AI-Driven Pharmaceutical Innovation: Exploring its role in Drug discovery, design, and Optimization

Abstract

Artificial intelligence (AI) has been identified as a potential 
technological tool capable of effectively employing humanized 
knowledge for providing therapeutic outcomes for a challenging 
complication. Remarkable inventions in Machine learning and AI 
presented a paradigm-shifting in drug discovery, formulation 
designing, and complementary testing of numerous pharmaceutical 
dosage forms. Effective utilization of AI algorithms enabled 
investigators to analyze huge biological data, including genomic and 
proteomic information, together with the successful 
identification/prediction of disease-related targets and their potential 
binding with potential drug candidates. Current technology provides 
researchers with more proficient and targeted drug discovery methods 
that ultimately enhance the likelihood of approvals of novel drugs. The 
current study also discussed numerous AI-based approaches being 
effectively utilized in pharmaceutical technology, describing its dual 
positive and negative consequences and promising opportunistic 
outcomes that might be attained following investment/utilization of AI 
in pharmaceutical industries, keeping in view its pivotal role in 
improved patient care and drug development.