Bayesian hierarchical modeling of receptor occupancy in PET trials.
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.
Vandenhende
F
F
Global Statistics, Lilly Research Laboratories, Mont-Saint-Guibert, Belgium. Francois@clinbay.com
Renard
D
D
Nie
Y
Y
Kumar
A
A
Miller
J
J
Tauscher
J
J
Witcher
J
J
Zhou
Y
Y
Wong
D F
DF
D001499:Bayes Theorem; D001921:Brain / Q000378:metabolism; D002986:Clinical Trials as Topic; D015195:Drug Design; D006801:Humans; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000008:administration & dosage / Q000097:blood / Q000378:metabolism; D010599:Pharmacokinetics; D014055:Tomography, Emission-Computed
D004364:Pharmaceutical Preparations