Computational Immunology

Julia Drylewicz

Research Group

Julia Drylewicz
In the era of personalized medicine, biomarkers play a crucial role in pharmaceutical drug development and clinical diagnostics assisting in patient selection and detect early disease indicators. We use a combination of biostatistics, bioinformatics and mathematical modeling in translational projects trying to improve overall patient care.
Group name: Biomarker Discovery and Personalized Medicine
Research field: Computational Immunology
Biomarker, Computational Biology, Machine Learning, Modelling, Proteomics, Random Forest, Systems Medicine, Transcriptomics, Translational Immunology

Contact

Lundlaan 6
3584 EA Utrecht
Department / Institute: Center for Translational Immunology/ University Medical Center Utrecht
Office: KB 03.044.0
Building: Wilhelmina Kinderziekenhuis
j.drylewicz@umcutrecht.nl
https://research.umcutrecht.nl/research-groups/computational-immunology-core/

Our Research

Our research line focuses on identifying immunological markers to tailor healthcare approaches for individual patients. This multidisciplinary initiative integrates fields such as immunology, bioinformatics, biostatistics and clinical research to explore diverse health conditions.

One central objective is to discover biomarkers—measurable indicators of disease processes or treatment responses—that can guide personalized interventions. By understanding how these biomarkers vary between individuals, we seek to improve the accuracy of diagnosis, prognosis, and therapeutic decision-making. The ultimate goal is to move beyond the “one-size-fits-all” approach in medicine and develop more targeted, effective treatments based on each patient’s unique biological profile.

The scope of the research spans various health areas, including infectious diseases, autoimmune disorders, and chronic inflammatory conditions. For example, in chronic diseases like atopic dermatitis, the goal is to define distinct disease subtypes and predict how different patients will respond to specific therapies, leading to more personalized care.

By employing cutting-edge technologies such as genomics, proteomics, and advanced computational tools, we aim to translate biomarker discoveries into practical clinical applications. These include predictive models for treatment response and disease progression, as well as the development of personalized therapeutic strategies. Our group is a multidisciplinary team composed of biostatisticians, bioinformaticians.

As part of the Computational Immunology Core, our role is also to provide methological support to researchers of the Center for Translational Immunology at the UMC Utrecht by mentoring and supervising fellow researchers to perform computational analyses on their experimental data, amongst others by developing user-friendly pipelines and by teaching them how to perform such analyses.