hema.to GmbH

hema.to GmbH

Softwareentwicklung

AI cytometry to advance precision immune medicine

Info

We are a deeptech AI company obsessed with solving cytometry and thereby make an outsized and lasting impact on immune medicine: we want to make sure every patient gets the right treatment at the right time for their unique immune systems.

Website
https://hema.to
Branche
Softwareentwicklung
Größe
11–50 Beschäftigte
Hauptsitz
Munich
Art
Privatunternehmen
Gegründet
2021

Orte

Beschäftigte von hema.to GmbH

Updates

  • Unternehmensseite von hema.to GmbH anzeigen, Grafik

    2.616 Follower:innen

     🎉 We are heading to Lisbon for the 13th ESLHO Symposium! 🌍 Following our success at ESCCA in Palma de Mallorca, we are thrilled to bring our cutting-edge hema.to base platform to ESLHO. We’ll be showcasing the power of AI-driven solutions to speed up the process from raw data to report, with higher precision and efficiency. With hema.to base, you can handle your growing cytometry sample volume 𝘢𝘯𝘥 get clearer insights into your data. Our AI not only classifies cell types but also detects diseases like Hairy Cell Leukemia, pointing you directly to the pathological cells and their phenotype. And the best part? We customize our AI to fit seamlessly into your specific workflow. Join Olivier Poulin, and João Moura Alves at the booth for a live demo and insightful discussions. Feel free to book a meeting in advance by emailing at athina@hema.to! We look forward to connecting with you in Lisbon! 🌟 #AI #Cytometry #DataDrivenMedicine #ESLHO #Hematology #Oncology

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  • Unternehmensseite von hema.to GmbH anzeigen, Grafik

    2.616 Follower:innen

    🪑 𝐖𝐞 𝐬𝐡𝐨𝐮𝐥𝐝'𝐯𝐞 𝐠𝐨𝐭𝐭𝐞𝐧 𝐦𝐨𝐫𝐞 𝐜𝐡𝐚𝐢𝐫𝐬 𝐟𝐨𝐫 𝐨𝐮𝐫 𝐛𝐨𝐨𝐭𝐡, because it's attracting a lot of attention at the ESCCA venue this year! 💪 We've been rather in stealth mode with our product development and hoping to make a big splash this year at the major venues -- we're therefore very happy to see people are excited about the future of clinical cytometry through compliant, plug&play AI cytometry. Together with the top-notch HpH Institut für Pathologie und Hämatopathologie Hamburg and especially the very experienced Holger Hauspurg, we've built out the product and clinical evidences that show AI can make your cytometry work faster 𝘢𝘯𝘥 better. At ESCCA, we've shown that our latest AI can: - Efficiently identify populations as small as 3% of total cells - Differentiation 𝘢𝘵 𝘴𝘪𝘯𝘨𝘭𝘦-𝘤𝘦𝘭𝘭 𝘭𝘦𝘷𝘦𝘭 a variety of blood cancers - Detect 𝘱𝘳𝘦𝘷𝘪𝘰𝘶𝘴𝘭𝘺 𝘶𝘯𝘯𝘰𝘵𝘪𝘤𝘦𝘥 secondary B-NHL clones - reduce the false negative rate for reliable screening of your patients A big thank you to our very competent product and tech team, notably Florian Pfisterer for the AI models used in this work, Judit Rial Saborido for shaping many of these new product features, João Moura Alves for his unrivaled cytometry expertise, Holger Hauspurg for his medical expertise and enabling us to work with real patient data, Dr. Aleksandra Mezydlo for designing+coordinating the studies and Athina Chavli and Olivier Poulin for getting people excited about hema.to at ESCCA. Last but not least Lara Rashdan for preparing hema.to for the upcoming audit that'll expand our CE mark to include our latest features! You can see the check out the full poster on https://www.hema.to/blog 🚀 More big things to come, subscribe to this LinkedIn page or reach out to Athina Chavli (athina@hema.to) or Olivier Poulin (olivier@hema.to).

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  • Unternehmensseite von hema.to GmbH anzeigen, Grafik

    2.616 Follower:innen

    Reminder to all (clinical) cytometrists that we will be proudly showcasing the future of AI cytometry at ESCCA starting tomorrow! Come find Olivier Poulin (olivier@hema.to) or Athina Chavli (athina@hema.to) at our booth. Spoiler alert, they will show you: - our vision for cytometry case management using automated priority triage - single-cell-classification of healthy 𝘢𝘯𝘥 diseased cells - automated, configurable reporting - automated QC for every patient on fluidics, compensation and more - they can explain our best-in-class compliance processes as an IVD - how we can deeply integrate hema.to into your LIS using our FHIR interface for a super smooth workflow - and much more.. 👉 More info on https://www.hema.to/

    Unternehmensseite von hema.to GmbH anzeigen, Grafik

    2.616 Follower:innen

    𝐌𝐞𝐞𝐭 𝐮𝐬 𝐚𝐭 𝐄𝐒𝐂𝐂𝐀 𝐢𝐧 𝐏𝐚𝐥𝐦𝐚 𝐝𝐞 𝐌𝐚𝐥𝐥𝐨𝐫𝐜𝐚! We will be showing our new product hema.to base: a clinical cytometry AI platform to go from raw data to report, faster and better. With hema.to base, we want to help you cope with your rapidly increasing number of cytometry samples 𝘢𝘯𝘥 sleep well at night. We do that using 𝐬𝐢𝐧𝐠𝐥𝐞-𝐜𝐞𝐥𝐥 𝐜𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 of not only cell type but also of disease (as in the example of the hairy cell leukemia in the screenshot of our product), pointing you exactly to the pathological cells and their phenotype. These AI models are not specific to one panel, we adapt our AI to your workflow. Athina Chavli, Olivier Poulin and our expert cytometrist João Moura Alves will be on-site, but feel free to book a meeting with them in advance (just drop a line to athina@hema.to)!

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  • Unternehmensseite von hema.to GmbH anzeigen, Grafik

    2.616 Follower:innen

    𝐌𝐞𝐞𝐭 𝐮𝐬 𝐚𝐭 𝐄𝐒𝐂𝐂𝐀 𝐢𝐧 𝐏𝐚𝐥𝐦𝐚 𝐝𝐞 𝐌𝐚𝐥𝐥𝐨𝐫𝐜𝐚! We will be showing our new product hema.to base: a clinical cytometry AI platform to go from raw data to report, faster and better. With hema.to base, we want to help you cope with your rapidly increasing number of cytometry samples 𝘢𝘯𝘥 sleep well at night. We do that using 𝐬𝐢𝐧𝐠𝐥𝐞-𝐜𝐞𝐥𝐥 𝐜𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 of not only cell type but also of disease (as in the example of the hairy cell leukemia in the screenshot of our product), pointing you exactly to the pathological cells and their phenotype. These AI models are not specific to one panel, we adapt our AI to your workflow. Athina Chavli, Olivier Poulin and our expert cytometrist João Moura Alves will be on-site, but feel free to book a meeting with them in advance (just drop a line to athina@hema.to)!

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  • Unternehmensseite von hema.to GmbH anzeigen, Grafik

    2.616 Follower:innen

    𝐒𝐨𝐦𝐞 𝐩𝐡𝐞𝐧𝐨𝐭𝐲𝐩𝐞𝐬 𝐚𝐫𝐞 𝐯𝐞𝐫𝐲 𝐭𝐫𝐢𝐜𝐤𝐲 𝐭𝐨 𝐝𝐢𝐚𝐠𝐧𝐨𝐬𝐞, such as for this patient that was diagnosed with CLL and MDS/AML. Our latest AI (that we will demo live at ESCCA in one week, come find us!) however identified an additional population consistent with a marginal zone lymphoma. This candidate MZL was not identified by the laboratory. 𝐖𝐡𝐲 𝐰𝐚𝐬 𝐭𝐡𝐢𝐬 𝐌𝐙𝐋 𝐦𝐚𝐲𝐛𝐞 𝐦𝐢𝐬𝐬𝐞𝐝? It is not easy to detect the pathological clone with MZL phenotype because the phenotype is not easy to distinguish and, overall, the B-cells seem polyclonal. This AI model was optimized to not miss out disease (very low false negative rate) of B-cell pathologies, and in this case suggests an additional DLBCL. These cells are lymphoid (TdT+, MPO-, CD13-) and have B-cell markers (CD19low, CD20, CD79b, CD22) but express CD34 and/or CD117, so more likely ALL than DLBCL. In future versions of this algorithm, we will include other diseases so that also an ALL will be classified correctly out-of-the-box, 𝘢𝘯𝘥 the most important thing is that this diseased population was detected for further phenotyping and diagnostic tests. If you wish to participate in testing out clinical AI for these diseases or new ones, write to Athina Chavli (athina@hema.to), she'll be delighted to talk to you at ESCCA or set up a meeting with our expert cytometrist João Moura Alves at ESLHO or our CEO Karsten Miermans during ICCS!

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