Trump's "Most Favored Nation" Executive Order, with Shawn Ferguson | Last Month In Healthcare

This video provides an in-depth exploration of recent headlines and trends in the healthcare industry, with a particular focus on pharmaceutical pricing, regulatory oversight, and the burgeoning role of artificial intelligence. The hosts, Spencer and Nathaniel, along with guest Shawn Ferguson, review key news from May 2025, discussing the implications of policy changes, technological advancements, and market dynamics. The conversation delves into the controversial "Most Favored Nation" executive order concerning drug pricing, the FDA's internal adoption of AI for drug approval processes, and the alarming increase in new drug costs, especially for rare diseases.

A significant portion of the discussion centers on the pharmaceutical sector's challenges and opportunities. The "Most Favored Nation" order, aimed at aligning U.S. drug prices with lower international rates, sparks debate about its potential impact on pharmaceutical R&D and the broader market. The speakers critically examine the industry's arguments against such policies, highlighting the existing imbalances in global drug pricing. Furthermore, the FDA's strategic move to deploy generative AI, in collaboration with OpenAI, for streamlining drug approval tasks is presented as a potentially transformative step, promising greater efficiency and precision in regulatory reviews, which could ultimately influence R&D costs.

Beyond policy and regulation, the video also reviews several past podcast episodes, with one particularly relevant segment discussing Signos, an AI-powered solution utilizing Continuous Glucose Monitors (CGMs). This segment highlights the application of AI in personalized health management, behavior change, and the collection of longitudinal data. The Signos app, which integrates wearable data and provides actionable prompts for diet and exercise, is positioned as an effective, sustainable alternative or complement to GLP1 medications for weight management, emphasizing the power of AI in driving positive health outcomes and addressing chronic conditions through behavioral modification. The discussion also touches upon broader healthcare issues like food additives, the rise of ambulatory surgery centers, and alleged kickback schemes in Medicare, providing a comprehensive, albeit varied, look at the current healthcare landscape.

Key Takeaways:

• Most Favored Nation (MFN) Drug Pricing Policy: Trump's executive order aims to reduce U.S. drug prices by linking them to the lowest prices paid in other developed nations. While the intent is to address price disparities, concerns exist regarding potential unintended consequences, lobbying efforts, and the pharmaceutical industry's claims of hampered R&D.
• AI Integration in FDA Processes: The U.S. FDA is deploying generative AI internally, in partnership with OpenAI, to enhance the drug approval process. This initiative is intended to reduce time spent on repetitive administrative and research tasks, aiming for increased efficiency and precision in regulatory reviews.
• Escalating Drug Costs: The median annual list price for new U.S. drugs has doubled in four years, reaching over $370,000 in 2025, with a growing focus on rare diseases. This trend underscores the financial burden on healthcare systems and patients, prompting discussions on R&D costs and the role of middlemen in pricing structures.
• Impact of R&D Costs on Drug Pricing: The pharmaceutical industry frequently cites high R&D costs as a justification for high drug prices. The adoption of AI by the FDA and other entities could potentially decrease these R&D expenses, theoretically leading to lower drug costs, though whether this translates to consumer savings remains a point of contention.
• Transparency in Drug Pricing and Rebates: The discussion highlights the complexity and lack of transparency in drug pricing, particularly concerning the rebate structure where Pharmacy Benefit Managers (PBMs) often collect significant portions of rebates, raising questions about the true cost and value for employers and patients.
• AI for Personalized Health and Behavior Change (Signos): The Signos platform, utilizing CGMs and AI, offers a personalized approach to diet and exercise by monitoring blood sugar responses and integrating wearable data. It provides actionable prompts to foster sustainable behavior change, presenting a data-driven alternative or complement to pharmacological interventions like GLP1s.
• Longitudinal Data for Health Outcomes: The Signos model emphasizes the importance of collecting longitudinal data over extended periods to understand individual physiological responses and drive effective, lasting behavioral modifications, moving beyond short-term interventions.
• Food System Scrutiny: The FDA's plan to review chemicals in the U.S. food supply, such as BHT, points to a growing awareness and concern about additives that are often restricted or illegal in other developed countries, highlighting a broader regulatory push for public health.
• Healthcare Delivery Models: The trend of hospitals outsourcing minor surgeries to ambulatory surgery centers (ASCs), as exemplified by Cleveland Clinic and Regent Surgical, aims to reduce costs and improve patient experience by separating routine procedures from acute care settings, potentially mitigating risks like hospital-acquired infections.
• Ethical Concerns in Healthcare Incentives: The DOJ lawsuit against major health insurers for alleged kickback schemes with brokers underscores the pervasive issue of perverse financial incentives in the healthcare industry, particularly in Medicare, where profit motives may compromise patient interests, especially for vulnerable populations like those with disabilities.

Tools/Resources Mentioned:

• OpenAI: Collaborating with the FDA for generative AI deployment in drug approval processes.
• Continuous Glucose Monitors (CGMs): Utilized by platforms like Signos for real-time blood sugar monitoring and personalized health insights.
• Wearable Data: Integrated by AI health apps (e.g., Signos) to provide comprehensive health monitoring and behavioral prompts.
• LinkedIn: Mentioned as a platform for professional networking and marketing, with Sims Tillerson cited as an expert.
• Giftology (Book): Authored by John Rulan, mentioned in the context of authentic relationship building.

Key Concepts:

• Most Favored Nation (MFN) Executive Order: A policy aimed at ensuring a country pays no more for goods (in this case, medications) than the lowest price offered in other developed nations.
• Generative AI: Artificial intelligence capable of generating new content, such as text, images, or other media, used by the FDA to automate and streamline tasks.
• Longitudinal Data: Data collected from the same subjects over an extended period, crucial for understanding long-term trends, behavioral changes, and the efficacy of interventions.
• Ambulatory Surgery Centers (ASCs): Outpatient facilities where surgical procedures that do not require an overnight hospital stay are performed, typically at a lower cost than hospitals.
• Pharmacy Benefit Managers (PBMs): Third-party administrators of prescription drug programs for commercial health plans, self-insured employer plans, Medicare Part D plans, and other government programs, often involved in rebate negotiations.

Examples/Case Studies:

• Signos: An AI-powered app that uses CGMs and other wearable data to provide personalized diet and exercise recommendations, aiming for sustainable weight loss and behavior change, positioned as an alternative or complement to GLP1s.
• Chick-fil-A Sandwich Ingredients: Cited as an example of common fast food items containing a surprisingly large number of ingredients (55 mentioned), many of which are unpronounceable chemicals, raising questions about food additives and processing.
• John Rulan's AI Chatbot Clone: An example of leveraging AI to preserve and continue the legacy and work of an individual after their passing, by uploading their body of work and voice into an AI chatbot.