Modulation of mesalamine release from enteric-coated matrix tablets using natural polysaccharides for localized colonic delivery
Bibliographic record
Abstract
Background: Inflammatory bowel diseases (IBD) require effective colon-targeted drug delivery for improved therapeutic efficacy and minimized systemic side effects. Objectives: The objective of this research was to develop and evaluate novel colon-targeted matrix tablet formulations of mesalamine (5-aminosalicylic acid) for the treatment of IBD. Materials and Methods: Mesalamine matrix tablets were prepared by wet granulation technique using pH-sensitive polymers (HPMC K4M) and biodegradable natural polysaccharides (pectin, chitosan, and guar gum). Tablets were characterized for physicochemical properties, drug content, and in vitro drug release. Compatibility studies using FTIR and DSC confirmed no interaction between mesalamine and polymers. The optimized formulations were enteric-coated with Eudragit S100 and ethyl cellulose. Drug release kinetics and stability studies were conducted. Results and Discussion: The uncoated formulations (M3, M6, M7) showed adequate protection against drug release in simulated gastric (0-2 h) and intestinal (2-5 h) fluids. The enteric-coated formulations (ME3, ME6, ME7) exhibited a lag time of around 2 hours and restricted drug release (<5%) in simulated gastric and intestinal fluids up to 5 hours. However, in simulated colonic fluid (pH 6.8) containing 4% rat cecal contents, these formulations showed enhanced drug release (71-83% in 12 h) due to biodegradation of polymeric matrices by colonic enzymes. Drug release kinetics indicated anomalous transport or super case-II transport mechanisms. Stability studies at 40°C/75% RH for 3 months revealed no significant changes. Conclusion: The developed colon-targeted mesalamine matrix tablets demonstrated the potential to protect the drug from release in the upper GIT while facilitating targeted drug delivery to the colon, which could improve therapeutic efficacy and minimize systemic side effects in the treatment of IBD.
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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) | 0.000 | 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".