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©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Exp Med. Sep 20, 2024; 14(3): 96042
Published online Sep 20, 2024. doi: 10.5493/wjem.v14.i3.96042
Published online Sep 20, 2024. doi: 10.5493/wjem.v14.i3.96042
Artificial intelligence as a tool in drug discovery and development
Maria Kokudeva, Department of Pharmacology and Toxicology, Faculty of Pharmacy, Medical University of Sofia, Sofia 1000, Bulgaria
Mincho Vichev, Healthcare Solutions, Sofia 1404, Bulgaria
Emilia Naseva, Faculty of Public Health, Medical University of Sofia, Sofia 1431, Bulgaria
Dimitrina Georgieva Miteva, Department of Genetics, Faculty of Biology, Sofia University St. Kliment Ohridski, Sofia 1164, Bulgaria
Dimitrina Georgieva Miteva, Tsvetelina Velikova, Medical Faculty, Sofia University St. Kliment Ohridski, Sofia 1407, Bulgaria
Co-first authors: Maria Kokudeva and Mincho Vichev.
Author contributions: Kokudeva M and Vichev M were involved equally in conceptualizing the idea and writing the draft; Miteva D, Naseva E and Velikova T wrote additional sections in the paper; Vichev M was responsible for the critical revision of the manuscript for relevant intellectual content; Velikova T was responsible for project administration and funding acquisition; All authors approved the final version of the paper prior to submission.
Supported by the European Union-NextGenerationEU , through the National Recovery and Resilience Plan of the Republic of Bulgaria, No. BG-RRP-2.004-0008.
Conflict-of-interest statement: All authors declare they have no conflicts of interest to disclose.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Maria Kokudeva, PharmD, PhD, Research Assistant, Department of Pharmacology and Toxicology, Faculty of Pharmacy, Medical University of Sofia, ul. Dunav 2, Sofia 1000, Bulgaria. kokudeva.mariya@gmail.com
Received: April 25, 2024
Revised: August 6, 2024
Accepted: August 12, 2024
Published online: September 20, 2024
Processing time: 125 Days and 21.4 Hours
Revised: August 6, 2024
Accepted: August 12, 2024
Published online: September 20, 2024
Processing time: 125 Days and 21.4 Hours
Core Tip
Core Tip: Embracing artificial intelligence (AI) expedites drug discovery and development by streamlining computational chemistry, molecular modeling, and data mining. Leveraging AI-driven algorithms enhances the accuracy and efficiency of identifying potential drug candidates and predicting their pharmacological properties. Integrating machine learning and deep learning frameworks into pharmaceutical research optimizes decision-making, accelerates drug design cycles, and ultimately advances novel therapies for various diseases.