Can We Slow Down Aging?

Twinn Health uses MRI scanning and Al to gain personalised insights into a patient's health and detect preventable disease early

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IN AN AGING WORLD, the ability to spot the early signs of conditions such as osteoporosis and sarcopenia could save billions of dollars in healthcare spending, slow down the onset of frailty, and ultimately improve the quality of life of the older population.

It is a vision that has always inspired Wareed Alenaini, first as a young girl growing up in a small town in Saudi Arabia and now as founder and CEO of health technology startup Twinn Health.

"The older members of my family would always complain to each other about their chronic conditions and the medications they took," she remembers. "Even back then I realized that those diseases could have been prevented if they had been detected earlier. Now with artificial intelligence (AI) and modern imaging techniques, we have the technology and the know-how to make it happen."

A chance conversation with a banking friend in London, where Alenaini completed her PhD at a leading research university, helped sow the first seeds of Twinn Health. "My friend uses machine learning to analyze financial data and make predictions about loan defaults. We realized we could use the same techniques to analyze images from magnetic resonance imaging (MRI) machines. We could detect patterns in organs and tissues acting as biomarkers for age-related diseases, many years before the first symptoms appear in a patient's blood."