Why Traditional MSL Training No Longer Works—And What to Do Instead

By Sarah Snyder

The Problem: MSL Training Is Stuck in the Past

Picture this: A new MSL sits at their desk, surrounded by stacks of scientific articles and slide decks, diligently highlighting and taking notes. This has been the standard training approach for decades—memorize the data, understand the endpoints, and hope that translates into meaningful KOL conversations.

But in 2025, this approach is fundamentally broken.

Today's MSLs face a radically different landscape:

✅ KOLs have instant access to the same data through PubMed alerts, clinical trial dashboards, and AI tools.
✅ Attention spans are shorter than ever—you have seconds to make an impact.
✅ Data delivery isn’t enough—the value of an MSL lies in creating insights, not just repeating information.

Example:
An MSL presents clinical trial data showing that their drug improved progression-free survival (PFS) by 2.1 months over the competitor’s product. But when the KOL asks, “What does this mean for overall survival?” or “How does this compare to real-world outcomes?”—the MSL freezes.

They know the numbers, but they don’t know how to translate them into meaningful clinical context.

The result? The KOL walks away without real confidence in the product’s impact—and the relationship stalls.

The Knowledge-Application Divide 

Understanding data ≠ communicating data.

Traditional training assumes that an MSL who can recite study endpoints can also navigate sophisticated scientific dialogue.

But knowing the data isn’t enough—MSLs need to apply it in real-world conversations.

Key Challenges:

❌ MSLs read papers through an academic lens—not a KOL engagement lens.
❌ Basic comprehension doesn’t prepare MSLs to handle comparative or contextual questions.
❌ Passive reading fails to build the skills needed for dynamic, real-time conversations.

Example:

A KOL asks, “What are the limitations of this study?” The MSL can repeat the trial's exclusion criteria but can’t explain how that impacts real-world patient selection.

Why Traditional Training Fails

💡 Memorization ≠ Confidence
Training MSLs to memorize confidence intervals, p-values, and secondary endpoints doesn’t prepare them for real conversations.

Example:
An MSL might know the competitor’s product achieved a 35% reduction in relapse rates. But when the KOL asks, “What’s driving that difference?”—the MSL can’t explain the mechanism of action because they were trained to deliver data, not insights.

💡 Lack of Comparative Thinking
Clinical conversations aren't about one product in isolation—KOLs want to know how it stacks up to competitors, how it applies to subpopulations, and how it fits into treatment guidelines.

Example:
A KOL asks, “How does this drug compare to the new phase 3 data from the competitor?” A traditionally trained MSL might say, “I’m not sure.”
An MSL trained in comparative thinking would say:
➡️ “That’s a great question—the competitor’s trial showed a 22% reduction, but it included a different patient population with higher baseline risk. Our drug performed better in high-risk patients.”

💡 Failure to Adapt to Real-World Conversations
KOL conversations aren’t scripted. Yet most training treats them that way.

Example:
A KOL challenges an MSL with, “This trial excluded patients over 65—how does that impact real-world applicability?”
➡️ A traditional MSL might default to, “I don’t have that data.”
➡️ A well-trained MSL would say:
“That’s an important consideration. In a real-world population, we’d expect to see a wider age range, so outcomes could vary. Are you seeing similar age-related differences in your practice?”

The Fix: Train for Application, Not Memorization

 To succeed, MSLs need to stop memorizing and start practicing.

✅ Scenario-Based Learning – Train MSLs to explain complex concepts concisely under pressure.
✅ Data Comparison Exercises – Build the skill of synthesizing and contrasting competing data sets on the spot.
✅ Active Dialogue Practice – Develop the ability to steer conversations and adjust to real-time feedback.

👉 Research proves it:

• Passive learning = 20% retention after 24 hours.
  
• Active learning (discussion + problem-solving) = 80% retention after 24 hours.

Example:
Instead of just reading the data, an MSL should practice responding to:
➡️ “The competitor’s drug showed a 25% reduction in cardiovascular events—how does your product compare?”

The Shifting Information Landscape

Twenty years ago, MSLs were the gatekeepers of clinical information.

Today, KOLs have that information at their fingertips.

The New Reality:

✅ Basic information delivery no longer provides value.
✅ KOLs expect insight, context, and strategic guidance.
✅ MSLs have less time than ever to make an impact.

What Works:

✅ Train for rapid synthesis—turn complex data into clear takeaways.
✅ Build strategic engagement skills—help MSLs steer conversations, not just respond.
✅ Prepare for the unexpected—teach MSLs how to handle unanticipated questions confidently.

From Data Delivery to Insight Creation

The real value of an MSL isn’t in the data—it’s in the dialogue.

KOLs don’t need an MSL to recite data they can find on their own. They need a thought partner who can:
✅ Provide strategic insights.
✅ Connect data to real-world clinical decisions.
✅ Facilitate deeper scientific conversations.

Example:
A KOL asks, “What challenges do you see with patient adherence?”
➡️ A data-focused MSL might say, “That wasn’t addressed in the trial.”
➡️ An insight-focused MSL would say:
“That’s an important consideration—Have you seen adherence issues with similar therapies?”

What Works:

✅ Shift from Telling → Asking – Train MSLs to prompt deeper discussions:

• “How might this data influence your treatment decisions?”
  
• “What challenges do you see in translating these findings?”
  
• “What additional evidence would strengthen your confidence?”
  

✅ Simulate Real Conversations – Train MSLs to pivot and adjust to the KOL’s response.
✅ Build Conversation Agility – Develop the skill to explore nuance, rather than delivering rehearsed answers.

The Future of MSL Training

The companies that win in 2025 will be the ones that recognize this shift—training MSLs not just to know the data, but to create strategic dialogue.

Essential Training Transformations:

➡️ From passive reading → To interactive, discussion-based training
➡️ From static content → To real-time synthesis and application
➡️ From delivering data → To guiding strategic conversations

Is Your MSL Training Keeping Up?

The question isn’t whether your MSLs know the data—it’s whether they can translate that data into meaningful conversations that influence clinical decisions.

👉 Are your MSLs ready for this new reality?

If not, it’s time to rethink your training. Let's build a program that creates confident, strategic, and adaptable MSLs—because memorizing data is no longer enough.

Contact us today to design a training program that builds insight-driven, high-impact MSL teams.

Stop training for memorization. Start training for impact.

✅ Ready to future-proof your MSL training? Let's talk. Let's talk.