Unraveling the artificial intelligence role in drug discovery and pharmaceutical product design: an opportunity and challenges

Abstract

Background: Artificial intelligence (AI) has become a novel approach for bioactive molecule search, target identification, prediction of lead molecule-target interaction, design of pharmaceutical formulations, and efficient conduction and prediction of results of clinical trials. Main body: AI has revolutionized the drug discovery and pharmaceutical product development. Traditional methods are time-consuming and costlier due to large experimentation number and low hit and success. Herein, AI can analyse a large dataset quickly to give possible outcomes. AI easily identifies potential drug targets by virtual screening of biological data, resulting in time-efficient and low-cost discovery of novel drug targets. AI can be used for the design of new drug candidates by analysing the possible molecular structures binding with targets. Moreover, AI can easily predict drug interactions with targets to exert therapeutic action. AI-enabled drug repurposing is based on the interaction of existing drugs with new targets or other explored target datasets. AI can play prominent role in accelerating the development of pharmaceutical products due to their role in optimization and process validation. The clinical trials have also become easy and faster with use of AI tools. Conclusion: Artificial Intelligence based tool can be employed in discovery of lead molecule, target identification, drug-target interaction, development of pharmaceutical product and clinical trials to accelerate the production of clinically acceptable therapeutics with higher success rate.