Drug discovery in the context of precision medicine and artificial intelligence

Abstract

ABSTRACT Introduction The drug development process traditionally includes rigorous pre-clinical testing in laboratories and animal models to assess the safety, efficacy, pharmacokinetics, and toxicology of potential drug candidates before progressing to human clinical trials. Developing AI, machine ML algorithms, and precision medicine (PM) approaches will facilitate identifying potential drug targets, predicting therapeutic outcomes, and optimizing the selection of lead compounds. Areas Covered The simultaneous use of AI and PM accelerates drug discovery and development by enabling more accurate drug efficacy and safety predictions and optimizing personalized therapy strategies. Expert Opinion Combining AI with PM in drug discovery can revolutionize how we develop new treatments. PM gives us a better understanding of diseases and allows us to personalize treatments for individual patients. AI uses large amounts of data (omics data) to speed up drug discovery by finding new targets, improving compounds, and simplifying clinical trials with algorithms and ML. Combining these two approaches can accelerate the discovery of new treatments and make it easier to use existing drugs for new purposes. Although challenges such as ethical issues and legal frameworks are still to be overcome, integrating PM with AI can significantly impact drug development.