NISS-Merck Virtual Meet-up: "Real World Data and its Applications in the Pharmaceutical Industry"

Randomized controlled trials (RCTs) have long been the gold standard for providing evidence to support the safety and efficacy of a new drug, vaccine, or biologic. Most pre-marketing product development programs are divided into three phases (phase 1, 2 and 3) with phase 3 consisting of large RCTs to confirm the safety and efficacy of a new molecular entity. However, complete reliance on RCTs comes at a price, as they are often not only costly but limited to very specific clinical circumstances. Patients in the RCTs are not necessarily representative of the target patients in the real world setting. On the other hand, real world data (RWD), data collected from a more heterogeneous population and often in an observational manner, do not provide the same assurances against biases, but have the potential to provide rich, diverse, and important information on compound performance in more realistic clinical settings. Unfortunately, data collection in the real world setting may be less rigorous and difficult to verify. This meet-up will focus on the roles that RWD can play in compound development, registration, and post approval.  This is an area of highly active research with ongoing debates. Some of the emerging ideas, if adopted, could dramatically change the status quo.

The format used for these meet-ups is two 20 minute talks followed by a panel discussion in which a moderator gives some of their own perspective and then asks questions of the speakers, some of their own and some of the ones submitted by the audience via the chat tool.

This is the fourth NISS-Merck Meet-up, the third one this year!

Watch the recording of the NISS-Merck Virtual Meet-up, October 4, 2018

Links to Presentation Slides below.

Previous Merck/NISS Meetups

The first virtual NISS-Merck meet-up was a conversation concerning the FDA draft guidance on “Multiple Endpoints in Clinical Trials” took place in September, 2017. The second meetup took place in January and focused on "ICH E9(R1): Estimands and Sensitivity Analysis in Clinical Trials". In April, "Applications of Machine Learning in the Pharmaceutical Industry" was the topic.  Follow the links if you would like to review the recordings from each of these sessions.