The evolution of precision medicine is increasingly reliant on the real-time analysis of dynamic biological data. Moving beyond static genetic testing, contemporary approaches utilize RNA sequencing paired with artificial intelligence to monitor active cellular and microbial mechanisms. By analyzing molecular signals across multiple biological samples-including stool, blood, and saliva-the Viome platform maps these real-time shifts to generate precise, data-driven nutritional strategies.
In this interview, we examine the scientific infrastructure underlying multi-omics technology and evaluate its practical applications within preventive healthcare and healthspan optimization.
Measuring Molecular Activity in Real Time
The study of the microbiome and human health has traditionally relied on static markers. The approach presented here utilizes RNA sequencing to observe genes during expression, making it possible to analyze active biological functions rather than the mere composition of an ecosystem.
Sogevity: How would you describe Viome’s core scientific approach, particularly your use of RNA sequencing and AI to analyze biological activity at the molecular level?
Viome: Viome’s core scientific approach is to measure biological activity directly, rather than relying only on static markers or broad population averages. We use RNA sequencing to understand which genes are actively being expressed by the microbiome and the human host, then apply AI to interpret these molecular signals in the context of health, nutrition, inflammation, metabolism, and disease risk. This allows us to move from simply identifying what organisms or genes are present to understanding what they are actually doing.
Sogevity: Viome focuses on “what the body is actively doing right now” rather than static markers. Can you explain what this means in practical terms for users?
Viome: Many health tests measure relatively static features, such as genetic markers (DNA variants) or the presence of certain microbes. Viome measures RNA, which reflects active biological function at the time of testing—such as whether pathways related to inflammation, gut barrier function, oxidative stress, or nutrient metabolism are turned up or down. The validity and clinical application of using metatranscriptomics to track these dynamic microbial functions are established across several of our peer-reviewed publications, including our foundational methodology study (Wiley, 2019) (PubMed, 2020) (PubMed, 2023) and research connecting gene expression to our health status (iScience 2024, Computational biotech 2024, BMC Gastroenterology 2025). For users, this means the results are more actionable because they reflect modifiable biology that can be changed with foods, supplements, and lifestyle, a framework further detailed in our scientific literature on precision health interventions (American Journal of Lifestyle Medicine, 2023).
Translating Molecular Data and Identifying Root Causes
Quantifying thousands of biomarkers raises the question of how to interpret massive datasets. This section addresses the methodology used to map biological pathways and identify the molecular imbalances linked to common symptoms such as fatigue or digestive issues.
Sogevity: How does Viome translate complex molecular data into personalized recommendations for food, supplements, and lifestyle interventions?
Viome: Viome’s platform analyzes RNA from stool, blood and saliva, then maps those signals to biological pathways that are supported by scientific evidence. We use this information to identify which nutrients are most likely to support the beneficial and reduce harmful pathways in each person. The result is a personalized plan designed to improve biological function rather than a generic list of healthy foods. The precise machine learning methodology, clinical validation framework, and algorithmic translation used to convert these molecular signals into individualized nutritional recommendations are described in detail in our dedicated scientific publication.
Sogevity: Many users come to Viome with symptoms such as fatigue, brain fog, IBS, anxiety, or metabolic issues. How does your approach help identify potential root causes behind these symptoms?
Viome: Viome has spent many years and millions of dollars conducting clinical research to identify modifiable root causes of many chronic diseases. When we say root causes, we mean measurable parts (RNA molecules) of human and microbiome physiology that 1. are strongly associated with a disease and 2. can be potentially reversed with nutrition. For example, sulfide production, secondary bile acids, methane production, and many other physiological processes are both measurable by our tests and modifiable with nutrition. Therefore, Viome tests identify earliest signs of molecular imbalances that could lead to symptoms and help users and their healthcare providers focus on these activities that may be modifiable.
The framework behind how we aggregate these real-time microbial and human pathway signals to track these imbalances is evaluated in our clinical preprint publication on medRxiv, which details the validation of our Disease Risk Score (DRS) framework across multiple common conditions like anxiety, metabolic issues, chronic fatigue, and IBS.
Methodology, Health Scores, and Scientific Validation
The evaluation relies on generating a series of specific health scores (covering digestive, immune, and metabolic functions). The following questions discuss the robustness of the machine learning models used and the clinical validation protocols carried out on extensive datasets.
Sogevity: What makes Viome’s combination of microbiome analysis, gene expression (RNA), and AI different from other microbiome or health testing platforms?
Viome: Other companies in the wellness space either focus on the human or some microbiome aspects of our health. In addition, the human tests are limited to ~100 biomarkers and microbiome tests are limited by only measuring the relative abundance of microorganisms. Viome offers a very comprehensive and much deeper molecular view by measuring active RNA expression in human cells and microbes, and in three different parts of the body (stool, blood, and saliva), each contributing significantly to our health.
AI has been a core component of our platform for nearly a decade because it enables the analysis of very complex and large biological data. By combining microbiome activity, human gene expression, and AI-driven interpretation, Viome can generate more personalized and mechanistically informed recommendations.
Sogevity: Your system generates health scores across multiple domains (digestive health, brain health, immune function, metabolism, sleep, etc.). How are these scores calculated and interpreted?
Viome: Viome’s health scores are generated by integrating molecular signals from RNA sequencing with curated scientific knowledge about biological pathways, and then linking them to different areas of disease and health.
By utilizing this methodology, which is described in our peer-reviewed papers validating both our stool-based scores and our saliva-based scores, we can quantify complex biological activities into understandable, actionable domains. These domains—such as digestive health, immune function, metabolic health, brain health, and sleep—help users track exactly where their biology may need support and how their molecular patterns change over time.
Sogevity: How do you ensure scientific robustness, particularly with over 20,000 clinical references and real-world biological data integration?
Viome: Our scientific robustness comes from a combination of training AI (machine learning) on very large and relevant datasets, and testing the accuracy of those models on large, independent, blinded datasets that follow robust standards set by the US HHS (CLIA). We start any discovery process by combining the world’s knowledge with our own molecular and health data, using advanced machine learning to identify patterns strongly associated with health and diseases. These patterns are selected from many different AI training sessions to create a machine learned model of how molecular data predict health and disease. As we demonstrated in our latest paper describing the validation of gut microbiome scores, we put this rigorous process into practice by using a set of ~10,000 stool samples for machine learning and then validating the findings on an independent set of ~70,000 blinded stool samples.
Perspectives on Preventive Healthcare and Aging
One of the primary objectives of RNA-based analysis is the early identification of physiological shifts. This final section explores the future integration of these multi-omics technologies into healthcare systems and their potential role in extending healthspan.
Sogevity: Viome positions itself as a preventive and longevity-focused company. How do you see RNA-based precision health contributing to extending healthspan in the coming years?
Viome: RNA-based precision health enables two major healthcare advances: 1. Catching physiological imbalances years or decades before symptoms onset, and 2. Helping address these imbalances through personalized nutrition and lifestyle interventions. Because RNA reflects active biology and can be modulated (unlike DNA), it can detect changes related to many aspects of human physiology before imbalances become more advanced clinical problems.
Sogevity: What are some of the most important insights Viome has uncovered so far about the relationship between microbiome activity, chronic disease risk, and aging?
Viome: One of Viome’s key insights is that the microbiome is not just a collection of organisms—it is an active biochemical system that influences most human biology tied to chronic disease and aging. We have seen that different people can have very different biological drivers behind similar symptoms or risk patterns, which helps explain why one-size-fits-all nutrition or therapies often fail. We are also learning that microbiome and host activity are deeply interconnected, making multi-sample analysis (blood, stool, and saliva) essential for understanding health and aging more accurately.
Sogevity: Looking ahead, how do you see AI and multi-omics technologies shaping the future of personalized preventive healthcare?
Viome: Once Viome tests become free to the users, based on strong health economic data, billions of people will take these tests from birth to death, to precisely guide their daily nutritional and lifestyle habits. AI and multi-omics will allow healthcare to move from generalized recommendations to highly personalized, mechanism-based prevention. Instead of waiting for disease to emerge, clinicians and individuals will be able to monitor biological functions across all organ systems, then intervene earlier and more precisely. The future of preventive healthcare will be built on measuring what is changing in real time and using that information to guide personalized action.
Towards a new medical paradigm?
The integration of transcriptomic data and artificial intelligence marks a definitive shift from a reactive medical model toward a preventive and predictive healthcare approach. Analyzing the correlations between microbiome activity and cellular aging remains a key focus of current research aimed at developing individualized health strategies. By tracking changes in active biology rather than baseline static traits, these technologies open new pathways for targeted biological age management and the gradual optimization of healthspan.
About Viome
Viome is a health and longevity company focused on applying scientific advancements to individual well-being management. Utilizing artificial intelligence and multi-omics analysis (stool, blood, and saliva), the company studies the root causes underlying the development of chronic diseases, biological aging, and microbial imbalances.
Their methodology centers on analyzing over 100,000 biomarkers and assessing nearly 70 distinct health scores (such as digestive health, immune function, metabolism, and sleep quality). These insights are used to generate personalized nutritional recommendations and synergetic ingredient formulations tailored to each user’s active biology at the time of testing. The predictive models developed by Viome are continuously trained and updated using clinical data sourced from more than 20,000 scientific study references.
Continue exploring longevity
Explore this longevity topic
