Empowering Clinical and Medical Affairs from Pre-Clinical Through Launch

Sarah (00:00):
It’s just about 11:00 AM Eastern Time so I think we can go ahead and get started. I’m Sarah, I’m from the Definitive Healthcare team. Thank you so much for joining us today for the first installment in our webinar series, Applications of Real World Data from Drug Development to Launch. So for this series we’ll be hosting a 30 minute webinar every other Tuesday at 11:00 AM Eastern Time starting today and running through June 8th. So I’m excited to introduce today’s session, Empowering Clinical and Medical Affairs from Preclinical through Launch and our presenter Robert Groebel.

(00:41):
So a few housekeeping items before we get started. As time permits, we will take a few audience questions at the end, so feel free to submit your questions throughout Robert’s talk. And additionally, all registrants will receive the recording of this session. So a bit more about Robert. Robert serves as the vice president of Global Medical Strategy at Monocl. With nearly 25 years in the healthcare arena and diverse experience in commercial and medical organizations internationally, Robert brings a skill set and perspective that is rare among pharmaceutical professionals. His expertise includes both domestic and international sales and product marketing, and deep experience in medical affairs, strategic operations, administration and staffing. Welcome, Robert.

Robert Groebel III (01:32):
Thanks, Sarah. Thanks very much for having me and thanks everyone for joining us today. This is a really exciting topic to be able to present, especially in the context of medical affairs and how they can further leverage real world evidence. And so as part of our agenda today, we’re going to talk about different data elements that you may want to consider as part of your insight strategy and then looking at how we can apply this data specifically to the medical affairs space, but also in a more market focused way. We’ll look at it as it relates to the development process and then a few novel applications of real world evidence. At the end, I’m hoping to save a little time for questions and answers, so we’ll be monitoring the chat to make sure that we get to everything that you’re looking to understand. So as we move forward, to kind of set the stage here, I think it’s important for us to recognize that we’ve had such an increase in the number of rare disease treatments that are in development today.

(02:35):
And because of this, the dynamic that we’re seeing is a real need for collaboration, a stronger collaboration across medical and commercial teams. Using data is important because that really helps to build the foundation for messaging, communication, around these compounds that are coming to market. While medical and commercial have always really been connected and part of the commercialization process, we think that the use of this real world data can really bridge the scientific evidence that’s coming out of medical and the value statements that are really being driven by your commercial team. So we’ll look at that a little further in the presentation. But I think it’s important to take a step back and really think about why it is we want to use real world evidence from a medical perspective. At the heart of what medical affairs is responsible for, it’s really insight generation, bringing information back into the organization to inform, knowledge, future understanding, choices as it relates to one activity versus another.

(03:45):
But I think when we consider insights, we really have to look at what it means to generate an insight. And so, there are a number of components that will talk about today. You have your data, which is really just a collection of facts, a series of facts that are provided to you. But once we’ve been able to process and assess that data, it turns into information and it’s now starting to become relevant. It’s starting to become something that we can take action on. Once we’ve been able to process the data, we’re looking for patterns in the data and that’s going to give us context to what that information is, and that’s really about the knowledge we’re able to generate from it. And then once we understand that knowledge we can look at the underlying nature of that to see what it’s telling us to do… .