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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".