MétaCan
Menu
Back to cohort
Record W4402580922 · doi:10.1093/jlb/lsae020

Biosimilar approval pathways: comparing the roles of five medicines regulators

2024· article· en· W4402580922 on OpenAlexfundaboutno aff
Ryan P. Knox, Vineet Desai, Ameet Sarpatwari

Bibliographic record

VenueJournal of Law and the Biosciences · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsnot available
FundersGovernment of CanadaAustralian GovernmentArnold Ventures
KeywordsBiosimilarDrug approvalMedicineAgency (philosophy)Public economicsPharmacologyBusinessDrugEconomics

Abstract

fetched live from OpenAlex

Biologics are playing an increasingly important role in health care globally but are placing a substantial burden on payers. The development of biosimilars-drugs that are highly similar to and have no clinically meaningful differences from originator biologics-is critical to improving the affordability and accessibility of these medications. Medicines regulators, however, have had varied success with biosimilars to date. We examined agency guidance documents, peer-reviewed articles, and gray literature related to biosimilars in Australia, Canada, the European Union, the United Kingdom, and the United States to evaluate variations in the approaches to biosimilar approval taken by their respective medicines regulators. We found that the medicines regulators take similar approaches to biosimilar approvals, but that differences in their policies and their jurisdiction's laws regarding testing requirements, indication extrapolation, exclusivities, and substitution may contribute to the varied successes of biosimilars observed. Policies supportive of product-specific guidance, extrapolation, shorter exclusivity periods, and substitution were correlated with greater success in biosimilar approval and uptake. As medicines regulators work to promote biosimilars, understanding the impact of these laws and policies is crucial. Reforms consistent with these policies can create regulatory environments more supportive of biosimilar approvals, promoting access to affordable biologics for patients globally.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
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 head0.030
GPT teacher head0.283
Teacher spread0.253 · 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.

Study designTheoretical or conceptual
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

Citations7
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Law and the BiosciencesSame topicBiosimilars and Bioanalytical MethodsFrench-language works237,207