Pharmacokinetic disposition of topical phosphodiesterase-4 inhibitor E6005 in patients with atopic dermatitis
Bibliographic record
Abstract
Background: A novel topical phosphodiesterase-4 inhibitor E6005 shows potential as effective treatment option for atopic dermatitis (AD); however, systemic exposure may cause potentially undesirable adverse reactions. In this study, we evaluated the relationship between the systemic exposure of E6005 and clinical parameters including skin condition and the incidence of AEs in patients with AD.Methods: The association analysis used the clinical data obtained in a previously conducted clinical study with topical E6005 in adult patients with AD. To estimate associations with drug exposure, generalized estimating equation logistic regression models were used, along with clinical data and plasma concentrations of M11, the major metabolite of E6005 (as an indicator for E6005 exposure).Results: The metabolite M11 was detected in 62 of 221 plasma samples from 72 subjects. From association analysis, SCORAD-A obtained prior to E6005 treatment was identified as the clinical parameter influenced to M11 detection with statistical significance (p = .003). M11 detection was not clearly associated with the incidence of adverse events occurred.Conclusion: Exposure to topical E6005 is associated with the eczema-associated area, however, that is not distinctly associated with its adverse drug reactions occurred after drug applications possibly due to E6005’s characteristics of tissue distribution.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".