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首页> 外文期刊>Clinical pharmacokinetics >Semi-mechanistic population pharmacokinetic drug-drug interaction modelling of a long half-life substrate and itraconazole.
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Semi-mechanistic population pharmacokinetic drug-drug interaction modelling of a long half-life substrate and itraconazole.

机译:半衰期较长的底物和伊曲康唑的半机械种群药代动力学药物相互作用模型。

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BACKGROUND: For compounds with a long elimination half-life, the evaluation of a drug-drug interaction (DDI) study can be challenging. The standard analytical approach of a non-compartmental analysis (NCA) might not be able to detect the full interaction potential and may lead to a significant underestimation of the interaction. The most appropriate method for data analysis might be a semi-mechanistic population pharmacokinetic modelling approach. OBJECTIVES: To accomplish a semi-mechanistic DDI model for a long-elimination-half-life drug substrate, tesofensine, and the cytochrome P450 (CYP) 3A4 inhibitor itraconazole, and to compare the results of the semi-mechanistic model with the results obtained from the standard NCA approach. Additionally, the impact of different schedules of itraconazole on tesofensine pharmacokinetics and the general performance of the standard NCA approach were evaluated. METHODS: Overall, 28 subjects received a single oral dose of tesofensine 2 mg; 14 of these subjects were coadministered an oral itraconazole 400 mg loading dose and a 200 mg maintenance dose for 6 days before and 5 days after administration of tesofensine. The dataset contained 465 plasma concentrations of tesofensine (full profiles) and 80 plasma concentrations of itraconazole (trough values). First, pharmacokinetic models of itraconazole and tesofensine were developed in parallel. Subsequently, a combined model was developed, taking into account CYP3A4 inhibition. The analyses were performed using NONMEM software. RESULTS: The plasma concentration-time profiles of itraconazole and tesofensine were best described by a one-compartment model for each drug, with first-order elimination rate constants that were both inhibited by itraconazole concentrations. Inhibition resulted in reduced clearances and prolonged elimination half-lives for tesofensine and itraconazole: using NCA, the actual study revealed an approximately 9% increase in exposure for the timeframe of the coadministration with itraconazole (the area under the plasma concentration-time curve (AUC) from 0 to 144 hours [AUC(144h)]), and the impact on exposure estimated to infinity (AUC(infinity)) was approximately 26%. These results are in contrast to the model-predicted results, where the inhibitory effect of itraconazole caused a 38% reduction in the clearance of tesofensine, leading to a 63% increased exposure. CONCLUSIONS: This analysis presents a semi-mechanistic population pharmacokinetic approach that may be useful for the evaluation of DDI studies. The model can be an aid in evaluating DDI studies for compounds with a long elimination half-life, especially when the inhibitor cannot be administered over a sufficient period. Additionally, the population model-based approach may allow simplification of the design and the analysis and interpretation of safety and efficacy findings in DDI studies.
机译:背景:对于具有长消除半衰期的化合物,药物-药物相互作用(DDI)研究的评估可能具有挑战性。非隔室分析(NCA)的标准分析方法可能无法检测到完整的交互作用潜力,并可能导致对交互作用的严重低估。数据分析的最合适方法可能是半力学总体药代动力学建模方法。目的:为半衰期长的药物底物,tesofensine和细胞色素P450(CYP)3A4抑制剂伊曲康唑建立半机械DDI模型,并将半机械模型的结果与获得的结果进行比较来自标准NCA方法。此外,评估了伊曲康唑的不同给药方案对tesofensine药代动力学的影响以及标准NCA方法的总体性能。方法:总体上,有28名受试者接受了2 mg tesofensine的单次口服剂量。这些受试者中的14名在服用tesofensine之前和之后的6天和6天分别口服口服伊曲康唑400 mg负荷剂量和200 mg维持剂量。该数据集包含465血浆替斯芬辛的血浆浓度(完整曲线)和80血浆伊曲康唑的血浆浓度(谷值)。首先,并行开发了伊曲康唑和tesofensine的药代动力学模型。随后,考虑到CYP3A4的抑制作用,建立了一个联合模型。使用NONMEM软件进行分析。结果:每种药物的单室模型最好地描述了伊曲康唑和tesofensine的血浆浓度-时间曲线,一阶消除速率常数均受到伊曲康唑浓度的抑制。抑制作用会导致替斯芬辛和伊曲康唑的清除率降低和消除半衰期延长:使用NCA,实际研究表明,与伊曲康唑合用的时间范围内血浆暴露量增加了约9%(血浆浓度-时间曲线下的面积(AUC) )从0到144小时[AUC(144h)]),估计对无穷大曝光量(AUC(无穷大))的影响约为26%。这些结果与模型预测的结果相反,在模型预测的结果中,伊曲康唑的抑制作用导致替斯芬辛清除率降低38%,导致暴露量增加63%。结论:该分析提出了一种半机械的群体药代动力学方法,可能对DDI研究的评估有用。该模型可以帮助评估具有长消除半衰期的化合物的DDI研究,尤其是当抑制剂不能在足够长的时间内给药时。此外,基于人群模型的方法可以简化DDI研究的设计以及对安全性和有效性研究结果的分析和解释。

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