人工智能在药物开发中的作用:通过机器学习和预测建模来增强制药化学
Deepak Kumar Dash1, Satyanarayan Pattnaik2, Arpita Namdeo1
1Department of Pharmaceutical Chemistry, Royal College of Pharmacy, Raipur, Chhattisgarh, India.
人工智能 (AI) 和机器学习 (ML) 可以显著改善药物设计和开发. 这些技术提供了更高效,更精确,更具成本效益的药物研究,有利于全球医疗保健.
科学领域:
- 制药科学 制药科学
- 计算化学的计算化学
- 生物技术是生物技术.
背景情况:
- 传统药物开发是低效的,昂贵的,耗时的.
- 挑战包括低效率,意想不到的准和漫长的时间表.
- 药物研究的进步受到当前方法的阻碍.
研究的目的:
- 探索AI和ML在制药药物设计和开发中的应用.
- 确定AI和ML如何提高药物发现的效率和精度.
- 评估AI和ML在克服传统药物开发挑战方面的潜力.
主要方法:
- 审查当前AI和ML在药物研究中的应用.
- 分析了在药物设计中展示AI/ML的案例研究.
- 探索预测建模和数据挖掘技术.
主要成果:
- 人工智能和机器学习的整合简化了药物发现管道.
- 增强的预测准确性减少了非目标效应.
- 可以实现加快时间表和降低开发成本.
结论:
- 人工智能和机器学习技术彻底改变了制药研究和开发.
- 这些进步有望实现更高效,更精确,更可持续的药物制造.
- 人工智能驱动的药物开发可以改变医疗保健并改善药物可用性.
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