Longevity & Aging Science
Nexrevo Bioinformatics partners with longevity-focused companies – from biotech startups and aging biomarker ventures to geroscience R&D labs and personalized aging solution developers – to accelerate breakthroughs in aging science.
The longevity industry is emerging at the intersection of biotechnology and digital health, aiming to extend healthy human lifespan.
We bring advanced data analytics and AI/ML capabilities to help identify biomarkers of aging, model age-related diseases, and discover geroprotective drugs. From multi-omics data integration and microbiome analysis to wearable sensor data and cloud platforms, we empower our B2B clients to transform the science of aging into practical, scalable solutions that improve healthspan.
Key Technologies Used
AI & Machine Learning for Longevity
Deep learning models and predictive algorithms drive discovery in aging research. We develop AI “aging clocks” that estimate biological age from biomarkers, and use machine learning for geroprotector drug discovery (identifying compounds that slow aging or prevent age-related diseases). These models help prioritize the most promising interventions and predict outcomes.
Multi-Omics & Biomarker Analytics
Advanced bioinformatics pipelines integrate genomics, epigenomics (e.g. DNA methylation patterns), transcriptomics, proteomics, and metabolomics data to uncover biomarkers of aging. For example, we analyze genomic variants, gene expression shifts, and protein markers that correlate with biological age. By combining diverse data types, our platforms reveal key aging pathways and molecular targets that single-data approaches might miss.
Wearables, IoT & Real-World Data
We leverage data from wearable devices and IoT health sensors (heart rate monitors, activity trackers, sleep sensors, etc.) to capture longitudinal health and lifestyle information. This continuous data is integrated with clinical and omics data to provide a holistic view of an individual’s aging process. Our cloud systems ingest and analyze these real-world data streams, enabling personalized insights (e.g. how activity levels or vitals correlate with biological age metrics).
Age-Related Disease Modeling (In Silico)
Using computational biology and simulation, we help model the progression of age-associated diseases (like Alzheimer’s, cardiovascular disease, or osteoporosis) under various scenarios. These digital models – sometimes called “digital twins” of aging – allow R&D teams to test hypotheses about interventions (such as a new senolytic drug or lifestyle change) and see potential effects on aging and disease outcomes virtually.
Microbiome & Metabolic Analysis
Our bioinformatics expertise extends to microbiome sequencing and metabolic data relevant to aging. We analyze gut microbiome composition and metabolic profiles to identify how they influence aging and vice-versa. This guides development of microbiomebased aging interventions (like probiotic supplements or dietary regimens) by pinpointing beneficial bacterial strains or metabolites that promote longevity.
Cloud Computing & Data Infrastructure
We deploy high-performance computing (HPC) and cloud-based data lakes to manage the massive datasets common in longevity research. Whether it’s large-scale genomics from biobanks or high-frequency wearable sensor data, our cloud platforms ensure secure, scalable storage and lightning-fast analysis. This infrastructure allows clients to collaborate globally and run complex analytics pipelines (e.g. genome-wide association studies for longevity traits or AI model training) in a compliant, reproducible environment.
Solutions Offered
Aging Biomarker Discovery Platforms
End-to-end computational workflows to identify and validate biomarkers of aging. We build platforms that ingest clinical study data and multi-omics datasets to find patterns that indicate biological age or predict age-related decline. These might discover new epigenetic “clocks,” proteomic signatures of aging, or blood-based biomarkers. The platforms include validation modules so clients can cross-verify these biomarkers against longitudinal patient data or known outcomes, ensuring any new aging marker is robust and clinically relevant.
AI Geroprotector Discovery
Drug discovery informatics tailored to longevity. We provide AI-driven screening tools to identify geroprotective compounds – molecules that could extend healthspan or treat age-related conditions. This includes virtual screening of compound libraries for activity on aging pathways, deep learning models predicting a compound’s effect on cellular senescence or damage repair, and tools for repurposing existing drugs for geriatric use. By narrowing the field to the most promising candidates, our solutions help longevity biotech firms move potential therapies into testing faster.
Personalized Longevity Management Platforms
We develop custom digital platforms that integrate an individual’s genomic data, biomarker profiles, wearable device metrics, and lifestyle information to generate personalized insights and recommendations. These solutions allow our clients to offer their customers a data-driven longevity plan – for instance, a dashboard that shows one’s “biological age” and risk factors, along with tailored guidance (diet, exercise, supplements, or therapies) to improve those metrics. Backed by AI analytics and user-friendly design, these platforms enable companies to engage end-users with actionable health insights while continuously learning from the data to refine recommendations.
Age-Related Disease Analytics
Analytical tools focused on age-associated diseases and conditions. We create solutions for analyzing datasets from geriatric studies and clinical trials – for example, identifying early predictors of Alzheimer’s or analyzing how a therapy impacts biomarkers of frailty. Our systems can stratify patients by biological age or risk profiles, helping researchers design more efficient clinical trials in the longevity space (such as selecting ideal candidates who are most likely to respond to an anti-aging therapy). Additionally, we integrate electronic health record data with research data to find real-world evidence of an intervention’s effect on age-related outcomes.
Microbiome & Nutrition Intervention Design
Specialized bioinformatics solutions for companies developing dietary, supplement, or microbiome-based longevity interventions. We provide data analysis pipelines that link dietary patterns and microbiome changes to aging markers. For example, our tools can help a client test how a high-fiber diet or a probiotic affects inflammation levels and epigenetic aging rates in study participants. These insights guide formulation of next-generation functional foods or supplements aimed at extending healthspan. We also build companion software that can recommend nutrition or microbiome-based adjustments for individuals based on their unique data, underpinned by our client’s research findings.
Applications & Impact
Accelerated R&D Breakthroughs
By implementing AI-driven discovery and cloud-based multiomics analytics, our clients dramatically reduce the time needed to uncover new aging biomarkers or drug targets. What once took years of wet-lab research can now happen in months – for instance, using our platform, a biotech startup identified a promising anti-aging compound 2× faster than with traditional screening.
Improved Efficacy & Health Outcomes
Data-driven personalization leads to more effective interventions. Companies deploying our solutions can demonstrate tangible healthspan improvements in their end-users – for example, users following personalized longevity plans might show slowed biological aging (measured by epigenetic clocks) or improved markers for age-related conditions.
More Efficient Clinical Trials
Longevity-focused companies use our analytics to design smarter trials and studies. By stratifying participants with aging biomarkers and predictive models, trials can achieve clear results with smaller sample sizes or shorter durations.
Insights & Thought Leadership
Explore perspectives on emerging trends in bioinformatics,
genomics, AI, and digital health innovation.
