An In Vitro Analysis of Disintegration Times of Different Formulations of Olanzapine Orodispersible Tablet: A Preliminary Report
Bibliographic record
Abstract
BACKGROUND: Orodispersible tablets (ODTs) are tablet or wafer forms of medication that disintegrate in the mouth, aided only by saliva. ODTs rely on different fast dissolve/disintegration manufacturing technologies. OBJECTIVES: Disintegration time differences for several olanzapine ODT forms were investigated. Risperdal M-Tab(®) was included as a non-olanzapine ODT comparator. RESEARCH DESIGN AND METHODS: Eleven olanzapine ODT examples and orodispersible risperidone strengths were evaluated in vitro for formulation composition, manufacturing method, disintegration and dissolution characteristics, and formulation differences in comparison with freeze dried Zydis(®) ODT. Automated dissolution test equipment captured ODT dissolution rates by measuring real-time release of active ingredient. A high-speed video camera was used to capture tablet disintegration times in warm simulated saliva. MAIN OUTCOME MEASURE: The main outcome measure was the disintegration and dissolution characteristics of the ODT formulations. RESULTS: The ODT manufacturing method was associated with time to disintegrate; the fastest were freeze dried tablets, followed by soft compressed tablets and then hard/dense tablets. Olanzapine Zydis(®) was the only ODT that completely disintegrated in less than 4 s for all strengths (5, 10, 15, and 20 mg), followed by 5-mg Prolanz FAST(®) (12 s) and then risperidone ODT 4 mg (40 s). Reasons for slow dissolution of the olanzapine generics may include low product potency, excipient binding, excipient solubility, active ingredient particle size and incomplete disintegration. CONCLUSIONS: Differences in the formulation and manufacturing process of olanzapine ODTs appear to have a strong influence on the disintegration time of the active compound; differences that may potentially impact their use in clinical practice.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".