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CHEN Baiyu, LYU Lunan, XU Xiaodi, et al. Reflections on improving drug success rates with AIDD and CADD[J]. J China Pharm Univ, 2024, 55(3): 284 − 294. DOI: 10.11665/j.issn.1000-5048.2024011302
Citation: CHEN Baiyu, LYU Lunan, XU Xiaodi, et al. Reflections on improving drug success rates with AIDD and CADD[J]. J China Pharm Univ, 2024, 55(3): 284 − 294. DOI: 10.11665/j.issn.1000-5048.2024011302
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Reflections on improving drug success rates with AIDD and CADD

  • School of Pharmacy, Fudan University, Shanghai 201203,China

Funds: This study was supported by the National Natural Science Foundation of China (No. 82273853, No. 82073765)
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  • Received Date: January 12, 2024
  • Available Online: June 24, 2024
    Graphical 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.

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