PSI Webinar
Personalised Medicine: Statistics for Companion Diagnostics
Date for Webinar: Thursday 4th May. 2-3.30pm UK time
Personalised medicines - which are designed to treat particular groups of patients - are becoming increasingly prominent. In order to identify patients suitable for treatment a companion diagnostic assay is often needed. The Personalized Medicines Coalition (PMC) recently published an article stating that 25% of NME approved by FDA in 2016 included a companion diagnostic.
This webinar will introduce and examine some of the considerations required for statisticians working in the field of companion diagnostics and will include information from an FDA (CDRH) speaker and perspectives/ case-studies from representatives from both a pharmaceutical company and a diagnostic company.
CLICK HERE TO VIEW THE FLYER
Speakers:
Meijuan Li, CDRH
Peter Cooper, Qiagen
Rachel Hodge, AstraZeneca
Abstracts:
Meijuan Li (CDRH)
Applications of personalized medicine are becoming increasingly prominent. A companion diagnostic assay (CDx) is often desired for patient enrollment in device-drug pivotal clinical trial(s) so that FDA can ensure that appropriate clinical and analytical validation studies are planned and carried out for CDx. However, such a requirement may be difficult or impractical to accomplish. A clinical trial assay (CTA) instead of CDx may be used for patient enrollment in drug-device pivotal clinical trial(s). A supplemental agreement study of CDx and CTA will be required to bridge the clinical results from CTA to CDx. In this webinar, we will discuss statistical challenges in study design and data analysis for bridging study. Particularly, we aimed to provide statistical methods on how to estimate the drug efficacy in CDx intended use population using results from bridging study and CTA-drug pivotal clinical trial.
Peter Cooper (Qiagen)
Perspective from Diagnostic Company
Rachel Hodge (Astrazeneca)
Perspective/Case-study from Pharmaceutical Company
To access the recording, please visit the Video-on-Demand Library.
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