What makes data truly valuable? Mike Rossi reminds us it’s only powerful when it’s accessible and when it actually helps us understand disease outcomes. 🎧 Tune in to episode 50 of Talking Precision Medicine → https://lnkd.in/dapxXXJJ
About us
Genialis, the RNA biomarker company, is creating a world where healthcare delivers the best possible outcomes for patients, their families, and their communities. Genialis develops and validates clinically actionable biomarkers informed by the world’s most ethnographically diverse cancer data sets to better predict patient responses and guide treatment decisions for targeted inhibitors, immunotherapies, and other emerging therapeutic classes. Genialis is trusted by pharma and diagnostics partners, and together, we are transforming medicine through data.
- Website
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https://www.genialis.com/
External link for Genialis
- Industry
- Biotechnology
- Company size
- 11-50 employees
- Headquarters
- Boston, MA
- Type
- Privately Held
- Founded
- 2015
- Specialties
- Data Fusion, Machine Learning, Biomedical Data Analysis, Omics Data Integration, Precision Medicine, Software Development, Data Visualization, Gene Signature, and Predictive Biomarker
Locations
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Primary
Get directions
177 Huntington Ave
Ste 1703 PMB 29417
Boston, MA 02115-3153, US
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Get directions
Koprska ulica 72
Ljubljana, 1000, SI
Employees at Genialis
Updates
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Berlin calling for #ESMOAI25! Excited to see our collaboration with Debiopharm, featured as a poster at ESMO AI & Digital Oncology Congress, taking place November 12–14. 🧬 “A large molecular model (LMM)-based predictor of clinical response to the WEE1 inhibitor Debio 0123 + carboplatin therapy” The abstracts are now live. Read it here: https://lnkd.in/dskgunWg 📍 Poster number: 62eP 🗓️ Session: Poster Display, Wednesday, Nov 12 ⏰ Time: 14:45–15:45 Discover how our biology-informed model predicts response to WEE1 inhibition and supports development of biomarker-driven treatment strategies.
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Genialis reposted this
CEO & cofounder, Genialis | Precision Oncology with RNA + AI: Reimagining Biomarkers for Every Target, Drug and Patient
This Tuesday I had the privilege to attend my first CEO Roundtable on Cancer annual meeting, and to present Genialis in a talk and a poster. My first impression was that the event represented the most dense assemblage of deeply serious and relevant stakeholders / decision makers that I've encountered. To wit, the morning kicked off with a fireside chat between Peter Pisters, President of MD Anderson Cancer Center and Marty Makary M.D., M.P.H., Commissioner of the FDA. Seriously relevant, with a freewheeling discussion spanning everything from surrogate endpoints, priority review programs, competition with China, and the new AI frontier. The entire day followed suit. Over the past few days, one idea has really stuck with me. There's a general consensus desire to speed up the development of new cancer medicines, and also to ensure medicines work better for patients. Speed and quality often find themselves at odds. So how can we achieve both in this space? One solution is better surrogate endpoints that accurately predict overall survival (and quality of life). These endpoints will take the form of AI-modeled predictive biomarkers trained on multimodal data. But to get enough of the right data, we need a new paradigm for pre-competitive data sharing among Pharma companies. What if a trusted neutral party like the CEORT's Project DataSphere hosted an effort to build a giant pre-competitive dataset of clinical trial SoC arms, as well as failed/shelved assets? This would enable the development of multimodal digital twins to power clinical trials with dramatically reduced recruitment needs, and to accurately predict meaningful endpoints like OS. Tell me what you think, and more importantly, tell me if you'd like to tackle this problem together! Many thanks to Sean Khozin, CEO of CEORT, and Jon McDunn, President of Project DataSphere Great to meet David Reese, Jean-Charles Soria, MD, PhD, Rodney Gillespie, Sunil Verma, Christine Duffy, Brian J. Brille, Christopher Viehbacher, Josh Bilenker, Laura Esserman, Kimryn Rathmell, Kiran Patel, Zhen Su, MD MBA, Sushil Patel, Alicia Zhou, PhD, Christian Hinrichs and many others focused on winning this fight!
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🎙️ Episode 50 of Talking Precision Medicine is live! 🎉 A big milestone, fifty episodes of conversations about the future of healthcare and health technology, and how advances in data and data science are fueling the next industrial revolution. In this episode, Rafael Rosengarten talks with Mike Rossi, VP of Translational Science and Multimodal Real-World Evidence Solutions at ConcertAI. They discuss: 🔹 What real-world data really means and how it becomes real-world evidence 🔹 Why federated systems are the future of oncology research 🔹 The growing role of AI in connecting and interpreting patient data 🔹 How data partnerships help bring new therapies to patients faster 👉 Listen here: https://lnkd.in/dapxXXJJ Thank you to all our guests and listeners who’ve joined us so far. Here’s to the next 50 episodes of Talking Precision Medicine.
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There’s not just one driver behind non-small cell lung cancer – there are many And finding them can make all the difference 🔬 In Slovenia, every newly diagnosed non-squamous NSCLC patient now gets next-generation sequencing (NGS) testing On our ePoster we're co-presenting at ESMO 2025 we analyzed real data from 2,559 patients across the country Here’s what we found: 🧩 59% carried at least one targetable driver alteration 🧩 KRAS was most frequent (36%) 🧩 EGFR followed (14%) See the rest here: https://lnkd.in/dhqUXskE Routine NGS testing doesn’t just detect variants It helps match patients to better treatments – and that’s real progress ✍ Kudos to our colleagues and partners from University Clinic Golnik, Faculty of Medicine, University of Ljubljana and Institute of Oncology Ljubljana: Katja Mohorčič, Roman Luštrik, Izidor Kern, Mitja Rot, Mark Uhlik, Žan Kuralt, Luka Ausec, Jasna But Hadzic
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Boston bound for #Targets25! The Genialis team will join the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics from October 22–26 Our conference schedule is live here: 👉 https://lnkd.in/dHmShVnk
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Still early in its run, The Brainiac Blueprint podcast is taking on some big scientific questions 🔎 The recent episode with Aditya Pai explores how AI modeling of KRAS biology could shape the future of biomarker development
💡 Traditional biomarkers only tell part of the story. In Ep 11 of 𝘛𝘩𝘦 𝘉𝘳𝘢𝘪𝘯𝘪𝘢𝘤 𝘉𝘭𝘶𝘦𝘱𝘳𝘪𝘯𝘵, Aditya Pai, Head of Business Development at Genialis, explains how modeling the entire biology of KRAS with AI creates “next-generation biomarkers.” These biomarkers can reveal: ✅ Why a drug works (or doesn’t) ✅ Why patients develop resistance ✅ How long a treatment may help ✅ When combination therapies are needed 👏 Incredible work that could change how cancer drugs are developed and how patients receive care. 🎧 𝗗𝗼𝗻’𝘁 𝗺𝗶𝘀𝘀 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗲𝗽𝗶𝘀𝗼𝗱𝗲 𝘁𝗼 𝘀𝗲𝗲 𝗵𝗼𝘄 𝗚𝗲𝗻𝗶𝗮𝗹𝗶𝘀 𝗶𝘀 𝗽𝘂𝘀𝗵𝗶𝗻𝗴 𝗼𝗻𝗰𝗼𝗹𝗼𝗴𝘆 𝗳𝗼𝗿𝘄𝗮𝗿𝗱: YT 👉 https://lnkd.in/emj_taqC Spotify 👉 https://bit.ly/4n72kUa Apple 👉 https://bit.ly/3VMNtlH
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Genialis reposted this
CEO & cofounder, Genialis | Precision Oncology with RNA + AI: Reimagining Biomarkers for Every Target, Drug and Patient
Great conversation this evening at BioTechX Europe in Basel. I had the privilege of moderating a panel on AI in Clinical Trials on behalf of The Alliance for Artificial Intelligence in Healthcare (AAIH). Thanks to panelists: Felix Baldauf-Lenschen, Altis Labs Joseph Pearson, QIAGEN Luca Finelli, Roche Genentech and Szabolcs Nagy, Turbine I am really jazzed by the idea of better surrogate end points, and enjoyed the debate around the commodification of data and algorithms, and where future differentiators may lie ...
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Is your October also this packed? 🙉 We’re wrapping up BioTechX Europe in Basel and heading straight to the ESMO - European Society for Medical Oncology Congress in Berlin Join us Oct 17–21 to chat about how AI and deep biological expertise come together to deliver on the promise of precision medicine P.S. Our joint abstract with University Clinic Golnik has been accepted as an ePoster – stay tuned! #ESMO25
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For most cancers, doctors have a map For pancreatic cancer ... it’s still 𝗴𝘂𝗲𝘀𝘀𝘄𝗼𝗿𝗸 🤷 Especially for pancreatic ductal adenocarcinoma (PDAC) – the most common and deadliest form, responsible for over 90% of pancreatic cancer deaths Genialis and Cleveland Clinic are working to change this We’re connecting the Genialis™ Supermodel – trained on one of the world’s largest and most diverse RNA-seq datasets – with Cleveland Clinic’s patient-derived organoid center to build and validate AI-powered biomarkers for PDAC The goal is clear: better guidance for physicians, and ultimately better outcomes for patients Dig deeper: https://lnkd.in/dmdqAxc9