Advice from the Expert - Unlocking Field Medical’s Power with AI

The Sorcero team sat down with medical experts Ralph Rewers (Gilead Sciences), Patrina Pellet, PhD (Medical Affairs Value) and Richard Swank, PhD (MSLGrowth.com and ex-Amgen) to get their take on how AI can empower MSL’s as their function continues to evolve. Throughout the conversations, three main trends emerged:

1. MSLs are expected to excel at both virtual and in-person engagements, connecting with a wider range of stakeholders that include both top KOLs and local-level clinicians.
   
   
2. AI can empower MSLs in two main ways: first, by accelerating the capture, synthesis, and sharing of insights, and secondly, by improving personalized HCP engagement - especially through the use of sentiment analysis
   
   
3. For AI to be successful in Medical Affairs, it requires dedicated resourcing and focused training to coach teams on how to best use the technology. Because AI budget and strategy typically sits outside of Medical Affairs, obtaining the necessary alignment and resources can be challenging.

Read on to hear the group’s expert advice on the changing role of the MSL, and how AI is powering two core MSL activities: insights generation and HCP engagement.

Part 1: A Shifting Landscape for MSLs

MSLs are operating in a hybrid world – which means they’re expected to excel at both in-person and virtual HCP engagement. As their role has changed, so too must the technologies, processes, and strategies that will help them excel.

• Ralph: While MSLs are still responsible for exchanging scientific information with internal teams and educating HCPs, how MSLs do their job has rapidly – and significantly – changed due to COVID. What was once a highly in-person job is now a hybrid mix of in-person and virtual, completely transforming the way MSLs engage with stakeholders. Technology has become central to MSL’s role, enabling them to expand their reach to a wider range of HCPs – such as community physicians – in addition to top KOLs. 
• Patrina: To add to this, since COVID, MSLs are expected to interact with a much wider range of stakeholders, and have the diverse skill set to match. With the rise in digital, MSLs must be as effective in person and they are virtually, and know how to use digital tools like AI to engage with HCPs and internal stakeholders.
• Rich: In this new environment, MSLs shouldn’t just curate a list of top KOLs - they need a sharper pulse on local HCPs in their region to determine how to improve care in the clinic. And while MSLs have proven their value and no longer have to defend their place in an organization, this shifting dynamic brings new responsibility and ownership. MSLs are now being asked to measure their impact more thoroughly.
  
  

Given this new environment, have MSLs embraced any type of standardization or training to help streamline and accelerate the insights generation process? 

• Rich: Many teams think they’ve embraced standardization. But in my experience, most still operate reactively, focusing their energy on responding to urgent leadership requests. MSLs should proactively engage with other functions to identify the field-level insights these groups need to inform medical strategy and solve potential challenges down the road. To tackle these problems as early as possible, the best companies are relying heavily on technology. Some use third-party software with CRM systems, while others employ AI to assimilate data and streamline insights gathering. Regardless of the approach, companies must define a thorough process that leverages technology to capture insights and share information with colleagues across departments.
  
  
• Patrina: The same is true with training - while companies may vary in how they train MSLs, they must have an overarching medical strategy that informs training and helps determine MSL’s priorities. In the past, many companies have relied on large workshop-style training; however, in this new hybrid environment teams should consider a coaching model to provide MSL’s with one-on-one guidance on effective HCP conversations that generate insights.
  
  
• Rich: To add to this, even before conducting any training, organizations must clarify and codify the definition of “insight”. Often, teams will mistake surface-level observations for insights – capturing just what an HCP said, but not the “why” or motivation behind this statement. For something to be considered an insight, teams must determine how to share this information and make it actionable. Without these elements, it’s not a true insight.
  
  

How well do you think MSLs uncover the “why” behind their observations, and link these insights back to medical strategy? Do MSLs have the right guidance from leadership to achieve this?

• Patrina: MSLs typically do a great job identifying insights and sharing takeaways from organized, in-person engagements like Scientific Congresses. However, field teams often struggle to map these insights back to the larger medical strategy. This is because many organizations don’t do a great job communicating medical strategy to their MSLs; they typically only share this vision once per year. In fact, in a recent Linkedin poll that we ran, we found that many MSLs lack sufficient training and understanding of their medical strategy. Leadership teams need to communicate medical strategy more frequently, and help guide MSLs towards the most valuable insights.
  
  
• Ralph: To add to this, MSLs should have a very close relationship with in-house strategy teams. These teams can help the field understand the most important information to focus on, and guide how they can uncover the “why” in their insights. And like Patrina said, communicating strategy shouldn’t be a one-and-done activity; teams must continuously reinforce these goals with their MSLs and ensure insights ladder up to the company’s strategic initiatives.

Part 2: Harnessing AI to power Insights Generation for MSLs

AI has shown promise to accelerate how MSLs gather, synthesize, and disseminate high-quality insights. But in some cases, companies struggle to adopt new AI solutions due to issues with budget and strategic alignment.

• Rich: The core challenge is that even when companies use AI, it’s rarely owned by medical affairs. This technology typically resides within commercial or enterprise teams, and as a result, the way the tools are funded, configured, and utilized doesn’t always align with the specific needs of MSLs. Medical affairs simply lacks sufficient in-house personnel with the necessary skill sets to directly tackle this type of work. Often, we’re instead forced to piggyback off of the technology strategies of other groups, rather than having tailored solutions that meet MSL’s needs.
  
  

• Patrina: To add to this, many medical affairs teams don’t fully understand the immense power of AI. Widespread education is crucial for securing buy-in and ensuring teams use this new technology correctly. Organizations must educate MSLs not only on how to use the technology but also on the full array of use cases it supports.

• Patrina: There are numerous ways that AI can help medical affairs teams generate insights. One big benefit is aggregating data from many sources, especially places like slides and PDFs that are difficult to extract data from. AI can also help coach MSLs on how to gather compliant insights that properly capture the “why” behind an HCP’s observation. Lastly, AI is very useful for quickly finding the most important insights and summarizing content so teams can easily digest key points across a body of data.
  
  

• Ralph: To help illustrate this, I worked at a company where we averaged about 140,000 global insights per year. By leveraging AI, we were able to ask very specific questions and quickly pull in relevant insights from various geographies to effectively answer those questions. This type of summarization is difficult and time-consuming without AI. One important thing to note about AI is its ability to remove human bias from the equation. AI helps us collate information rapidly, so we can gain a more comprehensive understanding of the topic at hand. Not only does this save time, but it also ensures that the insights we gather are objective and unbiased.

Part 3: Leveraging AI to power field engagement and personalization 

In addition to insights generation, AI has a great potential to enhance how MSLs engage with HCPs and KOLs. While AI can improve day-to-day interactions through enabling more personalized engagement, it can also help gauge evolving sentiment and power HCP’s scientific education journeys.

• Ralph: In the past, MSLs focused primarily on KOLs. Now, we must shift our efforts to also engage with community HCPs, especially in areas with high patient need. For example, in regions with elevated cancer rates, like the tobacco belt, MSLs can make a real difference in patient outcomes by dedicating more time and resources to supporting local doctors. When interacting with these community HCPs, our goal should be to quickly provide them with concise, actionable answers to their questions. They don’t have time to listen to long theoretical answers - they need practical information that can help them improve patient treatments. AI can help provide these concise, high-quality answers in an instant.
  
  

• Rich: I’ve seen a small number of companies successfully use AI to guide HCP engagement. They’re doing a great job using disparate data sources to tee up a suggested discussion topic or flag which physicians to engage with. With this AI-driven approach, these MSLs can expand their reach beyond their usual contacts and more easily connect with high-potential HCPs or important local physicians - something that many companies struggle to do. These AI suggestions give MSLs clarity on the right next steps to take, and which actions will best support the HCP’s overall educational journey.
  
  

• Ralph: To add to Rich’s point, most people understand the scientific education journey - that is, moving from having no awareness of the science, to having some awareness, to actually putting this information into practice. At the end of the day, the goal of medical affairs is to shorten the time between when the science is released to when HCPs use this science in the clinic. With this in mind, the bigger challenge becomes how to segment and engage with the right personas at the right time to accelerate this process. To achieve this, the most important area to focus on is sentiment - understanding how we change sentiment from a negative view of the science to a positive one. One of the best ways we can do this is to use technology like AI to objectively assess sentiment to understand and HCP’s true opinion.
  
  

• Patrina: Yes, sentiment is crucial. Medical Affairs teams are investing more resources and thought into evaluating the success of scientific engagement, but we still haven’t cracked the code. That being said, there are many unique and innovative ways we can measure impact with AI. As Ralph mentioned, leveraging AI to analyze sentiment and track changes over time can provide valuable insights that can complement qualitative feedback MSLs gather in the field. Another great way to use AI is to measure the strength of relationships with HCPs. Of course, this all hinges on having data available, which has numerous applications to assess the impact of HCP engagement efforts.

To learn more about the changing landscape for MSLs and how AI can help this evolving function, view the webinar. For insights on how medical affairs teams and life sciences organizations can take a responsible approach to AI, check out our recent whitepaper.