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Record W2946162392 · doi:10.3390/ph12020078

Tegsedi (Inotersen): An Antisense Oligonucleotide Approved for the Treatment of Adult Patients with Hereditary Transthyretin Amyloidosis

2019· article· en· W2946162392 on OpenAlexaboutno aff
Luı́s Gales

Bibliographic record

VenuePharmaceuticals · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaHorizon 2020 Framework Programme
KeywordsTransthyretinAmyloidosisMedicinePolyneuropathyAmyloid polyneuropathyEuropean commissionCardiac amyloidosisOligonucleotideAmyloid (mycology)PharmacologyInternal medicinePathologyDiseaseDNAGeneticsBiologyEuropean unionBusiness

Abstract

fetched live from OpenAlex

Tegsedi (Inotersen) is a chemically modified antisense oligonucleotide that inhibits the hepatic production of transthyretin (TTR). Several single-point mutations in TTR destabilize its structure, leading to the aggregation and accumulation of amyloid deposits in the nervous system, heart, kidneys and eyes. In July 2018, Tegsedi was approved by the European Commission for use in adults with stage one and two polyneuropathies. Later on, in October 2018, the FDA and Health Canada also approved its use for the treatment of the polyneuropathy of hereditary transthyretin-mediated amyloidosis (hATTR) in adults in the U.S. and Canada. Tegsedi was developed by Ionis Pharmaceuticals, the company that holds the global marketing license, together with its subsidiary Akcea Therapeutics.

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)0.000
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.293
Teacher spread0.278 · 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

Citations73
Published2019
Admission routes1
Has abstractyes

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