人工智能集成药物发现的当前进展:方法和应用
Yash Mathur1, Arunabh Choudhury1, Sneh Prabha1
1Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India.
Biotechnology advances
|July 10, 2025
概括
人工智能 (AI) 正在通过增强数据分析,虚拟查和临床试验优化来彻底改变药物发现. 本综述详细介绍了人工智能模型和工具,探讨它们对加速新疗法的发展的影响.
科学领域:
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 的采用在科学学科中迅速增加,包括人类医疗保健.
- 人工智能的跨学科性质有助于其在各种领域的应用,特别是药物开发.
- 人工智能模型和计算机硬件的进步正在提高科学研究中的精度和预测能力.
研究的目的:
- 在药物发现和开发管道中审查人工智能 (AI) 应用的最新进展.
- 提供AI模型,架构和在药物发现中使用的工具的概述.
- 讨论人工智能驱动药物发现的前景,挑战和局限性.
主要方法:
- 探索常用于药物发现的AI模型和架构.
- 对数据分析和功能注释的最先进的人工智能工具的审查.
- 在虚拟查和临床试验优化中分析AI应用.
主要成果:
- 人工智能模型越来越多地用于改善药物发现技术中的预测和参数.
- 人工智能工具正在增强药物发现工作流程的各个阶段,从初步分析到临床试验.
- 该审查强调了人工智能对加速新药的识别和开发的影响越来越大.
结论:
- 人工智能为药物发现和开发中的各种子主题提供了创新和改进的重要机会.
- 对人工智能的持续研究和开发对于克服现有的挑战和局限性至关重要.
- 人工智能的整合有望显著提高治疗开发的效率和成功率.
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