MedTech

Twinn.health has launched its AI-driven imaging platform that aims to revolutionise the early detection of age-related diseases. 

The platform, built on over a decade of research at Imperial College London, leverages advanced AI algorithms to analyse MRI data and provide risk assessments for common causes of frailty up to 10 years earlier than current methods.

The Twinn.health platform addresses a significant challenge in healthcare: the growing prevalence of age-related diseases and their impact on patients, healthcare systems, and economies. With an ageing global population, there is a pressing need for more effective, proactive diagnostic tools to identify and manage these conditions at an early stage.

“Twinn.health’s AI-powered platform offers a game-changing solution for age-related disease detection and management,” said Dr Wareed Alenaini, Founder and CEO of Twinn.health, which was founded in 2021. 

“Our mission is to unlock the true potential of imaging data to improve health outcomes and prevent multiple diseases with a single MRI scan.”

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Twinn.health’s platform is claimed to be the first of its kind to use MRI data for risk assessment in the context of frailty. It identifies chronic age-related diseases earlier than traditional molecular signals, making it a powerful tool for early intervention and prevention. 

The platform has been validated through a retrospective clinical study involving 400 patients and three radiologists, with promising results.

Key features of the platform include heatmaps, which are visual representations of areas of concern and adipose tissue within MRI scans; AI-generated risk scores reflecting a patient’s risk for highlighted diseases; and comprehensive AI case reports summarising key findings and analysis.

Twinn.health is currently raising a pre-Series A round to progress its metabolic disease AI through FDA approval and expand its disease pipeline. The company has already secured $800k in pre-seed funding and established data partnerships with the UK Biobank, University of Edinburgh and Imperial College London.

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