Churning of data is something that definitely all pharma companies need to invest in.
By Arno Tellmann
Having lived in India ten years ago, I was very happy when I got the opportunity to come back albeit in a different role this time. India has come to be a second home to me and my family. Among the many things we like about this country is its culture steeped in centuries of history and legends. I find the legends part especially fascinating.
There was this one particular story that caught my attention—the churning of the ocean, when the devas and asuras got together in their quest for the nectar of immortality. Believe it or not, today’s pharma companies are staring into an ocean of another kind—an ocean of data that’s all around us. The big question is can we churn this ocean to extract insights that may not yield immortality but at least help us find new ways to improve and extend lives? Well, the exploration has begun.
Data in pharma industry includes electronic health records, biomedical signal data, patient statistics, imaging data, discovery related literature, experimental data, genomic data, proteomic data, and records on clinical studies. Development of drugs involves generation of lot of data such as clinical trial data, trial operational data and finally business involves competitor data, sales and other medium of business data.
However, this abundant data is of no use if we don’t mine it to extract insights. The value of data can only be realised if we leverage data technologies such Artificial Intelligence (AI). AI has become the game changer, transforming many industries over the last two decades. The technology companies today completely rely on data for garnering insights and making products driven by AI for competitive advantage, improving customer experience and entering new markets. Can it work its miracle in the pharma industry as well?
Pharma companies are now looking for ways to apply AI to fasten the overall drug development process. AI can dramatically shorten clinical trails through faster enrollment, identifying right patient for right trial, better monitoring and remote monitoring, better patient experience and invention of digital biomarkers and end-points. It could also help us discover new treatments. There are 1060 drug like molecules which need to be examined to find all possible drug targets and it seems impossible right now. AI has the potential to fasten molecular and material research to explore these molecules.
However, similar to the churning of the ocean, analysing data also poses challenges of epic proportions. To begin with, we need to bring together the huge volume of data on one platform that makes it possible to apply AI tools on the data. While it may sound simple, it’s actually a Herculean task given that in the past we did not have a mechanism to sort data. Secondly, we need to train our people on data technologies so that they can make sense of the data. Thirdly, we need bring this system to such speed that it can give us real time insights just like Google Maps. If the system foresees challenge in a clinical trial it should be able to warn us much in advance so that we do not invest time, effort and resources on something that is more likely to lead to a dead-end.
Churning of data is something that definitely all pharma companies need to invest in. And as with the legend, this too would need the combined efforts of one and all—patients, employees of pharma companies, data scientists, regulatory authorities, and governments. Only together, we can make it happen!
Arno Tellmann is Head, Novartis Global Drug Development, India. Views are personal