Experimental investigation of dynamic drying in single pharmaceutical granules containing acetaminophen or carbamazepine using synchrotron X-ray micro computed tomography
Bibliographic record
Abstract
Drying time, velocity, and temperature are important aspects of the drying process for pharmaceutical granules observed during tablet manufacturing. However, the drying mechanism of single granules is often limited to modelling and simulation, with the internal and physical changes difficult to quantify at an experimental level. In this study, in-situ synchrotron-based X-ray imaging techniques were used for the first time to investigate the dynamic drying of single pharmaceutical granules, quantifying internal changes occurring over the drying time. Two commonly used excipients (lactose monohydrate (LMH) and microcrystalline cellulose (MCC)) were used as pure components and binary mixtures with one of either two active pharmaceutical ingredients of differing hydrophilicity/hydrophobicity (acetaminophen (APAP) and carbamazepine (CBZ)). Water was used as a liquid binder to generate single granules of 25 % to 30 % moisture content. Results showed that for most samples, the drying time and composition significantly influences the pore volume evolution and the moisture ratio, with the velocity and temperature of the drying air possessing mixed significance on increasing the rate of pore connectivity and moisture removal depending on the sample composition. Effects of active ingredient loading resulted in minimal influence on the drying of CBZ and generated binary mixtures, with APAP and its respective mixtures' drying behaviour dominated by the material's hydrophilic nature.
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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".