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Record W7042618712

Postmarketing Research for Opioid Abuse-Deterrent Formulations: A Narrative Review

2025· article· en· W7042618712 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsMiller Group (Canada)
Fundersnot available
KeywordsNarrative reviewOpioidMedical prescriptionFood and drug administrationNarcoticMillerPostmarketing surveillance
DOInot available

Abstract

fetched live from OpenAlex

Lynn Webster,1 Jeff Gudin,2 Jody L Green,3 Charles E Argoff4 1Dr. Vince Clinical Research, Overland Park, KS, USA; 2University of Miami, Miller School of Medicine, Miami, FL, USA; 3Inflexxion, a Division of Uprise Health, Irvine, CA, USA; 4Department of Neurology, Albany Medical College, Albany, NY, USACorrespondence: Lynn Webster, Executive Vice President, Scientific Affairs, Dr. Vince Clinical Research, 7401 W 91st St, Overland Park, KS, 66212, USA, Tel +1913-333-3000, Email LRWebsterMD@gmail.comAbstract: Although prescription opioids may be necessary to manage severe and persistent pain, many factors including concern for opioid abuse and misuse have led to restricted availability of these analgesics. Opioid abuse-deterrent formulations (ADFs) were developed to enhance resistance to tampering yet retain analgesic efficacy. US Food and Drug Administration (FDA) approval for the ADF designation is based on prespecified preclinical (category 1), pharmacokinetic (category 2), and/or clinical (category 3) evidence demonstrating abuse-deterrent properties. Currently, 4 opioid formulations carry the ADF designation: XTAMPZA® ER (oxycodone), OXYCONTIN® (oxycodone hydrochloride), HYSINGLA™ ER (hydrocodone bitartrate), and ROXYBOND™ (oxycodone hydrochloride). The FDA requires that ADFs undergo postapproval evaluation to assess their impact on meaningful reductions in abuse, misuse, and related clinical outcomes. An additional designation is available based on FDA assessment of these postmarket studies (category 4). However, none of the 4 opioid ADFs have yet attained this additional category 4 labeling. The impact of opioid ADFs on abuse, misuse, and related clinical outcomes is unclear. The objectives of this narrative review are 1) to describe the benefits of and need for ADFs; 2) to provide an overview of the FDA guidance for ADFs, with a focus on category 4 postmarketing requirements; and 3) to summarize select postmarketing studies of the ADF prescription opioids currently available in the US. We identified key postmarketing publications for these ADFs via PubMed searches and investigation of literature cited in relevant publications. Three opioid ADFs (XTAMPZA ER, OXYCONTIN, and HYSINGLA ER) currently report postmarketing research, generally demonstrating reduced nonoral abuse or misuse compared with non-ADFs or other ADFs. Of note, XTAMPZA ER has shown sustained lower levels of nonoral abuse or misuse compared with other ADFs, despite a substantial increase in dispensed prescriptions since its launch in 2016. Additional postmarketing research is needed, especially for HYSINGLA ER and ROXYBOND.Keywords: ADF categories, oxycodone, hydrocodone, postmarketing research

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.358
GPT teacher head0.645
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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