Park Sung Min, Lee Joomi, Seong Sook Jin, Park Jong Gwang, Gwon Mi-Ri, Lim Mi-sun, Lee Hae Won, Yoon Young-Ran, Yang Dong Heon, Kwon Kwang-Il, Han Seunghoon
Clinical Trial Center, Kyungpook National University Hospital, Daegu, South Korea.
Department of Biomedical Science, Kyungpook National University Graduate School, Daegu, South Korea.
BMC Pharmacol Toxicol. 2014 Dec 23;15:75. doi: 10.1186/2050-6511-15-75.
Triflusal is a drug that inhibits platelet aggregation. In this study we investigated the dose-exposure-response relationship of a triflusal formulation by population pharmacokinetic (PK) and pharmacodynamic (PD) modeling of its main active metabolite, hydroxy-4-(trifluoromethyl) benzoic acid (HTB).
This study was a randomized, open-label, multiple-dose, two-period, two-treatment, comparative crossover design. All volunteers received a single oral loading dose of 900 mg of triflusal on Day 1, followed by a dose of 600 mg/day from Day 2 to 9. Using data from 34 healthy volunteers, 476 HTB plasma concentration data points and 340 platelet aggregation data points were used to construct PK and PD models respectively using NONMEM (version 6.2). As the PD endpoint was qualitative, we implemented binary analysis of 'inhibition' and 'non-inhibition' rather than using the actual value of the test. The final PK-PD model was evaluated using a visual predictive check (VPC) and bootstrap.
The time-concentration profile of HTB over the entire dosing period was described by a one-compartment model with a first-order formation rate constant for HTB. Weight was selected as a covariate for clearance and volume of triflusal, respectively. The structure and the population estimates for triflusal PK were as follows: oral clearance (CL/F) = 0.2 · (weight/71.65)(0.845) L/h, oral volume of distribution (V/F) = 8.3 · (weight/71.65) L, and k f = 0.341 h(-1). A sigmoid relationship between triflusal concentration and the probability of significant inhibition with shape factor was chosen as the final PD model. No time delay between concentration and response was identified. The final structure between predicted concentration (C(y)(pred,ij) and the probability of inhibition of platelet aggregation (IPA) relationship was as follows: Probability of IPA = C(19)(pred,ij)/((84.9)(19) µg/mL + C(19)(pred,ij)). Thus, we concluded this relationship is more like quantal concentration-response relationship. The current dosing regimen was considered to be efficacious based on the EC 50 estimate of 84.9 μg/mL obtained in this study.
A PK and binary probability PD model of triflusal was successfully developed for Korean healthy volunteers. The model may be used to further prediction inhibition of platelet aggregation by triflusal.
Clinical Research Information Service (CRIS), KCT0001299 (Registered December 5, 2014).
曲氟尿苷是一种抑制血小板聚集的药物。在本研究中,我们通过对其主要活性代谢物羟基 - 4 -(三氟甲基)苯甲酸(HTB)进行群体药代动力学(PK)和药效学(PD)建模,研究了曲氟尿苷制剂的剂量 - 暴露 - 反应关系。
本研究采用随机、开放标签、多剂量、两期、两种治疗的比较交叉设计。所有志愿者在第1天接受单次口服负荷剂量900 mg曲氟尿苷,随后从第2天至第9天每天服用600 mg。利用34名健康志愿者的数据,分别使用NONMEM(版本6.2),将476个HTB血浆浓度数据点和340个血小板聚集数据点用于构建PK和PD模型。由于PD终点是定性的,我们实施了“抑制”和“未抑制”的二元分析,而不是使用测试的实际值。使用可视化预测检查(VPC)和自抽样法对最终的PK - PD模型进行评估。
在整个给药期内,HTB的时间 - 浓度曲线用具有HTB一级生成速率常数的单室模型进行描述。体重分别被选为曲氟尿苷清除率和分布容积的协变量。曲氟尿苷PK的结构和群体估计如下:口服清除率(CL/F)= 0.2·(体重/71.65)(0.845)L/h,口服分布容积(V/F)= 8.3·(体重/71.65)L,以及kf = 0.341 h(-1)。选择曲氟尿苷浓度与具有形状因子的显著抑制概率之间的S形关系作为最终的PD模型。未发现浓度与反应之间的时间延迟。预测浓度(C(y)(pred,ij))与血小板聚集抑制概率(IPA)关系的最终结构如下:IPA概率 = C(19)(pred,ij)/((84.9)(19) μg/mL + C(19)(pred,ij))。因此,我们得出结论,这种关系更类似于定量浓度 - 反应关系。基于本研究获得 的84.9 μg/mL的EC50估计值,当前给药方案被认为是有效的。
成功为韩国健康志愿者建立了曲氟尿苷的PK和二元概率PD模型。该模型可用于进一步预测曲氟尿苷对血小板聚集的抑制作用。
临床研究信息服务(CRIS),KCT0001299(2014年12月5日注册)。