The aim of pharmacovigilance is to identify and describe adverse events related to the use of medicines and to support wise therapeutic decisions. By nature, pharmacovigilance focuses on the unexpected and relies on effective methods for data-driven discovery. In this talk I will highlight initiatives seeking to improve our ability to do exploratory analysis in observational medical data, using statistical pattern discovery, latent class cluster analysis and natural language processing. I will use examples from VigiBase, the World Health Organisation’s global database of nearly 20 million individual case safety reports and from large collections of electronic medical records.
After participating in this activity, the learner should be better able to:
• Learn the newest methods for pharmacovigilance
• Learn the hands-on experience on applying cutting edge data mining methods and natural language processing to VigiBase and electronic health records
Dr. Niklas Norén, PhD
Chief Science Officer and Head of Research,
Uppsala Monitoring Centre, Sweden
Niklas Norén, PhD, is Chief Science Officer and Head of Research at the Uppsala Monitoring Centre. He is responsible for the scientific direction of the center and oversees 25 pharmacists, data scientists and medical doctors engaged in scientific development, safety signal detection and capacity building. He has published extensively on statistical pattern discovery in observational medical data, primarily adverse event reports and electronic medical records. His research on duplicate detection and subgroup discovery has been internationally awarded. In Europe, he has led collaborative projects in pharmacovigilance funded by the European Commission including: the signal detection work-package in PROTECT; the work-packages on detecting substandard medicines and drug dependence from adverse event reports in Monitoring Medicines; and the social media analytics work-package in WEB-RADR. Internationally, he led Uppsala Monitoring Centre’s contributions to the Observational Medical Outcomes Partnership and is a member of the editorial board for Drug Safety. He is currently engaged in the IMI EHDEN project, in the Observational Health Data Sciences and Informatics (OHDSI) collaborative and in a study of signal detection within the Sentinel Initiative. Dr. Norén holds a PhD in Mathematical Statistics from Stockholm University in 2007 and a Master’s degree in Engineering Physics from Chalmers University of Technology in 2002. He has worked in various positions at the Uppsala Monitoring Centre and affiliated organizations since 2003.