The 2019 Data Science Showcase at Johnson & Johnson brought together data scientists and business leaders from around the world to collaborate, share cutting-edge breakthroughs and envision the future of healthcare. While there were so many standouts during the three-day event, winners were ultimately selected—based on audience voting—in five tracks:
- Research and Development (R&D)
- Supply Chain
- Human Resources (HR), Finance, IT and Other Functions
- People, Processes and Technology
Let's take an up-close look at our five award winners to show you how data scientists at Johnson & Johnson are thinking big, making real-world impact and transforming healthcare from end to end.
R&D: Uncovering New Medical Insights
Glutamate: it's the primary "excitatory transmitter" in the brain, how one neuron tells another neuron to be active. Perhaps not surprisingly, then, compounds that regulate the transmission of glutamate hold tremendous therapeutic potential for patients. Our recent treatment-resistant depression (TRD) breakthrough is an example of that.
If we know something works for one indication, why not examine its potential efficacy for others? It's a question Gayle Wittenberg and her team are answering. As she put it: How do we "take the compounds we've already proven to be safe and biologically active in one disease and ask what other diseases they might be effective in? What other patients could we actually be helping?"
Searching for those potential new applications, unfortunately, turns out to be a Promethean task: To be at all comprehensive, in effect, you'd have to analyze the accumulated medical knowledge of humankind. But thanks to AI and advanced data science, that's exactly what Gayle and her team are doing—and so far, the results have been promising.
Gayle says she's excited about all the data science collaboration she sees going on at Johnson & Johnson, and so closed her presentation with a challenge to the audience: What would a biology hackathon even look like? In the year ahead, expect her to find out.
Supply Chain: Getting Treatments to Patients—Faster and For Less
When you're one of the world's largest healthcare companies, your products can touch a billion lives around the world every day. As a result, production scheduling gets complex. Surveying that complexity, Jingwen Wang and Ben Ruley asked a question: How do we know if we are, or are not, using an optimal production schedule?
This insight launched the investigational equivalent of a thousand ships, eventually suggesting a data science solution. The result is an analytics tool that incorporates data from multiple sources, including real-time changes in supply and demand, to find the single best production schedule.
It's a good example of how data science innovation at Johnson & Johnson is driving real-world impact, ensuring that patients get the treatments they need, when they need them, and at a lower cost, to boot.
Commercial: Anticipating the Needs of Patients
Imagine a one-of-a-kind magic eight ball, a tool capable of anticipaing and accurately forecasting future patient needs. If that sound impossible, think again. An interdisciplinary team at Johnson & Johnson just built it.
The goal? That's simple: connecting more patients with better treatment options, which should help us move the needle on key health outcomes.
During the pilot phase, the team had the new tool analyze de-identified patient histories from over a million people with Crohn’s disease, then collectively held their breath. How accurately would this tool be able to predict future behaviors and needs? Very accurately, as it turned out, and the scope of the pilot was subsequently scaled across multiple disease areas. It's another example of how we plan to use data science to influence and improve health outcomes going forward.
HR, Finance, IT and Other Functions: Improving Financial Forecasting
Accurate, reliable and timely financial forecasting is essential for any business, but especially for us, considering we're among the top 10 companies across all industries when it comes to investment in innovation and R&D.
Yet forecasting remains in many ways a manual process. A team of data scientists at Johnson & Johnson, led by Sahil Bhatia, Ravi Bobbe and Gurdeep Singh, wondered if they could change that.
The team launched a pilot whose objective was as straightforward as it was ambitious: Could data science be used to forecast financial statements more accurately than our current, manually dependent processes?
Initial results suggest it could. Plus, with more accurate forecasting processes in place, we should be able to continue to invest in new drugs, devices and treatment options. In turn, that should help us continue to make progress on the greatest healthcare challenges of our times.
People, Processes and Technology: Creating a Virtual Assistant for Business Insights
Dashboards can be immensely valuable tools for business leaders, offering granular visibility into performance and insights that inform strategy.
One problem with dashboards, though: Drilling down into the data and getting the answers you need isn't always fast or easy, even for people who are proficient with them.
Enter Daniela, winner of the People, Processes and Technology track at the 2019 Data Science Showcase.
Who or what is Daniela? The brainchild of two Daniels—Daniel Rodrigues and Daniel Thull—Daniela is a virtual data assistant that combines AI and natural language processing (NLP) to make accessing business insights as easy as, say, asking your virtual assistant to play Styx's "Mr. Roboto."
What's the revenue forecast for the quarter? Where is our supply chain in danger of bottlenecking? How is a new product performing in a given market? Thanks to the Daniels, there's no need to scour dashboards anymore. Just ask Daniela.
Join the Data Scientists at Johnson & Johnson Today!
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