Out of Time? 2 AI Approaches to Prepare for KOL Meetings Fast

You have an important meeting with a top KOL in your territory. It completely snuck up on you. Your schedule has been packed with conferences, back-to-back meetings, and somehow, you didn’t prepare as much as you should have.

Now, you’re staring at the clock with only an hour or two left to get ready.

Sound familiar? Don’t worry. You’re not alone. Many MSLs face this exact challenge. The good news? AI can help.

To show you how, I teamed up with Vivek Mukhatyar, an expert in both AI and Medical Affairs. Together, we explored how to leverage AI tools for last-minute pre-meeting preparation. In this article, we’ll break down two complementary approaches: Vivek’s custom GPTs, designed for deep insights and efficiency, and my versatile prompt-based strategy. We’ll show how these tools can help you stay prepared, build relationships, and add value. Even when time is tight.

Disclaimer: Use AI Responsibly

AI is an invaluable resource for MSLs, but it’s crucial to use it responsibly. Always validate outputs and ensure they align with your objectives. Follow your organization’s AI policies, and never input proprietary or sensitive data into public models. Think of AI as your assistant, helpful and efficient, but not a substitute for your expertise.

What Are Custom GPTs?

Custom GPTs are AI models tailored to specific needs and workflows. Unlike general-purpose AI tools that require structured prompts to guide them, custom GPTs are pre-trained with specific instructions, datasets, or parameters to provide consistent and highly relevant outputs. For example, a custom GPT designed for MSLs might focus on summarizing a KOL or a publication (you will see Vivek’s examples below).

Why They’re Valuable:

Custom GPTs streamline repetitive tasks, reduce the need for detailed prompting, and ensure outputs are aligned with your objectives. They are especially useful when you need a consistent process for complex tasks, like preparing for KOL meetings or analyzing literature.

Setting the Stage: Vivek’s Focus on Understanding the KOL and Their Research

Before diving into Vivek’s process, it’s important to understand his approach at a high level. His goal was twofold:

1. Learn About the KOL: Start with key details like their research focus, recent publications, and public appearances to ensure the AI is working with accurate and relevant data.
2. Extract Research Insights: Go beyond summaries to understand study limitations, identify potential discussion points, and uncover collaborative opportunities.

Using his custom GPTs, Vivek streamlined these steps into a process that saved time while delivering rich, actionable insights. Here’s how he did it.

Access his custom GPTs here:

• MSL Intelligence Assistant
• PDF Summarizer

Note: you may need a paid version to access the custom GPTs. Reach out to Vivek on LinkedIn with any questions.

Step 1: Confirm the KOL’s Identity

Vivek’s custom GPT begins by confirming the KOL’s identity. It generates a concise table summarizing key details about the KOL, such as their name, institution, and specialty. This ensures that the AI focuses on the correct individual.

Why This Matters:

Accurately identifying the KOL is critical. You don’t want the AI to give you a summary of the wrong physician. Always remember the AI can make mistakes you must be in the habit of fact-checking everything. This summary table makes it easy!

Step 2: Get a Summary of Key Research Insights

The GPT then pulls together an overview of the KOL’s research focus, recent publications, public appearances, and MSL discussion points. This gives the MSL a snapshot of the KOL’s current priorities and professional contributions. The GPT pulled an article where the KOL was featured in The Atlantic. This was probably a huge deal for Dr. Yosipovitch and is a great conversation starter. In just a few seconds, the GPT listed several ways the MSL can start building the relationship. This is a huge time saver for MSLs by minimizing the amount of time spent Googling the KOL.

Why This Matters:

Understanding a KOL’s research focus helps you align your discussion points with their interests, making the meeting more engaging and relevant.

Step 3: Dive Deeper with Publication Analysis

Now it’s time to review the KOL’s publications and figure out ways to add value. Vivek’s second custom GPT focuses on analyzing a specific publication. It provides:

• Co-Author Networks: Highlights collaborators and their affiliations, revealing potential competitor connections.
• Study Summaries: Extracts key findings and methodology for quick reference.
• Study Limitations: Identifies gaps or challenges, offering thoughtful talking points.
• Questions for Authors: Generates targeted questions to drive meaningful discussion. 

Vivek designed this custom GPT to give MSLs an edge and come to the table with something extra that other MSLs might not have. This is the power of using AI. It doesn’t only save you time. It can make you a better MSL.

Why This Matters:

These insights allow you to approach the meeting with a unique perspective. By discussing study limitations or suggesting collaborations, you position yourself as a critical thinker who adds value.

Setting the Stage: Patrina’s Prompt-Based Approach for Tailored Insights

Unlike Vivek’s custom GPT approach, my approach uses a well-crafted prompt to generate versatile insights to leverage in the meeting. The outputs are similar to Vivek’s custom GPTs but this method focuses on providing clear guidance to the AI to ensure it delivers outputs that make sense.

Before diving into my process, it’s important to understand my approach at a high level so that you can replicate it. This is how I think about using AI for this task. My goal was twofold:

1.  Get Ideas About What the KOL Values: Provide the AI with a clear role and detailed guidance about the KOL, including their name, institution, therapeutic area, and recent publications. By doing this, I ensure the AI’s output focuses on what’s most important to the KOL, helping me align my meeting preparation with their interests and priorities.
2. Ensure Actionable Output (Tell the AI What I Want): Use aspects from my pre-meeting planning framework and how to uncover what KOLs value prompt to structure the AI’s response, focusing on 10 key areas like key takeaways, conversation starters, and follow-up actions. When you give the AI structure like this, you get the output you want. Otherwise, the AI just produces what it thinks is best and it may miss the mark.

Using this approach, I leveraged a general-purpose AI to deliver highly relevant and actionable insights, without the need for custom tools. Here’s how I did it. 

Step 1: Assign a Role and Context

The prompt (full prompt below) starts by assigning the AI the role of an experienced senior MSL and providing detailed context about the KOL, such as their name, institution, therapeutic area, and recent publications. Learn more about prompting in my AI Guide to Creativity and Productivity for MSLs (page 4).

Why This Matters

Assigning a role ensures the AI generates outputs aligned with the unique needs of MSLs, while the detailed context increases the relevance and specificity of the results. When AI output feels wonky it can be because you didn’t tell the AI who it should act like or give it enough context.

Step 2: Use a Framework to Shape the Output

The prompt incorporates aspects of my existing pre-meeting planning framework and what KOLs value prompt, which focuses on 10 key areas. This helps ensure the AI generates insights that are actionable and useful for engaging with the KOL. These areas include:

• Key Takeaways: Summaries of critical findings from the KOL’s publications.
• Challenges and Pain Points: Potential hurdles in their research or practice.
• Emerging Topics: New trends that align with the KOL’s interests.
• Conversation Starters: Questions or comments to foster meaningful dialogue.
• Follow-Up Actions: Recommendations for post-meeting engagement.

Here’s a snippet of the output from the ChatGPT-4o model using this prompt. Read the entire output at the bottom of this post. 

Why This Matters:

By “plugging in” a proven framework, the prompt guides the AI to create output that directly supports the goals of pre-meeting planning, ensuring the output is useful.

Step 3: Customize and Experiment

The flexible nature of the prompt allows MSLs to tailor it to their needs. For example, you can substitute social media posts for publications or focus more deeply on specific areas like collaboration opportunities.

If you notice the output isn’t quite right, rework your prompt. For example, if the output is focusing on the wrong aspect of the KOL’s work, update the prompt to have it focus on the area that is useful to you.

Another example is that we could ask the AI to look for trends in the publications, as Vivek suggested in the video. The AI could help us understand if the KOL’s thinking has changed and how. The sky is the limit on how we customize this prompt!

Why This Matters:

This adaptability ensures the methodology remains versatile, enabling MSLs to experiment with different inputs and approaches to refine their process over time.

Patrina’s Pre-Meeting Planning Prompt You Can Use

Just copy and paste this prompt into your favorite AI tool, update with your information, and then hit submit. Feel free to get creative here and make it your own. You’ll see this is similar to my other pre-meeting planning and what KOLs value prompts.

“You are an experienced senior MSL and an expert in leveraging AI to enhance pre-meeting preparation and relationship-building with KOLs. Here’s the scenario:

– KOL Name: [Insert KOL’s Name]
– Institution: [Insert Institution]
– Area of Expertise: [Insert KOL’s Therapeutic Area/Research Focus]
– Relevant Publications: [Copy-paste relevant publications here]

Please provide insights into the following:

1. Key Takeaways: Summarize the most critical findings from the provided publications, emphasizing their impact on the field.
2. Motivations and Research Interests: Deduce potential areas of continued research and professional focus for the KOL.
3. Challenges and Pain Points: Identify possible hurdles or limitations faced by the KOL in their work or therapeutic area.
4. Emerging Topics: Point out related trends or new research areas that might be of interest based on the publications.
5. Value-Adding Data/Resources: Suggest relevant data, literature, or collaborative opportunities that could support the KOL’s research.
6. Personalized Engagement: Propose strategies for aligning your approach to reflect the KOL’s communication style and professional goals.
7. Conversation Starters: Develop questions or comments based on the publications that could help foster a meaningful discussion.
8. Key Collaborations: Highlight notable co-authors or frequent research partners that might be valuable to mention or inquire about.
9. Follow-Up Actions: Recommend potential follow-ups to maintain engagement and build the relationship post-meeting.
10. Non-Professional Interests: Note any insights into the KOL’s non-academic interests that could help establish rapport.

Ensure your response is concise, actionable, and optimized for a quick review to support effective pre-meeting preparation.”

Patrina’s Prompt & Full Output

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