One challenge in the world of medicine is to find clues that indicate the onset of complex diseases at an early stage. After all, when complex diseases can be detected in advance thanks to what are known as biomarkers, they can be treated early and in targeted fashion. Scailyte has developed a software program based on Artificial Intelligence (AI) in order to uncover these biomarkers more rapidly. “Our algorithms analyze millions of individual cells and identify patterns that indicate the potential onset of certain diseases”, explains Peter Nestorov, CEO of Scailyte, in a press release.
In contrast to conventional methods that require several weeks for data analysis, the Scailyte solution is able to investigate the data within as little as two to three days. Scailyte intends to initially only make the software available on the market for scientists. The first sales should be concluded in the fall, although there are plans for the software to then be standardized and offered for clinical purposes over the coming years. Moreover, services in the field of data analysis are set to become part of the business model.
In order that the software can then later be offered in practice, Scailyte is already working with hospitals with the aim of uncovering cancer biomarkers, for example. “We have already uncovered some biomarkers”, Nestorov commented. At the moment, evaluations are still being conducted in project partner buildings, although the start-up is, however, intending to construct its own laboratory in the near future.
To realize these growth plans, Scailyte is planning a major financing round in mid-2020. The intention is to raise between 20 and 40 million Swiss francs. Last December, Scailyte secured risk capital in the amount of 2.7 million francs.
Scailyte is a spin-off affiliated to the Swiss Federal Institute of Technology in Zurich (ETH) with its headquarters in Sursee.
