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Record W4323321720 · doi:10.1377/hlthaff.2022.00873

Patent Challenges And Litigation On Inhalers For Asthma And COPD

2023· article· en· W4323321720 on OpenAlexaff
Sanjay G. Reddy, Reed F. Beall, S. Sean Tu, Aaron S. Kesselheim, William B. Feldman

Bibliographic record

VenueHealth Affairs · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeneric drugCertificationFormularyParagraphBrand namesMedicineFood and drug administrationBusinessCompetition (biology)TyingAsthmaMarketingDrugPharmacologyLaw

Abstract

fetched live from OpenAlex

Between 1986 and 2020 the Food and Drug Administration (FDA) approved fifty-three brand-name inhalers for asthma and chronic obstructive pulmonary disease (COPD), but by the end of 2022 only three of those inhalers faced independent generic competition. Manufacturers of brand-name inhalers have created long periods of market exclusivity by obtaining multiple patents, many on the delivery devices rather than the active ingredients, and by introducing new devices that contain old active ingredients. Limited generic competition for inhalers has raised questions about whether the Drug Price Competition and Patent Term Restoration Act of 1984, also known as the Hatch-Waxman Act, for challenging patents is adequately facilitating the entry of complex generic drug-device combinations. For the fifty-three brand-name inhalers approved during the period 1986-2020, generic manufacturers filed challenges authorized by the Hatch-Waxman Act, which are known as paragraph IV certifications, on only seven products (13 percent). The median time from FDA approval to first paragraph IV certification was fourteen years. Paragraph IV certifications resulted in approved generics for only two products, each of which experienced fifteen years of market exclusivity before generic approval. Reform of the generic drug approval system is critical to ensuring the timely availability of competitive markets for generic drug-device combinations such as inhalers.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.214
GPT teacher head0.326
Teacher spread0.112 · 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 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

Citations9
Published2023
Admission routes1
Has abstractyes

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