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AstraZeneca paper evaluates early decision-making in drug-drug interaction prediction
Date: 08 Dec 2008
A new paper, to be published in the European Journal of Pharmaceutical Sciences, discusses the decision-making process for the prediction of drug-drug interactions using in vitro data. The study was undertaken by researchers at AstraZeneca, Charnwood, UK.
The article is entitled ‘Mechanism-based inhibition of cytochrome P450 enzymes: An evaluation of early decision making in vitro approaches and drug-drug interaction prediction methods.’
The authors suggest that the ability to use in vitro human cytochrome P450 (CYP) time-dependent inhibition (TDI) data for in vivo drug-drug interaction (DDI) predictions should be viewed as a prerequisite to generating the data. Also, ideally, assays should not produce superfluous data, but should be focused to predict the risk of DDI and toxicity.
As part of the study, two key screening schemes from the scientific literature and also a simple DDI prediction method were appraised. Using several clinical mechanism-based CYP DDI examples, the effectiveness of the DDI approach was assessed and compared to other widely available approaches including Simcyp. All methods compared favourably with the observed DDIs; however it was noted that Simcyp has the added advantage of providing the population variability for the predicted interaction as well as specific inhibitor-substrate interaction pairs already set up with all the relevant information.
A decision tree for use in a drug discovery setting has been proposed. The authors conclude that, although simple risk assessment tools have their place as an easy-to-use first line approach, it is desirable that DDI risk for candidate drugs should be additionally assessed using a more sophisticated tool such as Simcyp that incorporates disease states and variability due to anatomical, physiological and genetic factors.
The paper, by Kenneth H. Grime et al., is currently available as an e-publication ahead of print. Please click here for the abstract and full-text options.