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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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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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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What Does a Good Forecasting Platform Look Like?

Posted by Matt Wills on Wed, Oct 03, 2018

This post is the third in a four-part series on how pharmaceutical companies can elevate their forecasting operations. To learn more about next-generation analytics in forecasting, check out Matt’s session at the ZS Impact Summit, held Nov. 6-7 in Chicago.

Advances in data availability and the technology needed to harness that data have led many to ask how new technology could be used to implement advanced forecasting platforms for regional or global use. These platforms are typically software that sits online to enhance a forecasting process, whether specific to a country or used globally. Often, these questions are focused on increasing the efficiency of the existing forecasting team. While increasing the efficiency is important, it typically doesn’t generate enough organizational impact relative to the investment required to build and maintain a sophisticated piece of software. Platforms should strive to enable better decisions faster and more broadly than just reducing forecaster effort.


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