Last month, the Swiss pharma giant Novartis announced a partnership with the University of Oxford's Big Data Institute to use "artificial intelligence to understand complex diseases and improve drug development."
The official announcement states the five year collaboration will focus on "...using the BDI’s latest statistical machine learning technology and experience in data analysis, combined with Novartis’ wealth of clinical expertise and clinical trial data...the alliance expects to predict how patients will respond to existing and new medicines."
The partnership between Novartis and Oxford is the latest in a recent trend of collaborations aiming to apply advances in artificial intelligence and machine learning from academia to problems with broad industrial application.
Another recent, high profile collaboration was announced in October 2018 between the National Institutes of Health and Amazon. Specifically, NIH will use Amazon Web Services' cloud computing and data analytics capabilities to host and analyze large data sets in areas like plant and cancer genomics.
Similar to the recent NIH-Amazon partnership, the Broad Institute has been using the Google Cloud Platform since 2015 to optimize its genome sequencing and storage capabilities.
The interest in Big Data focused collaborations from pharma and biotech companies for biomedical applications is obvious. However, interest from traditional big tech companies like Amazon and Google may suggest these companies are now very interested in diversifying their business with offerings to institutions in biomedical and healthcare areas. In fact, as highlighted in a recent Nature article, big tech companies very often partner with individual researchers on projects that are of high interest to them.
As the need to combine expertise in data analytics with big data storage capacity increases, one can expect more such industry-academic collaborations in the near future.