A deeper view into healthy aging

Multi-dimensional, phenotypic biological age measurements to accelerate the discovery of healthy aging interventions.

Biological age, systems and organs.

Now, in a single longitudinal assay.

NAGI™ Biological Age is an AI-powered phenotypic biological age assessment that enables longitudinal, non-invasive quantification of biological aging of C. elegans models, a cornerstone organism in aging research.

DTU Biosustain and Novo Nordisk Foundation logo: academic and research collaboration with Nagi Bioscience on healthy aging innovations.
Harvard T.H. Chan School of Public Health logo: leading academic institution leveraging Nagi Bioscience platform SydLab One for aging biology research and metabolism and diet.
Telomir Pharmaceuticals logo: biotechnology company partnering with Nagi Bioscience in longevity and age-related disease research.
Bayer CropScience logo: global agrochemical and agroscience company working with Nagi Bioscience on developmental and reprodutive toxicity DART.
Immunic Therapeutics logo: biotech company advancing immune and neurodegenerative therapeutics with support from Nagi Bioscience.
Yeastup logo
ICMAB Institut de Ciència de Materials de Barcelona logo: microplastics ecotoxicology supported by Nagi Bioscience technology.
International Iberian Nanotechnology laboratory INL logo: safety toxicology testing of nanoparticles and how it affects models of neurodegeneration with the support from Nagi Bioscience technology.

A multidimensional approach to longevity interventions discovery

End-to-end Automated

Longitudinal, Non-Invasive Analysis

3 levels of AI-powered Analytics

60 Quantitative Phenotypic Descriptors

Physiologically Relevant and Ethical

Biological Age, Systems and Organs Age in just 5 days

Real science. Real impact.

A versatile assay connecting different health pathways.

NAGI™ Biological Age supports a wide range of applications, from early-stage screening to mechanism of action studies.

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TMRE-based assay for mitochondrial function evaluation

RNA-Seq workflow