New Technology of Thermoplastic Coating for Osmotic Pump Tablets: Study on in vitro Drug Release
Bibliographic record
Abstract
Aim The in vitro drug release profiles of metformin hydrochloride thermoplastic coated tablets and nifedipine thermoplastic coated tablets were studied. Methods By measuring the in vitro release profiles of the thermoplastic coated tablets of model drugs, the effects of membrane thickness, polyethylene glycol-1,500 (PEG1500) content, number of orifice, stirring speed, and release medium on the drug release were investigated, and the rule and mechanism of drug release were also analyzed by comparing with the osmotic pump tablets (OPTs). Results Thermoplastic coated tablets with single- or double-chamber construction performed the same function of controlling the drug release, operated under the same release mechanism (osmotic pressure drove the drug release), and exhibited the same release characteristics (zero-order release, unaffected by release medium, and stirring speed) and release rule (release rate was inversely proportional to the membrane thickness but proportional to the PEG1500 content) as compared with OPTs prepared by the common spray coating technology. Conclusion Thermoplastic coated tablets have the same release characteristics in vitro as OPTs. The new technology of thermoplastic coating can replace the spray coating technology of OPTs. This study provides theoretical basis and practical support for the industrialization and clinical application of thermoplastic coating technology.
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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 | 0.001 |
| 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".