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Data-Driven Strategies for Improved Site Activation and
Patient Enrollment Forecasting
Introduction
Cindy Venendaal, CCRA, MPH, PhD Senior Director, Project Management Clinipace Worldwide
Mark Shapiro, MA, MBA Vice President, Clinical Development Clinipace Worldwide
PRESENTERS
Step 1: Site Selection
Understand protocol and SOC for target patient population
Build robust site profile
Accelerate selection of sites that provide greatest chance of success
Use data used to develop start-up timeline, plan resources, and proactively identify potential budget variances
In Action: Data-Driven Site Selection
Step 2: Regulatory Docs & PSV
Precisely target sites with forecasting and feasibility data
Expedite completion of regulatory documents by electronic submissions
Save time with parallel pre-study site visits for select sites
In Action: Data-Driven Regulatory/Pre-Study
Step 3: Contracting and Budgeting
Time savings can be realized by using agreed upon standardized language from contract and budget templates
If EC/IRB approval is required before contract can be approved, site can review and provide feedback for contract while regulatory documents are with the EC/IRB
Contract can then be agreed upon, pending EC/IRB approval, modifying a serial process to a parallel process
In Action: Data-Driven Contracting/Budgeting
Step 4: Site Initiation Visit
Key activities include: – Collaborating to define a site-specific enrollment plan and target
– Build relationships among the principal investigator (PI), CRO and sponsor
Set date of site initiation visit determined based on expected date of EC/IRB approval
Invest time explaining the project and protocol to get full buy-in from site personnel – Improves enrollment
– Reduces time required for trial execution
Ongoing Activities
Update site activation and enrollment forecast models based on incoming real-time data
Strategic recommendations are possible if either enrollment or activations are not proceeding as planned – These can include:
• Change site profile
• Adjust the number or location of sites
• Adjust the protocol based on IRB/EC/MOH/Site feedback
Benefits of TEMPO
Polling Question
Forecasting Study Start-Up Timelines
Forecasting challenges – Forecasts should begin with historical data
– Past performance is no guarantee
– Uncertainty is inherent and asymmetric • Delays are power-law distributed
Considerations when forecasting study start-up timelines – Published forecasting models for clinical trials don’t take into account
nuances of sites operation
– Sites follow SOPs and complex processes are sometimes the result of outside accreditation (e.g., NCI CCC)
– Larger, more research-oriented sites tend to have more formal processes; smaller, less research-focused sites tend to have less formalized and more flexible processes for start-up
– Enrollment forecasting models developed to determine drug supply requirements (Poisson-Gamma)
Weekly Site Activation
For local IRBs, site activations are roughly Poisson distributed
For a 50-site study, the number of sites activated per week during start-up might look like this:
0%
5%
10%
15%
20%
25%
30%
0 1 2 3 4 5 6 7 8 9
Od
ds
Sites activated per week
92%
In Action: Effect of Site Structure on Timeline
Polling Question
Forecasting Enrollment
Enrollment is not linear – Enrollment is slow during start-up when few sites are activated
– Enrollment peaks only after most or all sites are active
Historic information should be the starting point
Feasibility data should be used cautiously for forecasting – Optimism bias
– Initial forecast ignores information about specific sites
Not all sites are the same – Site performance follows a Gamma or Power Law distribution
– Number of planned sites matters
Forecasts should be revised after data starts coming in
In Action: Forecasting Enrollment Rate
y = 0.862x-0.707 R² = 0.6638
0.00
0.50
1.00
1.50
2.00
2.50
1 10 100
Stu
dy
Enro
llmen
t R
ate
(Su
bje
cts
per
Sit
e p
er M
on
th)
Number of Study Sites
Phase 2, AML Treatment Study Enrollment Rates versus Number of Study Sites with 95% CI
Forecasting First Patient In
In the absence of recruitment advertising campaign before site activation, eligible subjects won’t be lined up waiting to enter trial
Expectations regarding duration between site activation and first subject enrolled should be tempered – If average sites are expected to enroll 1 subject per month, then the
average time from activation to FPI would be 15 days
Sites with fast activation may be highly motivated, but large sites tend to have more complex internal processes, and thus slower start-up
Questions?