pharmaphorumJanuary 21, 2019
Tag: Novartis , Oxford University , statistical machine learning , data analysis
The Swiss pharma has joined with the university’s Big Data Institute (BDI) in a five-year research alliance using anonymised data from around five million patients in the UK, together with anonymised data captured from Novartis’ clinical trials.
This is the latest part of Novartis’ digital transformation, a priority for CEO Vas Narasimhan, who took over in February last year.
Using the institute’s latest statistical machine learning technology and experience in data analysis, combined with Novartis’ trial data, the alliance expects to predict how patients will respond to existing and new drugs.
Through innovations in IT and AI technology the alliance will look for patterns in data, often across multiple sources such as imaging, genomics, and clinical and biological data, which cannot be detected by humans alone.
The aim is to identify insights into characteristics of complex diseases to understand what drives progression, and understand any similarities between diseases.
The alliance will focus initially on two areas – multiple sclerosis and dermatology and rheumatology – allowing for knowledge exchange between experts from the two organisations.
It will also draw on knowledge from other partners, such as the Medical Research Council Harwell Institute, which will contribute expertise in informatics and data "wrangling".
This is the process of converting and mapping data from its raw form to another format with the purpose of making it more appropriate for the task.
Oxford’s Department of Statistics is also providing expertise in statistical machine learning.
Mark Toms, chief scientific officer of Novartis UK, said: "This partnership with the BDI is aligned with the UK’s Life Sciences Industrial Strategy and offers the opportunity to expand our understanding and capabilities in data science at scale. As a leading medicines company driven by data and digital, Novartis expects the collaboration with the BDI to enhance its capabilities in data science and analytics."
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