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Toku Eyes
Toku Eyes
tokueyes.com

Locations

San Diego, CA, USA · Auckland, New Zealand · Liberty Station, San Diego, CA, USA

industry

Health · Medical Devices

Size

11-50 employees

Stage

Other

founded in

2018

Toku is creating a world focused on preventive healthcare, using the eye as a window to our health. We believe every person in the world should have access to early diagnosis of health conditions before it’s too late. How? By developing tools using AI and retinal images to enable accessible healthcare for early and accurate diagnosis of health conditions to empower everyday individuals. The retina has long been recognized as a unique window into an individual’s health, as the biomarkers present in retinal images may provide valuable insights into aging, inflammatory health, neurological health, and cardiovascular health. Bioage Not all people age equally. Every person has two ages: our chronological age (how old you are) and our biological age. Biological age (or bioage) is a measure of how well our cells, tissues, and organs are aging. Toku’s bioage product determines a person’s biological age, which can give an indication of their overall health, by looking at vascular, metabolic, inflammatory, and lifestyle indicators present in the retinal image. By knowing our bioage earlier, we can make conscious health choices to improve our health. Unlike our chronological age, our bioage is not fixed. Bioage uses retinal images and hence is non-invasive, time efficient, cost effective, and can be delivered by trusted healthcare providers. The retinal vasculature allows direct non-invasive visualization of the body’s microvasculature, as it is the only part of the body where scientists and clinicians can directly assess the health of an individual’s neuro-vascular tissues. Toku’s AI platform utilizes a revolutionary, patented method to evaluate more than 23 million technical parameters and 12 biological parameters in each retinal image, to produce a bioage outcome. The AI engine has learned patterns from images from over 1.3 million retinal images to recognize the various features of health.

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