Wyszukiwarka
Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation
Abstrakt
Deep eutectic solvents (DESs) are popular green media used for various industrial, pharmaceutical, and biomedical applications. However, the possible compositions of eutectic systems are so numerous that it is impossible to study all of them experimentally. To remedy this limitation, the solubility landscape of selected active pharmaceutical ingredients (APIs) in choline chloride- and betaine-based deep eutectic solvents was explored using theoretical models based on machine learning. The available solubility data for the selected APIs, comprising a total of 8014 data points, were collected for the available neat solvents, binary solvent mixtures, and DESs. This set was augmented with new measurements for the popular sulfa drugs in dry DESs. The descriptors used in the machine learning protocol were obtained from the σ-profiles of the considered molecules computed within the COSMO-RS framework. A combination of six sets of descriptors and 36 regressors were tested. Taking into account both accuracy and generalization, it was concluded that the best regressor is nuSVR regressor-based predictive models trained using the relative intermolecular interactions and a twelve-step averaged simplification of the relative σ-profiles.
Cytowania
-
0
CrossRef
-
0
Web of Science
-
0
Scopus
Autorzy (3)
Cytuj jako
Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- Licencja
-
otwiera się w nowej karcie
Słowa kluczowe
Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- Publikacja w czasopiśmie
- Opublikowano w:
-
MOLECULES
nr 29,
wydanie 20,
ISSN: 1420-3049 - Rok wydania:
- 2024
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/molecules29204894
- Weryfikacja:
- Brak weryfikacji
wyświetlono 15 razy
Publikacje, które mogą cię zainteresować
Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
- P. Cysewski,
- T. Jeliński,
- M. Przybyłek
- + 2 autorów
Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
- T. Jeliński,
- M. Przybyłek,
- R. Różalski
- + 1 autorów