Personalized Medicine
Why do some persons suffer from diabetes or Alzheimer's disease? Why does a cancer treatment work well for some patients but for others not at all? And why do some patients suffer from adverse effects of the treatment?
The answers to these and similar questions is: All persons have different genetic properties, and the genes affect if a person becomes sick or how medications take effect in the body.
Personalized Medicine aims to tailor the treatment of a patient to the person's individual characteristics. With the recent technological advances, detailed information about an individual's molecular and genetic properties has become accessible.
The main challenge is to find associations between the genotype and the phenotype (e.g., the onset or course of a disease, the effect of a treatment). As the human genome consists of billions of bases, gigantic amounts of data have to be analysed. Here machine learning comes into play.
We develop efficient algorithms to detect patterns, rules and statistical dependencies in large medical datasets with the ultimate goal to improve healthcare in collaborations with medical researchers.
We are involved in several national and international networks and collaborations on Personalized Medicine:
- Coordinating node of the MSCA Initial Training Network Machine Learning for Personalized Medicine (2013-2016)
- Coordinating node of the SPHN/PHRT Driver Project Personalized Swiss Sepsis Study (2018-2021)
- Coordinating node of the MSCA Initial Training Network Machine Learning Frontiers in Precision Medicine (2019-2022)