Tufts-eClinical Solutions Data Strategies & Transformation Study eClinical Solutions collaborated with
• Sponsors conducting a high number of trials and using 5-6 data sources can expect longer cycle times while they are researching or planning a formal data strategy; once sponsors implement a formal data strategy, database lock cycle times decrease by ~ 2 days. • Sponsors who have implemented a formal data strategy perceive their analytics critical capabilities to be more fully developed and mature. • Sponsors using a data hub / lake rate themselves as more mature in all critical capabilities with use of dashboards and visual exploration having statistically significant differences compared to those not using a data hub / lake.
Share of companies using or piloting data sources NonCRF Data
Direct Data Capture
Devices and Apps
Medical Images
EHR/ EMR
-Omics Data
Small sponsors (N=54)
88.0 %
68.5%
55.8%*
69.8%
22.0%*
26.0%
Mediumlarge sponsors (N=85)
86.9%
81.2%
77.1%*
70.6%
55.9%*
40.5%
Overall (N=147)
87.3%
74.8%
69.2%
67.8%
43.4%
35.5%
the Tufts Center for the Study of Drug Development in 2019 to survey pharmaceutical companies about their evolving clinical data demands and the tactics they are employing to manage and leverage
• More than two-thirds of all sponsors are using or piloting at least four primary data type in clinical trials CRF = Case report form; EHR/EMR = Electronic health record/electronic medical record *Subgroup Differences Significant at the P<.05 Level
Last Patient Last Visit (LPLV) to Database Lock (DBL) Cycle Times
their data. Highlights reveal new strategies
2017 Clinical Data Survey Results*
Overall
and digital transformation initiatives being taken.
eCS Clinical Data Survey Results
36.3
CoV=0.89 CoV=0.85
Large Sponsors
CoV=1.19
Medium Sponsors
CoV=0.67
Small Sponsors
CoV=0.75
41.2
33.7
CoV=1.15
CoV=0.82
CoV=0.68
44.5 33.7 38.4 42.7 41.9
Number of Days • LPLV to DBL cycle times have increased about 6 days overall since the previous study in 2017 • Large sponsors had the highest increase in LPLV to DBL (32%) since the previous study in 2017 *Study examining current and evolving EDC and clinical data usage practices across the drug development enterprise. Survey contained 22 questions, was open for 10 weeks, and garnered 257 completed responses from mostly sponsor organizations (75%)
Tufts-eClinical Solutions Data Strategies & Transformation Study
Status of formal data strategy among sponsor companies Formal data strategy implemented
Examining or planning a formal data strategy
Learn More The survey also found that
50% 45%
respondents with a formalized data
40%
strategy reported less difficulty with
35% 30%
data activities such as ingesting,
25% 20%
integrating and analyzing data. For
15% 10%
these additional insights and more,
5% 0%
Small sponsors (N=54)
contact us for the full survey results.
Mid-large sponsors (N=85)
• Half of all sponsors indicate they are considering or planning to implement a data strategy
Last Patient Last Visit (LPLV) to Database Lock Cycle Time Subgroups CoV=0.85
Overall Data Strategy Implemented
CoV=1.0
Planning or Researching Data Strategy
CoV=0.6
No Data Strategy Planned
CoV=1.1
1-2 Data Sources Utilized
CoV=0.7
3-4 Data Sources Utilized
CoV=0.8
5-6 Data Sources Utilized
CoV=0.9
Contact Us To learn more about the elluminate® Clinical Data Hub and how it can
41.2
enable your clinical data strategy,
36.1 47.9 41.8 43.6
contact us for a demo.
Request a Demo
35.1 50.7
Number of Days
• Sponsors who have implemented a formal data strategy have shorter cycle times than others with high variation • Organizations managing 5 - 6 data sources face longer times to achieve database lock with higher variation
Respondent Analytics Critical Capabilities Maturity by Use of Data Hub/Lake Percentage Rated Fully or Somewhat Mature and Capable
Using Data Hub/Lake (N=69)
Not Using Data Hub/Lake (N=41)
87.3% 87.3%
87.3%
87.3% 87.3%
87.3%
87.3% 87.3%
Analytics Dashboards*
Interactive Visual Exploration*
Publish, Share, and Collaborate on Analytic Content
Augmented Data Discovery
• Sponsors using a data hub / lake rate themselves as more mature in all critical capabilities with use of dashboards and visual exploration having statistically significant differences compared to those not using a data hub / lake *Chi-Square Value < 0.05
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Source for Figures: Tufts Center for the Study of Drug Development
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