Drug-drug interaction prediction: A Bayesian meta-analysis approach

Lang Li, Menggang Yu, Raymond Chin, Aroonrut Lucksiri, David A. Flockhart, Stephen D. Hall

Research output: Contribution to journalArticle

18 Scopus citations


In drug-drug interaction (DDI) research, a two drug interaction is usually predicted by individual drug pharmacokinetics (PK). Although subject-specific drug concentration data from clinical PK studies on inhibitor/inducer or substrate's PK are not usually published, sample mean plasma drug concentrations and their standard deviations have been routinely reported. In this paper, an innovative DDI prediction method based on a three-level hierarchical Bayesian meta-analysis model is developed. The first level model is a study-specific sample mean model; the second level model is a random effect model connecting different PK studies; and all priors of PK parameters are specified in the third level model. A Monte Carlo Markov chain (MCMC) PK parameter estimation procedure is developed, and DDI prediction for a future study is conducted based on the PK models of two drugs and posterior distributions of the PK parameters. The performance of Bayesian meta-analysis in DDI prediction is demonstrated through a ketoconazolemidazolam example. The biases of DDI prediction are evaluated through statistical simulation studies. The DDI marker, ratio of area under the concentration curves, is predicted with little bias (less than 5 per cent), and its 90 per cent credible interval coverage rate is close to the nominal level. Sensitivity analysis is conducted to justify prior distribution selections.

Original languageEnglish (US)
Pages (from-to)3700-3721
Number of pages22
JournalStatistics in Medicine
Issue number20
StatePublished - Sep 10 2007


  • Area under the concentration curve ratio (AUCR)
  • Bayesian model
  • Drug-drug interaction (DDI)
  • Meta-analysis
  • Pharmacokinetics (PK)
  • Prediction

ASJC Scopus subject areas

  • Epidemiology

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  • Cite this

    Li, L., Yu, M., Chin, R., Lucksiri, A., Flockhart, D. A., & Hall, S. D. (2007). Drug-drug interaction prediction: A Bayesian meta-analysis approach. Statistics in Medicine, 26(20), 3700-3721. https://doi.org/10.1002/sim.2837