On October 1st 2019, Swiss pharmaceutical powerhouse Novartis and American technology powerhouse Microsoft announced a five year collaboration to accelerate drug development. The collaboration will make use of the extensive resources and expertise of both companies to streamline and perhaps revolutionize the drug development process. In a joint statement, Novartis and Microsoft explained the challenges in more detail:
"The issue isn’t just a problem of the overwhelming volume. Much of the information exists in the form of unstructured data, such as research lab notes, medical journal articles, and clinical trial results, all of which is typically stored in disconnected systems. This makes bringing all that data together extremely difficult. Our two companies have a dream. We want all Novartis associates – even those without special expertise in data science – to be able to use Microsoft AI solutions every day, to analyze large amounts of information and discover new correlations and patterns critical to finding new medicines. The goal of this strategic collaboration is to make this dream a reality. This offers the potential to empower everyone from researchers exploring the potential of new compounds and scientists figuring out dosage levels, to clinical trial experts measuring results, operations managers seeking to improve supply chains more efficiently, and even business teams looking to make more effective decisions. And as associates work on new problems and develop new AI models, they will continually build on each other’s work, creating a virtuous cycle of exploration and discovery. The result? Pervasive intelligence that spans the company and reaches across the entire drug discovery process, improving Novartis’ ability to find answers to some of the world’s most pressing health challenges."
As previously reported on this blog, collaborations between big tech companies and research organizations (whether corporate or academic) are increasingly common. The often AI-based data processing capabilities of Big Tech is a powerful resource for research organizations looking to make the best use of the data they collect. More collaborations of this sort can be expected as the amount of data collected and, by extension, the need to process this data, continuously increases.
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