Your browser doesn't support javascript. This means that the content or functionality of our website will be limited or unavailable. If you need more information about Vinnova, please contact us.

3D-SELECT UPPSALA UNIVERSITY

Reference number
Coordinator Oncodia AB
Funding from Vinnova SEK 4 991 075
Project duration October 2019 - September 2022
Status Ongoing
Venture Eurostars

Purpose and goal

Europe has the highest incidence of ovarian cancer in the world with 65,000 cases diagnosed and 42,700 deaths each year, and a corresponding economic burden of €4.9B. This low survival rate is primarily due to difficulties in selecting the right therapy at the time of diagnosis. Addressing this unmet need, the project will uniquely combine expertise in 3D culturing, pathology, genomics, proteomics and AI to accelerate the development of the 3D-SELECT platform to analyse drug response on small tumour biopsies from individual patients and identify most efficacious treatment.

Expected results and effects

The project will deliver a platform (3D-SELECT) used for the selection of optimal and personalized ovarian cancer therapy. The collaboration will exploit cutting-edge 3D cell-culturing technology and extensive cross-border tumor diagnostics expertise to correlate the ex-vivo drug sensitivity of actual tumour biopsies with clinical outcome. The 3D-SELECT platform will enable high throughput, automated and accurate screening of available drugs to significantly improve patient survival.

Planned approach and implementation

The project will integrate 3D tumour culturing and drug sensitivity testing know-how (VitroScan) with a histopathology (AnaPath), proteomics (FHNW), genomics and biomarker knowledge (Uppsala University, Oncodia) for prediction model accuracy. Oncodia will perform the sequencing analysis of the data generated by Uppsala University. AI algorithms (Robovision) will facilitate automated analytics and rapid therapy selection. 3D-SELECT will enable ex-vivo drug testing on patient tumour tissue at diagnosis, to support selection of a therapy with positive clinical outcome.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 12 September 2019

Reference number 2019-03565

Page statistics