Simulating molecular models in drug design using artificial intelligence in the pharmaceutical industry

Background and Aims: The pharmaceutical industry has always been looking for new and efficient methods for the design and development of new drugs. Molecular model simulation using artificial intelligence (AI) has emerged as a powerful tool in this field. This article examines the role and importance of molecular model simulation using artificial intelligence in drug design in the pharmaceutical industry and, in particular, examines the challenges, opportunities and future trends in this area. Methods: case studies and scientific articles related to the application of artificial intelligence in drug design in the pharmaceutical industry are reviewed and analyzed. To collect information, reputable scientific databases such as PubMed, Scopus and Web of Science have been used. Also, reports and articles published by international organizations such as the World Health Organization (WHO) and the US Food and Drug Administration (FDA) have been reviewed. Results: The study shows that artificial intelligence, by increasing the accuracy and speed of molecular model simulations, has enabled faster and more accurate identification of drug compounds, prediction of their properties, and optimization of drug structures. The use of AI has reduced drug development time and costs, and increased the likelihood of their success. For example, using AI in drug design can save up to ۳۰% in research and development costs and reduce the time to market by up to ۵۰%. It has also shown positive results in identifying effective drug compounds against the coronavirus. Conclusion: This technology helps researchers simplify and speed up complex processes by providing powerful tools and algorithms. However, there are also challenges in using artificial intelligence in drug design, including the lack of sufficient data, the complexity of biological models, and the need for interdisciplinary expertise.

کلیدواژه ها:

Artificial Intelligence ، Medicine ، Simulation ، Molecular ، Pharmaceuticals