Release Kinetics of Hydroxypropyl Methylcellulose Governing DrugRelease and Hydrodynamic Changes of Matrix Tablet
Bibliographic record
Abstract
BACKGROUND: Hydrophilic Hydroxypropyl Methylcellulose (HPMC) matrix tablets are the standard role model of the oral controlled-release formulation. Nevertheless, the HPMC kinetics for the mechanistic understanding of drug release and hydrodynamic behaviors are rarely investigated. This study aims to investigate the release behaviors of both HPMC and paracetamol (model drug) from the hydrophilic matrix tablet. METHODS: Two different viscosity grades of HPMC were used (Low viscosity: 6 cps, High viscosity: 4,000 cps). Three different ratios of drug/HPMC (H:38.08%, M:22.85%, and L:15.23% (w/w) of HPMC amounts in total weight) matrix tablets were prepared by wet granulation technique. The release profiles of the drug and HPMC in a matrix tablet were quantitatively analyzed by HPLC and 1H-Nuclear Magnetic Resonance (NMR) spectroscopy. The hydrodynamic changes of HPMC were determined by the gravimetric behaviors such as swelling and erosion rates, gel layer thickness, front movement data,and distributive Near-Infrared (NIR) chemical imaging of HPMC in a matrix tablet during the dissolution process. RESULTS: High viscosity HPMC tablets showed slower release of HPMC than the release rate of drug, suggesting that drug release preceded polymer release.Different hydration phenomenon was qualitatively identified and corresponded to the release profiles. The release behaviors of HPMC and drug in the tablet could be distinguished with the significant difference with fitted dissolution kinetics model (Low viscosity HPMC 6cps; Korsmeyer-Peppas model, High viscosity HPMC 4000cps; Hopfenberg model, Paracetamol; Weibull model) according to the weight of ingredients and types of HPMC. CONCLUSION: The determination of HPMC polymer release correlating with drug release, hydrodynamic behavior, and NIR chemical imaging of HPMC can provide new insights into the drug release- modulating mechanism in the hydrophilic matrix system.
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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".