Evaluation of Synthesized Cross Linked Polyvinyl Alcohol as Potential Disintegrant
Bibliographic record
Abstract
PURPOSE: The present study deals with evaluation of crosslinked poly vinyl alcohol (PVA) as a potential disintegrant. METHODS: Crosslinking of PVA was carried out using glutaraldehyde as a crosslinker, in presence of acidic conditions. The crosslinking reaction was optimized for a) polymer: crosslinker ratio; b) temperature requirement and c) reaction duration. Certain physical parameters of the disintegrant (including sedimentation volume, hydration capacity, specific surface area and bulk and tap density) were determined and compared to the known disintegrants. Characterization was carried out using FT-IR, DSC, XRD, SEM and Photo microscopy studies. The developed excipient was also studied for acute toxicity in rats and found to be safe for oral use. RESULTS: Disintegration property of formed product was compared to known disintegrant (Ac-Di-Sol) and it was found to give better results. The disintegration mechanism of developed disintegrant was postulated based on results obtained from various physical evaluations including: Study of effect of disintegrant concentration, fillers, and hardness, mode of incorporation and method of granulation on disintegration activity. CONCLUSIONS: By changing the condition parameters of well known crosslinking reaction of PVA, we obtained a crosslinked product which had excellent disintegration activity, good flow and optimal tableting properties.
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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".