High-amylose sodium carboxymethyl starch matrices for oral, sustained drug release: development of a spray-drying manufacturing process
Bibliographic record
Abstract
CONTEXT: High-amylose sodium carboxymethyl starch (HASCA) was recently proposed as a material for oral, sustained drug-release tablets prepared by direct compression. It was produced on a pilot scale, but appeared to be unsuitable for tableting and sustained drug release. Pilot-scale dry powder HASCA was dispersed in hot water and then precipitated with ethanol to give a dry powder presenting the required properties, but very high volumes of ethanol were used to recover the product. OBJECTIVE: A process was therefore designed to transform totally amorphous pregelatinized HASCA by spray-drying into a suitable sustained drug-release excipient for matrix tablets while decreasing ethanol quantities. RESULTS AND DISCUSSION: During the first manufacturing step, that is, heating of the initial hydro-alcoholic suspension, powder and water concentrations are key parameters for the acquisition of excellent binding properties. Hence, a variable ratio of amylose Vh, a crystalline polymorph of amylose, to the amorphous form, is observed depending on the key parameter values. As the most crystalline samples give the weakest tablets, binding properties do not appear to be linked to the presence of a Vh form of amylose. On the other hand, a high water concentration results in excessive tablet strength, that is, inverse conditions leading to the appearance of a Vh form of amylose. Finally, variations in hydro-alcoholic composition appear to affect only tableting properties and do not influence the drug-release rate. CONCLUSION: A process designed to transform totally amorphous pregelatinized HASCA by spray-drying is proposed for easier, economical industrial HASCA production.
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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 | 0.001 |
| 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 | 0.001 |
| 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".