AI & Real-World Data: A Perfect Union

Posted by Arun Shastri on Mon, Jan 27, 2020

This blog post is the seventh in a series on the impact that AI will have on different business aspects of pharma.

Real world data (RWD) is as old as data itself. It was relatively useless, however, until it was digitized. And then once it was digitized, we struggled to analyze so much data at scale with any kind of efficiency.

Enter our ability to store and analyze large volumes of data and advancements in data science, algorithms and technology. With the help of AI, it’s now possible to truly leverage RWD and begin to understand patient populations in holistic ways that have so far eluded pharmaceutical companies. It’s accelerating the use of evidence across healthcare to support the focus on patient health outcomes.


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What Can J.R.R. Tolkien Teach Us About AI Adoption?

Posted by Asheesh Shukla on Wed, Dec 18, 2019

While companies are embracing AI, a recent study shows that their pursuits are driven more by fear of obsolescence than enthusiasm for change. Eighty percent of companies in a recent survey stated that they intend to expand their AI use over the next 12 months, but we also know that 77% of AI projects face challenges with business adoption, and less than 8% of companies have successfully implemented AI at the enterprise level.


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Want Reliable Advice? Consider Machines

Posted by Arun Shastri on Mon, Jun 17, 2019

An old story about Jeff Bezos that I read years ago resurfaced in my memory when I learned that Amazon just abruptly changed course and decided to shutter its restaurant delivery business. According to the teller of this tale, Bezos once visited Basecamp to give a talk and take questions from employees there. At one point, Bezos described the kind of people who are “right a lot.” The smartest people, he said, are always revising their thinking. They might think one thing today that they’ll readily contradict tomorrow because they have new data to support a new opinion.

Other luminaries have shared this opinion. Science fiction author Vernor Vinge, in his book Fire Upon the Deep, wrote “Intelligence is the handmaiden of flexibility and change.” Salesforce CEO Marc Benioff was quoted as saying, “You must always be able to predict what's next and then have the flexibility to evolve.”

I wholeheartedly agree with this line of reasoning, and I see direct connections to machine learning.


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A Panel of Experts Talk MDM in Healthcare: Three Takeaways

Posted by Ankit Jain on Mon, Jun 10, 2019

The potential of digital transformation is being realized across industries. In healthcare, advanced analytics has streamlined processes, sped up research and promises to drive better health outcomes. But advanced analytics are nothing without data, and unless you can break down data siloes across the enterprise and merge critical data into a single source of truth (otherwise known as master data management, or MDM), then your data will be insufficient to drive this kind of transformation.

I recently participated in a panel discussion for Informatica World 2019 with representatives from Intermountain Health and The American Cancer Society. We discussed MDM’s role in healthcare as a driver of digital transformation.

After reflecting on the conversation, I took three things away from the event:


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How to Get Pharma Leaders to Wrap Their Minds—and Their Arms—Around Advanced Analytics

Posted by Shreyas Murthi on Mon, Mar 11, 2019

 

The business of pharma is becoming more data-driven—from R&D to commercial—yet many pharma companies still struggle to garner leaders’ buy-in to build and operate the analytics programs that they need to fuel their success. They face tough challenges, including overcoming skepticism, proving the program’s value and scalability, finding the right talent and ensuring organizational collaboration.    


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