Identifying Rising Stars: CAR-T use case

Identifying Rising Stars: CAR-T use case

As most of you in the life sciences industry know, important stakeholders are increasingly turning to opinion leaders in their decision making. A fact well recognized by most companies, which has intensified the competition to work with influential opinion leaders in virtually all therapeutic areas. Therefore, it is now more important than ever to establish a close relationship with the opinion leaders of tomorrow, rising stars, as early as possible. But, identifying which medical experts that are on a trajectory towards an influential position – before your competitors – is a tremendously difficult task. Historically this has been more of an art than an data-driven objective and analytical process. Until today. In this post, we want to show you how to best utilize the capabilities that were recently introduced to Monocl EGO and how they help you apply a data-driven approach to your identification and characterization of rising stars.

Rising Star within CAR-T: real-life Use Case

Background

Company A was looking to establish a Scientific Advisory Board to serve as key strategic resources and provide scientific expertise and guidance for its global Phase 2 trial for CAR-T Cell Immunotherapy for Glioblastoma. The company was looking to bring onboard rising stars with a strong presence and influence in the scientific community. The desired individuals were to be located in the US and have experience in the combination of CAR-T and the target cd19.

Approach

A commonly applied approach in this scenario is to execute an initial screening and ranking of the US landscape of medical expert. Such a ranking is typically based on scientific influence and experience (research, speaking engagements, grant payments, clinical experience, news mentioning, clinical trial involvement, corporate engagements and more) within a desired area of interest, in this case CAR-T and cd19. However, there is an inherent flaw in this approach as it up-votes senior professionals. In addition, it tells us little about how much of the relevant activities that have been executed in recent years. Although CAR-T is a relatively young field, it is evolving at a swift pace. This makes it increasingly important to capture the people that have been performing relevant research lately and is currently pushing the envelope in the space, not 7 years ago. Now, let’s take a look at how to the capabilities that were recently introduced to Monocl EGO can help power the identification process.

Introducing a new approach: Look for recent relevance

The scientific community is making big leaps forward within the CAR-T space. This makes it increasingly important to identify experts that are currently performing relevant research related CAR-T and are a part of driving the change in the field. In addition, Company A wants to identify that experts that have experience in working with the target CD19. To ensure this, we apply our new proprietary ranking algorithm to all the activities that have been executed in the space over the last two years.

Below is a list of two cohorts of relevance ranked CAR-T/CD19, US experts. The left column represents experts ranked by their relevance score over the last 10 years in the space. The right are relevance ranked experts after we apply the cut-off for recent relevance. It now features a new more diverse set of experts, although the shortlist still mainly features senior experts.

Remember, the core of this project is to identify and build a relationship with young individuals that are on a trajectory towards an influential position. To ensure that all fit this bill, we now insert a second requirement – career start date.

Introducing a new approach: Filter for young professionals 

As a next step, we utilize the newly introduced filter for career start date. What this effectively does is ensure that we are only presented with experts that produced their first research paper after a preferred date. For this specific project, we are only interested in individuals that launched their research career after 2004.

This completely alters the results, as presented in the table below. This final shortlist now features young experts that meet Company A’s requirement on scientific influence, experience in the areas of interest, career phase and trending influence. All generated in a matter of minutes, enabled by machine learning and Big Data.

With this, we want to showcase how a data-driven approach can drive better decision making that. When applied in the right way, this approach to rising star identification and engagement gives you the possibility to build a strong structural, long-term competitive advantage.

Lastly, join us for our webinar on April 25th, 2018 and learn more about:

  • What characterizes a Rising Star?
  • Which Rising Stars are suitable broadcasters of your message?
  • Novel approaches to drive stakeholder identification, prioritization, and engagement.

Simply follow this link, register for the event and join the session by using a Mac, PC or a mobile device – we look forward to seeing you!

Felix Jansson
Business Development and Marketing Manager