Clinical and Molecular Effect of the Anti– <scp>IL</scp> ‐18 Antibody Aletekitug in Adults With Atopic Dermatitis
Bibliographic record
Abstract
BACKGROUND: Interleukin-18 (IL-18) is a pleiotropic cytokine implicated in atopic dermatitis (AD), affecting both type (T)1 and T2 immune pathways. An anti-IL-18 monoclonal antibody, aletekitug, was evaluated for its clinical and molecular effects in patients with moderate to severe AD. METHODS: This randomised, double-blind, parallel-group, placebo-controlled, 24-week study assessed adults with moderate-to-severe AD who were biologic-naïve or dupilumab-inadequate responders/intolerant. Participants received a single intravenous (IV) infusion of aletekitug 2 mg/kg or placebo. The primary endpoint was percentage change from baseline (PCFB) in Eczema Area and Severity Index (EASI) score at Week 12. Other endpoints included safety, patient-reported outcomes (PROs) and transcriptomics. RESULTS: Thirty-four participants (aletekitug, n = 23; placebo, n = 11) were randomised. A greater reduction in the PCFB in EASI score at Week 12 was demonstrated for patients who received aletekitug versus placebo (posterior median PCFB [95% credible intervals]: aletekitug, -68.3% [-79.68, -56.68]; placebo, -32.9% [-45.74, -21.10]), with effects still apparent at Week 24. Aletekitug improved PRO measures of itch, sleep disturbance, fatigue and quality of life versus placebo up to Week 24. Transcriptome analysis suggested aletekitug modulated lesional skin towards a non-lesional profile and exerted broad immunomodulatory effects, impacting several AD-associated signalling pathways, not limited to T2 immunity. Aletekitug was well tolerated, with no serious adverse events reported. CONCLUSION: A single 2 mg/kg IV dose of aletekitug was associated with improved outcomes at Week 12, which were sustained to Week 24, and modulated immune mechanisms beyond T2 inflammation. These results support IL-18 as a potential therapeutic target in moderate-to-severe AD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".