Bayesian Hierarchical Modeling of Receptor Occupancy in PET Trials

• Published in: Journal of biopharmaceutical statistics 2008-01, Vol.18 (2), p.256-272
• Main Authors: Vandenhende, F., Renard, D., Nie, Y., Kumar, A., Miller, J., Tauscher, J., Witcher, J., Zhou, Y., Wong, D. F.
• Format: Article
• Language: English
• Subjects: Bayes Theorem; Bayesian analysis; Brain - metabolism; Brain imaging; Clinical Trials as Topic; Drug Design; Heirarchical model; Humans; Models, Biological; PET; Pharmaceutical Preparations - administration & dosage; Pharmaceutical Preparations - blood; Pharmaceutical Preparations - metabolism; Pharmacokinetics; Receptor occupancy; Tomography, Emission-Computed
• ISSN: 1054-3406; 1520-5711
• DOI: 10.1080/10543400701697158

Receptor occupancy (RO) PET is a non-invasive way to determine drug on target. Given the complexity of procedures, long acquisition times, and high cost, ligand displacement imaging trials often have a limited size and produce sparse RO results over the time course of the blocking drug. To take the best advantage of the available data, we propose a Bayesian hierarchical model to analyze RO as a function of the displacing drug. The model has three components: the first estimates RO using brain regional time-radioactivity concentrations, the second shapes the pharmacokinetic profile of the blocking drug, and the last relates PK to RO. Compared to standard 2-steps RO estimation methods, our Bayesian approach quantifies the variability of the individual RO measures. The model has also useful prediction capabilities: to quantify brain RO for dosage regimens of the drug that were not tested in the experiment. This permits the optimal dose selection of neuroscience drugs at a limited cost. We illustrate the method in the prediction of RO after multiple dosing from a single-dose trial.