The Evolution of Clinical Data Strategies & Digital Transformation
The Evolution of Clinical Data Strategies & Digital Transformation
The data from this study can help you understand how clinical data sources are growing, how that is impacting the industry and how to mitigate disruption.
As revealed in the Tufts-eClinical Solutions Data Strategies & Transformation Study Results*, where 149 sponsor organizations were surveyed, the life sciences industry must adopt new data strategies and improve technology infrastructure to accelerate drug development.
The volume of data is growing
Sponsors are contending with more data than ever before. Over two-thirds of clinical trial sponsors are using or piloting at least four types of data
50%
of sponsors perceive these data management activities as time-consuming and labor-intensive
Data integration and management is time consuming
Top three most time consuming:
Initiating relationships with data providers
Performing data review and cleaning
Transforming and mapping data
Followed by:
Importing or ingesting data
Curating data
Analyzing data
Tools to centralize and standardize data are unsophisticated
75% of companies are still using SAS as the primary tool for data integration and publishing.
Cycle times are increasing
40% increase since 2017
Companies using 4 or more sources are experiencing an increase of more than four weeks in last patient last visit (LPLV) to database lock cycle.
Only 1/3 of sponsors have implemented a formal data strategy
Top 3 Digital Transformation Accelerators
1
Defined Data
Strategies
Executing these strategies decreases database lock cycle times by an average of two weeks
2
Technology
Platforms
Sponsors using a data hub/lake rate their analytic competencies and capabilities higher
3
Advanced
Analytics
Nearly 3 out of 4 sponsors are expanding data scientists’ roles to support advanced analytics
A data strategy defines what data is needed and how it should be presented to the data consumer.
