Optimizing Global Clinical Trial Enrollment: A Case Study That Can Save You Millions
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Why? Drug and biologic makers are using simplistic predictions that don’t take into account such real-life variables as disease prevalence in a particular country or the possibility that patients will not enroll in a trial.
But there is an answer.
VOI Consulting’s Todd Clark recently forecasted patient enrollment for a trial of a cancer treatment in 23 countries for a top-10 pharmaceutical firm. The results demonstrated that the company could meet its recruitment goals and save $4 million at the same time by eliminating seven countries and 24 sites from its original plan.
How did he do this? By using what is called Monte Carlo Analysis — a mainstay of predicting results in such highly variable situations. Todd ran 10,000 computer simulations of patient enrollment for each country that took into account all the known variables and produced reliable estimates of where the sponsor would and wouldn’t meet its enrollment goals.
And, now, he’ll show you how …
In this 90-minute Encore presentation, VOI Consulting President Todd Clark will show attendees the difference between standard models and the Monte Carlo Analysis and where the dangerous spots in the data are. In addition, you’ll watch as he runs a real-time demonstration of 10,000 enrollment simulations and shows how the results influenced the sponsor’s initial assumptions regarding the trial’s scope, depth and cost.
Sign up your entire team to listen in and discover:
- The four key steps in constructing the enrollment model
- The few variables sponsors can control and the many more they cannot
- The inherent flaws in standard analyses and how they negatively affect a trial
- The benefits of using Monte Carlo Analysis in predicting enrollment
- An online, real-time demonstration of running 10,000 enrollment simulations
- How the resulting predictions were used to advise the sponsor which countries to target and which ones to avoid, cutting eight percent of the trial’s budget.