Bayesian hierarchical modeling of receptor occupancy in PET trials

F. Vandenhende, D. Renard, Y. Nie, A. Kumar, J. Miller, J. Tauscher, J. Witcher, Y. Zhou, D. F. Wong

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)256-272
Number of pages17
JournalJournal of biopharmaceutical statistics
Volume18
Issue number2
DOIs
StatePublished - Mar 1 2008
Externally publishedYes

Keywords

  • Bayesian analysis
  • Brain imaging
  • Heirarchical model
  • PET
  • Receptor occupancy

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)

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