Computational machine learning estimation of digitoxin solubility in supercritical solvent at different temperatures utilizing ensemble methods

Computational machine learning estimation of digitoxin solubility in supercritical solvent at different temperatures utilizing ensemble methods

Abstract The solubility of medications in supercritical solvent is the most important factor that can be determined via appropriate computational tools. This work explores the modeling of digitoxin solubility as the case study in supercritical CO2 and solvent density utilizing ensemble methods. Temp...

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Main Authors: Hadil Faris Alotaibi, Waqed H. Hassan, Ahmed Kateb Jumaah Al-Nussairi, Narinderjit Singh Sawaran Singh, Ahmed Salah Al-Shati, M. M. Rekha, Subhashree Ray, Aashna Sinha, Gunjan Garg
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Pharmaceutical process
Drug particles
Machine learning
Solubility
Supercritical CO2
Online Access:https://doi.org/10.1038/s41598-025-15049-x
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https://doi.org/10.1038/s41598-025-15049-x

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