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Record W3005819287 · doi:10.17925/enr.2019.14.2.73

Ozanimod in Multiple Sclerosis

2019· article· en· W3005819287 on OpenAlexafffund
Beyza Ciftci-Kavaklioglu, E. Ann Yeh

Bibliographic record

VenueEuropean Neurological Review · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsUniversity of TorontoSickKids Foundation
FundersJuno TherapeuticsOntario Institute for Regenerative MedicineHospital for Sick ChildrenMultiple Sclerosis SocietyAlexion PharmaceuticalsF. Hoffmann-La RocheStem Cell NetworkBiogenNational Multiple Sclerosis Society
KeywordsMedicineMultiple sclerosisPhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

Over the past decade, many new and effective therapies for multiple sclerosis (MS) have been approved for use, including a therapy, fingolimod, whose mechanism of action is the non-selective modulation of the sphingosine-1-phosphate receptor (S1PR).While this therapy is effective for MS, cardiac and other side effects have prompted the development of therapies in this class with reduced cardiac effects.In this article, we review the biological basis for, and clinical trials related to, one such therapy, ozanimod, a small-molecule S1PR modulator with greater selectivity for non-cardiac receptor subtypes than fingolimod.We review phase I pharmacokinetic and pharmacodynamic trials and pivotal clinical trials investigating the safety and efficacy of ozanimod.Together, these trials suggest superior efficacy over interferon beta-1a in relapsing MS and good tolerability.Future studies are needed to establish whether this agent is associated with fewer unwanted cardiac effects than its predecessor, fingolimod.

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: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.004

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 head0.044
GPT teacher head0.238
Teacher spread0.194 · 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
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

Citations0
Published2019
Admission routes2
Has abstractyes

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