Predicting brain concentrations of drug using positron emission tomography and venous input: modeling of arterial-venous concentration differences

ObjectiveIn 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 (Tav).MethodsBrain kinetics (Cbr) was described as the convolution of arterial plasma kinetics (Car) with an arterial-to-brain impulse response function (Tbr). The arterial plasma kinetics was obtained as venous plasma kinetics (Cve) convolved with the inverse of the arterio-venous transform (Tav−1). The brain kinetics was then given by Cbr=Cve*Tav−1*Tbr. 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.ResultsThe 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.ConclusionWe 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.

[1]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[2]  Adriaan A Lammertsma,et al.  Radioligand studies: imaging and quantitative analysis , 2002, European Neuropsychopharmacology.

[3]  N. Benowitz,et al.  Modeling Nicotine Arterial–Venous Differences to Predict Arterial Concentrations and Input Based on Venous Measurements: Application to Smokeless Tobacco and Nicotine Gum , 2002, Journal of Pharmacokinetics and Pharmacodynamics.

[4]  L. Lesko,et al.  Integration of pharmacokinetic and pharmacodynamic studies in the discovery, development, and review of protein therapeutic agents: A conference report , 2001, Clinical pharmacology and therapeutics.

[5]  N. Benowitz,et al.  Apparent tolerance to the acute effect of nicotine results in part from distribution kinetics. , 1987, The Journal of clinical investigation.

[6]  S. Gunn,et al.  Positron Emission Tomography Compartmental Models , 2001, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[7]  Roger N Gunn,et al.  Positron Emission Tomography Compartmental Models: A Basis Pursuit Strategy for Kinetic Modeling , 2002, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[8]  L. Lesko,et al.  Optimizing the Science of Drug Development: Opportunities for Better Candidate Selection and Accelerated Evaluation in Humans , 2000, Journal of clinical pharmacology.

[9]  M. Bergström,et al.  Blood–Brain Barrier Penetration of Zolmitriptan—Modelling of Positron Emission Tomography Data , 2006, Journal of Pharmacokinetics and Pharmacodynamics.

[10]  M Danhof,et al.  Relevance of arteriovenous concentration differences in pharmacokinetic-pharmacodynamic modeling of midazolam. , 1998, The Journal of pharmacology and experimental therapeutics.

[11]  Bengt Långström,et al.  Positron emission tomography microdosing: a new concept with application in tracer and early clinical drug development , 2003, European Journal of Clinical Pharmacology.