Please note that the free NISS-Merck-HPSS Virtual Meet-Up Real World Data and its Applications in the Pharmaceutical Industry has been rescheduled to October 4, 2018, 11 am -12:15 pm.
The link from the original post will work to connect on Oct 4th .
Attendee_Link_NISS_Merck_ASA_HPSS_04-Oct-2018
Password: NISS2018
The agenda for the meet-up is as follows:
- Welcome (Dan Holder, Merck, and Kelly Zou, Pfizer/Chair ASA-HPSS)
- Real-World Evidence? Then Disrupt Their Outdated Regulatory Infrastructure* (Anirban Basu, Univ. Washington)
- Real World Evidence in Pharma: Best Practices and Innovations (Douglas Faries, Eli Lily)
- Panel Discussion moderated by Kelly Zou. Panelists are Anirban Basu and Douglas Faries.
Previous NISS-Merck Meet-Ups can be viewed at the links below.
· NISS-Merck Meet-Up Apr 2018 Machine Learning in Pharma
· NISS-Merck Meet-Up Jan 2018 ICH Estimands and Sensitivity Analysis
· NISS-Merck Meet-Up Sep 2017 Multiple Outcomes
Abstract:
The National Institute of Statistical Science (NISS), Merck, together with the ASA – Health Policy Statistics Section are sponsoring a Virtual Meet-Up on 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.