Cambridge and Manchester, UK, February 2019
Two artificial intelligence (AI) companies, Biorelate Limited and Intellegens Limited, today announced their success in the third round of the Innovate UK open grant funding competition. Together, the two companies have secured over £300,000 from Innovate UK and will co-invest an additional £130,000 to deliver a partnership project entitled: “Chemeia: A synergistic AI integrated architecture for augmenting high value dark-data”.
Project Chemeia ('Chem-ee-a') will test the potential for combining the capabilities of Biorelate’s deep text mining (Galactic AI TM ) technology with Intellegens’ sparse data solution, to produce up to date, comprehensive, and reliable data sets for high-value R&D work.
Biorelate and Intellegens are two high-technology companies specialising in the development and application of novel AI techniques that can solve common problems associated with optimising data curation for R&D.
Data curation is a critical component of scientific research and development (R&D) in many areas including biological research and advanced materials manufacturing – helping to ensure that results from in-house experiments and information from external sources can be integrated for further analysis.
Current AI methods for curating scientific experimental data can be slow and are prone to leaving gaps in the information they produce. Existing techniques are costly to deploy at scale. Estimates suggest that around 80% of published scientific literature is unused and the effort of data curation is an obstacle to research. This project will determine how modern AI approaches can make this better.
Biorelate CEO and founder Dr Daniel Jamieson said ‘Adequate data curation underpins so much of the future success of research and development in science and Biorelate is continually investing in innovative ways to improve this. What really excites me about this project is the prospect of bringing two completely different, game-changing technologies together to achieve something entirely novel. We can’t wait to start!’
Intellegens CEO and co-founder Ben Pellegrini said ‘We are excited to work with the team at Biorelate to bring together the best parts of our AlchemiteTM platform with Galactic AI TM . Independently, our AI technologies are proven; together they have the potential to take the pain out of data curation. Biorelate curates databases from the analysis of published scientific literature – allowing researchers to extract structured biological knowledge for use in a variety of applications. We work with sparse data, using our deep learning algorithm to make accurate predictions in datasets that are as little as 0.05% complete. With the funding granted by Innovate UK we’ll be able to exploit the synergies between these two approaches and see if it is possible to create a powerful new approach that can transform data curation.”
Both CEOs agreed that ‘Funding from Innovate UK has made this project possible. This support will help us contribute to the UK’s position as a leading nation in this field.’
Manchester Science Park, Manchester, UK, M15 6JJ
Biorelate is developing Galactic AITM, an advanced text analytics & data mining cloud-based platform. Galactic reduces research risks, increases commercial awareness and helps solve biomedical research’s greatest challenges.
Eagle Labs, 28 Chesterton Road, Cambridge, Cambridgeshire,
United Kingdom, CB4 3AZ
Intellegens have developed Alchemite, which builds on existing numerical curated resources (sparse data) by using AI to predict ranked unknown data-points and uncertainties. No other solution on the market can replicate Alchemite's low cost modelling, prediction, error detection & parameter optimisation for big, sparse, numerical data.
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Intellegens is a spin-out from the University of Cambridge that has developed a unique Artificial Intelligence (AI) method for training neural networks from incomplete data. The technique, developed in the Department of Physics, has been applied to drug discovery and material design but as the technique is generic it can be applied to many domains where there is big, incomplete data.