Ultrasound-assisted solution crystallization of fotagliptin benzoate: Process intensification and crystal product optimization
Bibliographic record
Abstract
The ultrasound-assisted crystallization process has promising potentials for improving process efficiency and modifying crystalline product properties. In this work, the crystallization process of fotagliptin benzoate methanol solvate (FBMS) was investigated to improve powder properties and downstream desolvation/drying performance. The direct cooling/antisolvent crystallization process was conducted and then optimized with the assistance of ultrasonic irradiation and seeding strategy. Direct cooling/antisolvent crystallization and seeding crystallization processes resulted in needle-like crystals which are undesirable for downstream processing. In contrast, the ultrasound-assisted crystallization process produced rod-like crystals and reduced the crystal size to facilitate the desolvation of FBMS. The metastable zone width (MSZW), induction time, crystal size, morphology, and process yield were studied comprehensively. The results showed that both the seeding and ultrasound-assisted crystallization process (without seeds) can improve the process yield and the ultrasound could effectively reduce the crystal size, narrow the MSZW, and shorten the induction time. Through comparing the drying dynamics of the FBMS, the small rod-shaped crystals with a mean size of 9.6 μm produced by ultrasonic irradiation can be completely desolvated within 20 h, while the desolvation time of long needle crystals with an average size of about 157 μm obtained by direct cooling/antisolvent crystallization and seeding crystallization processes is more than 80 h. Thus the crystal size and morphology were found to be the key factors affecting the desolvation kinetics and the smaller size produced by using ultrasound can benefit the intensification of the drying process. Overall, the ultrasound-assisted crystallization showed a full improvement including crystal properties and process efficiency during the preparation of fotagliptin benzoate desolvated crystals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".