Prospective dose selection and acceleration of paliperidone palmitate 3‐month formulation development using a pharmacometric bridging strategy. (24th July 2016) - Samtani, Mahesh N.; Nandy, Partha; Ravenstijn, Paulien; Remmerie, Bart; Vermeulen, An; Russu, Alberto; D'hoore, Peter; Baum, Ellen Z.; Savitz, Adam; Gopal, Srihari; Hough, David
Abstract : Aims: To prospectively select the dose of the paliperidone palmitate 3‐month (PP3M) formulation, using a pharmacometric bridging strategy based on the paliperidone palmitate 1‐month (PP1M) formulation previously approved for schizophrenia treatment. Methods: Pharmacokinetic (PK) data from a 6‐month interim analysis of a single dose PP3M Phase I clinical trial was integrated with a previously developed PP1M population‐PK model. The model was updated to incorporate formulation as a covariate on absorption parameters and to explore the most critical design element of the Phase III study: the PP1M‐to‐PP3M dose multiplier for patients switching formulations. Plasma paliperidone concentrations were measured at predetermined intervals during Phase III, enabling comparison of the multiple‐dose PK between PP1M and PP3M. Exposure matching was assessed graphically to determine whether paliperidone plasma concentrations from the two formulations overlapped. Results: Prospective steady‐state PK simulations revealed that a 3.5 multiple of the PP1M dose would yield a corresponding PP3M dose with comparable exposure. The prospective pharmacometric simulation and observed Phase III PK data agreed closely. Phase III results confirmed the hypothesis that efficacy of PP3M was noninferior to that of PP1M. The similarity in exposures between the two formulations was likely a key determinant of the equivalent efficacy between the two products observed in the Phase III study. Conclusions: Successful prospective PP3M Phase III clinical trial dose selection was achieved through the use of pharmacometric bridging, without conducting a Phase II study and using only limited Phase I data for PP3M. We estimate that this strategy reduced development time by 3–5 years and may be applicable to other drug development projects.