人工智能的最新研究在中吸收药物的吸收
Thi Tuyet Van Tran1,2,3, Hilal Tayara4, Kil To Chong5
1Department of Electronics and Information Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea.
Journal of chemical information and modeling
|October 11, 2023
概括
本综述概述了用于预测药物吸收性质的最新人工智能方法. 它强调了关键的数据库和未来的方向,以改善药物发现和降低开发成本.
科学领域:
- 药物化学 药物化学
- 药物开发 药物开发
- 计算化学计算化学
背景情况:
- 药物吸收对于治疗疗效至关重要,并影响ADMET的整体特征.
- 吸收不良是药物开发失败的主要原因之一.
- 准确预测吸收性质对于有效的药物查至关重要.
研究的目的:
- 提供关于预测药物吸收性质的近期in silico研究的全面概述.
- 审查从2019年到现在的吸收预测中的人工智能应用.
- 确定吸收预测研究中的挑战和未来方向.
主要方法:
- 关于药物吸收预测的in silico研究的文献综述.
- 对用于吸收性质预测的人工智能技术的分析.
- 调查支持吸收预测的公共数据库.
主要成果:
- 自2019年以来,使用人工智能在in silico药物吸收预测方面取得了重大进展.
- 确定对吸收预测研究有价值的关键公共数据库.
- 总结当前的挑战和有前途的未来研究途径.
结论:
- 形方法,特别是人工智能,对于通过预测吸收来加速药物发现至关重要.
- 需要进一步的研究来应对现有的挑战,并完善预测模型.
- 本综述为开发新的吸收预测方法提供了指导方针.
相关概念视频
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