SODAS Inaugural Lecture Series 2017
Data has become part of the basic fabric of social life in many different ways. What sorts of questions do we need to start asking in order to understand, prepare for, and shape our futures with and through digital data?
The Centre for Social Data Science (SODAS) at the University of Copenhagen is convening its inaugural Lecture Series on the theme of Data Futures. Speakers from different disciplines are asked to reflect on the most pressing questions for contemporary society as we face futures living with and through data. The lectures will be aimed at an interdisciplinary audience - all welcome.
23 June 2017 - Søren Brunak
The Centre for Social Data Science (SODAS) is pleased to announce its sixth lecture in the DATA FUTURES Lecture Series, on Friday 23rd June, 11.00am in Room 35.3.20, CSS Campus, UCPH.
The lecture will be given by Professor Søren Brunak, who is Head of the Translational Disease Systems Biology Group at the Novo Nordisk Foundation Centre for Protein Research, Copenhagen University.
Please find the title and abstract of Prof Brunak's lecture below
Multi-morbidity disease trajectories in a complete, unbiased population
Patient record data remain a rather unexplored, but potentially rich data source for discovering correlations between diseases, drugs and genetic information in individual patients. All over the world human genomes are being sequenced at low cost, but in order to interpret genomes they must typically be matched up against disease phenotypes and treatment outcomes from many individuals, eventually arriving at the concept of precision medicine. Many drugs are today prescribed and dosed in a “one size fits all” manner (e.g. using patient weight); the data driven idea in personalized medicine is to identify a better founded relationship between patient features and choice of treatment. A fundamental question is the basic definition of phenotypic categories. As an alternative to the conventional single disease model the talk will describe attempts to create phenotypic categories and patient stratification based on longitudinal data covering long periods of time. We carry out temporal analysis of clinical data in a more life-course oriented fashion. We use data covering 6-7 million patients from Denmark collected over a 20 year period and use them to “condense” millions of individual trajectories into a smaller set of recurrent ones. This set of trajectories can be interpreted as re-defined phenotypes that potentially themselves could be treatment targets as opposed to a single diagnosis or a single disease. Healthcare is today not successful in handling patients with multi-morbidities and the talk will discuss this problem in the context of big biomedical data.
Any questions, please contact Antonia Walford: email@example.com