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Record W4414084632 · doi:10.2196/70312

Therapeutic Drug Monitoring for Precision Dosing of Janus Kinase Inhibitors: Protocol for a Prospective Observational Study

2025· article· en· W4414084632 on OpenAlexvenueno aff
Jérémie Tachet, Laurent A. Décosterd, Monia Guidi, François Girardin

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsObservational studyDosingTherapeutic drug monitoringProtocol (science)Janus kinaseDrug

Abstract

fetched live from OpenAlex

BACKGROUND: Janus kinase inhibitors (JAKIs) are small molecules used orally to treat inflammatory and hematological disorders. They have demonstrated impressive efficacy across multiple indications. However, concerns have emerged regarding their safety profile. Despite their growing clinical use, therapeutic drug monitoring is not yet established for JAKIs, but it could help address exposure-dependent efficacy and tolerability issues through individualized treatment approaches. OBJECTIVE: This protocol aims to characterize the pharmacokinetics of the 6 most prescribed JAKIs in Switzerland (abrocitinib, baricitinib, fedratinib, ruxolitinib, tofacitinib, and upadacitinib) and identify factors influencing drug exposure. It seeks to explore exposure-response relationships to assess the impact of drug exposure markers on efficacy and safety. Ultimately, these findings will contribute to establishing therapeutic intervals. METHODS: This prospective observational study, conducted throughout Switzerland, was approved by the Cantonal Ethics Committee in August 2023. Consenting adults (aged ≥18 years) who are capable of judgment and who are prescribed JAKIs are enrolled in the study, either for sparse sampling during routine medical visits to collect trough or random plasma concentrations or for a detailed pharmacokinetic substudy involving serial blood sampling over an 8-hour period. The characterization of JAKI pharmacokinetics, including associated variability and the effect of specific covariates, such as age, body weight, BMI, sex, disease type, drug-drug interactions, or concomitant pathophysiological conditions, will be performed using nonlinear mixed effect modeling techniques. Relationships between JAKI exposure and efficacy and safety will be assessed. RESULTS: By August 2024, a total of 276 blood samples were collected from 107 patients, the majority being female individuals (n=62, 57.9%). The patients had a median age of 51 (range 17-87) years and a median body weight of 69 (range 39-132) kg. Most patients recruited were taking ruxolitinib (n=44, 41.1%), upadacitinib (n=39, 36.4%), or baricitinib (n=11, 10.3%). CONCLUSIONS: The framework of the study will allow the characterization of the pharmacokinetic profiles of JAKIs and their variability in real-world conditions. On the basis of novel therapeutic drug monitoring approaches, we expect to explore the relationship between drug exposure, treatment response, and tolerability, providing essential information for precise dose optimization. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/70312.

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)0.039
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.039
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.037
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0330.007

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 head0.360
GPT teacher head0.588
Teacher spread0.228 · 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 designObservational
Domainnot available
GenreProtocol

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

Citations2
Published2025
Admission routes1
Has abstractyes

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