Population Pharmacokinetic and Pharmacodynamic Modeling for the Prediction of the Extended Amlitelimab Phase 3 Dosing Regimen in Atopic Dermatitis
Bibliographic record
Abstract
Amlitelimab is a fully human, nondepleting, anti-OX40 ligand monoclonal antibody being investigated for the treatment of moderate-to-severe atopic dermatitis (AD) in adults and adolescents. Population pharmacokinetic (PopPK) and pharmacokinetic/pharmacodynamic-Eczema Area and Severity Index (PopPK/PD-EASI) models were used to inform dosing regimen selection for amlitelimab phase 3 trials. The PopPK model was developed using phase 1 (healthy volunteers) and phase 2 (participants with AD) trial data, including individual exposure variables from the STREAM-AD phase 2b trial following subcutaneous amlitelimab doses ranging from 62.5 to 250 mg given every 4 weeks (Q4W). The PopPK model was used to compute exposures for an extended dosing regimen of 250 mg Q12W (with 500 mg loading dose [+LD]). The PopPK/PD-EASI model was developed from phase 2 trials to predict treatment responses (EASI values) with selected dosing scenarios. Finally, the dose for individuals with lower body weight (i.e., < 40 kg) was determined. Utilizing the PopPK model, the amlitelimab 250 mg Q12W + LD computed exposures were between the exposures of 62.5 mg Q4W and 250 mg Q4W + LD efficacious doses in the STREAM-AD trial. Using the PopPK/PD-EASI model, the simulated efficacy for dosing scenarios of 250 mg Q12W + LD regimen from initiation or 250 mg Q4W + LD for 24 weeks followed by Q12W to Week 60 was similar to continuous 250 mg Q4W. Simulations identified that a twofold dose reduction would allow participants < 40 kg to achieve amlitelimab exposures within the range observed in participants ≥ 40 kg on 250 mg Q4W or Q12W. These results support evaluation of a Q12W dosing regimen for adults and adolescents in phase 3 trials.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".