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Mechanism-based population pharmacokinetic modelling in diabetes: Vildagliptin as a tight binding inhibitor and substrate of dipeptidyl peptidase IV

机译:基于机制的糖尿病群体药代动力学建模:Vildaglitin作为二肽肽酶IV的紧密结合抑制剂和基材

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Aims: To assess the pharmacokinetics of vildagliptin at different doses and build a mechanism-based population model that simultaneously describes vildagliptin pharmacokinetics and its effects on DPP-4 activity based on underlying physiology and biology. Methods: Vildagliptin concentrations and DPP-4 activity vs. time from 13 type 2 diabetic patients after oral vildagliptin 10, 25 or 100mg and placebo twice daily for 28days were co-modelled. NONMEM VI and S-ADAPT were utilized for population modelling. Results: A target-mediated drug disposition (TMDD) model accounting for capacity-limited high affinity binding of vildagliptin to DPP-4 in plasma and tissues had good predictive performance. Modelling the full time course of the vildagliptin-DPP-4 interaction suggested parallel vildagliptin dissociation from DPP-4 by a slow first-order process and hydrolysis by DPP-4 to an inactive metabolite as a disposition mechanism. Due to limited amounts of DPP-4, vildagliptin concentrations increased slightly more than dose proportionally. This newly proposed model and the parameter estimates are supported by published in vitro studies. Mean parameter estimates (inter-individual coefficient of variation) were: non-saturable clearance 36lh -1 (25%), central volume of distribution 22l (37%), half-life of dissociation from DPP-4 1.1h (94%) and half-life of hydrolysis 6.3h (81%). Conclusions: Vildagliptin is both an inhibitor and substrate for DPP-4. By utilizing the TMDD approach, slow dissociation of vildagliptin from DPP-4 was found in patients and the half-life of hydrolysis by DPP-4 estimated. This model can be used to predict DPP-4 inhibition effects of other dosage regimens and be modified for other DPP-4 inhibitors to differentiate their properties.
机译:目的:评估不同剂量的Vilantlitin的药代动力学,并构建一种基于机制的人口模型,同时描述Vildagliptin药代动力学及其对基于潜在生理学和生物学的DPP-4活性的影响。方法:Vildagliptin浓度和DPP-4活性与13型糖尿病患者在口服vilyagliptin 10,25或100mg和每日两次的安慰剂28天的时间相同。 NONMEM VI和S - 适应用于人口建模。结果:靶介导的药物处理(TMDD)模型核算用于血浆和组织中Vildagliptin对DPP-4的Vildaglittin对DPP-4的能力有限的高亲和力结合具有良好的预测性能。建模Vildagliptin-DPP-4相互作用的全时间过程通过DPP-4通过缓慢的一阶方法与DPP-4的平行Vilyagliptin离解,并通过DPP-4水解至作为配置机制的非活性代谢物。由于DPP-4的有限量,Vildagliptin浓度略高于比例略高于剂量。这种新提出的模型和参数估计得到了在体外研究中出版的。平均参数估计(各种变异系数)是:不可饱和间隙36LH -1(25%),分布22L的中央体积(37%),来自DPP-4的解离的半衰期(94%)水解6.3h(81%)的半衰期。结论:Vildagliptin是DPP-4的抑制剂和底物。通过利用TMDD方法,在患者中发现VIDAGLIPTIN从DPP-4的缓慢解离,并通过DPP-4估计水解的半衰期。该模型可用于预测其他剂量方案的DPP-4抑制作用,并用于其他DPP-4抑制剂以区分其性质。

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