Yo Han Kim, Namyi Gu, Mi Jo Kim, Hee Youn Choi, Hae Sun Jeon, Eunhwa Kim, Kyun-Seop Bae, Hyeong-Seok Lim
Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, Seoul, Republic of Korea
Objectives: Ticagrelor is a reversible platelet P2Y12 receptor inhibitor which has been developed as a treatment of acute coronary syndrome. The objectives of these analysis were intended to provide a modeling and simulation methodology that could be used to characterize the pharmacokinetics(PK) and pharmacodynamics(PD) of ticagrelor.
Methods: Two studies were conducted: In vitro PD study, where we draw blood samples from 24 healthy male subjects and added ticagrelor and its active metabolite at various randomly selected concentration ranges. Then we measured platelet aggregation using an aggregometer. The in vitro pharmacodynamic data were analyzed using nonlinear mixed effects modeling (NONMEM) and response-surface pharmacodynamic model was built for ticagrelor.
In clinical PK-PD study, serial blood samples were collected from 12 healthy male subjects after single oral administration of ticagrelor 180 mg. Blood samples were processed for plasma concentrations and platelet aggregation test. Plasma concentrations of ticagrelor and its metabolite were measured by validated high performance liquid chromatography. Plasma concentration-time data were analyzed, using NONMEM to estimate population pharmacokinetic parameters and evaluate relationships between parameters.
Results: In the response surface model, the synergistic interaction was identified in the mixtures of ticagrelor and its active metabolite, AR-C124910XX. Although both ticagrelor and AR-C124910XX inhibited platelet aggregation, ticagrelor was more potent than AR-C124910XX with the IC50 of approximately 17% compared to AR-C124910XX in this study.
A three-compartment model with mixed zero order and first order absorption and lag time best described ticagrelor pharmacokinetics. Population estimates for absorption rate constant (ka), central volume of distribution (V2), systemic clearance (CL), peripheral volume of distribution (V3), inter-compartmental clearance (Q), lag time (ALAG1) and D1 were 1.23 h-1, 113 L, 29.7 L h-1, 173 L, 18.8 L h-1, 0.220 h and 0.476 h-1, respectively.
Using the PD model from in vitro study and the PK model from clinical PK-PD study, the anti-platelet effect over time on ticagrelor was simulated and compared with real observed platelet aggregation data. This showed good agreement between prediction and observation, validating the PD model built from the in vitro study.
Conclusions: The current methodology could be applied to identifying optimal dosing regimens of anti-platelet therapy and could be useful for efficient novel drug development.
References:
[1] Minto CF, Schnider TW, Short TG, Gregg KM, Gentilini A, Shafer SL. Response surface for anesthetic drug interactions. Anesthesiology 2000; 92:1603–16.
[2] Husted, S. and J.J. van Giezen, Ticagrelor: the first reversibly binding oral P2Y12 receptor antagonist. Cardiovasc Ther 2009; 27(4):259-74.
Reference: PAGE 23 (2014) Abstr 3139 [www.page-meeting.org/?abstract=3139]
Poster: Drug/Disease modeling - Other topics