Find motivated, clinically matched cancer patients for your clinical trial.
Learn about the proven approach that delivers 40% more qualified cancer patients, 20% faster than traditional recruitment methods.
It's Time to Rethink Cancer Trial Enrollment.
- How artificial intelligence (AI) can quickly deliver highly-motivated and clinically qualified cancer patients to enroll in your clinical trial.
- How insight captured during predictive planning can successfully mitigate risk and identify enrollment barriers based on multiple study design scenarios, all prior to study launch.
Wednesday, June 2, 2021 12:30pm ET/9:30am PT
Anthony Gulotta, Senior Director,
Sales at TrialJectory
PRESENTER: Anthony Gulotta
Anthony has extensive experience bringing to market & scaling AI-powered recruitment solutions. As the Director of Sales, Anthony monitors the oncology drug development landscape to strategically identify opportunities where Trialjectory can significantly improve cancer patient outcomes. His clinical industry experience coupled with his emerging technology background make him one of the leading experts in AI-based patient recruitment. Please join Anthony as he walks us through a comprehensive platform demo of TrialJectory. You will also learn how this award-winning and patented AI-powered patient matching tool offers significant ROI including reduced costs and study enrollment timelines.
© 2021 by TrialJectory
A recent report from Tufts University named oncology the largest and fastest growing segment in drug development. The same report analyzed the complexities facing trial delivery, including patient enrollment.
A growing cancer study pipeline will also increase the demand for study participants. Success getting life-saving drugs to market will require scalable recruitment offerings, that deliver with precision and speed without sacrificing a patient-centered experience.
This webinar will take a closer look at how the right approach to cancer patient enrollment can drive operational efficiencies and significant ROI. Take-aways include: