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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/9702

Title: Bayesian hierarchical modeling of receptor occupancy in PET trials
Authors: Vandenhende, F.
Renard, D.
NIE, Yan
Kumar, A.
Miller, J.
Tauscher, J.
Witcher, J.
Zhou, Y.
Wong, D. F.
Issue Date: 2008
Publisher: TAYLOR & FRANCIS INC
Citation: JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 18(2). p. 256-272
Abstract: 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.
Notes: [Vandenhende, F.; Renard, D.] Lilly Res Labs, Mont St Guibert, Belgium. [Nie, Y.] Univ Hassrlt, Biostat Dept, Diepenbeek, Belgium. [Kumar, A.; Zhou, Y.] PET Ctr, Sch Med, Baltimore, MD USA. [Miller, J.] Lilly Res Labs, Clin Pharmacol, Indianapolis, IN USA. [Tauscher, J.] Lilly Res Labs, Dept Imaging, Indianapolis, IN USA. [Witcher, J.] Lilly Res Labs, Global PK PD, Indianapolis, IN USA.
URI: http://hdl.handle.net/1942/9702
DOI: 10.1080/10543400701697158
ISI #: 000253763000004
ISSN: 1054-3406
Category: A1
Type: Journal Contribution
Validation: ecoom, 2009
Appears in Collections: Research publications

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