Data-driven modeling of supercritical CO₂ processing with optimized machine learning: prediction of clobetasol propionate solubility
Nidal H. Abu-Hamdeh, Mohammed N. Ajour · 2026
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Description
Nidal Abu-Hamdeh and Mohammed Ajour build computer models of a drug process in this 2026 paper. They study how well a skin drug, clobetasol propionate, dissolves in carbon dioxide held under high pressure and heat, a state used in clean drug making.
Only heat and pressure were fed to the models as inputs. The team boosted three base models and tuned them with a search method named for fireflies. The best model matched the lab data very closely, well ahead of the weakest of the three. Such models can help makers pick process settings by screen test instead of by many costly lab runs.
Catalog record
| CREATOR | Nidal H. Abu-Hamdeh, Mohammed N. Ajour |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 17 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |