Applications of AI in the Development of Personalized Medicine and Pharmacogenomics

Abstract

As the applications of AI become more prominent in the healthcare industry, its  relevance continues to grow in pharmacogenomics. Through AI methods like machine learning, scientists have been able to efficiently advance personalized drug development for patients with genetic variations and critical medical problems. This paper assesses how geneticists are using AI tools in pharmacogenomics to advance drug development in the healthcare industry. Pharmacogenomic testing has the potential to be a more efficient and cheaper alternative for traditional genetic testing; however, this testing is not currently used in primary health care due to a lack of knowledge on the functioning of pharmacogenomic tests. Additionally, many geneticists and the general public have shown skepticism surrounding the effects of AI and pharmacogenomic testing on other aspects of society – like environment and political concerns. This research introduces the basics of artificial intelligence and pharmacogenomics, later explaining how both of them are used together in the creation of medications and addressing public concerns surrounding the use of AI in pharmacogenomics. Despite these concerns, this research finds that AI is a helpful resource in genetic testing that will be of assistance to scientists and an ally in advancing drug development in healthcare.