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Updated: Jan 18, 2026

Solubility of Hydrophobic Compounds in Aqueous Solution Using Combinations of Self-assembling Peptide and Amino Acid
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Published on: September 20, 2017

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拉洛西芬在超临界CO2中的溶解度和药物溶解度的相关性通过混合机器学习和基于梯度的优化

Hadil Faris Alotaibi1, Chou-Yi Hsu2, Fadhil Faez Sead3,4

  • 1Department of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah Bint AbdulRahman University, Riyadh, 11671, Saudi Arabia. Hfalotaibi@pnu.edu.sa.

Scientific reports
|September 11, 2025
PubMed
概括

研究人员使用机器学习模型来预测拉洛西芬的溶解度和超临界二氧化碳 (CO2) 的密度. 这有助于通过超临界方法开发药物纳米粒子.

关键词:
药物计算方法 药物计算方法额外的树木 额外的树木梯度增强可以提高梯度.机器学习 机器学习过程建模的过程建模.随机的森林随机的森林可溶性 可溶性 溶性

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