The past few years, particularly the recent months, have brought on an onslaught of regulatory headwinds to the biopharma industry. Management of the impact of administrative orders; Inflation Reduction Act (IRA) Tariff policies also require companies to reform their pricing processes to maintain revenue streams.
As Senior Vice President of the Center for Exceptional Model N, my team and I have worked closely with pharmaceutical manufacturers to navigate these policy shifts. We have seen first hand how legislative obligations and market dynamics are reshaping the industry's revenue strategy. Artificial intelligence (AI) is the key to skillfully responding to these changing dynamics.
Policy pressure
Even before President Donald Trump took office, Pharma lobbyists were Request a change In IRA drug price negotiation regulations. But Trump reaffirmed the federal government's commitment to the process through an executive order in April. Medicare drug price negotiations. The directive also includes an initiative to remove what is called “so-called.”Pill Penalty“It is a positive change for the industry by leveling the time frame for molecular drugs, large and small, to qualify for negotiations. However, speculation that the administration will strive to eliminate price negotiations is being placed on a break.
The industry was already working on the impact of the IRA before these directives. in Model N's 2025 income reportCompiled before the second Trump presidency, 62% of drug executives surveyed expressed concern about the impact of the IRA on their pricing strategy, with 87% saying they have already changed launch plans for certain diseases or treatment areas.
In May, Trump signed a massive executive order renewing efforts to implement it “Most Preferred Country” (MFN) policy. The order aims to reduce US drug costs by linking specific drug prices together to significantly reduce certain drug prices overseas. Industry groups estimate that the regulations are costly The pharmaceutical industry is $1 trillion.
The proposal reflects previous versions introduced during Trump's first period, stagnating amid legal challenges and industry pushbacks. The new EO lacks details on how benchmark prices are calculated and relies on immediate, non-regulatory voluntary compliance. For now, the industry is in a retention pattern.
meanwhile, Customs Additional wrenches can be thrown into the activities of the pharma company. If established, trade policies will increase the cost of drug production and additional strain margins. But President Trump has returned some of his tariff threats, leaving their future uncertain.
In summary, it moderately measures current risk levels for MFN and tariffs. It is significant enough to guarantee planning and scenario modeling, but not enough to cause immediate crisis.
These potential policy changes, combined with IRA obligations, require pharmaceutical companies to fundamentally restructure their pricing frameworks to maintain margins. More than half of the Model N survey executives have indicated that they plan to make significant investments in their pricing strategies over the next two years, even before the latest executive order. Many are turning to AI and data analytics to optimize revenue.
The value of AI in revenue management
Responding to ongoing market and regulatory changes with speed and reliability requires pricing agility that only intelligent data systems can offer. If implemented, the MFN executive order adds to the complexity of this response, requiring manufacturers to quickly gain new visibility into global prices and product volumes in comparable international markets.
Achieving transparency and flexibility depends on comprehensive, up-to-date data from many different sources. Manually gathering and preparing this information requires extensive time and resources, and often results in error, incomplete information and delays. Additionally, teams are unable to keep up with weekly, if not frequently, regulatory policies.
When companies build integrated systems that connect internal and external data sources, AI automates the collection, standardization, enhancement and management of information from drug portfolios, current contracts, sales and supply chain metrics, formalities, regulations, competitor prices, and market trends.
AI can quickly analyze this data to detect new patterns and opportunities. The resulting insights allow manufacturers to build a dynamic, differentiated pricing framework for targeted customer segments that explains policy impacts and fluctuating changes in demand. The appetite for AI-powered tools is growing. 62% of leaders surveyed by Model N say they use or plan to manage revenue using generated AI.
When changing government policies, predictive analytics is especially valuable for pharma companies. AI can model how different scenarios affect revenue.
- The impact of changes in tariff charges on production costs.
- The IRA inflation penalty, which requires manufacturers to rebate the difference when Medicare drug prices rise faster than inflation, cancels potential profits from higher prices in the commercial market.
- How pricing and rebate structures change will change revenue and sales.
When the cap is capped, such as Medicare negotiations, inflation-based penalties, or MFN policies, there is a narrow room for operation. Under these conditions, the data strategy is not about driving price, but about promoting sales volume and extracting maximum values from contracts and portfolios. Our customers have focused on rebate modeling to determine whether discounts designed to drive more sales will pay off. Therefore, AI and analysis help companies adapt within their existing boundaries and optimize their net revenue through better contract management, dynamic pricing strategies, and alternative distribution models.
It is impossible to predict any policy changes and advance market changes. What pharmaceutical companies can do is prepare flexible, data-based pricing strategies that allow for quick pivots. By adopting AI-driven revenue management, manufacturers can maintain R&D investments that drive long-term innovation while maintaining compliance, patient drug access and margins. As more managers prioritize sophisticated pricing strategies and analytics to maximize portfolio value, the industry has the opportunity to become more efficient, responsive and innovative.
