Abuse-deterrent features of an extended-release morphine drug product developed using a novel injection-molding technology for oral drug delivery
Bibliographic record
Abstract
OBJECTIVE: A novel technology platform (Guardian™ Technology, Egalet Corporation, Wayne, PA) was used to manufacture morphine abuse-deterrent (AD), extended-release (ER), injection-molded tablets (morphine-ADER-IMT; ARYMO® ER [morphine sulfate] ER tablets; Egalet Corporation), a recently approved morphine product with AD labeling. The aim of this article is to highlight how the features of Guardian™ Technology are linked to the ER profile and AD characteristics of morphine-ADER-IMT. RESULTS: The ER profile of morphine-ADER-IMT is attributed to the precise release of morphine from the polymer matrix. The approved dosage strengths of morphine-ADER-IMT are bioequivalent to corresponding dosage strengths of morphine ER (MS Contin®; Purdue Pharma LP, Stamford, CT). Morphine-ADER-IMT was very resistant to physical manipulations intended to reduce particle size, with <10 percent of particles being reduced to <500µm, regarded by the US Food and Drug Administration as a relevant cutoff for potential insufflation in their generic solid oral AD opioid guidance. Furthermore, morphine was not readily extracted from the polymer matrix of morphine-ADER-IMT in small- or large-volume solvent extraction studies that evaluated the potential for intravenous and oral abuse. CONCLUSIONS: The ER profile and AD characteristics of morphine-ADER-IMT are a result of Guardian™ Technology. The combination of the polyethylene oxide matrix and the use of injection molding differentiate morphine-ADER-IMT from other approved AD opioids that deter abuse using physical and chemical barriers. The high degree of flexibility of the Guardian™ Technology enables the development of products that can be tailored to almost any desired release profile; as such, it is a technology platform that may be useful for the development of a wide range of pharmaceutical products.
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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".