Artificial Intelligence and Drug Interactions

6 October 2017

Dr C. Goehrs MD - MSC Biomedical Informatics
C-NAPPS CEO, Bordeaux, France

It has been shown that drug-drug interactions (DDI) are a significant cause of hospital admissions: as much as 4.8% of the admissions in the elderly population [1]. Improved DDI information could help reduce such adverse effects. [2]. Still, health professionals describe a lack of tools that meet their needs and are clinically relevant [3]. Furthermore, the DDI problematic underline a vastly larger problem about the management of drug-related information and data. These problematics has been the focus of a joint research effort lead by Bordeaux University, Stanford University and the C-napps company, in order to develop an international semantic model describing drugs data, and to implement clinical relevant tools for pharmacists and physicians. The first proof of concept has been the development of a new and comprehensive system to manage DDI, based on the ANSM’s recommendations, and leveraging artificial intelligence technologies.

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[1Becker, Matthijs L., et al. "Hospitalisations and emergency department visits due to drug–drug interactions: a literature review." Pharmacoepidemiology and drug safety 16.6 (2007): 641-651

[2Dechanont, Supinya, et al. "Hospital admissions/visits associated with drug–drug interactions: a systematic review and meta-analysis." Pharmacoepidemiology and drug safety 23.5 (2014): 489-497

[3McEvoy, Dustin S., et al. "Variation in high-priority drug-drug interaction alerts across institutions and electronic health records." Journal of the American Medical Informatics Association 24.2 (2016): 331-338

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