While data analytics, IoT, and AI are fast becoming normalized terms in the business world, it is generally perceived as reserved for the more adventurous companies, and not for the likes of conservative industries such as pharmaceuticals.

Jamie Davies

June 23, 2016

3 Min Read
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While data analytics, IoT, and AI are fast becoming normalized terms in the business world, it is generally perceived as reserved for the more adventurous companies, and not for the likes of conservative industries such as pharmaceuticals.

This is certainly not the case anymore according to AstraZeneca’s Steve Woodward who is leading the charge of data analytics within the pharma giant.

Data is one of the areas which is defining the future of the business, mainly because of the vast amount of data which the company has. And this is only increasing at a faster and faster rate. For Woodward, a DevOps approach was crucial to increase the pace of development and production. The team is currently processing around 2,500 queries a minute, meaning the implementation of containers was a must.

This forward looking position could be seen as unusual for the pharmaceutical industry, but for Woodward it’s a necessity.

“From concept to going live and production was some of our projects can be done in a matter of weeks,” said Woodward. “This involved the coding and architecture, and was only possible because of the Devops and cloud approach which we have embraced in the company.

“First and foremost, we want to make sure the patient is maintaining a good quality of life. We want to ensure the impact we are having on their lives isn’t negative, and this is primarily done through the implementation of new technology.”

This patient-centric approach has been realized through IoT and a greater understanding of data analytics. Through collecting data from a number of different sources including Fitbit, smart fabric, humidity sensors and locations beacons, the team can understand what impact medicine is having on an individual’s day-to-day life. Is the patient more active before or after taking the medicine? Have there been any notable changes in the patient’s metabolism? What impact is the medicine having on an individual in different environments which weren’t outlined in the clinic trials?

All this information individually means nothing to the team, however bringing it all together tells a story, and helps companies like AstraZeneca move forward with the concept of “the hospital in the home”.

This information is currently aiding the company in developing and honing medicine for the moment, but there are big plans for the future. Woodward highlighted to us the next steps are bots, and from there artificial intelligence and then onto predictive medicine. In terms of the bots, this is a very rudimentary currently. Certain factors and certain circumstances can trigger the bot to alert a GP or emergency services. But in the future, AI has the potential to alter the way a patient is treated and make decisions for the forthcoming treatment of the patient. Are these the first steps away from reactive medicine? Are these breakthroughs the beginning of predictive medicine?

While this is certainly promising progress from an industry which is generally perceived as reserved, the acceptance of IoT and such data practices by older demographics is unknown for the moment. Predictive medicine could be the answer to an NHS which is under strain, but the practicalities may just be out of reach for the moment.

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