SERENE ER Analysis Part 2 SERENE-UC: Exposure-response Analysis of Higher Versus Standard Adalimumab Dosing Regimens for Patients with Moderately to Severely Active Ulcerative Colitis.
Sven StodtmannMong-Jen ChenAna Victoria Ponce-BobadillaTricia K Finney-HaywardJasmina KalabicNael M MostafaPublished in: Clinical pharmacology in drug development (2024)
SERENE UC (NCT02065622) evaluated whether a higher adalimumab induction regimen improved patients with ulcerative colitis (UC) response, but a flat dose-response relationship was found in the induction study. We investigated exposure-response (ER) relationships in induction and maintenance studies considering patients' baseline characteristics. Adalimumab exposures were simulated using the established population pharmacokinetic model. Multivariable logistic regressions were used to assess the efficacy endpoints (clinical remission, endoscopic remission, endoscopic improvement) at weeks 8 and 52. In the induction study, an increasing ER trend with heterogeneity between induction regimens was shown, suggesting average concentration (C avg ) had a significant impact on primary efficacy endpoints within each group. However, data were not described by a single ER curve. Using inverse effective clearance as the exposure metric described trends across induction regimens with a single curve. Patients with inherently lower effective adalimumab clearance responded better. The patient response rates at week 52 showed no heterogeneity. A short-term increase in adalimumab dose did not drive better responses for induction, and apparent ER relationships were better explained by patient-inherent lower clearance. Conversely, during maintenance up to week 52, increasing the concentration via dose translated to better responses more robustly. The ER findings for SERENE UC were consistent with SERENE CD.
Keyphrases
- ulcerative colitis
- rheumatoid arthritis
- endoplasmic reticulum
- estrogen receptor
- juvenile idiopathic arthritis
- breast cancer cells
- ejection fraction
- machine learning
- single cell
- disease activity
- ultrasound guided
- systemic lupus erythematosus
- magnetic resonance imaging
- big data
- clinical trial
- artificial intelligence
- chronic kidney disease
- patient reported
- single molecule