Joint Call for Proposals: National Data Streams (NDS)
On the road towards establishing a Swiss personalized health ecosystem, SPHN and PHRT have launched a joint call for proposals for National Data Streams (NDS).
NDS are multidisciplinary consortial research infrastructures (platforms) involving a national network of clinical and science/engineering partners. NDS that build on pre-existing infrastructures and data sets are preferred, should encompass clinical as well as analytical data (e.g., multi-omics), and include a lighthouse research project.
For NDS grantees, please find all grant management documents on the right side of this window.
The following 4 NDS projects will start in summer 2022:
- Personalized, data-driven prediction and assessment of infection-related outcomes in Swiss ICUs (IICU) (Prof. Dr. Adrian Egli (USB) & Prof. Dr. Karsten Borgwardt (ETHZ))
- Swiss Personalized Oncology National Data Stream (SPO-NDS) (Prof. Dr. Olivier Michielin (CHUV) & Prof. Dr. Bernd Bodenmiller (ETHZ))
- Pediatric personalized research network Switzerland (SwissPedHealth) – a Joint Pediatric National Data Stream (Prof. Dr. Luregn Schlapbach (University Children’s Hospital Zurich) & Prof. Dr. Julia Vogt (ETHZ))
- LUCID, Low Value of Care in Hospitalized Patients, a National Data Stream on Quality of Care in Swiss university hospitals (Dr. Marie Méan (CHUV) & Dr. Guillaume Obozinski (EPFL)).
Each NDS project will receive up to CHF 5 million and have a runtime of 3 years. SPHN funding requires matching funds from the participating institutions.
More information on the funded NDS projects will follow soon.
Please note: the call for National Data Streams is not taking new applications.
For any remaining questions, please contact email@example.com.
Documents for NDS PIs:
Grant management documents
- SPHN funds release form
- Financial reporting template (coming soon)
- Annual activity report template (coming soon)
SPHN regulations and guidelines
- SPHN Funding regulations
- SPHN financial reporting guidelines (coming soon)
- Ethical framework for responsible data processing
- Information Security Policy
- Reporting Actionable Genetic Findings to Research Participants