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Practical Management of Biosimilar Use in Inflammatory Bowel Disease (IBD): A Global Survey and an International Delphi Consensus

2023· preprint· en· W4386332198 on OpenAlexafffund
Ferdinando D’Amico, Virginia Solitano, Fernando Magro, Pablo A. Olivera, Jonas Halfvarson, David T. Rubin, Axel Dignaß, Sameer Al Awadhi, Taku Kobayashi, Natália Sousa Freitas Queiroz, Marta Calvo, Paulo Gustavo Kotze, Subrata Ghosh, Laurent Peyrin‐Biroulet, Silvio Danese

Bibliographic record

VenuePreprints.org · 2023
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsMcGill University Health CentreLunenfeld-Tanenbaum Research InstituteWestern University
FundersUCB PharmaJanssen PharmaceuticalsGenentechNorgineCelltrionAstellas PharmaEisaiMitsubishi Tanabe Pharma CorporationCelgenePfizerBiogenEA Pharma Co., Ltd.Gilead SciencesSeres TherapeuticsAstraZenecaEli Lilly and CompanySamsungBristol-Myers SquibbDr. Falk PharmaVifor PharmaHospital for Sick ChildrenKyorin PharmaceuticalTillotts PharmaAmgenNovo NordiskFalk FoundationNational Science Foundation
KeywordsBiosimilarInflammatory bowel diseaseDelphi methodMedicineDelphiHealth careInflammatory Bowel DiseasesKnowledge managementIntensive care medicineDiseaseBusinessComputer scienceEconomicsEconomic growth

Abstract

fetched live from OpenAlex

While biologic originators’ patents are expiring, biosimilars are emerging to take their place, offering significant cost savings to healthcare systems. Many challenges still need to be addressed in the clinical practice of inflammatory bowel disease (IBD). A global survey was organized to highlight physicians’ current knowledge and beliefs and to gain insight about their practical management and remaining concerns and obstacles associated with starting a biosimilar, switching from an originator to a biosimilar, or switching from one biosimilar to another (multiple switches and reverse switching). Fifteen physicians with expertise in the field of IBD from 13 countries attended a virtual international consensus meeting to develop practical guidance regarding biosimilar adoption worldwide, considering the survey results. Consensus was reached on 10 statements regarding biosimilar effectiveness, safety, indications and rationale, multiple switches, therapeutic drug monitoring of biosimilars, non-medical switching and future perspectives.

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)0.077
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0770.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.003
Scholarly communication0.0020.003
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.239
GPT teacher head0.431
Teacher spread0.192 · 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.

Study designQualitative
DomainMethods
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

Citations6
Published2023
Admission routes2
Has abstractyes

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