Latest news with #Owkin
Fast Company
3 days ago
- Health
- Fast Company
The lab of the future: An artificial superintelligence for biology
The lab as we know it today is being transformed by how we think about medical research and drug discovery, as well as the intersection of artificial intelligence and biotechnology. As someone who has transitioned from a doctor to a tech CEO, I've witnessed firsthand how our mindset around medicine and innovation needs to evolve to keep pace with the accelerating changes in technology. In my journey, one of the most important lessons I've learned is: You can be too smart for your own good. It may sound counterintuitive, but when building a company or investing in new technologies, the smartest people often fall into the trap of overcomplicating things. A brilliant idea isn't always enough. You need the right people who can think creatively, take risks, and make it happen in the real world. For me, the mindset shift from doctor to CEO was about understanding that it's not just about medical knowledge; it's about building the right ecosystem to nurture that knowledge and turn it into real and transformative change. I believe that a crucial part of that ecosystem for my company, Owkin, is a new form of intelligence: a biological artificial superintelligence (BASI) to complement the ingenious human minds working with us. Next generation AI tools, like K Navigator, Owkin's agentic co-pilot for researchers, and K Pro for pharma, which is in the pipeline, will allow us to understand the full complexity of biology that has been beyond human understanding so far. This forms the backbone of Owkin's mission: We are creating the next-generation pharma focused on discovering cures and significantly enhancing pipeline value by developing a new intelligence system capable of decoding biological truths at scale. AI can fill the innovation gap left by pharma As the pharmaceutical industry increasingly focuses on a handful of blockbuster drugs, it's leaving behind many areas of medicine that are crucial for the future of healthcare. Too many diseases remain uncured as traditional pharma struggles to navigate the complexity of biology to augment care with efficient new molecules and diagnostics. From rare diseases to precision oncology, there's an innovation gap that AI is perfectly positioned to fill. AI can identify previously overlooked opportunities and streamline the development of treatments that are highly personalized and targeted. Unlike traditional pharmaceutical companies that are heavily reliant on large-scale, high-risk projects, AI companies can operate in a more agile, data-driven way. We can make smaller, more informed bets, leveraging machine learning and vast datasets to uncover insights that were once out of reach. This shift enables faster and more efficient drug discovery, with the added benefit of offering solutions for diseases that may not have attracted the attention of big pharma. Cell lines alone aren't going to work Most traditional biological research has been based on cell lines—cells removed from the human body and grown in petri dishes. But as we look to the future, there's a growing realization that cell lines, and other traditional research methods, are becoming outdated. While once a staple in biomedical research, they do not accurately replicate the complexity of human biology, and they fail to capture the diversity and variability that exists in real patients. AI-driven models are capable of moving beyond the limitations of cell lines by integrating data both from research done in cells and tissues removed from the body (in vitro) and from research done in living animals (in vivo). This validation approach, which incorporates multiple data types and sources, allows us to create more reliable and predictive models of human diseases. Science is advancing, and so is regulation. The FDA's recent announcement of plans to phase out animal testing in favor of 'more effective, human-relevant methods' means that we are entering an era where therapies can be tested on human tissue models from the very start. In collaboration with leading academic centers, Owkin has developed a patient-derived, lab-grown organoid (a mini version of a human organ), a breakthrough that brings us closer to faster, more accurate, and humane drug discovery. The combination of clinical data, genomic insights, and AI not only accelerates the development of new treatments but also increases their chances of success in clinical trials. The lab of the future The lab of the future will be one where AI is at the center, guiding discovery, improving precision, and increasing efficiency. Validation using real-world data will allow us to make better decisions and achieve higher rates of success. The traditional research process is being upended by these new technologies, and that's a good thing. The future of medicine will not just rely on human expertise, but on the power of AI and data to transform how we understand and treat disease. AI will deliver transformative therapies at an exponential scale, addressing the complexities of biology that traditional pharmaceutical approaches often cannot solve. Labs will become automated and serve as the ultimate playground for scientists, driving the future of drug discovery by harnessing the full potential of advanced AI systems. In these dynamic labs, organoids and agents will come together to work in synergy, allowing scientists to model and simulate human biology with greater accuracy. AI-driven technology will decipher biological patterns to identify the patients most likely to respond to specific treatments, significantly improving the chances of success in clinical trials and beyond. Seamlessly integrating these cutting-edge tools into the lab environment will transform the way we approach drug discovery, targeting diseases with a level of precision that was previously unimaginable. By pioneering the use of data, biology, and AI to decode the fundamental mechanics of disease and advance medical science, it will be possible to establish a foundation for the future of a 'positive singularity' in medicine. Through this innovative ecosystem, AI can revolutionize medicine. The time to innovate is now, and the possibilities are endless.
Yahoo
21-05-2025
- Business
- Yahoo
Global AI in Diagnostics Market to Register Stunning Growth at a CAGR of ~22% by 2032
The increasing incidence of infectious and chronic illnesses is boosting the need for early and precise diagnosis, with AI playing a crucial role by improving detection and enabling quicker clinical decisions. At the same time, the widespread adoption of digital health and imaging technologies creates a solid base for integrating AI into current healthcare systems, enhancing both efficiency and accuracy. Furthermore, ongoing product innovation by major global players, driven by progress in machine learning and growing regulatory backing, is accelerating the availability of AI-based diagnostic solutions. New York, USA, May 21, 2025 (GLOBE NEWSWIRE) -- Global AI in Diagnostics Market to Register Stunning Growth at a CAGR of ~22% by 2032 | DelveInsight The increasing incidence of infectious and chronic illnesses is boosting the need for early and precise diagnosis, with AI playing a crucial role by improving detection and enabling quicker clinical decisions. At the same time, the widespread adoption of digital health and imaging technologies creates a solid base for integrating AI into current healthcare systems, enhancing both efficiency and accuracy. Furthermore, ongoing product innovation by major global players, driven by progress in machine learning and growing regulatory backing, is accelerating the availability of AI-based diagnostic solutions. DelveInsight's AI in Diagnostics Market Insights report provides the current and forecast market analysis, individual leading AI in diagnostics companies' market shares, challenges, AI in diagnostics market drivers, barriers, trends, and key market AI in diagnostics companies in the market. Key Takeaways from the AI in Diagnostics Market Report As per DelveInsight estimates, North America is anticipated to dominate the global AI in diagnostics market during the forecast period. In the component segment of the AI in diagnostics market, the software category captured a significant revenue share in 2024. Notable AI in diagnostics companies such as Aidoc, Owkin, Inc., Siemens Healthineers, PathAI, Ibex, Owkin, Inc., Imagen Technologies, Aiforia, RADLogics, Terarecon, Inc., Prenosis, Inc., Ibex, Google LLC, GE HealthCare, DreaMed, Riverain Technologies, Terarecon, Inc., Aiforia, RADLogics, and several others are currently operating in the AI in diagnostics market. In September 2024, Ibex Medical Analytics (Ibex), a leader in AI-powered cancer diagnostics, introduced the latest advancements in its innovative product platform, Ibex-AI. These new features, developed in collaboration with expert pathologists worldwide who actively use the platform in routine clinical practice, highlight Ibex's ongoing commitment to creating cutting-edge diagnostic tools tailored to the needs of healthcare professionals on the frontlines of patient care. In October 2023, Lucida Medical Ltd announced that it received Class IIb CE certification for its AI-powered prostate cancer detection software, Prostate IntelligenceTM (PiTM). Leveraging advanced AI technology, PiTM analyzes MRI scans and is seamlessly integrated into the radiologist's workflow. In March 2023, Qritive launched its latest AI-driven innovation, QAi Prostate, designed specifically for prostate cancer diagnosis. Utilizing cutting-edge machine learning algorithms, QAi Prostate analyzes whole slide images of prostate core needle biopsies with high precision. To read more about the latest highlights related to the AI in diagnostics market, get a snapshot of the key highlights entailed in the Global AI in Diagnostics Market Report AI in Diagnostics Overview Artificial Intelligence (AI) is revolutionizing diagnostics by enabling faster, more accurate detection of diseases through advanced data analysis and pattern recognition. AI-powered systems can analyze medical images such as X-rays, MRIs, and CT scans with high precision, often matching or exceeding the performance of human radiologists in identifying abnormalities like tumors, fractures, or infections. By processing vast amounts of data from electronic health records, lab results, and genomics, AI algorithms can also uncover hidden correlations, assist in early disease prediction, and support personalized treatment plans. Moreover, AI is streamlining workflows in diagnostic laboratories and reducing the burden on healthcare professionals. For instance, AI-driven tools can automate routine tasks such as blood sample analysis or pathology slide interpretation, allowing clinicians to focus on complex cases. In resource-constrained settings, AI has the potential to bridge the gap in healthcare access by providing decision support to less experienced practitioners. As AI continues to evolve, integrating real-time data and improving interpretability, it holds the promise of significantly enhancing diagnostic accuracy, speed, and overall patient in Diagnostics Market Insights North America is expected to dominate the overall Artificial Intelligence (AI) in Diagnostics market over the forecast period, driven by advanced healthcare infrastructure, significant investments in AI technologies, and widespread adoption of digital health solutions. The United States, in particular, leads the region due to its early adoption of cutting-edge technologies, strong presence of leading AI and healthcare companies, and supportive regulatory frameworks. The growing demand for early and accurate diagnosis, especially for chronic and complex diseases such as cancer and cardiovascular conditions, has propelled the integration of AI into diagnostic tools and platforms. Major healthcare institutions in the region are increasingly leveraging AI algorithms for imaging analysis, pathology, and predictive diagnostics, further accelerating market growth. Moreover, robust government initiatives and funding programs supporting AI research in healthcare continue to fuel innovation and development. Strategic collaborations between technology firms and medical institutions are resulting in AI solutions with improved accuracy and efficiency, contributing to enhanced patient outcomes. The presence of a tech-savvy population, favorable reimbursement policies for AI-enabled diagnostic procedures, and a well-established ecosystem of data-driven healthcare systems also contribute to North America's leading position in this domain. As AI technologies mature and gain greater clinical acceptance, the region is expected to remain at the forefront of global advancements in AI-driven diagnostics. To know more about why North America is leading the market growth in the AI in diagnostics market, get a snapshot of the AI in Diagnostics Market Outlook AI in Diagnostics Market Dynamics The AI in diagnostics market has seen significant growth due to technological advancements in machine learning (ML) and artificial intelligence (AI), allowing for the automation and enhancement of diagnostic processes. AI-powered diagnostic tools are revolutionizing areas such as imaging, pathology, and molecular diagnostics, enabling faster, more accurate results with reduced human error. This has become especially crucial in areas like cancer detection, where early identification can significantly impact treatment outcomes. AI algorithms, capable of analyzing vast datasets, can detect patterns and abnormalities in medical imaging that may be missed by the human eye, leading to earlier intervention. The market dynamics are also being influenced by the increasing demand for personalized healthcare. As healthcare systems move towards precision medicine, AI in diagnostics plays a vital role by tailoring diagnostic tests and treatments based on individual genetic profiles. This is particularly significant in oncology, where molecular diagnostics are being enhanced by AI to offer more targeted therapeutic options. With this move toward personalized diagnostics, the role of AI in predicting disease outcomes and treatment responses continues to expand, driving the need for more sophisticated diagnostic tools. Furthermore, regulatory approvals and integration with healthcare systems are key to AI's success in diagnostics. Governments and healthcare bodies are gradually developing guidelines for AI in clinical settings, which is boosting investor confidence and enabling more widespread adoption. However, challenges such as data privacy concerns, interoperability issues, and the need for large-scale validation studies still pose barriers to the full-scale integration of AI diagnostics. As a result, partnerships between AI companies and traditional diagnostic firms are becoming more common to combine the strengths of AI technologies with the reliability and credibility of established healthcare systems. The growing prevalence of chronic diseases and the increasing burden on healthcare systems globally are also driving the adoption of AI in diagnostics. AI can assist in managing large patient populations by streamlining workflows, reducing diagnostic errors, and providing healthcare professionals with better decision-making tools. The market is also seeing the emergence of AI-driven platforms that offer end-to-end diagnostic solutions, from initial patient consultation to final diagnosis, creating a more seamless healthcare experience. As AI technologies continue to mature, the market is expected to experience even greater expansion, making healthcare more accessible, efficient, and accurate. Get a sneak peek at the AI in diagnostics market dynamics @ AI in Diagnostics Market Dynamic Analysis Report Metrics Details Coverage Global Study Period 2022–2032 AI in Diagnostics Market CAGR ~22% AI in Diagnostics Market Size by 2032 USD 8 Billion Key AI in Diagnostics Companies Aidoc, Owkin, Inc., Siemens Healthineers, PathAI, Ibex, Owkin, Inc., Imagen Technologies, Aiforia, RADLogics, Terarecon, Inc., Prenosis, Inc., Ibex, Google LLC, GE HealthCare, DreaMed, Riverain Technologies, Terarecon, Inc., Aiforia, RADLogics, among others AI in Diagnostics Market Assessment AI in Diagnostics Market Segmentation AI in Diagnostics Market Segmentation By Component: Hardware/software, and Services AI in Diagnostics Market Segmentation By Application: Infectious Disease Diagnostics, Radiology, Oncology, Cardiology, and Others AI in Diagnostics Market Segmentation By Technology: Machine Learning, Natural Language Processing, and Others AI in Diagnostics Market Segmentation By Geography: North America, Europe, Asia-Pacific, and Rest of World Porter's Five Forces Analysis, Product Profiles, Case Studies, KOL's Views, Analyst's View Which MedTech key players in the AI in diagnostics market are set to emerge as the trendsetter explore @ AI in Diagnostics Companies Table of Contents 1 AI in Diagnostics Market Report Introduction 2 AI in Diagnostics Market Executive Summary 3 Competitive Landscape 4 Regulatory Analysis 5 AI in Diagnostics Market Key Factors Analysis 6 AI in Diagnostics Market Porter's Five Forces Analysis 7 AI in Diagnostics Market Layout 8 AI in Diagnostics Market Company and Product Profiles 9 KOL Views 10 Project Approach 11 About DelveInsight 12 Disclaimer & Contact Us Interested in knowing the AI in diagnostics market by 2032? Click to get a snapshot of the AI in Diagnostics Market Trends Related Reports AI in Cancer Diagnostics Market AI in Cancer Diagnostics Market Insights, Competitive Landscape, and Market Forecast – 2032 report deliver an in-depth understanding of the market trends, market drivers, market barriers, and key AI in cancer diagnostics companies, including iCAD, Inc., ibex-ai, Roche Diagnostics, Kheiron Medical Technologies Limited, MVision AI Inc., Siemens Healthineers AG, GE HealthCare, NVIDIA Corporation, Digital Diagnostics Inc., IBM Corporation, Azra AI, ConcertAI, PathAI, Median Technologies, Paige AI Inc., Therapixel, Flatiron, Freenome Holdings Inc., Sonrai Analytics, among others. Artificial Intelligence In Clinical Trials Market Artificial Intelligence In Clinical Trials Market Insights, Competitive Landscape, and Market Forecast – 2032 report delivers an in-depth understanding of the market trends, market drivers, market barriers, and key AI in clinical trials companies, including TEMPUS, NetraMark, ConcertAI, AiCure, Medpace, Inc., ICON plc, Charles River Laboratories, Dassault Systèmes, Oracle, Certara, Cytel Inc., Phesi, DeepHealth, Inc., H1, TrialX, Suvoda LLC, Risklick, Lokavant, Research Solutions, among others. Artificial Intelligence In Drug Discovery Market Artificial Intelligence In Drug Discovery Market Insights, Competitive Landscape, and Market Forecast – 2032 report delivers an in-depth understanding of the market trends, market drivers, market barriers, and key AI in drug discovery companies, including IBM Corporation, Numedii Inc, Deep Genomics, NVIDIA Corporation, Atomwise Inc, Cloud Pharmaceuticals Inc, Alphabet Inc (DeepMind), Insilico Medicine, BenevolentAI, Exscientia, Cyclia, Valo Health, Owkin Inc, Verge Genomics, BioSymetrics, among others. Artificial Intelligence in Drug Commercialization Market Artificial Intelligence in Drug Commercialization Market Insight, Competitive Landscape, and Market Forecast – 2032 report delivers an in-depth understanding of market trends, market drivers, market barriers, and key AI in drug commercialization companies, including EVERSANA, Lyfegen, Syneos Health, McKinsey & Company, ICON plc., Clarivate., Thermo Fisher Scientific Inc., Viseven, ZS Associates, Cloud Pharmaceuticals Inc., among others. Artificial Intelligence in Precision Medicine Market Artificial Intelligence in Precision Medicine Market Insight, Competitive Landscape, and Market Forecast – 2032 report delivers an in-depth understanding of market trends, market drivers, market barriers, and key AI in precision medicine companies, including TEMPUS, GE HealthCare, Envisionit Deep AI (Pty) Ltd., Aignostics, Inc., Proscia Inc., Ultivue, Inc., Prenosis, Inc., IBEX, Cleerly, Inc., Paige AI, Inc., Densitas® Inc., Photocure ASA, iCAD, Inc., Eko Health, Inc., Owkin, Inc, Massive Bio, Deep Bio Inc., Atomwise Inc., among others. About DelveInsight DelveInsight is a leading Business Consultant and Market Research firm focused exclusively on life sciences. It supports pharma companies by providing comprehensive end-to-end solutions to improve their performance. CONTACT: Contact Us Shruti Thakur info@ +14699457679
Yahoo
06-05-2025
- Business
- Yahoo
Owkin Launches K Navigator, a Ground-breaking Agentic Co-pilot to Speed up Breakthroughs in Biomedical Research by 20x
K Navigator increases researcher productivity by 20x¹, accelerating biomedical breakthroughs and outperforming leading generalist LLMs Analyzes and visualizes multimodal patient data, plus exclusive access to MOSAIC Window, a subset of the world's largest spatial omics dataset in oncology Built by biologists, for biologists. Free to use for academic researchers.² NEW YORK & PARIS, May 06, 2025--(BUSINESS WIRE)--Owkin, a leading agentic AI company, has launched K Navigator, an AI-powered research co-pilot designed to revolutionize biomedical science. K Navigator is an agentic playground where researchers can explore, refine, and validate hypotheses, accelerating the quality and pace of their discoveries. With K Navigator, Owkin moves closer to its vision of developing the world's first Biological Artificial Superintelligence (BASI). A single natural language interface - K Navigator enables users to explore and visualize data, refine questions, and uncover insights with ease. It accelerates literature reviews across 26.5 million scientific articles, reveals unexplored and unpublished research areas, and delivers more accurate analysis, drawing on 19 biomedical databases featuring thousands of patients. Exclusive access to cutting-edge spatial transcriptomic data - It exclusively accesses and analyzes newly released spatial multiomic data at single cell resolution from MOSAIC Window,³ a subset of the largest spatial omics dataset in oncology, providing researchers with insights and accuracy unmatched by any other AI co-pilot. MOSAIC data is generated by top tier academic universities across Europe and the US. Superior performance - On tasks related to analyzing public datasets, K Navigator matches large language models (including reasoning models like 03 from OpenAI) and outperforms them in detecting cancer-related patterns.⁴ Free for the academic research community - K Navigator is free to academic researchers to strengthen the first AI agentic biomedical collective intelligence. Owkin is working with world-leading institutions to shape and continuously improve it. The next update of the product will include seamless collaboration, result sharing, and project organization, as well as advanced histology tools for filtering, grouping, heat mapping, and deeper digital pathology slide analysis. Transforming research beyond academia - Later this year Owkin will launch K Pro, an extended AI co-pilot featuring a suite of agents to solve complex pharma challenges across data exploration, drug discovery, and drug development. Thomas Clozel, MD, Owkin Co-founder and CEO, commented: "Over the past century, we've made tremendous progress in chemistry; progress that has only accelerated with the help of AI. But biology is a different challenge altogether: it's too complex for the human mind alone, with its vast networks of genes, cells, and interactions. "To truly understand disease and develop cures for unmet medical needs, we need to productize research by augmenting and accelerating discovery at every level. That's why we developed K Navigator. The ultimate aim for K is to curate large language models and foundation models with patient-level data at scale, so we can move closer to ground-truth biology and finally capture its full complexity." Dr. Ingo Ringshausen, Principal Investigator at University College London & Consultant Haematologist University College London Hospital said, "After my first hands-on experience with K Navigator, I was immediately struck by its exceptional ease of use. The potential impact for research teams is obvious, in particular thanks to its robust multi-omics patient data exploration capabilities." Dr. Cécile Alanio, Deputy Director of Clinical Immunology Laboratory, Institut Curie said: "K Navigator is an amazing product that gives us the autonomy we've been missing to explore data independently. It empowers researchers while enabling bioinformaticians to focus on more complex analytical challenges. The features are truly impressive, it allows us to get a feel for the data - which is what I love most about it." About Owkin Owkin is an agentic AI company on a mission to explore complex biology to speed up and scale research for the creation of new treatments and diagnostics for patients. Owkin K, our AI co-pilot combines unparalleled access to multimodal data, cutting-edge AI to quantify biology and pioneering agentic AI to achieve Biological Artificial Superintelligence in the future. References 20x productivity is an average across various tasks for example: generating a spatial transcriptomics plot takes on average 1 minute, compared to 3 days and drug target characterization (annotation) is on average 75% faster with K compared to manual methods. Initial signup includes free access to the beta version for a 6-month evaluation period. We're currently limited to a restricted number of users for the evaluation period of our beta version of K-Navigator. At the moment, access is available to a small group of users, and we've set up a waitlist for everyone else interested in joining. MOSAIC is a global initiative led by Owkin and uniting top academic centers (Charité - Universitätsmedizin Berlin, University of Pittsburgh, Institut Gustave Roussy, Lausanne University Hospital - CHUV, and Uniklinikum Erlangen), to create the world's largest spatial omics and multimodal dataset in oncology and revolutionize therapeutic targets and biomarker discovery. MOSAIC Window is a 60-patient subset from the larger MOSAIC dataset. This dataset is pseudonymized, pre-processed, and made available to researchers through K Navigator. We benchmarked K-Navigator against a subset of the public benchmark LAB-Bench. On most tasks, K-Navigator performs on-par with all frontier LLMs tested, including reasoning ones. K-Navigator shows superiority on the oncogenic signature subtask. In oncogenic signature, models are asked to identify genes belonging to very specific gene sets that behave in a certain way in cancer models. Legal notice Certain potential users of Owkin K may be subject to anti-gift or anti-bribery regulations based on their profession and jurisdiction. Owkin is collecting all pertinent information from potential users to ensure that anti-gifting and bribery laws are followed across jurisdictions. Owkin reserves the right to restrict access to certain users who are prohibited from accepting them under applicable regulations. 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Business Wire
06-05-2025
- Business
- Business Wire
Owkin Launches K Navigator, a Ground-breaking Agentic Co-pilot to Speed up Breakthroughs in Biomedical Research by 20x
NEW YORK & PARIS--(BUSINESS WIRE)--Owkin, a leading agentic AI company, has launched K Navigator, an AI-powered research co-pilot designed to revolutionize biomedical science. K Navigator is an agentic playground where researchers can explore, refine, and validate hypotheses, accelerating the quality and pace of their discoveries. With K Navigator, Owkin moves closer to its vision of developing the world's first Biological Artificial Superintelligence (BASI). K Navigator is an agentic AI playground where researchers can explore, refine, and validate hypotheses, accelerating the quality and speed of their discoveries by 20X. A single natural language interface - K Navigator enables users to explore and visualize data, refine questions, and uncover insights with ease. It accelerates literature reviews across 26.5 million scientific articles, reveals unexplored and unpublished research areas, and delivers more accurate analysis, drawing on 19 biomedical databases featuring thousands of patients. Exclusive access to cutting-edge spatial transcriptomic data - It exclusively accesses and analyzes newly released spatial multiomic data at single cell resolution from MOSAIC Window,³ a subset of the largest spatial omics dataset in oncology, providing researchers with insights and accuracy unmatched by any other AI co-pilot. MOSAIC data is generated by top tier academic universities across Europe and the US. Superior performance - On tasks related to analyzing public datasets, K Navigator matches large language models (including reasoning models like 03 from OpenAI) and outperforms them in detecting cancer-related patterns.⁴ Free for the academic research community - K Navigator is free to academic researchers to strengthen the first AI agentic biomedical collective intelligence. Owkin is working with world-leading institutions to shape and continuously improve it. The next update of the product will include seamless collaboration, result sharing, and project organization, as well as advanced histology tools for filtering, grouping, heat mapping, and deeper digital pathology slide analysis. Transforming research beyond academia - Later this year Owkin will launch K Pro, an extended AI co-pilot featuring a suite of agents to solve complex pharma challenges across data exploration, drug discovery, and drug development. Thomas Clozel, MD, Owkin Co-founder and CEO, commented: 'Over the past century, we've made tremendous progress in chemistry; progress that has only accelerated with the help of AI. But biology is a different challenge altogether: it's too complex for the human mind alone, with its vast networks of genes, cells, and interactions. 'To truly understand disease and develop cures for unmet medical needs, we need to productize research by augmenting and accelerating discovery at every level. That's why we developed K Navigator. The ultimate aim for K is to curate large language models and foundation models with patient-level data at scale, so we can move closer to ground-truth biology and finally capture its full complexity.' Dr. Ingo Ringshausen, Principal Investigator at University College London & Consultant Haematologist University College London Hospital said, 'After my first hands-on experience with K Navigator, I was immediately struck by its exceptional ease of use. The potential impact for research teams is obvious, in particular thanks to its robust multi-omics patient data exploration capabilities.' Dr. Cécile Alanio, Deputy Director of Clinical Immunology Laboratory, Institut Curie said: 'K Navigator is an amazing product that gives us the autonomy we've been missing to explore data independently. It empowers researchers while enabling bioinformaticians to focus on more complex analytical challenges. The features are truly impressive, it allows us to get a feel for the data - which is what I love most about it. ' About Owkin Owkin is an agentic AI company on a mission to explore complex biology to speed up and scale research for the creation of new treatments and diagnostics for patients. Owkin K, our AI co-pilot combines unparalleled access to multimodal data, cutting-edge AI to quantify biology and pioneering agentic AI to achieve Biological Artificial Superintelligence in the future. References 20x productivity is an average across various tasks for example: generating a spatial transcriptomics plot takes on average 1 minute, compared to 3 days and drug target characterization (annotation) is on average 75% faster with K compared to manual methods. Initial signup includes free access to the beta version for a 6-month evaluation period. We're currently limited to a restricted number of users for the evaluation period of our beta version of K-Navigator. At the moment, access is available to a small group of users, and we've set up a waitlist for everyone else interested in joining. MOSAIC is a global initiative led by Owkin and uniting top academic centers (Charité - Universitätsmedizin Berlin, University of Pittsburgh, Institut Gustave Roussy, Lausanne University Hospital - CHUV, and Uniklinikum Erlangen), to create the world's largest spatial omics and multimodal dataset in oncology and revolutionize therapeutic targets and biomarker discovery. MOSAIC Window is a 60-patient subset from the larger MOSAIC dataset. This dataset is pseudonymized, pre-processed, and made available to researchers through K Navigator. We benchmarked K-Navigator against a subset of the public benchmark LAB-Bench. On most tasks, K-Navigator performs on-par with all frontier LLMs tested, including reasoning ones. K-Navigator shows superiority on the oncogenic signature subtask. In oncogenic signature, models are asked to identify genes belonging to very specific gene sets that behave in a certain way in cancer models. Legal notice Certain potential users of Owkin K may be subject to anti-gift or anti-bribery regulations based on their profession and jurisdiction. Owkin is collecting all pertinent information from potential users to ensure that anti-gifting and bribery laws are followed across jurisdictions. Owkin reserves the right to restrict access to certain users who are prohibited from accepting them under applicable regulations.
