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New study compares dynamic and static models for drug-drug interaction prediction
Date: 02 Dec 2010
A paper published in the British Journal of Clinical Pharmacology describes a study to assess two drug-drug interaction (DDI) models. The work was undertaken by scientists at the University of Manchester, UK and Simcyp Limited.
The authors assessed static and dynamic models for their ability to predict DDIs using the Simcyp Population-based Simulator. The dynamic model allowed investigation of the impact of active metabolites, dosing time and inter-individual variability in DDI magnitude. Prior studies have compared different models rather than both models within Simcyp and therefore have not provided direct comparisons using consistent parameters.
Thirty-five in vivo DDIs were predicted with similar prediction success between the dynamic and static models (71% and 77% within two-fold respectively). Differences were observed with dose staggering and when active metabolites were incorporated which highlights the importance of these variables in DDI prediction. The inclusion of many compounds from multiple studies allowed general trends to be drawn and the authors provide a thorough discussion of their results.
The lead author of the paper, Eleanor J. Guest, received partial funding for her PhD studentship from Simcyp.
The paper is entitled ‘Assessment of algorithms for predicting drug-drug interaction via inhibition mechanisms: comparison of dynamic and static models.’ Please click here for a link to the abstract and full text options.