Latest news with #Viome
Yahoo
09-07-2025
- Business
- Yahoo
Microsoft, Viome Life Sciences Partner to Power Next-Gen Personalized Healthcare with AI, Azure
Microsoft Corporation (NASDAQ:MSFT) is one of the best US stocks to buy and hold in 2025. On July 7, Viome Life Sciences announced a collaboration with Microsoft. The partnership will accelerate the next generation of preventive and personalized healthcare by integrating Viome's extensive dataset of human and microbial gene expression with Microsoft Azure infrastructure services, such as Azure Ultra Disk Storage and Virtual Machines. Viome's AI platform is designed to transform this complex biological data into personalized nutrition and health insights. The integration of Viome's RNA science with Azure's secure and scalable HIPAA-compliant infrastructure services is expected to enable a new model of proactive and home-based healthcare guided by molecular data. A development team working together to create the next version of Windows. Viome's flagship product is the Full Body Intelligence Test, which is described as one of the most advanced home-based health tests. It analyzes both human and microbial gene expression from saliva, blood, and stool samples. To date, Viome has completed over one million analyses across 106 countries, generating more than 10 quadrillion biological data points, making its metatranscriptomic (RNA sequencing) dataset the most comprehensive of its kind. Microsoft Corporation (NASDAQ:MSFT) develops and supports software, services, devices, and solutions worldwide. Viome is a longevity and preventive healthcare company that uses AI to bridge the gap between scientific breakthroughs and their practical implementation as health solutions. While we acknowledge the potential of MSFT as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you're looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the . READ NEXT: and . Disclosure: None. This article is originally published at Insider Monkey. Sign in to access your portfolio
Geek Wire
07-07-2025
- Business
- Geek Wire
Microsoft and the microbiome: Viome works with tech giant to optimize AI for molecular health
Naveen Jain, Viome CEO and founder, worked at Microsoft early in his career. (Viome Photo) Viome, a life sciences startup founded by veteran tech entrepreneur Naveen Jain, announced a collaboration with Microsoft to scale its molecular analysis platform — part of what Viome describes as a new era of AI-powered preventive health and wellness. Viome says Microsoft's cloud and AI infrastructure — specially tuned for its purposes in conjunction with the tech giant — will allow it to process biological data more efficiently. The idea is to expand access, reduce costs, and accelerate data processing and diagnostics. For Jain, it's a full-circle moment. Before founding such companies as InfoSpace, Intelius, and Moon Express, he was a Microsoft group manager in the 1980s and '90s, working on the business side of MSN while current Microsoft CEO Satya Nadella ran engineering for Microsoft's online division. 'Satya will someday be known as being one of the best CEOs in human history,' Jain said, using some of his trademark exuberance to describe Viome's work with the tech giant. 'He has changed Microsoft to be a company that's an unbelievably great partner.' Their collaboration addresses a massive scaling challenge. Viome says it has data from more than 1 million samples (including blood, saliva, and stool) from people in 106 countries, generating what it calls an unprecedented set of more than 10 quadrillion biological data points. Processing this data requires large memory footprints and high-speed storage, rather than the GPU-heavy computing more typical of everyday AI workloads. That difference is what drove the Microsoft collaboration, said Guru Banavar, Viome's CTO and head of AI, who previously led the team that built the foundational AI platform for IBM's Watson. Guru Banavar, Viome's CTO and head of AI. (Viome Photo) The underlying architecture developed by Microsoft and Viome 'was put together specifically to handle this type of bioinformatics with a very large-scale catalog, with a large-scale data set that's being transferred back and forth,' Banavar said. Other life sciences companies on Microsoft's Azure cloud and AI platform may also now benefit from this work, but Banavar said their early collaboration gives Viome a strategic advantage. The Bellevue, Wash.-based company's platform analyzes how genes and microbes in the body are actively functioning in real time, not just which ones are present in the body. Viome then uses that data to generate personalized health insights and recommendations. Viome does this by focusing on RNA, which plays a key role in how genes are expressed and regulated, rather than DNA, which serves as the body's more static genetic blueprint. The long-term idea is to create what it calls 'biological digital twins' — computer models that can predict how individuals will respond to specific foods and interventions. Viome is straddling the line between consumer wellness and clinical diagnostics as it looks to address issues ranging from depression to early-stage oral cancer. On the consumer side, it offers testing kits for saliva, blood and stool samples, with prices currently ranging from $229 to $299. Customers collect the samples at home and send them to Viome's lab for analysis. Results include personalized diet and nutrition insights, with options to subscribe to supplements and oral care products ranging from $79 to $199 a month. These offerings fall under the wellness category and are generally not subject to FDA regulation. According to Jain, Viome distinguishes itself in the wellness space by conducting blinded, placebo-controlled studies to validate its recommendations, publishing in peer-reviewed journals. A Viome testing kit and the company's app. (Viome Photo) The rise of AI and molecular analysis has led to a boom in competition in the personalized health sector, with companies like Thorne, ZOE, BIOHM and others offering various approaches to microbiome testing and wellness insights. At the same time, Viome has developed diagnostic tools that analyze RNA biomarkers to detect disease — including a test for early detection of oral cancer that has received FDA breakthrough device designation. That designation is designed to speed the review of promising technologies, but it is not equivalent to full FDA clearance or approval. Jain said he was inspired to start the company after his late father was diagnosed with pancreatic cancer. The experience led him to question why people develop chronic conditions, and whether diseases like cancer, diabetes and heart disease could be prevented by detecting earlier biological changes. The company's technology originated from a biodefense project at Los Alamos National Laboratory. This was an outgrowth of an approach Jain started pursuing in 2015 with his company BlueDot, aiming to commercialize scientific breakthroughs from institutions like Los Alamos and Oak Ridge National Laboratories. Founded in 2016, Viome has raised $225 million in total funding from investors including Khosla Ventures, Bold Capital, West River Group, Marc Benioff, Ezaki Glico, and Jain himself. Viome now employs close to 100 people and had nearly 100% year-over-year revenue growth, according to Jain, who declined to provide specific financials. Most customers, he said, not only take the tests but also subscribe to personalized nutrition products.
Cision Canada
07-07-2025
- Health
- Cision Canada
VIOME COLLABORATES WITH MICROSOFT TO DELIVER PREVENTIVE HEALTHCARE WITH ONE OF WORLD'S LARGEST RNA DATASETS
Viome's AI-Powered Platform Delivers Personalized Health Insights and Redefines Wellness Worldwide, Integrating Microsoft Azure BELLEVUE, Wash., July 7, 2025 /CNW/ -- Viome Life Sciences, a leader in AI-powered, RNA-based molecular diagnostics and personalized nutrition, today announced a collaboration with Microsoft to accelerate the next generation of preventive and personalized healthcare. As part of this collaboration, Viome will integrate its dataset of human and microbial gene expression, along with its cutting-edge bioinformatics and AI-powered recommendation engine, with Microsoft Azure infrastructure services, including Azure Ultra Disk Storage and Virtual Machines. Viome's AI platform transforms this data to deliver personalized nutrition and health insights designed to help individuals stay healthy, prevent chronic disease, and promote longevity. The integration of Viome's RNA science with Azure's secure and scalable HIPAA-compliant infrastructure services enables a new model of proactive home-based healthcare guided by molecular data. "We're excited to partner with Microsoft to create a biological digital twin for every individual, helping us make illness optional," said Naveen Jain, Founder and CEO of Viome. "This collaboration enables us to utilize large and complex biological datasets, delivering personalized health insights once thought impossible. Our mission is to empower people with the tools they need to stay healthy at home by using food, not pharmaceuticals, as medicine." Viome's Full Body Intelligence™ Test is one of the most advanced home-based health tests, analyzing both human and microbial gene expression from saliva, blood, and stool samples. Unlike static DNA tests, Viome's platform captures dynamic molecular activity, enabling precise, actionable nutrition and precision supplement recommendations to help reduce disease risk and optimize wellness. Biological data generated from Viome tests are processed in the cloud through Azure infrastructure services. Viome's AI models analyze human and microbial gene expression to detect early signs of inflammation, immune system dysfunction, and gut and molecular patterns that often precede chronic conditions. With more than 10 quadrillion biological data points, Viome's metatranscriptomic (RNA sequencing) dataset is the most comprehensive of its kind. To date, the company has completed over one million analyses across 106 countries. "Modern biology is based on data science," said Dr. Guru Banavar, Founding Chief Technology Officer at Viome. "What makes Viome unique is our ability to pair accurate, clinically relevant wet lab data with powerful AI-driven analysis. We're thrilled to collaborate with Microsoft to decode molecular signals at scale and transform raw biology into personalized health insights. With Microsoft, we can securely scale our existing platform to process petabyte-scale customer data and make preventive healthcare accessible to all." Viome's precision nutrition platform has been clinically shown to reduce symptoms of IBS by up to 58% and symptoms of depression and anxiety by up to 31%. It has also demonstrated a statistically significant reduction in HbA1c, the primary biomarker of diabetes. These results reinforce that food can be medicine, and that the future of disease prevention begins with personalized molecular insights. "Through our collaboration, we're gaining a deeper understanding of how cutting-edge biology and AI can come together to create impactful home-based health solutions," said Elena Bonfiglioli, General Manager, Worldwide Healthcare at Microsoft. "Integrating Microsoft Azure infrastructure services with Viome's scientific leadership and innovation are helping to better support the next generation of life science pioneers." Viome's proprietary AI platform delivers a growing suite of personalized health features, including: BioAge™ Score: Measures biological aging to guide longevity strategies. InflammAging™ Score: Tracks chronic inflammation driving disease and aging. Boosters & Blockers™: Personalizes nutrition to optimize health outcomes. Health Connections™: Links each person's biological data to over 25 chronic conditions, including diabetes, IBS, and depression. To explore Viome's Full Body Intelligence Test or learn more about personalized health, visit About Viome Viome is a longevity and preventive healthcare company committed to bridging the gap between scientific breakthroughs and their practical implementation as health solutions. Utilizing cutting-edge AI and the world's largest gene expression database, Viome's home-based tests offer individuals personalized nutritional guidance and innovative microbiome health products to enhance lifespan and health. Viome has empowered over half a million users with its unique approach that marries groundbreaking proprietary RNA sequencing methods with AI technology. This combination analyzes epigenetic biomarkers, providing robust, AI-driven health insights that contribute significantly to promoting a healthy lifespan. With its top-tier precision nutrition recommendations, Viome offers a comprehensive and personalized solution to aging. This is more than just health optimization; it's a revolution in understanding how we age and enabling us to do so with vitality and wellness. Media Contacts: Chris Hempel Spark Public Relations for Viome [email protected] 1-775-813-0285 SOURCE Viome Life Sciences
Yahoo
17-06-2025
- Health
- Yahoo
A biotech company sold over 500,000 AI-powered health testing kits. Two C-suite leaders share how they kept science at the center.
This article is part of "Build IT: Connectivity," a series about tech powering better business. Viome is aiming to transform disease detection, starting with the gut. The Washington-based biotech startup offers at-home testing kits that analyze saliva, stool, and blood samples. Using RNA analysis, scientists at Viome can evaluate how genes and gut microbes are behaving in real time. Once the tests are done, AI is applied to the results to generate personalized food and supplement recommendations. Users might be told to avoid spinach to reduce inflammation or take specific probiotics to support digestion and immunity. So far, the company said it has sold more than half a million testing kits. Backed by Salesforce CEO Marc Benioff and venture capital firm Khosla Ventures, Viome is now scaling its tools to detect early signs of disease, including oral and throat cancer. As Viome expands, the stakes are high. Grand View Research found that the global home care testing market is projected to grow more than 9% annually through 2030. As more consumers turn to medical testing kits for early disease detection and preventive care, the risks of misdiagnosis or ineffective treatment may surge if the tools aren't built with precision. To ensure its technology is both scientifically accurate and commercially viable, Viome relies on tight, ongoing collaboration between its research, engineering, and product teams. In a roundtable interview, Business Insider spoke with Momo Vuyisich, Viome's chief science officer, and Guru Banavar, the company's chief technology officer, to discuss how the science and technology teams work together to deliver products that are ready for market. The following has been edited for length and clarity. Business Insider: Viome offers a range of products, including microbiome kits and early-stage cancer detectors. How do your science and tech teams work together to keep the AI models accurate, safe, and compliant? Momo Vuyisich: It's not just collaboration between science and tech — it's a companywide effort. On the science side, we focus on three areas: lab work, data analysis, and clinical research. Whenever we're working on a health product, we rely on clinical research to guide development. This includes observational studies, where we learn from large groups of people, and interventional trials, where we test whether a tool works in real-world settings. For diagnostics, that means formal device trials. In the lab, we use a method called metatranscriptomics, measuring RNA to understand what's happening in the body right now. Unlike DNA, which stays the same, RNA changes based on things like diet or environmental exposure. That allows us to detect early signs of disease like inflammation or even cancer, based on how genes are being expressed. We measure gene activity across human cells, bacteria, and fungi, and we also identify the types of microbes present in a sample. Guru Banavar: What makes our approach powerful is the scale and detail of the data we collect. Each customer sends us stool, blood, and saliva samples, which we use to generate tens of millions of data points showing what's happening in their gut, blood, and mouth. Once that data hits Viome's cloud platform, my team steps in. We use AI to figure out not just what organisms are present, but what they're doing, like whether they're producing anti-inflammatory compounds or if certain biological systems are out of balance. We work with molecular data, which is far more complex than the text data most AI tools are trained on. So we use a range of machine learning methods, such as generative AI and algorithms that learn from labeled examples and draw insights based on patterns, where it's appropriate. The key is using the right tool for the right problem, whether we're detecting disease, recommending foods, or flagging health risks. And because this work spans many fields, our team includes experts in biology, computing, cloud engineering, and more. Today, everything runs in the cloud, which allows us to operate at scale. At-home medical testing and preventive health are fast-moving industries. How do you make sure you're not moving too fast and overpromising on scientific outcomes? Vuyisich: From the very beginning, we made clinical research a core part of how we operate. We didn't just start building products. We started by measuring biological markers that were already published to impact human health, especially those linked to micronutrients. That was our foundation. One of our earliest major studies was on glycemic response, how people's blood sugar changes after eating. We spent millions of dollars running large-scale studies in the US and Japan, and we used that data to build machine learning models that predicted how a person would respond to certain foods. Afterward, we validated those models before we integrated them into our app. We've followed that same process for everything from food and nutrition recommendations to our diagnostic test for cancer. We learn from both customer data and formal research, but the bottom line is we validate before we implement. Banavar: On the tech side, we've built systems that help us move quickly while still being careful. We've automated a lot of the heavy lifting — like processing biological data and generating recommendations — so we're not starting from scratch every time. When a new cohort of users joins Viome, we often retrain our models to reflect new biological data and ensure relevance. Some parts of that process are automated, but the final checks and tuning are still done by hand to make sure the model meets our standards before it goes live. Another important piece is user education. Our app is designed to let people engage however they want, whether they're just looking for simple guidance or want to dive deep into science. It's an important part of making sure our customer base understands and can follow our recommendations. Have you ever had to resolve conflicts between business priorities and scientific standards? Banavar: Yes, and it's natural in a multidisciplinary environment. We all come from different backgrounds. Biologists and machine learning engineers often describe the same process in totally different ways. Momo comes from the molecular side, I come from the computational side. Sometimes we talk past each other, meaning we miss things we say to one another that go beyond our domains of expertise. That's why ongoing communication is so important. There's also the tension between speed and robustness. For example, when we're building a new feature in the app, I'm OK launching a minimum viable product, MVP for short, which is a working prototype with basic functionality. But when it comes to health models, we won't release them until we've validated the science. If it takes two more weeks to fine-tune, so be it. We'll put a message in the app saying that a specific score, or a health indicator based on a user's test results, is still being worked on — and that's fine with me. Vuyisich: It all comes down to defining what the MVP is. If it provides enough value for someone to pay for it and feel good about it, that's the threshold. But an MVP for a toy can be rough and basic. An MVP for a cancer diagnostic needs to be very mature. We don't have a dynamic where business tells science what to do. We sit at the same table and make decisions together. If the science can't hit the original target, we reassess. Can we lower the bar slightly and still provide value? If the answer is yes, we'll launch. The worst-case scenario is launching something that isn't ready, but even that teaches you something. If no one buys it, you've learned a lot. Sometimes your friends and family say it's amazing, but no one pays for it. That's a signal. But an even worse scenario is waiting too long for perfection. That's buried more companies than anything else. If Apple had waited until the iPhone had all the features of iPhone 16, it would've gone out of business. Instead, they launched the first iPhone. They could be embarrassed today about how poor it was. But it worked. People paid for it. That's what matters: bring it to market. What lessons have you learned from building and scaling Viome that could help other companies trying to bring AI health products to market responsibly? Banavar: First, there is no substitute for generating robust scientific data to support the value of health products. Second, when applying AI to health products, focus on areas and methods that can be independently validated and, ideally, interpretable, where companies can explain how the AI models reached their results to scientists, clinicians, and users. Finally, it's possible, even in the health domain, to build products with an MVP mindset and implement a process for continuous improvement. Vuyisich: Deeply understand the problem you're trying to solve and identify a robust solution. At Viome, we set out to find the root causes of chronic diseases and cancer, which required measuring tens of thousands of human biomarkers relevant to health. Also, use a method that's accurate, affordable, and scalable. We spent over six years optimizing one lab test — metatranscriptomics — to go beyond the gold standard. This one test gives us thousands of biomarkers across multiple sample types with high accuracy. Finally, it's all about the people. Build a leadership team that deeply understands business and science, is aligned with the mission, and puts the company ahead of personal interests. Hire motivated, self-managed employees, train them well, and continuously coach them. Read the original article on Business Insider
Business Insider
17-06-2025
- Health
- Business Insider
A biotech company sold over 500,000 AI-powered health testing kits. Two C-suite leaders share how they kept science at the center.
This article is part of " Build IT: Connectivity," a series about tech powering better business. Viome is aiming to transform disease detection, starting with the gut. The Washington-based biotech startup offers at-home testing kits that analyze saliva, stool, and blood samples. Using RNA analysis, scientists at Viome can evaluate how genes and gut microbes are behaving in real time. Once the tests are done, AI is applied to the results to generate personalized food and supplement recommendations. Users might be told to avoid spinach to reduce inflammation or take specific probiotics to support digestion and immunity. So far, the company said it has sold more than half a million testing kits. Backed by Salesforce CEO Marc Benioff and venture capital firm Khosla Ventures, Viome is now scaling its tools to detect early signs of disease, including oral and throat cancer. As Viome expands, the stakes are high. Grand View Research found that the global home care testing market is projected to grow more than 9% annually through 2030. As more consumers turn to medical testing kits for early disease detection and preventive care, the risks of misdiagnosis or ineffective treatment may surge if the tools aren't built with precision. To ensure its technology is both scientifically accurate and commercially viable, Viome relies on tight, ongoing collaboration between its research, engineering, and product teams. In a roundtable interview, Business Insider spoke with Momo Vuyisich, Viome's chief science officer, and Guru Banavar, the company's chief technology officer, to discuss how the science and technology teams work together to deliver products that are ready for market. The following has been edited for length and clarity. Business Insider: Viome offers a range of products, including microbiome kits and early-stage cancer detectors. How do your science and tech teams work together to keep the AI models accurate, safe, and compliant? Momo Vuyisich: It's not just collaboration between science and tech — it's a companywide effort. On the science side, we focus on three areas: lab work, data analysis, and clinical research. Whenever we're working on a health product, we rely on clinical research to guide development. This includes observational studies, where we learn from large groups of people, and interventional trials, where we test whether a tool works in real-world settings. For diagnostics, that means formal device trials. In the lab, we use a method called metatranscriptomics, measuring RNA to understand what's happening in the body right now. Unlike DNA, which stays the same, RNA changes based on things like diet or environmental exposure. That allows us to detect early signs of disease like inflammation or even cancer, based on how genes are being expressed. We measure gene activity across human cells, bacteria, and fungi, and we also identify the types of microbes present in a sample. Guru Banavar: What makes our approach powerful is the scale and detail of the data we collect. Each customer sends us stool, blood, and saliva samples, which we use to generate tens of millions of data points showing what's happening in their gut, blood, and mouth. Once that data hits Viome's cloud platform, my team steps in. We use AI to figure out not just what organisms are present, but what they're doing, like whether they're producing anti-inflammatory compounds or if certain biological systems are out of balance. We work with molecular data, which is far more complex than the text data most AI tools are trained on. So we use a range of machine learning methods, such as generative AI and algorithms that learn from labeled examples and draw insights based on patterns, where it's appropriate. The key is using the right tool for the right problem, whether we're detecting disease, recommending foods, or flagging health risks. And because this work spans many fields, our team includes experts in biology, computing, cloud engineering, and more. Today, everything runs in the cloud, which allows us to operate at scale. Vuyisich: From the very beginning, we made clinical research a core part of how we operate. We didn't just start building products. We started by measuring biological markers that were already published to impact human health, especially those linked to micronutrients. That was our foundation. One of our earliest major studies was on glycemic response, how people's blood sugar changes after eating. We spent millions of dollars running large-scale studies in the US and Japan, and we used that data to build machine learning models that predicted how a person would respond to certain foods. Afterward, we validated those models before we integrated them into our app. We've followed that same process for everything from food and nutrition recommendations to our diagnostic test for cancer. We learn from both customer data and formal research, but the bottom line is we validate before we implement. Banavar: On the tech side, we've built systems that help us move quickly while still being careful. We've automated a lot of the heavy lifting — like processing biological data and generating recommendations — so we're not starting from scratch every time. When a new cohort of users joins Viome, we often retrain our models to reflect new biological data and ensure relevance. Some parts of that process are automated, but the final checks and tuning are still done by hand to make sure the model meets our standards before it goes live. Another important piece is user education. Our app is designed to let people engage however they want, whether they're just looking for simple guidance or want to dive deep into science. It's an important part of making sure our customer base understands and can follow our recommendations. Have you ever had to resolve conflicts between business priorities and scientific standards? Banavar: Yes, and it's natural in a multidisciplinary environment. We all come from different backgrounds. Biologists and machine learning engineers often describe the same process in totally different ways. Momo comes from the molecular side, I come from the computational side. Sometimes we talk past each other, meaning we miss things we say to one another that go beyond our domains of expertise. That's why ongoing communication is so important. There's also the tension between speed and robustness. For example, when we're building a new feature in the app, I'm OK launching a minimum viable product, MVP for short, which is a working prototype with basic functionality. But when it comes to health models, we won't release them until we've validated the science. If it takes two more weeks to fine-tune, so be it. We'll put a message in the app saying that a specific score, or a health indicator based on a user's test results, is still being worked on — and that's fine with me. Vuyisich: It all comes down to defining what the MVP is. If it provides enough value for someone to pay for it and feel good about it, that's the threshold. But an MVP for a toy can be rough and basic. An MVP for a cancer diagnostic needs to be very mature. We don't have a dynamic where business tells science what to do. We sit at the same table and make decisions together. If the science can't hit the original target, we reassess. Can we lower the bar slightly and still provide value? If the answer is yes, we'll launch. The worst-case scenario is launching something that isn't ready, but even that teaches you something. If no one buys it, you've learned a lot. Sometimes your friends and family say it's amazing, but no one pays for it. That's a signal. But an even worse scenario is waiting too long for perfection. That's buried more companies than anything else. If Apple had waited until the iPhone had all the features of iPhone 16, it would've gone out of business. Instead, they launched the first iPhone. They could be embarrassed today about how poor it was. But it worked. People paid for it. That's what matters: bring it to market. What lessons have you learned from building and scaling Viome that could help other companies trying to bring AI health products to market responsibly? Banavar: First, there is no substitute for generating robust scientific data to support the value of health products. Second, when applying AI to health products, focus on areas and methods that can be independently validated and, ideally, interpretable, where companies can explain how the AI models reached their results to scientists, clinicians, and users. Finally, it's possible, even in the health domain, to build products with an MVP mindset and implement a process for continuous improvement. Vuyisich: Deeply understand the problem you're trying to solve and identify a robust solution. At Viome, we set out to find the root causes of chronic diseases and cancer, which required measuring tens of thousands of human biomarkers relevant to health. Also, use a method that's accurate, affordable, and scalable. We spent over six years optimizing one lab test — metatranscriptomics — to go beyond the gold standard. This one test gives us thousands of biomarkers across multiple sample types with high accuracy. Finally, it's all about the people. Build a leadership team that deeply understands business and science, is aligned with the mission, and puts the company ahead of personal interests. Hire motivated, self-managed employees, train them well, and continuously coach them.
