Oncology clinical trial complexity remains higher than any other therapeutic area, with more endpoints and inclusion/exclusion criteria. This contributes to high site and patient burden and nearly 30% of patients dropping out before study completion. Clinical trials must become more patient-centric, and the COVID-19 pandemic has only further underscored the need to do so.

This mini-webinar will focus on how advanced real-world data and innovative AI technologies work together to reduce patient burden and optimize study design and success. This webinar will feature our recently launched Digital Trial Optimization SaaS solution, which uses powerful oncology real-world data combined with AI-enabled technologies. This is part of our series of short webinar practicums that illustrate how real-world data and technology solutions in oncology can support novel study designs.

Oncology Clinical Study Optimization: Burden Analysis to Reduce Complexity

Mar 23, 202110:00am EDT20 minutes

What you will learn:

  • Rapid iteration of alternative study designs with reduced complexity
  • Impact of different I/E criteria and value-ranges on recruitment potential and likelihood of patient completion of the study
  • Patient burden analysis for broader provider participation, patient participation, and patient retention
  • How AI and ML drive real-time optimizations and analyses to improve study design

Who should attend:

  • Clinical researchers focused on oncology RWD and clinical trial design and feasibility

  • Clinical trial feasibility analysts looking to expand traditional site footprints and increase patient diversity in oncology trials

  • R&D leaders looking for advanced RWE methodologies and technologies

  • RWE Center of Excellence leaders focused on driving enterprise efficiencies at scale

About the Speaker

Jamie Powers, DrPH, has over 15 years experience at the intersection of real-world data, predictive analytics, and technology solutions for clinical trials. He has worked as a data scientist and consultant in life sciences. In his previous roles with Cambridge Semantics, PerkinElmer, SAS, and IQVIA, Jamie brought data science, AI and machine learning, and SaaS technologies to improve outcomes. At ConcertAI, Jamie brings his comprehensive technical and strategic acumen to also improve outcome and drive innovation for customers. His passion for innovation in data science and oncology research helps him deliver valuable data and technology insights. Jamie has a DrPH in biostatistics and epidemiology from the University of North Carolina at Chapel Hill.