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Record W2793257861 · doi:10.1002/cpdd.439

Systemic Pharmacokinetics, Safety, and Preliminary Efficacy of Topical AhR Agonist Tapinarof: Results of a Phase 1 Study

2018· article· en· W2793257861 on OpenAlexaff
Robert Bissonnette, Lakshmi Vasist, Jonathan Bullman, Therese Collingwood, Geng Chen, Tomoko Maeda‐Chubachi

Bibliographic record

VenueClinical Pharmacology in Drug Development · 2018
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsInnovaderm (Canada)
FundersGlaxoSmithKline
KeywordsMedicineTolerabilityPharmacokineticsNonsteroidalAtopic dermatitisIncidence (geometry)CohortAdverse effectSafety profileOpen labelPharmacologyDermatologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Tapinarof cream is a novel topical nonsteroidal agent that represents a unique class of anti‐inflammatory molecules targeting the aryl hydrocarbon receptor. Study 201851 was an open‐label, 2‐cohort sequential study that assessed the systemic pharmacokinetics, safety, and efficacy of tapinarof in adults with moderate to severe atopic dermatitis. A total of 11 participants were enrolled: 5 received 2% cream, and 6 received 1% cream. Tapinarof was systemically absorbed, and measurable amounts were detected in both cohorts. Generally, plasma exposure was greater with the 2% cream and decreased from day 1 to day 21. Median T max ranged from 1 to 4 hours. Preliminary efficacy results were similar between the 1% and 2% concentrations, with the 1% cream showing better tolerability based on 3 subjects in the 2% cohort who discontinued treatment because of systemic AEs. The efficacy and safety of 1% tapinarof support results of previous positive studies that used a different formulation. However, conclusions in the present study are limited because of the open‐label design and small number of participants. The 1% cream was selected as the concentration for use in future studies because of its lower AE incidence and efficacy comparable to the 2% cream.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.788

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.424
Teacher spread0.380 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations40
Published2018
Admission routes1
Has abstractyes

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