83% of life sciences organizations release the
clinical database after first patient, first visit, which is
associated with downstream delays of up to a month in key data
management activities
One of the largest, most in-depth surveys of clinical data
management professionals shows that the time it takes companies to
design and release clinical study databases is having a negative
impact on conducting and completing trials.
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According to the 2017 eClinical Landscape Study from Tufts
Center for the Study of Drug Development, it takes companies an
average of 68 days to build and release a clinical study database.
Delays in releasing the study database are associated with an
increase of nearly a month downstream for other data management
processes such as patient data entry and time to lock the database
at the end of the study. Respondents that deliver the database
after first patient, first visit (FPFV), take nearly twice as long
to enter patient data throughout the study and about 75% longer to
lock the study database when compared to those that deliver the
final database before FPFV.
“The study results indicate that companies face a growing number
of challenges in building and managing clinical study databases,”
said Ken Getz, research associate professor and director at the
Tufts Center for the Study of Drug Development. “The results also
show that the release of the clinical study database after sites
have begun enrollment is associated with longer downstream cycle
times at the investigative site and at study close out.”
Electronic Data Capture (EDC) Providers and System
Use
EDC is the most widely adopted clinical application, used by all
respondents (100%), followed by randomization and trial supply
management (77%), electronic master file (70%), and safety (70%)
systems. A majority (58%) of respondents use either Medidata Rave
or Oracle Inform as their primary EDC system.
When asked about the type of data managed in their EDC, all
(100%) CROs and sponsors cite electronic case report form (eCRF)
data, followed by local lab and quality of life data (60% each).
However, respondents say eCRF data is the highest volume of data
they manage in their EDC system (at an average of 78% of the total
data managed). The next highest data volumes reported are central
lab data and local lab data at 5% each. Remaining data types
reported are each 4% or less. This demonstrates the need for
processes and systems to support the industry’s vision to have
complete study data in their EDC.
More than three-quarters (77%) say they have issues loading data
into their EDC application and most (66%) say EDC system or
integration issues are the primary reasons they are unable to load
study data.
Impact of Database Build Delays on Trial Cycle Times
The survey finds several common causes for clinical database
build delays. Protocol changes is cited most by 45% of respondents,
underscoring the challenge data management professionals have in
dealing with changes as they are finalizing the clinical trial
database for the start of the trial. This highlights the need to
optimize the database design process with standards and systems
that support more flexible design and rapid development.
Initial database delays also have significant downstream impacts
on the time it takes sites to enter patient data in the EDC
throughout the trial, as well as the final lock of the database
once the study is complete. It takes on average five days from
patient visit to when the data is entered into the EDC for
companies that release the database before FPFV. When the database
is released after FPFV, data entry time doubles to 10 days.
The impact of database build delays is even greater by the time
companies get to database lock. Those who always release the
database before FPFV get to database lock in an average of 31 days.
Those who never release the database before FPFV take more than
three weeks longer (54 days) to lock the database.
Sponsors take roughly 40% longer than CROs to build the database
(73 vs. 53 days) and to get to database lock (39 vs. 28 days).
Also, those using the two leading EDC systems report roughly 20%
longer data cycle times (123 days) than those using other EDC
systems (99 days), which includes time for database build (75 vs.
60 days), patient data entry (9 vs. 7 days), and database lock (39
vs. 32 days).
“Database build processes have remained largely unchanged over
the past 10 years, and the process will only get more complicated
as CROs and sponsors manage an increasing variety of clinical trial
data,” said Richard Young, vice president of Veeva Vault EDC.
“Organizations compensate for technology limitations by reducing
the volume of data they input. Our focus should be on improving EDC
systems so sponsors and CROs are no longer limited, and instead can
run the trial they want.”
The 2017 eClinical Landscape Study: Assessing Data Management
Practices, Performance, and Challenges from Tufts Center for the
Study of Drug Development, sponsored by Veeva Systems (NYSE: VEEV),
reviews the state of data management in life sciences with an
in-depth look at the insights and opinions of clinical data
management professionals at more than 250 companies, including
sponsors and CROs, with an average of 17 years of experience in
clinical data management. Download the report at
veeva.com/EDCSurvey.
To learn more about the findings, see the presentation from Ken
Getz, research associate professor and director at the Tufts Center
for the Study of Drug Development, and Richard Young, vice
president of Veeva Vault EDC, at the SCDM 2017 Annual Conference on
Monday, Sept. 25 at 3:00 p.m. in the exhibit hall.
About the Tufts Center for the Study of Drug
Development
The Tufts Center for the Study of Drug Development at Tufts
University provides strategic information to help drug developers,
regulators, and policy makers improve the quality and efficiency of
pharmaceutical development, review, and utilization. Tufts CSDD,
based in Boston, conducts a wide range of in-depth analyses on
pharmaceutical issues and hosts symposia, workshops, and public
forums, and publishes Tufts CSDD Impact Reports, a bi-monthly
newsletter providing analysis and insight into critical drug
development issues. For more information, visit csdd.tufts.edu.
About Veeva Systems
Veeva Systems Inc. is a leader in cloud-based software for the
global life sciences industry. Committed to innovation, product
excellence, and customer success, Veeva has more than 550
customers, ranging from the world's largest pharmaceutical
companies to emerging biotechs. Veeva is headquartered in the San
Francisco Bay Area, with offices in Europe, Asia, and Latin
America. For more information, visit veeva.com.
Research Highlights
2017 eClinical Landscape Study:
Assessing Data Management Practices,
Performance, and Challenges
The 2017 eClinical Landscape Study examines the state of
clinical data management in the life sciences industry. The goal of
the research is to understand current clinical data management
practices and assess the performance and challenges of electronic
data capture (EDC) systems.
One of the largest, most in-depth clinical data management
studies to date, this research captures the insights and opinions
of 250 clinical data management professionals, including sponsors
and CROs with an average of 17 years of clinical data management
experience.
Clinical Systems and EDC Data Landscape
- EDC applications are the most prevalent
clinical applications, used by all (100%) respondents, followed by
randomization and trial supply management (77%),
safety/pharmacovigilance (70%), electronic trial master file (eTMF)
(70%), and clinical trial management (CTMS) (61%) systems.
- A majority (58%) of respondents use
Medidata Rave or Oracle Inform as their primary EDC application. No
other application was used by more than 6% of organizations.
- While all respondents use an EDC
system, roughly one-third (32%) use paper case report forms (CRFs),
indicating these organizations still rely on manual processes to
manage data during their clinical trials.
- Organizations say they manage a wide
range of data types in their primary EDC system including eCRF
(100%), local lab (60%), quality of life (60%), central lab (57%),
and ePRO (34%) data. Only 10% of companies have genomic data or
mobile health data in their EDC.
- While companies have variety of data
types in their EDC, respondents say the largest proportion of the
data in their EDC system is eCRF data (estimated at 78% of total
data managed). All other data types were each estimated at 5% or
less of the total volume of data in the EDC, including local lab
data (5%), central lab data (5%), quality of life data (4%), and
ePRO data (3%). Genomic data and mobile health data make up the
smallest portion of data in EDC systems at 0.4% and 0.3%
respectively.
Clinical Data Management Cycle Times
- On average, it takes 68 days to build
and release a study database, 8 days from patient visit to enter
data in the EDC system throughout the study, and 36 days from the
study’s last patient visit to database lock.
- Sponsors, as well as those using the
two most prevalent EDC applications (Medidata Rave and Oracle
Inform), report longer times to build and release the study
database and to lock the database after last patient, last visit.
- Average number of days to build and
release the database:
- 73 days for sponsors vs. 53 days for
CROs
- 75 days for those using the two most
widely used EDC systems vs. 60 days for those using other EDC
systems
- Average number of days to lock the
study database:
- 39 days for sponsors vs. 28 days for
CROs
- 39 days for those using the two most
widely used EDC systems vs. 32 days for those using other EDC
systems
Clinical Study Database Build Times and the Impact on
Clinical Trial Cycle Times
- The up-front time it takes to build and
release the clinical database has potentially significant impacts
on downstream processes, including time to enter patient data in
the EDC throughout the study and time to final database lock after
last patient, last visit.
- It takes on average five days from
patient visit to when the data is entered into the EDC for
companies that release the database before FPFV, and database lock
time is 31 days.
- It takes on average 10 days from
patient visit to when the data is entered into the EDC for
companies that release the database after FPFV, and database lock
time is 54 days.
- Nearly one-third (32%) of sponsors
“often” or “always” release their EDC after FPFV has occurred,
compared to 20% of CROs.
- One-third (36%) of those using the two
most prevalent EDC applications “often” or “always” release their
EDC after FPFV has occurred, compared to 22% of those using other
EDC applications.
Top Causes for Database Build Delays and Data Loading
Challenges
- The most common cause for database
build delays is protocol changes (45%), followed by user acceptance
testing (17%), and database design functionality (15%).
- Database build delays due to protocol
changes are higher among CROs (52%) than sponsors (44%). Whereas
database build delays due to design functionality are lower among
CROs (7%) than sponsors (18%).
- Database build delays due to database
design functionality is associated with significantly longer time
to lock the database after last, patient last visit (50 days vs.
the 36-day average).
- Three-quarters of respondents (77%)
have issues that prevent them from loading data into their primary
EDC system. Most (66%) cite EDC system issues or integration issues
as the top challenges that prevent them from loading data.
View source
version on businesswire.com: http://www.businesswire.com/news/home/20170921005426/en/
Veeva SystemsRoger Villareal,
925-264-8885roger.villareal@veeva.comorTufts Center for the Study
of Drug DevelopmentRachel Stanton,
617-636-2170rachel.stanton@tufts.edu
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