Formulation And Characterization Of Mucoadhesive Tablets For Prolonged Drug Release
Bibliographic record
Abstract
This study focuses on the formulation and evaluation of atenolol mucoadhesive tablets, aiming to enhance drug absorption and bioavailability. Hypertension, affecting a significant portion of the adult population, can lead to severe cardiovascular conditions. Atenolol, a beta-blocker, effectively manages hypertension and other heart-related issues. The study used mucoadhesive polymers like hydroxypropyl methylcellulose (HPMC), tamarind gum, and badam gum to prepare the tablets via direct compression. The formulation process included optimizing drug release kinetics and mucoadhesive strength. Pre-compression parameters such as angle of repose, bulk density, and compressibility index were evaluated. Post-compression evaluations covered organoleptic properties, hardness, friability, weight variation, and in-vitro dissolution. Stability studies followed ICH guidelines to ensure long-term efficacy and safety. Key findings include consistent drug content, adequate hardness, and desirable swelling behavior. The optimized formulation demonstrated prolonged drug release and significant mucoadhesive properties, confirming its potential for improved therapeutic applications. Statistical analyses validated the formulation's consistency and reliability.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".