Jennifer Rider, ScD, MPH, is an epidemiologist with nearly 20 years in oncology research. Prior to joining the company in 2020, she was an Assistant Professor in the Department of Epidemiology at the Boston University School of Public Health, where she taught graduate coursework in cancer epidemiology and epidemiologic methods. Jennifer’s research focused primarily on prostate cancer risk factors and tumor biomarkers, and resulted in more than 90 peer-reviewed publications. In 2013, she was the recipient of a Prostate Cancer Foundation Young Investigator Award. At ConcertAI, Jennifer uses her strong methodological background and deep knowledge of genitourinary cancers to lead HEOR and ECA studies for life science customers. Jennifer earned a doctorate in epidemiology from the Department of Epidemiology at the Harvard T.H. Chan School of Public Health, and holds an MPH from the University of Massachusetts-Amherst.
Factoring race and ethnicity into clinical and HEOR studies to better understand disparities in cancer outcomes presents a variety of challenges to study design and conceptualization. Please join our short webinar on an epidemiological approach to using real-world data and AI optimization and prediction technologies to rapidly analyze patient clinical and demographic characteristics, biomarkers, treatment and outcomes – to aid the further investigation of health disparities.
We will expand on the epidemiologic concept of mediation and how real-world data can help us identify factors on the pathway between race/ethnicity and treatment outcomes that could be targeted with interventions to reduce disparities.
This webinar will also feature our recently launched Digital Trial Optimization SaaS solution, which uses powerful oncology real-world data combined with AI-enabled technologies. This is the third in a series of short webinar practicums that will illustrate how real-world data and technology solutions in oncology can support novel study designs.
What you will learn:
- The role of real-world data in mediation analysis
- Accelerating outcomes analyses for health disparities studies
- Identifying key factors, from biomarkers to other related to healthcare access, using AI-enabled RWD and SaaS applications
- Selecting which intermediates to target to produce the largest benefits in outcomes
Who should attend:
- The role of real-world data in mediation analysis
- Accelerating outcomes analyses for health disparities studies
- Identifying key factors, from biomarkers to other related to healthcare access, using AI-enabled RWD and SaaS applications
- Selecting which intermediates to target to produce the largest benefits in outcomes