Reps, Jenna M. and Garibaldi, Jonathan M. and Aickelin, Uwe and Soria, Daniele and Gibson, Jack E. and Hubbard, Richard B. (2014) Signalling paediatric side effects using an ensemble of simple study

Background: Children are frequently prescribed medication ‘off-label’, meaning there has not been sufficient testing of the medication to determine its safety or effectiveness. The main reason this safety knowledge is lacking is due to ethical restrictions that prevent children from being included in the majority of clinical trials. Methods: Multiple measures of association are calculated for each drug and medical event pair and these are used as features that are fed into a classifier to determine the likelihood of the drug and medical event pair corresponding to an adverse drug reaction. The classifier is trained using known adverse drug reactions or known non-adverse drug reaction relationships. Results: The novel ensemble framework obtained a false positive rate of 0.149, a sensitivity of 0.547 and a specificity of 0.851 when implemented on a reference set of drug and medical event pairs. The novel framework consistently outperformed each individual simple study design. Conclusion: This research shows that it is possible to exploit the mechanism of causality and presents a framework for signalling adverse drug reactions effectively.