Who's Keeping Score? A Quantitative Approach to Trial Feasibility

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With most trials failing to meet enrollment timelines, current approaches for feasibility fall short of identifying and minimizing risk. Sponsors must arm themselves with the right tools to own this analysis throughout the trial lifecycle. We will discuss a quantitative approach that operationalizes feasibility score tracking. Luke Stewart used this presentation at Clinical Trial Innovation Summit in Boston on April 25, 2017.

Données & analyses

1Copyright © 2017, Saama Technologies
Who’s Keeping Score?
A Quantitative Approach to Trial Feasibility
Luke Stewart
Director, Product Management
April 25, 2017

2Copyright © 2017, Saama Technologies
Trial Feasibility and Site Selection: A Losing Battle…?

3Copyright © 2017, Saama Technologies
Who’s Keeping Score?

4Copyright © 2017, Saama Technologies
Close Loop on Actual Performance vs Projected Scoring
Attributes of Approach
• Sponsor-driven
• Systematic scoring
• Learning over time
Early Protocol Feasibility Site Feasibility Study Startup Study Execution
0 months-18 months -6 months 12+ months
Scoring
i.e., Protocol Amendmentsi.e., Site Surveys i.e., Site Screening Rate

5Copyright © 2017, Saama Technologies
Predictive Example
PREDICTING PATIENT
ENROLLMENT USING MACHINE
LEARNING AND ARTIFICIAL
INTELIGENCE:
• Previous participation in clinical
trials
• Disease / Therapeutic area
• Proximity to site
• Study complexity
• Demographic information
• Socio-economic status
PREDICTING SITE PERFORMANCE
USING MACHINE LEARNING AND
ARTIFICIAL INTELIGENCE:
• Previous terminated studies at the site
• Screen failure rate
• Study complexity
• Number of patients matching
inclusion/exclusion criteria within close
proximity (25 miles) of site
• Socioeconomic status of eligible
patients in close proximity of site
• Disease / TA
• Staffing and facility information

6Copyright © 2017, Saama Technologies
Call to Action
Visit us at Booth 16
– Share your thoughts and
stories
– See demo
Start Keeping Score

Who's Keeping Score? A Quantitative Approach to Trial Feasibility

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