Drug Launches: Pricing and Total Cost

"There’s no bad risk, there’s just mispriced risk... we helped one carrier achieve a 29.1% improvement in their loss ratio just through better risk selection."

How do stop-loss carriers and self-funded employers accurately predict which groups are going to run well and which ones are about to see skyrocketing claims?

My guest this week is Ali Panjwani, Founder and CEO of Merit Medicine. Ali transitioned from a career in biotech and pharmaceutical public policy, where he helped price and launch complex, rare-disease drugs, to solving one of the biggest problems in self-funded healthcare: predicting catastrophic risk before it happens.

In this episode, we dive into the evolution of predictive analytics and medical underwriting. Ali explains how Merit Medicine uses AI and access to a massive database (covering 95% of commercial claims in the US) to project a group's healthcare spend using just a simple census file. We discuss why a group that ran poorly last year might actually be a great risk this year, how to prevent underwriters from "playing on tilt," and the ongoing debate over how to finance multi-million-dollar cell and gene therapies.

If you are a benefits consultant, an MGU, or a stop-loss carrier trying to understand how technology is fundamentally changing the way healthcare risk is predicted and priced, this episode is a must-listen.

Thank you to our 2026 sponsors!

ParetoHealth: ParetoHealth empowers midsize employers with a long-term solution to reduce volatility and lower overall health benefits costs. Visit ParetoHealth.com/spencer to learn more.

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Chapters:

• (00:00:00) Intro: The Evolving Landscape of Healthcare Risk
• (00:04:28) Ali's Background: From Biotech to Public Policy
• (00:09:47) The Complexity of Launching & Pricing New Drugs
• (00:13:30) Shifting Focus: Who Actually Pays for Healthcare?
• (00:16:34) The Data Access Problem for Self-Funded Employers
• (00:19:50) How Merit Medicine Predicts Risk with Just a Census File
• (00:23:24) Why Merit Looks Backwards to Predict the Future
• (00:26:27) How Stop-Loss Carriers & MGUs Use Predictive Analytics
• (00:29:41) "There Is No Bad Risk, Only Mispriced Risk"
• (00:33:04) The Danger of Underwriting "On Tilt" (Past vs. Future Claims)
• (00:37:37) Can Predictive AI Help Apply Specific Lasers?
• (00:40:10) The Evolution of Underwriting Tech
• (00:45:04) Proving the Model: A 29.1% Loss Ratio Improvement
• (00:49:10) The Cell & Gene Therapy Debate: Public Pools vs. Financing
• (00:55:14) Closing Thoughts: The Future of Predictable Premiums

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