MétaCan
Menu
Back to cohort
Record W1487549987 · doi:10.18433/j32g6p

Do Regulatory Bioequivalence Requirements Adequately Reflect the Therapeutic Equivalence of Modified-Release Drug Products?

2010· article· en· W1487549987 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2010
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBioequivalenceEquivalence (formal languages)PharmacokineticsPharmacologyDrugMetric (unit)NifedipineMedicineMathematicsEconomicsInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To demonstrate that current regulatory requirements for bioequivalence (BE) do not always reflect therapeutic equivalence. To investigate the potential usefulness of an additional metric, the partial AUC. METHODS: Pharmacokinetic information was reviewed and evaluated on the pharmacokinetics of modified-release methylphenidate and nifedipine products. RESULTS: In studies of modified-release products of methylphenidate as well as of nifedipine, traditional regulatory criteria found two formulations to be bioequivalent even though their concentration profiles strongly diverged during the period of absorption. An additional metric, partial AUC, discriminated strongly between the concentrations of the drug products. CONCLUSIONS: The current regulatory criteria for the acceptance of BE do not always reflect the therapeutic equivalence of modified-release drug products. With some modified-release products, the application of an additional metric, the partial AUC, yields an improved discriminatory representation.

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.

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)0.024
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.675
GPT teacher head0.613
Teacher spread0.062 · 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