Non-linear mixed effects modelling of positron emission tomography data for simultaneous estimation of radioligand kinetics and occupancy in healthy volunteers

The aim of this work was to develop a model simultaneously estimating (11)C-AZD9272 radioligand kinetics and the relationship between plasma concentration of AZD9272 and receptor occupancy in the human brain. AZD9272 is a new chemical entity pharmacologically characterised as a noncompetitive antagonist at the metabotropic glutamate receptor subtype 5 (mGluR5). Positron emission tomography (PET) was used to measure the time course of ((11)C-AZD9272) in the brain. The study included PET measurements in six healthy volunteers where the radioligand was given as a tracer dose alone as well as post oral treatment with different doses of unlabelled AZD9272. Estimation of radioligand kinetics, including saturation of receptor binding was performed by use of non-linear mixed effects modelling. Data from the regions with the highest (ventral striatum) and lowest (cerebellum) radioligand concentrations were included in the analysis. It was assumed that the extent of non-displaceable brain uptake was the same in both regions while the rate of CNS uptake and the receptor density differed. The results of the analysis showed that AZD9272 binding at the receptor is saturable with an estimated plasma concentration corresponding to 50% occupancy of approximately 200 nM. The density of the receptor binding sites was estimated to 800 nM and 200 nM in ventral striatum and cerebellum respectively. By simultaneously analysing data from several PET measurements and different brain regions in a non-linear mixed effects framework it was possible to estimate parameters of interest that would otherwise be difficult to quantify.

[1]  L Aarons Population approaches/sparse data analysis for human variability in kinetics and dynamics. , 1996, Environmental toxicology and pharmacology.

[2]  L. Farde,et al.  Kinetic Analysis of Central [11C]Raclopride Binding to D2-Dopamine Receptors Studied by PET—A Comparison to the Equilibrium Analysis , 1989, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[3]  Mark Slifstein,et al.  Measuring Drug Occupancy in the Absence of a Reference Region: The Lassen Plot Re-Visited , 2010, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[4]  Osama Mawlawi,et al.  Imaging Human Mesolimbic Dopamine Transmission with Positron Emission Tomography: I. Accuracy and Precision of D2 Receptor Parameter Measurements in Ventral Striatum , 2001, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[5]  J. Andersson,et al.  Development of PET radioligands synthesized from in-target produced [11C]methane , 2010 .

[6]  Brett Connolly,et al.  Species differences in mGluR5 binding sites in mammalian central nervous system determined using in vitro binding with [18F]F-PEB. , 2007, Nuclear medicine and biology.

[7]  Valerie Treyer,et al.  Evaluation of the Metabotropic Glutamate Receptor Subtype 5 Using PET and 11C-ABP688: Assessment of Methods , 2007, Journal of Nuclear Medicine.

[8]  J. S. Duncan,et al.  Benzodiazepine Receptor Quantification in vivo in Humans Using [11C]Flumazenil and PET: Application of the Steady-State Principle , 1995, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[9]  M. O. Karlsson,et al.  The importance of modeling interoccasion variability in population pharmacokinetic analyses , 1993, Journal of Pharmacokinetics and Biopharmaceutics.

[10]  M. Mintun,et al.  A quantitative model for the in vivo assessment of drug binding sites with positron emission tomography , 1984, Annals of neurology.

[11]  Margareta Hammarlund-Udenaes,et al.  Blood–Brain Barrier Transport Helps to Explain Discrepancies in In Vivo Potency between Oxycodone and Morphine , 2008, Anesthesiology.

[12]  Jae Kyeong Jeong,et al.  Modeling of Brain D2 Receptor Occupancy‐Plasma Concentration Relationships with a Novel Antipsychotic, YKP1358, Using Serial PET Scans in Healthy Volunteers , 2007, Clinical pharmacology and therapeutics.

[13]  E N Jonsson,et al.  Xpose--an S-PLUS based population pharmacokinetic/pharmacodynamic model building aid for NONMEM. , 1999, Computer methods and programs in biomedicine.

[14]  Stefano Zamuner,et al.  Prediction of Repeat-Dose Occupancy from Single-Dose Data: Characterisation of the Relationship between Plasma Pharmacokinetics and Brain Target Occupancy , 2011, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[15]  Ronald Boellaard,et al.  Population Pharmacokinetic Analysis for Simultaneous Determination of Bmax and KDIn Vivo by Positron Emission Tomography , 2005, Molecular Imaging and Biology.

[16]  Stefano Zamuner,et al.  PII: S0969-8051(01)00275-X , 2001 .

[17]  Julian C. Matthews,et al.  Kinetic analysis of neuroreceptor binding using PET , 2004 .

[18]  R. P. Maguire,et al.  Consensus Nomenclature for in vivo Imaging of Reversibly Binding Radioligands , 2007, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[19]  K. Zilles,et al.  Human brain atlas: For high‐resolution functional and anatomical mapping , 1994, Human brain mapping.