From artificial intelligence and AI scientists to pharmaceutical analytics – 2019 Catalyst Grant Winnersedit
BPT Analytics, Intoolab and MLprior, three projects aiming to disrupt the academic space, are the latest recipients of the Catalyst Grant award for innovative startups.
LONDON, UK: Noon, 25 September 2019. Research industry technology company Digital Science has today revealed the latest winners of its prestigious Catalyst Grant award: BPT Analytics, Intoolab and MLprior have been awarded a grant.
An international initiative to develop innovative projects and technologies The Catalyst Grant offers an award of up to £25,000 or $30,000 for concepts with the potential to transform scientific and academic research. Digital Science is well known for its engagement with the research community, and the grant supports ideas at an early stage of development, without the need for a complete business or development plan.
BPT Analytics – Ukraine
BPT Analytics is an online business intelligence tool for the pharmaceutical industry. The tool is built on top of an up-to-date database of life science companies, which tracks what they do and how they perform in the market. It follows the team’s already established and growing publishing platform BioPharmaTrend.com, which features articles from leading pharma professionals and business leaders.
“While there is a plethora of large-scale business intelligence platforms on the market, the majority of them are too general for such a domain-specific market as drug discovery, so they can’t grasp important nuances, critical for decision making,” says co-founder Dr. Andrii Buvailo.
The early prototype of the analytics platform and database has already had good traction and Buvailo alongside fellow co-founder Dr. Oleg Kucheryavyi are looking to expand covering all major areas of the pharmaceutical industry. Buvailo believes BPT’s key strength is in its ‘extraordinary level of detail’ – as the tool clusters data about companies by numerous domain-specific parameters.
“BPT Analytics aims to eliminate as much guesswork from the practice of pharmaceutical industry strategists, business developers, and decision-makers, as is possible,” says Buvailo. “By providing them with visualized access to systematic and constantly curated data about the most innovative industry players, trends, and opportunities.”
They are looking into incorporating machine learning modules in the near future to help improve data mining and recommendation systems.
Intoolab – Greece / UK
Intoolab is an artificial intelligence platform built for pharmaceutical companies and researchers. Its main feature, Tzager, an AI scientific tool which scours through millions of research papers, helps find causal connections and join the dots between papers that would otherwise take significant time. The tool has been developed in collaboration with a number of universities worldwide and a pilot has been completed at Aarhus University in Denmark.
“The biggest problem in drug discovery is that there are millions of research papers with different information, but there are also millions of potential combinations of concepts that could solve specific problems,” says CEO Nikos Tzagkarakis. He believes most of the solutions try to focus on specific segments of the field. “We are trying to solve the problem at its core by not just connecting information, but also creating an intelligence that understands the mechanics of ‘why’ things happen.”
The team behind Intoolab, based in London and Athens, believe Tzager has a unique approach which is ‘deeply needed in the field of artificial intelligence’. They intend to broaden Tzager’s knowledge and deploy more powerful servers using the winning grant funds.
“The grant will enable us to develop our deep learning methods faster and also connects us with the valuable network of Digital Science,” says Tzagkarakis. “We are confident Tzager will become increasingly intelligent and we’re excited for the first time it will figure out an original solution in medicine and drug discovery.”
MLprior – Moscow, Russia
MLprior is a tool which uses AI-based analysis to predict whether a scientific paper will be accepted at a conference. The co-founders behind the product, Denis Volkhonskiy and Vladislav Ishimtsev, have both been actively researching AI with a focus on creating new models and algorithms at Skolkovo Institute of Science and Technology for the past five years. They are joined by PhD students Nikita Klyuchnikov from Skolkovo Institute of Science and Technology and Pavel Shvechikov from Higher School of Economics, who make up the four-person team.
The co-founders had previously created a system which predicted share price on changes in the news, but have shifted focus to scientific articles. They’ve constructed an algorithm for personal paper recommendations based on user behaviour and are now working on creating a unique algorithm for scientific paper analysis and prediction of acceptance at conferences.
“Our product simplifies and speeds up the process of writing scientific papers,” says Volkhonskiy. “We use artificial intelligence for analysing the text of the article and suggesting improvements.”
Volkhonskiy says paper rejection rates at conferences are high and often researcher feedback can take months. He believes their tool will help increase the probability of success by improving the article text using an AI-based model to search for poor sentence construction, article flow and more general grammatical issues.
“We hope to become a must-have service for each researcher. Researchers spend several months on polishing scientific papers from draft to publication, checking formulas and correcting mistakes – our tool will hopefully help save a lot of time.”
Steve Scott, Director of Portfolio Development at Digital Science said: “Once again, we would like to thank the community of researchers and entrepreneurs for sharing their ideas and passion with us. The field for this round of the Catalyst Grant was brimming with great ideas and narrowing down the entries proved a real challenge.
The three winners reflect our belief that AI and machine learning solutions will offer step-changes in the way we analyse and interact with data, whether that be for business intelligence, discovery or creation. We hope the grant, and our ongoing support, will help each of them achieve their next milestone.”
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Digital Science is a technology company working to make research more efficient. We invest in, nurture and support innovative businesses and technologies that make all parts of the research process more open and effective. Our portfolio includes admired brands including Altmetric, Anywhere Access, Dimensions, Figshare, ReadCube, Symplectic, IFI Claims, GRID, Overleaf, Labguru, BioRAFT, PeerWith, TetraScience and Transcriptic. We believe that together, we can help researchers make a difference. Visit www.digital-science.com and follow @digitalsci on Twitter.