Kaessner Nele, Nave Rüdiger, Roepcke Stefan, Facius Axel, Lahu Gezim
Nycomed: a Takeda Company, Konstanz, Germany.
Int J Clin Pharmacol Ther. 2012 Sep;50(9):665-77. doi: 10.5414/CP201737.
The development of intranasal fentanyl (INFS) aimed for a rapid treatment of breakthrough pain (BTP) in cancer patients. The pharmacokinetics (PK) of INFS was well characterized in healthy subjects, while PK investigations in cancer patients are limited.
The objective was to develop a population PK model for fentanyl in volunteers and patients following INFS administration, to evaluate the influence of potential covariates and to simulate the exposure of fentanyl after repeated dosing in cancer patients.
PK data from ten clinical trials were used for model development. The final model was validated with nonparametric bootstrap and visual predictive check. In addition, the secondary PK parameters (AUC0-tlast, Cmax, tmax) of a separate validation data set of INFS were predicted and compared to noncompartmental analysis results. Afterwards, repeated dose PK profiles in cancer patients were simulated.
Plasma profiles after INFS administration were best described by a three-compartment model. Significant covariate relationships were identified for naltrexone and oxymetazoline co-treatment. Influences of body weight, BMI, sex and cancer patient as subject type were considered not to be clinically relevant. PK parameters for subpopulations of cancer patients were derived. Steady state simulations revealed that an extension from the current SmPC scenario to 6 pain episodes per day would yield similar Cmax values.
A robust population PK model for INFS was developed. The model enhances the understanding of fentanyl PK after INFS dosing in cancer patients with BTP, a population for whom real-life data would be very hard to obtain.
鼻内芬太尼(INFS)的研发旨在快速治疗癌症患者的爆发性疼痛(BTP)。INFS的药代动力学(PK)在健康受试者中已得到充分表征,而在癌症患者中的PK研究有限。
建立志愿者和患者在给予INFS后芬太尼的群体PK模型,评估潜在协变量的影响,并模拟癌症患者重复给药后芬太尼的暴露情况。
来自十项临床试验的PK数据用于模型开发。最终模型通过非参数自助法和可视化预测检验进行验证。此外,预测了INFS单独验证数据集的次要PK参数(AUC0 - tlast、Cmax、tmax),并与非房室分析结果进行比较。之后,模拟了癌症患者的重复剂量PK曲线。
给予INFS后的血浆曲线用三室模型能得到最佳描述。确定了纳曲酮和羟甲唑啉联合治疗的显著协变量关系。体重、BMI、性别和癌症患者作为受试者类型的影响被认为在临床上不相关。得出了癌症患者亚组的PK参数。稳态模拟显示,将当前的产品特性总结(SmPC)方案扩展到每天6次疼痛发作将产生相似的Cmax值。
建立了一个强大的INFS群体PK模型。该模型增强了对BTP癌症患者给予INFS后芬太尼PK的理解,对于这一群体而言,实际生活中的数据很难获得。