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Optimizing Protocol Planning, Feasibility,
and Site Selection through an Integrated
View of Clinical Trial Operations and Other
Data Sources
Elisa Cascade
Session Format
• We will be testing out a new polling system
during this lunch session to solicit feedback from
attendees
• Following the session, results will be available to
participants in the SCOPE presentation slides
• Please be patient with us and the
new technology
• Our fingers are crossed…
2
Initial Test of the Polling System
Audience Poll #1:
• Which of the following best describes your
company / affiliation?
1. Pharmaceutical company
2. CRO
3. Other provider to pharmaceutical companies
and/or CROs
4. Investigator / Site Staff
5. Other
3
Poll #1 Results
Pharmaceutical Company
32%
CRO23%
Other provider to pharma/CROs
25%
Investigator/Site11%
Other9%
4
Which of the following best describes your company/affiliation? (n=44)
Finding the Right Investigative Sites &
Accurately Predicting Enrollment
• Today’s challenge is matching the right
investigator to a particular protocol to avoid non-
enrolling or under enrolling sites
– 11% do not enroll a patient
– 37% fail to meet enrollment targets
• Better matching has the potential to decrease
costs, improve quality, & improve investigator
satisfaction
5
Source: Tufts Center for the Study of Drug Development 2013.
Poll #2: Is Site Selection Evidence Driven
in Your Company?
6
• Variation in how
pharmaceutical companies
and CROs select sites,
sometimes even within the
same organization
• Tendency is to work with the
sites you know
– Especially when the
process is decentralized
1. Use own list of investigators
or existing site relationships
2. Use of an internal database
with metrics
3. Use of an internal database
with metrics + at least one
other external data source
(e.g., 3rd party subscription)
4. Internal database with
metrics + external data
sources + EMR
5. Don’t perform this function
How does your company select sites?
Poll #2 Results
24%21%
38%
17%
0%
10%
20%
30%
40%
50%
Use own list ofinvestigators or
existing siterelationships
Use of an internaldatabase with metrics
Use of an internaldatabase with metrics
+ at least one otherexternal data source
(e.g., 3rd partysubscription)
Internal database withmetrics + external
data sources + EMR
7
How does your company select sites? (n=29)
Note: n=12 don’t perform this function.
Operational Challenges with Relationship
& Evidence Approaches
• Process that relies on previous relationships
– Challenging to share knowledge across projects/teams
– Organization may lack common tools for accessing data
• Evidence-driven process
– Requires data sources to be used sequentially or
– May require manual effort to integrate data across sources
Commercial solutions are available today to address these challenges
8
Case Example: DrugDev SiteCloud
• Integrates investigator, site, and protocol data in a secure hosted system:
– Assigns a universal identifier known as the DrugDev Golden Number, to match and master records
– Toolset with an integrated view of information indexed to the same DrugDev Golden Number
• In addition to helping individual companies, SiteCloudalso powers:
– The Investigator Databank collaboration
– The TransCelerate Investigator Registry
Technologies such as SiteCloud provide the platform and toolset for evidence-based site selection
9
Factors Used to Predict Site Performance
• Limited published literature around factors used to predict site performance
• Potential factors mentioned across publications include:
– Clinical research focus
– Site experience in the indication
– Available patient population
– Performance on previous studies
– Time to first subject consented
10
Poll #3: What’s Most Important in Site
Selection?
Audience Poll:
• In your own experience, which of the following
factors do you consider to be most important
when selecting a site for a study?
1. Clinical research focus
2. Site experience in the indication
3. Available patient population
4. Performance on previous studies
5. Time to first subject consented
11
Poll #3 Results
62%
19%
17%
2%
0%
0% 20% 40% 60% 80% 100%
Available patient population
Site experience in the indication
Performance on previous studies
Clinical research focus
Time to first subject consented
12
In your own experience, which of the following factors do you consider to be most important when selecting a site for a study? (n=42)
Alignment of Evidence to Predictive
Factors
• CTMS is the only source for site-level performance and speed
• Historically, CTMS data has been limited to internal company studies,
however, data sharing has emerged as an option for collaborations
(e.g., Investigator Databank)
Factor FDA 1572 Clinical Trials Registries (e.g.,
clinicaltrials.gov)
Clinical Trial Management
Systems (CTMS)
EMR/EHR
Research focus
Site experience
Performance on previous studies
Speed
Available patients
13
Poll #4: To Share or Not to Share?
1. No, we would not be
willing to share data
2. Yes, we would be willing
to share data, but only at
the aggregate/de-
identified level
3. Yes, we would be willing
to share data at the
investigator and
aggregate level
• Individual company attitudes towards sharing differ based on whether investigators and data are seen as a:– Competitive advantage or
– Shared resource
• Options for sharing:– Aggregate level (de-
identified, consent not required): supports country selection and enrollment planning
– Investigator level (requires consent): informs site selection
Would your company be willing to share data to view others data?
14
Poll #4 Results
No, we would not be willing to
share data23%
Yes, we would be willing to
share data, but only at the
aggregate/de-identified level
31%
Yes, we would be willing to
share data at the investigator and aggregate level
46%
15
Would your company be willing to share data to view others data? (n=39)
Poll #5: Use of Evidence & Sharing to
Predict Enrollment?
16
• Variation also observed in how enrollment projections are prepared
– Study-level projections based on KOL feedback and previous studies
– Study-level feedback based on bottom-up investigator feasibility responses
– Sophisticated study-level simulation models
1. Projected based on KOL
feedback and previous
experience
2. Projected based on
bottom-up aggregation of
investigator responses
3. Projected based on
results from simulation
models
4. Don’t perform this
function
How does your company project enrollment?
Poll #5 Results
10%
38%
52%
0%
10%
20%
30%
40%
50%
60%
Projected based on KOLfeedback and previous
experience
Projected based on bottom-up aggregation of investigator
responses
Projected based on resultsfrom simulation models
17
How does your company project enrollment? (n=29)
Note: n=10 don’t perform this function.
Poll #6: Accuracy of Enrollment
Projections?
Audience Poll:
• How accurate is your initial enrollment
projection?
1. Extremely accurate
2. Somewhat accurate
3. Somewhat inaccurate
4. Extremely inaccurate
5. Don’t perform this function
18
Poll #6 Results
16% 53% 28% 3%
0% 20% 40% 60% 80% 100%
Response
Extremely accurate Somewhat accurate
Somewhat inaccurate Extremely inaccurate
19
How accurate is your initial enrollment projection? (n=32)
Note: n=8 don’t perform this function.
Moving Towards More Realistic
Projections
• Despite best efforts, we often hear reports of
dissatisfaction with initial projections
– Quality of data inputs?
• Mean (study average) vs. median (50% of sites)?
– Lack of historical comparator studies?
– Other, non-quantifiable factors?
• Use of an integrated, evidence based approach
to study planning, feasibility, and investigator
selection should help narrow the projection gap
20
Potential Benefits of Using an Integrated,
Evidence-based Approach
• Improved country selection
• More realistic recruitment projections
• Less time spent prioritizing/selecting investigators
• Reduced rescue sites potentially needed
• Decreased costs and time associated with start-up of rescue sites
• Fewer non-performing and under-performing sites
• Decreased IT time and costs of investigator and site data mastering
• Potential for tracking of investigators and sites across multiple systems (e.g., payments, investigator portals)
21
Moving Towards a Return on Investment
(ROI) Calculation (1)
• While the integrated, evidence based approach is appealing, most companies require an ROI prior to approving spend
• DrugDev contracted with an external group to develop an ROI model for our SiteCloud platform
– Use of a universal identifier known as the DrugDevGolden Number, to match and master records
– Toolset with an integrated view of information indexed to the same DrugDev Number
– Enablement of data sharing across companies
• The model is populated with:
– Company specific data on time/costs
– % benefit based on customer interviews
22
Moving Towards a Return on Investment
(ROI) Calculation (2)
• Model is rolling out to customers now, but early feedback suggests it is not possible to generate ROI for the “average” company, due to variation in:
– Current processes
– Cleanliness of CTMS data
– Number of data sources
– Toolset currently available
– Personnel type and costs
– Previous quality initiatives
– Participation in data sharing
• We would welcome the opportunity to share the variation in ROI resulting from an integrated, evidence based approach in a future SCOPE forum
23
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