AIDD与CADD提升药物成功率的思考  

Reflections on improving drug success rates with AIDD and CADD

作　　者：陈柏宇 吕泸楠 徐小迪 张滎 李炜[1] 付伟[1] CHEN Baiyu;LYU Lunan;XU Xiaodi;ZHANG Ying;LI Wei;FU Wei(School of Pharmacy,Fudan University,Shanghai 201203,China)

机构地区：[1]复旦大学药学院,上海201203

出　　处：《中国药科大学学报》2024年第3期284-294,共11页Journal of China Pharmaceutical University

基　　金：国家自然科学基金项目(No.82273853,No.82073765)。

摘　　要：随着人工智能(AI)和计算科学的迅速发展,特别是人工智能药物设计(AIDD)与计算机辅助药物设计(CADD)技术的引入,自然语言处理、图像识别、深度学习和机器学习等多种技术为新药开发提供了革命性的新途径,大幅提升了研发流程的效率和成功率。在药物发现过程中,AI技术加速了药物靶点的识别、候选药物的筛选、药理评估及质量检验,有效降低了研发风险和成本。本文深入探讨AIDD和CADD技术在药物研发中的应用,分析它们在提升药物设计成功率和药物研发效率方面的思考与探索,并探讨这些技术的未来发展趋势及可能面临的挑战。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.

关 键 词：人工智能药物设计 计算机辅助药物设计 药效团 分子生成 基于片段的药物设计 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] R914[自动化与计算机技术—控制科学与工程]