Johnson & Johnson’s Collaborative Approach to AI & Predictive Analytics
Add bookmarkAI is emerging as a powerful medical science tool. From accelerating drug discovery to increasing supply chain resiliency, the potential of AI to revolutionize the health sciences space is seemingly limitless.
Considering this, its no surprise that the the global artificial intelligence (AI) in healthcare market is forecasted to grow from 3.39 Billion in 2019 to 61.59 Billion by 2027 at a CAGR of 43.6%.
One of the key pioneers in this area is Johnson & Johnson. As covered on our sister site, the Intelligent Automation Network, J&J kickstarted its digital transformation roughly 10 years ago. Since then, the company has used machine intelligence to automate over 60 global processes and launch a number of ambitious AI projects.
Predicting the next COVID-19 HotSpot
As a producer of everything from fever reducing drugs such as Tylenol to COVID-19 vaccines, understanding how the virus spreads and predicting the next outbreak was critical to ensuring the right resources were directed to the right places at the right time.
As explained by Najat Khan, Chief Data Science Officer and Global Head of R&D Strategy and Operations, Janssen Pharmaceutical Companies of Johnson & Johnson on the company website, “the virus is moving quite fast, and it’s seemingly unpredictable. But it’s not actually unpredictable. By combining several types of data into an advanced analytical model using new techniques, we are driving insights and leading the way to a deeper understanding of this disease in order to help shape our clinical development program.”
With this in mind, data scientists at J&J/Janssen built it’s globally recognized COVID-19 surveillance dashboard using predictive analytics and data visualization techniques.
Clinical Trials Reinvented
With billions of lives at stake, J&J not only had to accelerate the clinical trials for its COVID-19 vaccine, but also ensure they ran seamlessly. As part of this process, J&J partnered with Janssen partnered with Dr. Dmitri Bertsimas’ team at MIT to build a new predictive algorithm that uses a combination of machine learning and epidemiological infectious disease models known as SEIR.
Dubbed DELPHI, this new epidemiological model predicts state-by-state infection and mortality rates based upon each state’s policy decisions. Using Delphi, J&J was able to determine when and where to test the vaccine.
As Najat Khan, explained in a different interview with MIT’s student newspaper, “To run a trial like this, which is very, very large, it’s important to go to hot spots where we anticipate the disease transmission to be high so that you can accumulate those events quickly. If you can, then you can run the trial faster, bring the vaccine to market more quickly, and also, most importantly, have a very rich dataset where you can make statistically sound analysis.”
The Future of AI at J&J
Though there are few applications of AI more compelling than the development of life saving treatments and vaccines, J&J is currently embedding AI into all facets of the organization.
In a recent WSJ interview, J&J’s CIO, Jim Swanson, shed light on the organization’s larger AI strategy, “At J&J, IT owns the technology that underpins AI: cloud computing, data repositories, APIs. But we’ve embedded the data science in our functions, where it is closest to the business problems we’re looking to solve. We’ve also created a data science council, with representation from each part of the business, that oversees our portfolio, talent, and technology.”
He also added, “The organizational model should reflect the maturity of the AI capabilities. For organizations just getting started with AI, a centralized model typically builds critical mass. Then, it should be distributed. I like a hybrid model. Being fully decentralized is like herding cats—the technology does not get leveraged effectively.”
As a result of this integrated approach, we expect to see more cutting-edge and out-of-the box applications of AI from J&J in years to come. Stay tuned as we're just starting to dig in.
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