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Record W4303699377 · doi:10.18433/jpps33081

A Survey of the Criteria Used for the Selection of Alternative Comparator Products by Participating Regulators and Organizations of the International Pharmaceutical Regulators Programme

2022· article· en· W4303699377 on OpenAlexaffvenue
Andrew Tam, Alfredo García‐Arieta, Ivana Abalos, Eduardo Agostinho Freitas Fernandes, Gustavo Mendes Lima Santos, Zulema Rodríguez Martínez, Milly Divinsky, Rami Kariv, Henrike Potthast, April C. Braddy, Clare Rodrigues, Erwin Guzmán Aurela, Liliana Carolina Arévalo González, Diego Gutierrez Triana, Ben Jones, Choongyul Ahn, Hyuna Kim, So Hee Kim, Ryosuke Kuribayashi, Aya Myoenzono, Kohei Shimojo, Joy Van Oudtshoorn, Cornelia Bigler, Ricarda Meincke, Matthias S. Roost, Chantal Walther, Li-Feng Hsu, Christopher H. Crane, Tony Jarman

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2022
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsHealth Canada
FundersEuropean Commission
KeywordsInnovatorComparatorProduct (mathematics)BioequivalenceEuropean unionBusinessComputer scienceRisk analysis (engineering)MarketingMedicinePharmacologyMathematicsEngineeringIntellectual property

Abstract

fetched live from OpenAlex

The safety and efficacy of a generic product are partly based on demonstrating bioequivalence to the innovator product; however, when the innovator product is no longer available as a comparator product, a survey conducted within the Bioequivalence Working Group for Generics (BEWGG) of the International Pharmaceutical Regulators Programme (IPRP) indicated that the criteria for selecting an alternative comparator product varies. For most members of the BEWGG, an existing marketed generic that was approved based on a comparison with the locally registered innovator product can be used, contingent on criteria that ranges from allowing any generic to be used, to allowing only specific criteria-defined generics to be used. Notwithstanding the acceptability of a generic as an alternative comparator, it is not always the preferred comparator for several jurisdictions. Some jurisdictions require the use of a locally sourced alternative innovator comparator (e.g., the same medicinal ingredient manufactured by a different company) or a foreign innovator comparator. Unlike the other members of the BEWGG, the European Union (EU) has no such options available, rather mechanisms are in place to allow manufacturers to develop a new comparator. The criteria described herein regarding the use of an alternative comparator product can also be applied to scenarios where a specific strength of a series of strengths or an innovative fixed dose combination are discontinued. The results of the survey demonstrate that while criteria for selecting alternative comparator products are not harmonized among the BEWGG participants, the common concern for all jurisdictions is to select a comparator product that meets the safety and efficacy standards of the original innovator product.

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)0.164
metaresearch head score (Gemma)0.191
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.866

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1640.191
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.009
Science and technology studies0.0020.002
Scholarly communication0.0060.004
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.106
GPT teacher head0.421
Teacher spread0.315 · 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.

Study designObservational
DomainMethods
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

Citations0
Published2022
Admission routes2
Has abstractyes

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