Data-Driven Strategies for Improved Site Activation and Patient Enrollment Forecasting

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Rosemary Robinson
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1 Data-Driven Strategies for Improved Site Activation and Patient Enrollment Forecasting

2 Introduction PRESENTERS Mark Shapiro, MA, MBA Vice President, Clinical Development Clinipace Worldwide Cindy Venendaal, CCRA, MPH, PhD Senior Director, Project Management Clinipace Worldwide

3 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

4 In Action: Data-Driven Site Selection

5 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

6 In Action: Data-Driven Regulatory/Pre-Study

7 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

8 In Action: Data-Driven Contracting/Budgeting

9 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 buyin from site personnel Improves enrollment Reduces time required for trial execution

10 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

11 Benefits of TEMPO

12 Polling Question

13 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)

14 Odds 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: 30% 25% 92% 20% 15% 10% 5% 0% Sites activated per week

15 In Action: Effect of Site Structure on Timeline

16 Polling Question

17 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

18 Study Enrollment Rate (Subjects per Site per Month) In Action: Forecasting Enrollment Rate Phase 2, AML Treatment Study Enrollment Rates versus Number of Study Sites with 95% CI y = 0.862x R² = Number of Study Sites

19 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

20 Questions?

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