Precision diagnostics to immune medicine using AI-assisted analysis of single-cell blood data
hema.to raises €3.6M
Today, diagnostics of blood cancer and other immune diseases from cytometry involves trained analysts and doctors assessing abstract, high-dimensional point clouds using their experience and training. This costs a lot of valuable time (anywhere from minutes to hours per sample, roughly 20 minutes on average), which is a real issue given the immense and increasing shortage of trained laboratory personnel. Besides this increasing pressure on laboratory staff, this process is known to be subjective, with a typical 30% analysis variability between operators. Because of these hurdles, the known and documented capability to guide more personalized treatment using cytometry data is severely underleveraged. hema.to aims to dramatically improve this process using its modern cloud-based Machine Learning platform, helping labs to process their case load, laboratory personnel to cope with increasing demand, give every patient an objective second opinion and empower doctors with new insights to personalize treatment to their patient’s unique immune system.
On a mission to helps labs globally with their clinical cytometry workflows
"Europe’s largest leukemia lab had the real need to speed-up their internal analysis workflows and worked with us to build a world-first AI prototype. After the success of demonstration of AI-assisted clinical cytometry, we noticed that all labs have the same manual workflows and pain points. We founded hema.to two years ago to help labs across the world with their clinical cytometry workflows", Karsten Miermans, co-founder and CEO of hema.to.
Using their large and growing proprietary database of diverse sources of cytometry data, hema.to has built algorithms that can predict biomarkers of disease directly from the raw data returned by the blood measurement device. This is a to-date unsolved challenge, since the lack of standardized measurement protocols introduces complex data variability that have so far hindered automation. hema.to specializes in combining data from diverse sources to learn predictive biomarkers of disease. The team has already deployed this technology into the clinical routine for decision support at two laboratories — the Institute for Hematopathology, Hamburg, and Result Laboratorium Dordrecht, and will next expand the number of users, number of diseases supported as well as as improve the quality of their AI models.
hema.to is headquartered in Munich and led by a team of data science experts that have been working together for years already, prior to starting hema.to. Since founding almost two years ago, they acquired CE-IVD conformity of their product, performed a four-center clinical study and brought it into clinical routine in two laboratories. With this second financing round, they will substantially grow the team with a focus on AI and software engineers for product development, but also immunologists/cytometrists and business development and partnerships.
"We have been convinced by the founding team, composed of three former entrepreneurs from the same company, with three PhD profiles, at a stage where they are going to scale their go to market, which is coherent with our deep tech seed investment thesis. I rejoice because hema.to is Elaia’s first investment in Germany", Anne-Sophie Carrese, Managing Partner at Elaia Partners.
"The unique A.I.-based approach developed by hema.to has a transformative potential in cytometry, filling a high unmet need for this method that provides key health and biological metrics in many indications. We are proud and thrilled to join hema.to’s team in this endeavor", David Sourdive, Venture Partner at Elaia Partners.
"We look for investments that meet a critical market need and founders on a mission to make healthcare sustainable and future-proof. hema.to has the potential to accelerate precision diagnostics in immune medicine: improving diagnostic quality at scale and at the same time supporting laboratory personnel to optimize their valuable time", Christian Lautner, Managing Partner at Heal Capital, concluded.
"We are very impressed with the speed and quality of the hema.to team’s AI development so far. We look forward to all further steps to improve leukaemia diagnostics in this great consortium!", Nik Raupp, Senior Investment Manager at HTGF.
"We started hema.to not realizing how much our skillset in AI could help to advance immune medicine. With the very complex immune system increasingly a target of therapies, we believe that there will be a sharply growing demand for AI models trained on large databases for precision diagnostics of the immune system. We’re thrilled to have the support of Elaia, Heal Capital and HTGF in addressing one of the greatest challenges of modern medicine", Karsten Miermans, Co-founder and CEO of hema.to.
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