The Rise of Artificial Intelligence in Pharma: Shaping the Future of Drug Discovery

Authors : Ayça Dedeoglu Erdogan, Armanç Mat, Enise Ece Gürdal, Meric Koksal Akkoc

Pages : 583-602

Doi:10.55262/fabadeczacilik.1411661

View : 59 | Download : 68

Publication Date : 2024-10-23

Article Type : Review Paper

Abstract :Drug discovery as an important scientific area that serves human health, requires continuous advancement for improved quality of life and survival rates. However, drug discovery is a long and expensive process. The studies aimed at dealing with these problems have enabled to combination of AI with drug development stages. For every step of the R&D process, AI plays a vital role in facilitating and accelerating the work. Firstly, AI methods (deep learning and convolutional neural networks) help predict the 3D structure of an unresolved protein making it easier for the rational design of compounds to target a specific protein among other potential outcomes. After estimation of the protein structure of interest, it is also possible to determine the protein-ligand interactions by utilizing AI technologies like random forest. The other stage, namely finding the hit compounds is also possible through AI-assisted QSAR models such as deep neural networks. Besides, there are many AI methods (k-nearest neighbor and support vector machines) for ADMET prediction to optimize lead compounds. Finally, AI techniques also aid in choosing the most suitable synthesis plan. In the light of the latest advances, AI has become the focus of the pharmaceutical industry. However, despite the potential benefits of AI in drug discovery, several challenges must be considered including the availability of suitable data and bioethical issues. This article provides a comprehensive review of the benefits and applications of AI in various stages of drug discovery. In addition, the open-source act model and bioethical issues are also discussed.
Keywords : artificial intelligence, drug discovery, machine learning, deep learning