Syvänen Stina, Blomquist Gunnar, Appel Lieuwe, Hammarlund-Udenaes Margareta, Långström Bengt, Bergström Mats
Uppsala Imanet, Box 967, 75109, Uppsala, Sweden.
Eur J Clin Pharmacol. 2006 Oct;62(10):839-48. doi: 10.1007/s00228-006-0179-y. Epub 2006 Aug 8.
In a positron emission tomography (PET) study, the concentrations of the labeled drug (radiotracer) are often different in arterial and venous plasma, especially immediately following administration. In a PET study, the transfer of the drug from plasma to brain is usually described using arterial plasma concentrations, whereas venous sampling is standard in clinical pharmacokinetic studies of new drug candidates. The purpose of the study was to demonstrate the modeling of brain drug kinetics based on PET data in combination with venous blood sampling and an arterio-venous transform (T(av)).
Brain kinetics (C(br)) was described as the convolution of arterial plasma kinetics (C(ar)) with an arterial-to-brain impulse response function (T(br)). The arterial plasma kinetics was obtained as venous plasma kinetics (C(ve)) convolved with the inverse of the arterio-venous transform (T(av) (-1)). The brain kinetics was then given by C(br)=C(ve)*T(av) (-1)*T(br). This concept was applied on data from a clinical PET study in which both arterial and venous plasma sampling was done in parallel to PET measurement of brain drug kinetics. The predictions of the brain kinetics based on an arterial input were compared with predictions using a venous input with and without an arterio-venous transform.
The venous based models for brain distribution, including a biexponential arterio-venous transform, performed comparably to models based on arterial data and better than venous based models without the transform. It was also shown that three different brain regions with different shaped concentration curves could be modeled with a common arterio-venous transform together with an individual brain distribution model.
We demonstrated the feasibility of modeling brain drug kinetics based on PET data in combination with venous blood sampling and an arterio-venous transform. Such a model can in turn be used for the calculation of brain kinetics resulting from an arbitrary administration mode by applying this model on venous plasma pharmacokinetics. This would be an important advantage in the development of drugs acting in the brain, and in other circumstances when the effect is likely to be closer related to the brain than the plasma concentration.
在正电子发射断层扫描(PET)研究中,标记药物(放射性示踪剂)在动脉血和静脉血中的浓度往往不同,尤其是在给药后即刻。在PET研究中,药物从血浆向脑内的转运通常采用动脉血浆浓度来描述,而在新药候选物的临床药代动力学研究中,静脉采样是标准方法。本研究的目的是证明基于PET数据结合静脉血采样和动静脉转换(T(av))对脑内药物动力学进行建模。
脑内动力学(C(br))被描述为动脉血浆动力学(C(ar))与动脉到脑的脉冲响应函数(T(br))的卷积。动脉血浆动力学通过静脉血浆动力学(C(ve))与动静脉转换的倒数(T(av) (-1))卷积得到。然后脑内动力学由C(br)=C(ve)*T(av) (-1)*T(br)给出。这一概念应用于一项临床PET研究的数据,该研究中动脉血和静脉血采样与脑内药物动力学的PET测量同时进行。将基于动脉输入的脑内动力学预测结果与使用有或没有动静脉转换的静脉输入的预测结果进行比较。
基于静脉血的脑内分布模型,包括双指数动静脉转换模型,与基于动脉血数据的模型表现相当,且优于没有转换的基于静脉血的模型。还表明,具有不同浓度曲线形状的三个不同脑区可以用一个共同的动静脉转换和一个个体脑内分布模型进行建模。
我们证明了基于PET数据结合静脉血采样和动静脉转换对脑内药物动力学进行建模的可行性。通过将该模型应用于静脉血浆药代动力学,这样的模型可反过来用于计算由任意给药模式产生的脑内动力学。这在作用于脑内的药物开发以及其他效应可能与脑内而非血浆浓度更密切相关的情况下将是一个重要优势。