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Nostos Genomics claims it can dramatically speed up the time it takes to diagnose genetic diseases. We got an exclusive look at the 12-slide deck it used to raised the cash.", "slideCount": 12, "companyName": "Nostos Genetics", "description": "A Berlin-based genetic analysis startup has just raised a €5 million ($5.6 million). Nostos Genomics claims it can dramatically speed up the time it takes to diagnose genetic diseases. We got an exclusive look at the 12-slide deck it used to raised the cash. A startup that claims it can dramatically reduce the time needed to diagnose genetic diseases has just raised €5 million ($5.6 million) in fresh funds. Berlin-based Nostos Genomics uses an AI-driven platform to analyze a patient's genome and identify gene variants known to cause disease. The company claims its technology can reduce the traditional analysis process down from 12 hours to two minutes. To get a diagnosis;; a patient's doctor sends blood or saliva off to a genetics testing lab where the DNA is put through a sequencing machine. The output of this is a \"very long file\" that lists all of the DNA's mutations;; compared to a sample. \"This is actually quite challenging because if you were to sequence your DNA or my DNA;; we would find about 4 million differences;;\" said Rocío Acuña Hidalgo;; Nostos Genomics cofounder and CTO. \"The difficulty here is really understanding which of these 4 million differences is actually meaningful and having an impact on your health;; in causing a disease;; or putting you at risk for certain complications.\" This is where the startup steps in. Traditionally;; a doctor or scientist sifts through this data to find disease-causing matches. Instead;; the sequencer's output can be fed into Nostos Genomics software;; which can identify gene variants responsible for more than 10;;000 diseases;; the company said. It first annotates the data;; looking at whether a mutation is common or in a region where genes commonly change between people. The annotated data is processed by a machine learning algorithm which;; mimicking the manual process;; reveals whether a mutation is damaging. The software produces a list of diagnoses;; labelled disease-causing or otherwise;; and includes a confidence score. This allows those using the software to know how much evidence and data there is behind the prediction. This is then processed by another machine learning algorithm. The algorithm then combines the disease-causing mutations with clinical data;; such as why the patient went to the doctor for genetic testing in the first place;; to rank the mutations and understand which one is the most likely diagnosis. The company claims its software cuts costs;; improves accessibility for testing;; increases process accuracy;; and reduces the chance of misdiagnosis. David Gorgan had the idea when someone close to him went undiagnosed for years. He met Acuña Hidalgo;; then a genomics mutations researcher and now his cofounder;; on the Entrepreneur First accelerator where she told him the condition may be genetic – \"which wasn't realized for a long time by other physicians.\" \"I really realised that this difficult journey is something that is shared by hundreds of millions of people around the world;;\" Gorgan said. \"There is a big opportunity with clinical genetic tests to diagnose people much faster but at the same time;; also quite a big bottleneck and making sure that people can actually get results in time and get clear results.\" The company works with private and hospital labs;; and operates a SaaS model. It currently operates in the UK and Europe;; and is looking to enter the US. 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