Abstract Details
Activity Number:
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350
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #311233
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Title:
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Clinical Trial Enrollment Modeling with Random Staggered Site Start-Up Times
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Author(s):
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Steven Southwick*+ and Bradley Ferguson and Valerii Fedorov and Vladimir Anisimov
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Companies:
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Quintiles and Quintiles and Quintiles and Quintiles
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Keywords:
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enrollment ;
prediction ;
modeling ;
Poisson processes
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Abstract:
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With rising competition between pharmaceutical companies and increasingly strict drug regulations,running clinical trials efficiently and effectively is crucial for the drug development process. Enrolling subjects is a vital and costly part of that process and being able to accurately model enrollment is of utmost importance. Many current enrollment models are deterministic and fail to account for various sources of variability in the enrollment process. This could lead to missed deadlines and unmet enrollment goals. We propose a model in which subjects arrive at sites according to Poisson processes with site specific enrollment rates. We also model the site start up times (SSU) using a Uniform,Beta,or Gamma distribution. This allows for more realistic assumptions when planning a clinical trial. We include the option to set an enrollment start date which means that even if a site has started,it cannot enroll until the enrollment start date is met. This could be due to regulatory reasons or lack of medical supplies. One benefit of our approach is that all derivations have closed form analytical solutions and thus are fast and precise and do not rely on monte carlo approximations.
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Authors who are presenting talks have a * after their name.
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