26th May 2025
EIT Health has selected seventeen teams to go through the Deep Tech Venture Builder (DTVB) Programme, a unique programme aimed at innovators in academia. One of the supported project teams is based at the Institute of Science and Technology Austria.
Specifically designed to support academic teams with deep tech solutions, EIT Health’s DTVB programme provides start-ups with the right support to overcome the most frequent hurdles experienced when launching to market. Notoriously known as the “Valley of Death” – where many promising ideas fail to transition out of academic environments – successfully navigating this stage requires overcoming the most common challenges such as bureaucratic hurdles, funding uncertainties, and making the transition from research to practical innovation.
“During 2023 and 2024 we conducted several focus groups, workshops and interviews with more than 100 key stakeholders in the healthcare ecosystem at a European level and the insights gathered helped shape this programme. Now the DTVB programme is a reality, and we are excited to see it come to life with such innovative and promising projects. We are thrilled to witness the journey of these innovative projects and the transformative impact they will have on the healthcare landscape,” says Maria Escarti, DTVB Programme Lead at EIT Health.
The Austrian DTVB project by ISTA
Cell shape is a critical medical biomarker for disease progression, but it primarily focuses on two-dimensional data analysis. Subtle differences indicative of disease onset are still difficult to catch because of insufficient attention to the three-dimensionality in which our brain functions. However, dissecting cells from 3D images is a slow, labor-intensive task, making it prone to errors and difficult to scale.
The shAIpe project developed by Austria-based company Institute of Science and Technology Austria (ISTA) together with its dedicated technology transfer organisation xista innovation, addresses this unmet need with a deep learning-based solution that automates any cell shape detection in 3D. With their AI-based algorithm trAIce, they established a Technology for Rapid, Accurate, Intuitive, and Consistent Evaluation, enabling clinical precision diagnostics and patient stratification. The main competitive advantages are speed, reliability, and reduced need for manual effort compared to existing market solutions, paving the way for more efficient research and new diagnostic tools.
With the support of the DTVB programme, the project team of shAIpe will access expert guidance, technical resources, and a collaborative innovation environment that will translate their prototype into a robust, scalable product.
Ultimately, the project aims to accelerate scientific discovery and improve early diagnosis of neurological diseases by transforming how cell images are analysed.
“At xista, we’re proud to serve as the venture builder behind the shAIpe program, helping bold ideas like trAIce unlock new frontiers in diagnostics, drug discovery, and the understanding of cellular morphology. By supporting Diego Milardovich, as he advances the application of Professor Sandra Siegert’s pioneering research, we believe trAIce can set new standards for both cellular morphology insights and medical image analysis, delivering real-world impact,” says Prudence Donovan, Entrepreneurship and Innovation Lead at xista.
During the DTVB programme all selected consortia will work to transform their deep tech academic research into successful ventures by bridging the gap between intellectual property and start-up creation. They will be provided hands-on support to help de-risk early-stage innovations and guided through both pre-maturation and maturation phases.
Read more about all 17 selected projects: click here
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