UK-based Mendelian receives over €570k for its rare disease diagnostics


London-based healthtech startup Mendelian, which specialises in the diagnosis of rare diseases, has received a grant of over €570k from Innovate UK, to build solutions that will assist GPs in identifying NHS patients with rare or hard to diagnose conditions and diseases. Mendelian’s solutions are already being used by 50k users in over 150 countries.

In the UK it takes an average of 5.6 years, eight clinicians (including four specialists) and three misdiagnoses before the correct rare disease is identified. Another health economics report commissioned by Mendelian revealed that over the last 10 years, undiagnosed rare disease patients have cost the NHS over £3.4 billion.

“It’s clear that this ‘diagnostic odyssey’ is not only causing patients distress and emotional turmoil but is also extremely frustrating for clinicians, as well as costly for healthcare systems and ultimately tax-payers,” said Dr. Peter Fish, Head of Clinical Partnerships at Mendelian. “To help solve this pressing issue we’re delighted to be providing a solution within the NHS, for not only rare disease patients, but also those with hard to diagnose conditions. Crucially, Mendelian’s technology is being implemented at the general practice stage, right at the beginning of the patient journey with the aim of identifying these conditions as early on as possible.”

Mendelian will use the financing to implement its specialised screening system, which provides augmented intelligence and data analysis to deliver the fast, accurate and automated identification of patients who may have rare diseases. Once the technology has analysed a patient’s symptoms, the GP is notified, who can then refer the patient to a specialist or recommending further analysis and testing.

“We are delighted to support Mendelian as part of our work into rare diseases,” said Piers Ricketts, Chief Executive at the Eastern Academic Health Science Network. “With over 3 million rare disease patients in the UK, innovative technologies using data analytics and machine learning like this are increasingly vital in ensuring that these conditions are diagnosed earlier to provide more targeted and personalised treatment for patients.”