Reciprocal Powered Time model for Release Kinetic Analysis of Ibuprofen Solid Dispersions in Oleaster Powder, Microcrystalline Cellulose and Crospovidone
Bibliographic record
Abstract
PURPOSE: A physically sound derivation for reciprocal power time (RPT) model for kinetic of drug release is given. In order to enhance ibuprofen dissolution, its solid dispersions (SDs) prepared by cogrinding technique using crospovidone (CP), microcrystalline cellulose (MC) and oleaster powder (OP) as a novel carrier and the model applied to the drug release data. METHODS: The drug cogrounds with the carriers were prepared and subjected to the dissolution studies. For elucidation of observed in vitro differences, FT-IR spectroscopy, X-ray diffraction patterns, DSC thermograms and laser particle size measurement were conducted. RESULTS: All drug release data fitted very well to newly derived RPT model. The efficiency of the carriers for dissolution enhancement was in the order of: CP>OP>MC. The corresponding release kinetic parameter derived from the model, t50% (time required for 50% dissolution) for the carrier to drug ratio 2:1 were 2.7, 10.2 and 12.6 min, respectively. The efficiency of novel carrier, OP, was between CP and MC. FT-IR showed no interaction between the carriers and drug. The DSC thermograms and X-ray diffraction patterns revealed a slight reduced crystallinty in the SDs. Also grinding reduced mean particle size of drug from 150.7 to 44.4 microm. CONCLUSIONS: An improved derivation for RPT model was provided which the parameter of the model, t50%, unlike to previous derivations was related to the most important property of the drug i.e. its solubility. The model described very well drug release kinetics from the solid dispersions. Cogrinding was an effective technique in enhancing dissolution rate of ibuprofen. Elaeagnus angostifolia fruit powder was suggested as a novel potential hydrophilic carrier in preparing solid dispersion of ibuprofen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".