Introduction:
The MSL Society conducted an online survey on “Enhancing KOL Engagement by Leveraging Data” between January 8 -28, 2021. The survey was conducted in conjunction with the January 28th webinar that Huma.ai sponsored and co-presented with Sanofi on “Personalizing KOL engagements by leveraging data”. This article summarizes the key findings and discusses the next steps for leveraging data to help MSLs be successful in their KOL engagements in this new era of digital.
Demographics:
Over 80% of respondents were from Pharma, with representation from medical devices and diagnostic companies. Over 50% of the MSLs were field-based with < 2 years of experience. The survey looked at the MSL field team, a combination of MSL field team plus managers as well as both US and Global. There were some interesting differences in the responses that will be discussed in this article.
Results:
Barriers to adopting new solutions that enable MSLs to personalize their engagements with KOLs
The results were quite interesting. > 30% MSL field team members did not know of any barriers to adopting new solutions whereas the MSL Managers and Directors cited budget constraints as the main reason preventing them from adopting new solutions. The data was similar between the US and Global. The results clearly highlight the need for management buy-in to bring in new solutions within MSL teams that will help them with personalizing their KOL engagements. We definitely see an opportunity for Huma.AI to be part of the solution for Medical Affairs teams to embrace digital transformation. We need to provide accurate metrics on how these new solutions will increase efficiencies, uncover new insights that can be leveraged for strategic planning across the organization and not just limited to MSL teams. Some of the features we see that will help reduce barriers are the need for an ease-of-use platform solution, explainable AI (so subject matter experts know how the answers are derived), and most importantly leveraging human intelligence through a feedback loop so the platform can continually learn from the users. Clearly, with Medical Affairs teams being subject matter experts, there is a need for deploying a human-centric AI approach to better understand patient experiences and gain insights into the behaviors of thought leaders and healthcare practitioners. Medical affairs teams generate a vast amount of data but are not able to effectively use these data to generate insights on who their stakeholders are and what do they need. Human-centric AI allows for the ability to obtain all the relevant data, analyze it quickly, surface actionable insights and drive them back into operational systems to affect events as they are still unfolding. The advantage is to make fast and better decisions and quickly act on insights gained from large amounts of medical data.
Another key feedback from the survey was the need for training on best practices on leveraging new AI-enabled technologies within Medical Affairs. Because this is relatively new, the community as a whole would benefit from training with Medical Affairs teams that have successfully deployed machine-learning-enabled tools within their organization. Some of the challenges we see are that adoption and deployment of these tools are still in progress, but we believe it is never too early to share best practices and successful use cases with the community so that everyone can benefit from lessons learned.
One of the key feedback from the Jan 28th webinar was that many MSLs are not leveraging their CRM for KOL engagement but instead view CRMs as a necessary tool to input their engagements for performance metrics. We see CRM as a vital tool to be leveraged for KOL engagement, particularly when it is connected with additional data sources (field notes either in CRM or other platforms + public data sources + KOL mapping tools). Huma.AI is planning to organize a workshop on best practices to leverage CRM data based on the feedback. We are committed to working collaboratively to empower MSL teams to leverage data for their KOL engagements.
Primary barriers to incorporating social media as part of your Key Opinion Leader or Digital Opinion Leader engagement
MSLs are intrigued about using social media as part of their KOL or DOL engagement but are clear they need additional guidance on acceptable use of social media. Again, this is a relatively new data source, and we believe there is a huge opportunity for MSL organizations to provide guidance on best practices in terms of white papers to help companies navigate the use of social media. It is clear that KOLs are adopting social media to share their opinions on results presented at scientific congresses as well as feedback on the use of drugs etc. especially in this age when engagements are virtually all-remote. Being able to uncover these opinions would be important as part of the MSL KOL engagement strategy. Part of the current challenge with leveraging social media data is uncovering the few critical and useful information against the background of noisy data – this is why machine-learning enabled solutions would be ideal for this purpose. Having training sessions for best practices as well as successful use cases would be important to allay some of the hesitance to leverage social media.
Primary Methods for expanding KOL network in the absence of in-person scientific meetings such as Medical Conferences and Symposia
The results were slightly different between the USA and Global data. Global MSL teams had a slight preference for educational webinars and virtual scientific meetings versus using PubMed and reaching out directly via direct email communications. US MSL teams leveraged both resources equally. Part of the reason could be related to preference for Global teams for initial introductions via scientific meetings before following-up email versus sending out cold -mails.
Effective methods that company utilize to support MSL/KOL engagement
The survey results suggest that companies are using several methods to support MSLs in their KOL engagement which includes education and training on digital tools, digital content generation, company-sponsored webinars, and company-sponsored Ad Boards. Clearly, companies need to expand training programs to help MSL teams adopt digital tools for KOL engagements though it is great to see that multiple resources are being leveraged to support MSL teams.
During virtual KOL engagements, what are the MOST important resources in generating targeted discussions?
The survey results highlighted the top 3 resources that MSLs consider as most important: 1. Leveraging internal MSL teams and resources 2. On-demand and customizable content generation 3. Clinical trial data from multiple data sources. CRMs would be an ideal tool for MSLs to leverage internal data resources for engaging KOLs. The feedback we received from our recent webinar is that MSL teams can definitely improve on using their CRMs effectively to connect with internal MSL team resources with additional training.
Figure 1: During virtual KOL engagements, what are the MOST important resources in generating targeted discussions? US data from MSL + Managers
One of the interesting resources that MSLs viewed as important was being able to generate on-demand and customizable content. We view this as in line with targeted messaging. Many MSL teams are used to power-point presentations that are not easily customizable. What if machine-learning enabled tools enabled MSL teams to generate custom power-points prior to KOL engagements? There are new solutions available that generate a customizable power-point that captures a story around the topic that an MSL would like to engage a KOL with. Targeted messaging is so critical in the virtual engagement era where KOLs value MSLs that know exactly the information they need at the right time. Being able to customize MSL messaging is critical for successfully targeted discussions.
From our previous survey results, we were aware of MSL teams’ preference for using clinical trial information to help with their KOL engagement. The current publicly available tools such as PubMed and Clinical trials.gov are rich with data but they require complex filtering and are not built to gain business intelligence on KOLs easily. What if we could combine several data sources so that we can generate personalized KOL dashboards that include their publications, participation in clinical trials, social media posts plus internal CRM data?
Conclusion:
Survey results suggest that MSLs are open to embracing digital transformation and companies are starting to provide training for them. However, in order to scale deployment and adoption, we need to have wider management buy-in, and budget invested to deploy new solutions such as machine-learning enabled technologies to empower MSLs with data they can leverage when engaging with KOLs. We need to have a much better forum for discussing challenges and sharing success stories. Investing in human-centric AI approaches that can close the last mile and connect CRM data with insights from free-text notes as well as connect disparate data silos such as private CRM plus public data sources such as PubMed combined with an easy-to-use interface will help reduce the barrier to adoption of these new technologies and enable organizations to target KOL engagement driven by data.
Authors:
Dr. Sabita Sankar
Dr. Sankar obtained her PhD from the Institute of Molecular and Cell Biology in Singapore. She completed her postdoctoral fellowships at Yale and Duke Universities. She then spent the next several years at Celgene as Group Leader in the Oncology Research Department and co-led the project team that developed CC-223 and CC-115, mTOR, and mTOR/DNA-PK inhibitors. Prior to joining Huma AI, she spent several years in both scientific affairs and business development roles at several diagnostic companies including MolecularMD, Biodesix, and Ambry Genetics, providing genomic and proteomic solutions to Pharma clients. Dr. Sankar’s expertise includes a unique mix of both drug discovery and diagnostic perspectives.
Dr. Lana Feng
Dr. Lana Feng is the co-founder and CEO of Huma.AI. She came from Novartis Oncology Business Unit where she established international partnerships for their late-stage targeted therapy programs. Dr. Feng joined Novartis through its acquisition of Genoptix. She built the BioPharma division at Genoptix, where she grew the business by forging alliances with pharmaceutical companies and providing biomarker and companion diagnostics development for targeted therapies. Prior to Genoptix, Dr. Feng held key positions at GeneOhm Sciences and Nanogen. Dr. Feng obtained her Ph.D. in Developmental Biology from Indiana University and did her post-doctoral training at UC, San Diego.
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