Generation Lab, a longevity startup co-founded by Dr. Irina Conboy, has raised an $11 million seed funding round, bringing its total funding to $15 million, to expand its innovative SystemAge biological-age diagnostic platform.

The funding round was led by Accel and included notable investors such as Samsung Next, Zone2, Aoki Labs, Build Your Legacy Ventures, and Markham Valley Ventures, reflecting strong market interest.

Since launching less than a year ago, Generation Lab has rapidly gained traction, partnering with over 275 clinics worldwide and amassing a dataset of more than 300 million human-aging data points.

This swift adoption indicates a rising demand for personalized health-span insights and longevity diagnostics, positioning Generation Lab as a leader in proactive healthcare.

The platform focuses on measuring 'biological noise,' a dysregulation in molecular systems that signals early systemic decline, providing a more precise aging diagnostic than traditional methods.

Initial clinical results show regenerative therapies like MUSE Stemcell have reversed brain age by an average of 13.6 years and reproductive system age by 4.9 years, with lifestyle changes also improving biological age across various organs.

This early traction underscores the increasing demand for personalized longevity insights and health diagnostics that can inform targeted interventions.

Generation Lab plans to use the new funding to accelerate global adoption of SystemAge, emphasizing its focus on systems-based biological aging measurement rather than predictive models.

The seed funding round, led by Accel and including investors like Samsung Next, brought the company's total funding to $15 million, placing it among the top 1% of startup seed rounds.

The company aims to shift healthcare from reactive to proactive by providing comprehensive early diagnostic insights that enable targeted interventions to slow or reverse aging.

SystemAge assesses the health and aging of 19 organ systems through a single blood test, offering specific biological ages and risk profiles with claimed 99.9% diagnostic accuracy.