Cystotech are detecting bladder cancer
Raising a successful seed round as a research spin-out
Spinning out from a University research project takes enormous effort, will, time– and capital. Raising a seed round for a complex, research-heavy startup takes just the right mix of timing, luck, educated investors and hard work. A mix, Aarhus-based Cystotech, recently succeeded in finding.
Two of the five co-founders of Cystotech, MD, CEO, Jacob Elmose Jensen, and Clinical Trial Manager,COO, Anna Munk Nielsen, have successfully spun out a solution to detect bladder cancer, from a research project at Aarhus University. Together with a strong team, they’re developing a support tool for bladder cystoscopy, using tech-based on Computer Vision and Deep Learning Artificial Intelligence.
The team knew, that getting investors to bite, meant bringing in more commercial competencies, which they found in their now co-founder and investor, Claus Hansen.
“Claus has become a part of the team because he has competencies that complement ours. He is used to think business strategic,”says Jacob, and points to the rest of the team’s more product-based and HealthTech-industry competencies.
With Claus taking lead, they started pitching to investors. In May this year, the Aarhus University spin-out landed a seed round from a local fund and syndicate of angels. Claus has experience from co-founding and investing in multiple life-science startups and he has a personal ambition of utilising his expertise within the field to help more companies grow.
“Having lived and worked based out of Aarhus all my life I do have a personal ambition to bring Aarhus on the map on a larger scale within the Medtech & lifescience segment,” says Claus Hansen.
READ THE FULL ARTICLE: STARTUPAARHUS.COM
Update August 2023: Cystotech has raised a pre-seed funding round consisting of soft funding from the Innovation Fund Denmark of DKK 1.4M and hard funding of DKK 5.1M. In total, DKK 6.5M. Cystotech is developing a potential first-to-market software as a medical device (SaMD) that can initially detect and later categorize bladder cancer during live surgery.
