THE ROLE OF ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY AND DEVELOPMENT

Abstract

Medicine research and production are complex and costly processes, historically based on empirical and experimental methods. Recently, advances in artificial intelligence (AI) have promised to transform the pharmaceutical industry, enabling more efficient and cost-effective processes through data analysis, machine learning and deep learning. This study used an integrative literature review, including 20 articles selected through searches in databases such as BVS, SciELO, PubMed, EbscoHost and Google Scholar. The inclusion criteria considered articles published in the last 4 years, in Portuguese, English or Spanish, that addressed the use of AI in the discovery and production of drugs. The analysis highlighted that AI is significantly accelerating drug discovery, improving efficiency, reducing costs and optimizing production time. Examples include the analysis of large data sets, advanced molecular modeling, and toxicity prevention. The COVID-19 pandemic has highlighted the crucial role of AI in responding quickly and effectively through interdisciplinary collaborations and deep learning models. In short, AI is revolutionizing pharmacology by accelerating the discovery of new treatments and personalizing medicine. However, it is essential to face challenges such as adapting healthcare professionals, implementing appropriate regulations and ensuring ethics in the use of AI. Broad collaborations and transparent data sharing are key to maximizing the benefits of this emerging technology.