On 29 August 2019 at 3.15 p.m., in J.Liivi str. 2 room 404, Sulev Reisberg will defend his thesis "Developing computational solutions for personalized medicine" for obtaining the degree of Doctor of Philosophy (in computer science).
Supervisor:
Prof. Jaak Vilo (Institute of Computer Science, UT)
Opponents:
Prof. Dan Roden (Vanderbilt University, Tennessee, USA),
Dr. Patrick Kemmeren (Princess Máxima Center for Pediatric Oncology, The Netherlands).
Summary:
Although medicine has always been an individualized interaction between a patient and a doctor, the term “personalized medicine” has entered into common use during recent decades. The general idea behind it is to provide more effective clinical care and prevention of the diseases by more finely dividing patients and diseases into subgroups based on the genetic data.
Doctoral thesis of Sulev Reisberg is strongly related to Estonian state-level approach to integrating personalized medicine into routine clinical practice. It uses genetic data from Estonian Biobank and focuses on computational issues.
Polygenic risk scores are mathematical models that estimate based on individual genetic data whether the patient has a low, medium or high risk of developing certain diseases. This thesis was one of the first
studies that indicated a problem that existing models are most suitable for Europeans. For other populations, the estimated risk could be the opposite to the true risk.
Pharmacogenomics is a field that investigates, how fast we metabolize medical drugs. Although a lot of information of this kind was already available, so far there was no concrete step-by-step decision algorithm on how to make specific recommendations based on the genetic data of a patient. In this doctoral thesis, software was built and used for producing pharmacogenomic reports for 44 thousand gene donors. It turned out that for 99.8% of the gene donors a dosage adjustment for at least one investigated drug is recommended.
In order to bring personalized medicine solutions into clinical practice, but also for investigating gene- disease associations, these solutions have to be integrated with health information systems. In this thesis,
genetic data and electronic health records were linked to conduct a phenome-wide association study. In this study, it was investigated whether there are any diseases, that are linked to genetic mutations that were previously been associated with asthma and liver diseases.
As of today, a state-level project has been started to build an IT-infrastructure to bring the outcomes of the doctoral thesis of Sulev Reisberg to routine clinical practice.