University of Bristol spinout Rosa Biotech has secured £415,000 in angel investment to accelerate pre-clinical trials for its AI-driven platform that aims to make earlier diagnoses of liver disease.
Rosa Biotech is aiming to speed up the diagnosis of different diseases by combining protein design and machine learning.
The startup is initially targeting the early identification of non-alcoholic fatty liver disease (NAFLD) which, if left untreated, can develop into steatohepatitis (NASH) and liver failure. Rosa Biotech says the Western world has experienced a 100% increase in NASH cases during the last 30 years, with this trend expected to accelerate in the coming decades.
Rosa Biotech’s Pandra platform combines patented synthetic biology with machine learning, and specialises in the detection of a range of life-threatening diseases with high accuracy in patient blood samples.
The £415,000 investment, described as “Seed+”, comes from technology and life sciences entrepreneurs and kickstarts Rosa’s Series A funding round, which is planned for later this year.
Mark Street-Docherty, CEO of Rosa Biotech, said: “The prevalence of NAFLD is increasing at an alarming rate, placing an ever-growing burden on specialist healthcare resources. With over 100 therapeutic interventions in clinical development, it’s critical that healthcare providers can cost-effectively screen for early signs of this condition, enabling treatment and lifestyle changes to occur early enough to prevent permanent liver damage and failure.
“With Series A funding expected to follow later in the year, this is an incredibly exciting time for our business. Pandra technology is moving ever closer to commercialisation and will enable Rosa Biotech to save lives and help protect vital healthcare infrastructure.”
In March, Rosa Biotech published its founding research, which detailed the diversity of protein structures designed by the Woolfson group – the namesake of co-founder, Professor Dek Woolfson – over the last decade, and how they were used to produce biosensors applicable in medical diagnostics.
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