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Record W2933544291 · doi:10.1177/2042098619836032

Abuse potential of mirogabalin in recreational polydrug users

2019· article· en· W2933544291 on OpenAlexaff
Jeanne Mendell, Naama Levy‐Cooperman, Ed Sellers, Bradley Vince, Debra Kelsh, James Lee, Vance Warren, Hamim Zahir

Bibliographic record

VenueTherapeutic Advances in Drug Safety · 2019
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Toronto
FundersDaiichi Sankyo Company
KeywordsPregabalinMedicinePlaceboCrossover studyPharmacologyDrugRandomized controlled trialAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Mirogabalin is a selective calcium channel α 2 δ subunit ligand being developed to treat neuropathic pain. In accordance with US Food and Drug Administration (FDA) guidance, the human abuse potential of mirogabalin (15–105 mg) was examined, relative to placebo, diazepam (15 or 30 mg), and pregabalin (200 or 450 mg), in two single-dose, randomized, double-blind, placebo- and active-controlled crossover studies in recreational polydrug users who could discern between positive comparator and placebo. The primary endpoint was maximum observed effect ( E max ) for Drug Liking Visual Analog Scale. At therapeutic doses, mirogabalin Drug Liking E max did not differ significantly from placebo and was significantly lower than diazepam and pregabalin. This indicates therapeutic doses mirogabalin may have less abuse potential versus diazepam or pregabalin. At supratherapeutic doses (⩾4× therapeutic dose), mirogabalin had significantly higher Drug Liking E max than placebo, but lower E max than pregabalin. In both studies, therapeutic doses of mirogabalin demonstrated limited evidence of abuse potential.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.280
Teacher spread0.273 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations19
Published2019
Admission routes1
Has abstractyes

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