Reflections on improving drug success rates with AIDD and CADD

VernacularTitle:AIDD与CADD提升药物成功率的思考
Author: Baiyu CHEN ; Lunan LYU ; Xiaodi XU ; Ying ZHANG ; Wei LI ; Wei FU
Publication Type:Journal Article
Keywords: artificial intelligence drug design / computer-aided drug design / pharmacophore / molecular generation / fragment-based drug design
From: Journal of China Pharmaceutical University 2024;55(3):284-294
CountryChina
Language:Chinese
Abstract: Abstract: The rapid advancements in artificial intelligence (AI) and computational sciences, particularly through the introduction of artificial intelligence drug design (AIDD) and computer-aided drug design (CADD) technologies, have revolutionized pathways in drug development. These include techniques such as natural language processing, image recognition, deep learning, and machine learning. By employing advanced algorithms and data processing techniques, these technologies have significantly enhanced the efficiency and success rate of R&D processes. In drug discovery, AI technologies have accelerated the identification of drug targets, screening of candidate drugs, pharmacological assessments, and quality control, effectively reducing R&D risks and costs. This article delves into the application of AIDD and CADD in drug development, analyzing their roles in enhancing the success rates and efficiencies of drug design, exploring their future trends, and addressing the potential challenges.