在药物设计困难和制药行业未来潜力的背景下探索人工智能和机器学习模型
Periyasamy Natarajan Shiammala1, Navaneetha Krishna Bose Duraimutharasan1, Baskaralingam Vaseeharan2
1Department of Information Technology, AMET Deemed to be University, Kanathur, Chennai, Tamil Nadu 603112, India.
Methods (San Diego, Calif.)
|October 1, 2023
概括
人工智能 (AI) 通过识别目标和设计分子来加速药物发现. 这项技术快速选数百万种化合物,彻底改变了制药开发和优化.
科学领域:
- 制药科学 制药科学
- 计算化学计算化学
- 生物技术是生物技术.
背景情况:
- 人工智能 (AI),包括深度学习,为增强和加快新药发现和开发提供了巨大的潜力.
- 虽然药物发现中的AI正在出现,但它有望改变传统方法,并增加未来的相关性.
结论:
- 人工智能辅助的药物发现正在迅速发展,在整个制药管道中都有应用.
- 目前的人工智能方法面临局限性,但未来的研究有望进一步创新.
- 整合人工智能对于未来高效有效的药物发现和设计至关重要.
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