Malidi Ahamadi
Merck Research Laboratories, Merck & Co., Inc., Whitehouse Station, NJ, USA;
Objectives: Preladenant is an Adenosine type 2A (A2a) receptor antagonist that was in development for Parkinson Disease (PD). Population exposure-response analysis was applied to: quantify efficacy and safety relationships for preladenant in a Phase 2B trial including individuals with Parkinson disease and motor fluctuations on levodopa therapy; to assess interaction with concomitant anti-PD medications; to identify subpopulations demonstrating differential response; and to assist future Parkinson’s disease clinical studies.
Methods: A total of 199 individuals with moderate to severe idiopathic Parkinson disease provided data for this analysis. Individuals on a stable anti-parkinsonian treatment regimen were treated with placebo or oral preladenant, 1, 2, 5 or 10 mg BID. A hierarchical, longitudinal PK-PD model related predicted preladenant concentration to the probability of a patient being in the “off” state at each half-hourly assessment over the three days preceding a clinical visit.
Results: A two-compartment population PK model with transit compartment absorption model described preladenant concentration. The effect of concomitant anti-PD medication was modeled based on prior historical data in combination with the reported frequency of a given patient’s treatment regimen. An Emax model of the synergistic effect of preladenant described the reduction in “off” probability as a function of time and concomitant anti-PD drug effect. To explore implications of the models for development decisions, statistically realistic predictions of how Preladenant affects key “off” time endpoints were generated. The final model was used to predict efficacy responses for subjects under possible treatment and population scenarios.
Conclusions: This work identified an exposure-relationship between preladenant and “off” probability. Concomitant treatment frequency was identified as a key covariate predicting this endpoint. Simulations based on this model provided a quantitative framework in support of dosing and other development recommendations. More frequent levodopa users have less “off” time response. Future clinical needs to consider this important factor.
References:
[1] Hauser, R. A.; Cantillon, M.; Pourcher, E.; Micheli, F.; Mok, V.; Onofrj, M.; Huyck, S.; Wolski, K. (2011). “Preladenant in patients with Parkinson’s disease and motor fluctuations: a phase 2, double-blind, randomised trial”. The Lancet Neurology 10 (3): 221–229.
[2] Inaki F. Trockmiz, PhD, Tarja H. Naukkarinen, MSc, Hanna M. Ruottinen, MD, Urpo K. Rinne, MD, Ariel Gordin, MD, and Mats 0. Karlsson, PhD, Population pharmacodynamic modeling of levodopa in patients with Parkinson’s disease receiving entacapone, Clin Pharmacol Ther 1998;64:106-16-16
Reference: PAGE 25 () Abstr 5924 [www.page-meeting.org/?abstract=5924]
Poster: Drug/Disease modeling - CNS