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Record W2590797524 · doi:10.1080/13543776.2017.1296950

Patent disclosure requirements for therapeutic antibody patents

2017· review· en· W2590797524 on OpenAlexaboutno aff
Carmela De Luca, Anastassia Trifonova

Bibliographic record

VenueExpert Opinion on Therapeutic Patents · 2017
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessAntibodyPharmacologyMedicineImmunology

Abstract

fetched live from OpenAlex

INTRODUCTION: Therapeutic antibodies have grown to become an important product class within the biopharmaceutical market. A prerequisite to their commercialization is adequate patent protection. Disclosure requirements and the types of claims available in different jurisdictions can impact the scope of protection available for antibodies. Areas covered: A comparative review of statutory bases, patent office practices and selected decisions in Canada, the United States and the United Kingdom related to disclosure requirements is provided. Expert opinion: Differences in disclosure requirements exist in different jurisdictions which can impact the type of claims obtained and their survival when attacked in litigation. Including a wide variety of claim types is a key strategy to ensuring therapeutic antibodies are adequately protected. Method of use claims may provide advantages and broader protection in some circumstances and should also be considered.

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)0.010
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.040
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0230.003

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 head0.620
GPT teacher head0.482
Teacher spread0.137 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2017
Admission routes1
Has abstractyes

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