Many companies in the life sciences industry experience rapid global growth, both organically as well as through merger and acquisition. While growth is, of course, great and welcome, it also comes with some challenges.
With respect to clinical operations and clinical trial management, aligning processes can be rather challenging as different parts of the business and varying geographical locations typically have established ways of managing studies, as well as their own set of tools and spreadsheets. These inefficiencies leave the data from each of these trials in disparate tools with no easy way to consolidate and obtain full visibility across all the studies in the organization.
A Single, Global CTMS and Related Processes Were the Answer
Pfizer encountered similar challenges to those described above and determined that the best way to address this problem would be to implement a single, global enterprise clinical trial management system (CTMS). At the same time, the organization took this opportunity to ensure that all of its global clinical operations processes, which will be supported by the new CTMS, are aligned.
This guide analyzes how artificial intelligence – including machine learning – can be used by pharmaceutical and medical device companies to improve the clinical data review and cleansing process.
Pfizer took a very deliberate approach when it designed and implemented its CTMS to ensure that all of the information that would be stored and tracked in the system was meaningful. Historically, the organization had a flexible policy for what data could or should be stored in the CTMS. It was seen as all things to all people in the organization, so it grew to hold data that was not necessarily meant to be in a CTMS. If other systems did not have a specific place to track some related study information, user groups would simply request for additional data points to be collected in CTMS, even if there was no legitimate reason for it to reside there.
Embarking on a fresh clinical trial management system implementation enabled Pfizer to make a key change: The company’s business leaders instituted a policy that requires the data stored in CTMS to provide actionable insight to CTMS users. That is, if the data would not be used, reviewed, and acted on in some way by CTMS users, and it didn’t have a specific business objective, it should not be included in the new system.
To learn more about Pfizer’s implementation of Oracle CTMS in the Cloud, you can download the paper here or fill out the form below.
Perficient and Pfizer showcased this success story during Oracle Health Sciences Connect 2019. The session, “Key Takeaways from the Oracle CTMS Cloud Implementation,” highlighted the strategy and process behind the implementation, along with the challenges, considerations, and tips for implementing the solution.