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Lifebit raises $3M to scale-up AI-powered analysis of DNA data

Making sense of DNA data is a two-step process, namely the biochemical-sequencing of the DNA and the analyzing and extracting insights from the sequenced DNA data. As of today in 2018, the first part of this process is now almost fully automated requiring minimal human intervention. Even sequencing costs have dropped below $1,000 and soon they will reach $100, according to the industry. The second part of the process, however, is a long way from being automated because it’s very complex, time-consuming and requires highly specialized experts to analyze the data. Now a startup plans to address this problem. London-based Lifebit is building a cloud-based cognitive system that can reason about DNA data in the same way humans do. This offers researchers and R&D professionals, with limited-to-no computational and data analysis training, and their corresponding organisations (ie. pharmaceutical companies), a highly scalable, modular and reproducible system that automates the analysis processes, learns from the data and provides actionable insights. It’s now closed a $3m (£2.25m) Seed funding round led by Pentech and Connect Ventures, with participation from Beacon Capital and Tiny VC (AngelList). The company is simultaneously announcing the launch of its first product, Deploit, what it claims is the world’s first AI-powered genomic data analysis platform, and, says the company, is already being trialled by major pharmaceutical and biotech companies. The main “competitor” for Lifebit is the DIY process of analysing and getting actionable insights out of genomics and biodata. Organisations, both in industry and research, build custom software and hardware solutions to be able to analyse the huge volumes of genomic and biodata at scale. This leads to a large waste of resources since custom software and hardware is expensive and hard to scale and maintain. A few platforms have been created like DNAnexus and SevenBridges. However, these platforms tend to lack flexibility, don’t integrate with the way the vast majority of bioinformaticians work, operate like black boxes which fail to provide the user with full control and transparency, can be very costly to use, and enforce lock-downs. All in all, if the user stops using these platform,…

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