Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
Abstract
:1. Introduction
2. Results and Discussion
2.1. Solubility Dataset
2.2. Extension of EDA Solubility Space with Neat Solvents
2.3. Extension of EDA Solubility Space with Aqueous Binary Solvents
2.4. Machine Learning Solubility Model
2.5. The Solubility Space Characteristics
3. Materials and Methods
3.1. Materials
3.2. Solubility Measurements
3.3. Instrumental Analysis of Solid Residues
3.4. Solubility Data Curation
3.5. Model Development
3.6. Molecular Descriptors
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Sample Availability
References
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Solvent [CAS number] | Structure | Log (xEest) | EI (PCOP = 0) |
---|---|---|---|
enflurane [13838-16-9] | –1.20 ± 0.42 (–1.29) | 0.47 | |
DMSO [67-68-5] | –1.22 ± 0.20 (–1.28) | 0.26 | |
isoflurane [26675-46-7] | –1.29 ± 0.46 (–1.05) | 0.56 | |
NMP [872-50-4] | –1.40 ± 0.09 (–0.92) | 0.97 | |
2-ethenoxyethanol [764-48-7] | –1.41 ± 0.09 (–1.35) | 0.97 |
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Przybyłek, M.; Jeliński, T.; Mianowana, M.; Misiak, K.; Cysewski, P. Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study. Molecules 2023, 28, 6877. https://doi.org/10.3390/molecules28196877
Przybyłek M, Jeliński T, Mianowana M, Misiak K, Cysewski P. Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study. Molecules. 2023; 28(19):6877. https://doi.org/10.3390/molecules28196877
Chicago/Turabian StylePrzybyłek, Maciej, Tomasz Jeliński, Magdalena Mianowana, Kinga Misiak, and Piotr Cysewski. 2023. "Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study" Molecules 28, no. 19: 6877. https://doi.org/10.3390/molecules28196877