Population pharmacokinetic and exposure–efficacy analysis of ixekizumab in paediatric patients with moderate‐to‐severe plaque psoriasis (IXORA‐PEDS)
Bibliographic record
Abstract
AIMS: Ixekizumab is a high-affinity monoclonal antibody that selectively targets interleukin-17A used in the treatment of adult and paediatric patients with moderate-to-severe psoriasis. This analysis evaluated the pharmacokinetics (PK) of ixekizumab and the exposure-efficacy relationship in paediatric patients aged 6 to <18 years with psoriasis. METHODS: Population PK and exposure-efficacy models were developed. The models used data from paediatric patients with psoriasis participating in the Phase 3 IXORA-PEDS trial in which patients were dosed according to weight categories. The exposure-efficacy model is a Psoriasis Area and Severity Index (PASI) time course model using data up to Week 12, a co-primary efficacy endpoint. RESULTS: A 2-compartment population PK model describes the PK of ixekizumab in paediatric patients with the effect of body weight incorporated on clearance and volume terms using an allometric relationship. The weight category-based dosing ensured that ixekizumab mean trough serum concentrations in paediatric patients with psoriasis (3.20-3.33 μg/mL) were within the range of concentrations observed in adult patients with psoriasis (mean [standard deviation]: 3.48 [2.16] μg/mL) administered an efficacious dosing regimen. The observed PASI response rates at Week 12 in paediatric patients (91.9/81.8/52.5% for PASI75/90/100) are well predicted by the final exposure-efficacy model and response rates are similar or higher than those achieved in adults (86.2/66.6/35.0% for PASI75/90/100). CONCLUSION: This analysis is the first to describe the PK and exposure-efficacy relationship of ixekizumab in paediatric patients with psoriasis. The analyses support the selection of the weight category-based ixekizumab dosing regimens approved for use in paediatric patients with psoriasis.
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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 | 0.004 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".