Population PK–PD analyses of CD25 occupancy, CD56brightNK cell expansion, and regulatory T cell reduction by daclizumab HYP in subjects with multiple sclerosis

Abstract

Aim: Daclizumab high yield process (HYP) is a humanized IgG1 monoclonal antibody that binds to the α-subunit of the interleukin-2 receptor and is being developed for treatment of multiple sclerosis (MS). This manuscript characterized the pharmacokinetic–pharmacodynamic (PK–PD) relationships of daclizumab HYP in subjects with MS. Methods: Approximately 1400 subjects and 7000 PD measurements for each of three biomarkers [CD25 occupancy, CD56brightnatural killer (NK) cell count, regulatory T cell (Treg) count] from four clinical trials were analyzed using non-linear mixed effects modelling. Evaluated regimens included 150 or 300 mg subcutaneous (s.c.) every 4 weeks. Results: CD25 occupancy was characterized using a sigmoidal maximum response (Emax) model. Upon daclizumab HYP treatment, CD25 saturation was rapid with complete saturation occurring after approximately 7 h and maintained when daclizumab HYP serum concentration was ≥5 mg l-1. After the last 150 mg s.c. dose, unoccupied CD25 returned to baseline levels in approximately 24 weeks, with daclizumab HYP serum concentration approximately ≤1 mgl-11L. CD56brightNK cell expansion was characterized using an indirect response model. Following daclizumab HYP 150 mg s.c. every 4 weeks, expansion plateaus approximately at week 36, at which the average maximum expansion ratio is 5.2. After the last dose, CD56brightNK cells gradually declined to baseline levels within 24 weeks. Treg reduction was characterized by a sigmoidal Emaxmodel. Average maximum reduction of 60% occurred approximately 4 days post 150 mg s.c. dose. After the last dose, Tregs were projected to return to baseline levels in approximately 20 weeks. Conclusions: Robust PK–PD models of CD25 occupancy, CD56brightNK cell expansion and Treg reduction by daclizumab HYP were developed to characterize its key pharmacodynamic effects in the target patient population.