Artificial intelligence enabled ChatGPT and large language models in drug target discovery, drug discovery, and development

著者: Chiranjib Chakraborty, Manojit Bhattacharya, Sang‐Soo Lee - Molecular Therapy — Nucleic Acids 2023 被引用: 76

Drug discovery has been revolutionized recently by different computational approaches like artificial intelligence (AI), deep learning (DL), and quantum mechanical methods. Drug discovery and development was a prolonged process previously. Developing one small-molecular drug might take 15 years on average, costing around US $2 billion. A paradigm shift has recently been noted in drug discovery using computational technologies during the past few years.1,2 Biotech-based drug discovery companies developed their new business models guided by molecular modeling techniques with AI and DL for “small-molecule hit generation” and “hit to lead generation.”3,4 In this direction, computational-guided ultra-large physics-based virtual screening techniques have been used in drug discovery.