists to publish their experimental and theoretical details in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.