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We focus on the data analytics and inference challenges posed by modern medicine. These are caused by the increasing complexity of medical data, such as the high number of variables (e.g. blood measurements, genomic data) that can be measured for each patient, interactions between diseases, and the heterogeneity of diseases and patient groups (no two patients with the same disease respond in the same way to treatment).


The challenges are also  prompted by the new ambition of medicine, to achieve personalized treatments: the right treatment, for the right person, at the right time. This requires using  intelligently the vast amount of new data that we can nowadays collect and that tells us about the differences between individuals. This is especially true for heterogeneous diseases like cancer. With effective personalized cancer treatment we strive to put an end to 75 years of chemotherapy. 

Dealing with the above challenges requires novel mathematical and statistical approaches. Our strategy is to model carefully all uncertainties in the data and their relationships (also known as Bayesian Modelling)  and to use mathematical methods from physics to make complicated calculations feasible. 


Our Vision

A future where precision medicine is realized through advanced quantitative methods. We strive to unlock the potential of datasets and reduce the high failure rate of clinical trials, to optimize healthcare outcomes.

Our Mission

Develop new quantitative methods to meet the data analytics and inference challenges of modern medicine. We combine the precision of Bayesian inference methods with the power of mathematical techniques from physics.

Our Values

Our company prioritizes innovation, collaboration, patient-centricity, and continuous learning. We work in close collaboration with medical researchers and practitioners.
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