Calorimetric Relaxation in Pharmaceutical Molecular Glasses and Its Utility in Understanding Their Stability Against Crystallization
Bibliographic record
Abstract
Glassy states of three pharmaceuticals, acetaminophen, griseofulvin, and nifedipine, and an acetaminophen-aspirin (1:1 mol) alloy were made by slow cooling of the melt and studied by calorimetry. Measurements were performed by cooling and heating at significantly slow rates of 20 K/h, which were comparable to the rate used in adiabatic calorimetry. The results were modeled in terms of a nonexponential, nonlinear structural relaxation. The calorimetric relaxation of all four pharmaceutical samples were less nonexponential than those of polymeric or inorganic glasses, and this finding was attributed to additional contributions to energy change that would arise from temperature and time dependent variation in the hydrogen bond population, the extent of isomerization, and/or the ionic equilibria that exist in these materials. Four calculated and relevant parameters for the pharmaceutical samples were, ln A = -183, beta = 0.75, x = 0.4, and Delta h* = 457 kJ/mol for acetaminophen, ln A = -170, beta = 0.75, x = 0.45, and Delta h* = 516 kJ/mol for griseofulvin, ln A = -189, beta = 0.69, x = 0.39, and Delta h* = 503 kJ/mol for nifedipine, and ln A = -160, beta = 0.70, x = 0.50, and Delta h* = 363 kJ/mol for the acetaminophen-aspirin alloy. The significance of these parameters and, in particular, their values are discussed in the context of the stability of the pharmaceuticals against crystallization and compared against the significance of the localized motions of the JG relaxation in the same context. Acetaminophen was found to be significantly more prone to crystallization on heating than the other two pharmaceuticals as well as the acetaminophen-aspirin alloy.
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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 | 0.001 |
| 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".