We are working on setting up a PH Translation and Implementation Unit where, together with translational research labs, we optimize processes, platforms and data integration / interface so that innovative non-routine analytics and decision support with high potential impact in healthcare can be performed and refined up to the point of full integration in the clinical routine.

The subunits with immediate benefit and well-established activities and collaborations are in the field of Oncology, Infectious Diseases, and Neuroimmunology but we are happy to support ideas from any clinical/disease area and technology.

If you are working on an innovative non-routine analytics and decision support with high potential impact in healthcare please get in touch.

PHB had already a strong involvement in the oncology field which led to significative progresses in this area with several technologies being established and/or now in the implementation pipeline.

Personalized Drug Screening Platform

A Personalized Drug Screening Platform has been established by the group of Prof. Mohamed Bentires-Alj at the Department of Biomedicine. Briefly, patient’s tumor-derived miniature three-dimensional tissue cultures (so called tumor organoids) are grown in the lab and used to test anti-cancer drugs (and combination of drugs) thus allowing the identification of the most personalized and efficacious treatment for an individual patient by testing a wide range of drugs directly on avatars of her/his tumor and providing this information to the oncologists and the tumor boards.

Here the in-depth tumor characterization beyond standard of care and the clinical and translational data interface/integration takes place, bringing treatment decision support for personalized therapies. This will be a direct link to personalized patient care, allowing new treatment opportunities for patients who have escaped standard of care therapies or for which several standard of care exist without a rationale for selection. 

Contacts:

• Email: Prof. Mohamed Bentires-Alj
• Email  Dr. Maren Diepenbruck
• Email  Dr. Shan Yang

IT solution for clinical decision making support

In the framework of the SPHN PHRT funded SPO-NDS we will provide a robust, integrated and harmonized multi-dimensional dataset (composed of high quality clinical and -omics data) together with an IT solution to present it at the local and national molecular tumor boards to improve clinical decision support. A data management system, from infrastructure to standardization of data set generation and organization of data, and the onboarding of the data generating technologies as well as the national tumor board web application will be set up during the course of the project. 

Contacts:

• Email: Dr. Bram Stieltjes
• Email: Dr. Leonardus Bosch

High quality data patterns, in-depth sample characterization and translational findings can be tested as potential predictive biomarkers and personalized assessment for infectious diseases, where characterization and outcome prediction can be achieved and fed back to the clinic to support clinical decision making. Better understanding via clinical phenotyping and generation of a curated data set with specific feedback loops from data scientists to the clinic will increase the overall data quality and data-driven decision-support in infectiology. A collaboration between Siemens and the University Hospital is already currently ongoing to develop a software for clinical decision support for sepsis prediction and risk stratification. Furthermore, there is interest from Roche diagnostics to test decision making algorithms in this realm.

Contacts:

• Email: Dr. Bram Stieltjes

High quality data patterns, in-depth sample characterization and translational findings have a great potential as predictive biomarkers and personalized assessment also in the paediatric field. These efforts are particularly important and time critical in the context of the funded SPHN National Data Stream SwissPedHealth and the funded SPHN paediatric demonstrator projects and involve a connection of UKBB to the USB CDW.

Contact:

• Email: PD Dr. Julia Bielicki
• Email: Dr. Bram Stieltjes

In close collaboration with DBE and RC2NB, imaging biomarkers and novel lab tests will be integrated  to develop and validate digital biomarkers and innovative methods of information processing and artificial intelligence in the field of multiple sclerosis and other neuroimmunological diseases enabling personalized disease management and finding better therapies and treatment strategies. In addition, in the context of CLINNOVA, a federated imaging data sharing infrastructure will be built, tested, and deployed in this area.

Contacts:

• Email:  Prof. Cristina Granziera
• Email:  Dr. Bram Stieltjes