Boost Patient Recruitment With Data-Centric Trial Planning

Posted by Venkat Sethuraman on Fri, Aug 16, 2019

Denise N. Bronner, Gaurav A. Singh and Ray Zhong co-wrote this blog post with Venkat Sethuraman

A common struggle for pharmaceutical companies is poor patient recruitment for clinical trials. As a consequence, 80% of clinical trials fail to meet their enrollment goals, suffer delayed timelines and absorb skyrocketing R&D costs. Ultimately, the patient suffers from delays in the release of needed therapies. Currently, pharmaceutical companies are partnering with trial matching startups to enhance clinical study design, matching and data collection. With analytics and platforms, pharmaceutical companies are beginning to streamline the clinical trial process in hopes of increasing new entrants to the market.


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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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Making the Case for a New Analytics Consumption Model

Posted by ZS Editors on Thu, Nov 29, 2018

Industries like retail and technology are transitioning to an AI-driven, personalized approach to surfacing insights to end users, and they’re reaping the benefits. Life sciences companies have the same opportunity to capitalize on the runaway growth in data and rethink the way that analytics are consumed.  

ZS recently partnered with IDC to study how commercial life sciences teams are currently consuming data, and to determine their data and analytics pain points. The study revealed that sales and marketing professionals in life sciences want


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Pharma Should Be Making More Data-Driven Deployment Decisions

Posted by Pratap Khedkar on Wed, Nov 28, 2018

This is the second post in a three-part series on commercial resource planning.

As the pharma industry’s customers evolve with the shifts in the healthcare landscape, pharma companies can no longer take a static, semiannual, one-size-fits-all approach to commercial resource planning. They need to take an agile, localized, customized approach to aligning commercial resources to better meet their customers’ evolving needs—and they need the right analytics capability to mine the customer and market insights they need to get it done.


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Has Gawande Found the Right Man for the Job?

Posted by Pratap Khedkar on Thu, Sep 20, 2018

Paul Darling co-authored this blog post with Pratap Khedkar.

What kind of skills will it take to run the day-to-day operations for a potentially paradigm-shifting undertaking in U.S. healthcare delivery? It turns out that it's hands-on experience helping patients navigate the complexities of healthcare options and helping employers control healthcare costs, powered by an undercurrent of digital health expertise.


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