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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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.002

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 teacher head, not a consensus.

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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