The $56.2 billion ten-drug target that destroyed the list-price myth. Medicare Part D spent approximately 20% of program drug costs on the first 10 drugs eligible for IRA price negotiations. Negotiations have resulted in discounts of 38%-79% to list price, with new prices hitting in January 2026.
As more drugs are added each year, the Congressional Budget Office expects negotiated, net prices to drop about 50% on average. While it may seem that manufacturers could offset these reductions through increased volume and improved affordability, this assumption is largely incorrect.
While increased volume may benefit a few drugs in specific cases, for most drugs selected for IRA negotiations, relying on volume to offset price cuts is unrealistic.
The underlying financial reality remains unchanged, and no amount of optimistic modeling changes it.
The Donut Hole Bright Spot: Discount Exemption
Starting in 2025, the old Part D “donut hole” disappeared. In its place, manufacturers of brand-name drugs must pay discounts (rebates):
10% on drugs purchased between the deductible and
$2,000 in out-of-pocket spending, and 20% above that threshold.
Drugs selected for IRA negotiation are exempt from these discounts. The Centers for Medicare & Medicaid Services (CMS) has explicitly stated that losses from lower prices could be more than offset by avoiding the mandatory discounts, especially if the “maximum fair price” (MFP) falls at or near the ceiling price.
This is not a volume offset, but rather a form of liability avoidance. For drugs with significant catastrophic-phase utilization, this exemption can result in substantial savings.
For some drugs, the financial impact may be favorable, but for most, it will not. Pharmaceutical finance teams should model the benefit of avoided discount liability by patient distribution across benefit phases and compare it to the MFP reduction to determine the net financial effect.
The Adherence Bump: Measurable But Small
In 2024, Part D enrollees had to spend $8,000 to reach the catastrophic coverage phase. The drop to $2,000 in 2025 reduced prescription expenses for millions of older adults and people with disabilities. It is estimated that this will save about 19 million enrollees about $7.4 billion annually.
The out-of-pocket cost maximum should improve adherence and increase total volume, but how much remains uncertain and will vary by drug. A Blue Cross Blue Shield of Louisiana study found that after the expansion of zero-dollar copays, medication adherence rose in the treatment group by 2.1 percentage points relative to controls. The Employee Benefit Research Institute estimates that a 1% decrease in out-of-pocket costs will prompt a 0.23% increase in utilization.
Pharmaceutical finance teams should model various utilization volume increases by drug, using historical elasticity studies. However, these gains will likely only marginally offset a 40-50% price reduction.
Overall, increased utilization from improved adherence will likely have a minimal impact on offsetting price reductions.
The Elasticity Problem: People Buy Drugs Because They're Sick, Not Because They Want To
Price elasticity of demand (PED) is where volume offset runs into the conceptual brick wall.
Empirical estimates of PED for pharmaceuticals suggest they are relatively price-inelastic, although with substantial variation by drug, cost-sharing, substitutes, and complements. For example,
- The landmark RAND Health Insurance Experiment of the 1970s famously estimated that the elasticity of medical spending with respect to its out-of-pocket price is −0.2.
- A 2014 study published in the Journal of Managed Care Pharmacy estimated that PED ranged from -0.015 to -0.157 across 8 medication categories.
- In a 2018 study, the National Library of Medicine found that PED was -0.16. However, there was substantial dispersion across the copayment tiers, ranging from -0.09 to -0.87.
Pharmaceutical demand is widely recognized as highly price-inelastic. With a PED of 1.6%, a 10% price decrease would result in only a 1.6% increase in volume. Applying the CBO’s projected 50% price reduction would yield an estimated 8% volume increase. For example, consider a drug with $100 million in annual revenue:
- Pre-IRA: $100M revenue
Post-IRA price: $50M at old volume, assuming CBO estimates - Post-IRA volume bump estimate of 8%: Revenue increases to $54M
- Net Revenue loss: $46M
This reflects basic economic principles. For essential medications, demand remains relatively stable regardless of price. Patients do not significantly increase or decrease their usage in response to price changes alone. Diabetics don’t double their insulin purchases because the price dropped. Cancer patients don’t decide to skip chemo because of the price and then suddenly decide to start again if it drops.
Pharmaceutical finance teams should be cautious when modeling scenarios having a PED greater than –0.25, unless supported by clear historical evidence or involve unique therapeutic categories.
The “Real” Size Of The Haircut
CMS has announced discounts of 38% to 79% off list prices for the first ten drugs. However, these figures do not account for previously required rebates. A more accurate comparison is to pre-IRA net prices.
The Brookings Institution’s Center on Health Policy ran the numbers and determined the following:
- The first round of negotiations, encompassing 10 drugs, resulted in an average MFP decrease of 22% relative to the pre-IRA net price.
- In November 2025, CMS announced price cuts for 15 drugs in round two, with an average MFP that is 44% below the estimated pre-IRA net price.
Total savings are estimated at $12.5 billion (slightly higher than CMS’s $12 billion estimate) with five drugs: Trelegy Ellipta, Xtandi, Pomalyst, Ibrance, and Linzess, accounting for 43% of the savings.
The drugs most affected are those with the smallest existing rebates, narrow competition, and minimal PBM leverage. Manufacturers of these drugs will experience the largest reductions.
Specialty Drugs: Where Elasticity Goes to Die
Industry analysts state that for drugs treating small or orphan populations, utilization restrictions are essentially price-inelastic. The patients who need these drugs are already getting them (or trying to). There’s no untapped reservoir of cancer patients who were waiting for a price break to start treatment.
The volume offset argument is only valid where latent demand exists. While some demand may be present for drugs with broad populations and adherence challenges, it is minimal for third-line oncology drugs or biologics for rare conditions.
What Finance Teams Should Actually Model
Do not rely on volume offset as a primary recovery strategy. Instead, focus on building models that capture the interactions among MFP reductions, discount exemptions, realistic volume responses, and benefit-phase dynamics.
1. Quantify the Discount Exemption First
This is the offset lever that can actually move the needle. For drugs currently not yet on the list, start by calculating what the drug would owe under the new Manufacturer Discount Program if it weren’t selected for negotiation. Use historical data of patient distribution across the different benefit phases to determine how many beneficiaries would hit the initial coverage phase (10% discount territory) versus the catastrophic (20% discount territory). This is your discount liability.
For high-cost specialty drugs where most patients will quickly blow through the $2,000 cap, catastrophic-phase utilization dominates, and the 20% discount exemption saves serious money.
Compare the avoided discount liability against an estimated MFP revenue reduction. If the exemption value exceeds 60-70% of the estimated MFP price cut, you’ve got a product that might survive IRA negotiations without major damage compared to the alternative.
2. Use Defensible Elasticity Assumptions
Pharmaceutical price elasticity ordinarily ranges from -0.10 to -0.20, with specialty drugs at the lower end. Use -0.15 as a base case, -0.10 for specialty and oncology drugs, and -0.20 only if supported by therapeutic-class-specific evidence.
3. Model Adherence Gains Separately
The $2,000 out-of-pocket cap will improve adherence, but the effect is limited. Based on research, assume 1-3% adherence improvement for drugs where cost was a meaningful barrier. This translates to roughly the same percentage increase in volume.
Avoid double-counting, as adherence gains and price elasticity effects overlap. Patients who did not fill prescriptions due to cost are the same individuals who respond to lower prices. Treat adherence improvements as a subset of the elasticity effect.
4. Know Your Pre-IRA Rebate Position
Your pre-IRA net price determines how much the MFP actually hurts. Drugs with large existing rebates of 30-40% off gross will see smaller incremental cuts when MFP takes effect. Drugs with smaller rebates (10-15% off gross) will get hit harder because the MFP represents a much larger drop from their actual realized price.
Pull your rebate data by channel and payer. Calculate your true net price, not the Average Sales Price (ASP) or Wholesale Acquisition Cost (WAC). Model the MFP as a delta from that real number. If you are looking for external validation of internal numbers, Brookings and MedPAC publish therapeutic-class rebate ranges that can serve as sanity checks.
5. Factor in Medicare Population Growth
Part D enrollment growth varies annually, but a good assumption is 2-3% per year as boomers age in. Disease prevalence for conditions like diabetes, cardiovascular disease, and autoimmune disorders is also rising in the Medicare population. This organic growth provides volume tailwind independent of IRA dynamics.
This growth should be included in models, but it is not an IRA offset, as it would occur regardless. The key consideration is whether IRA-driven volume gains are incremental to baseline growth, not whether baseline growth compensates for price reductions.
6. Run Real Scenarios, Not Fairy Tales
Develop three scenarios for each affected drug: worst case, base case, and optimistic case. If the optimistic case still shows 25%+ revenue decline, that’s the reality you’re looking at. If your worst case shows a manageable impact because discount exemptions are large, you’ve found a defensible position.
7. Get the Right Tools for Scenario Planning
Multi-variable modeling that incorporates price changes, volume responses, discount exemptions, and benefit phase dynamics is challenging to perform in Excel. Spreadsheets are suitable for single scenarios but become difficult to manage when running sensitivity analyses across multiple drugs, elasticity assumptions, and regulatory parameters.
Modern FP&A software like Farseer are built for exactly this problem. JGL Pharma, a pharmaceutical company operating across 60+ markets, uses Farseer to model best-, base-, and worst-case revenue scenarios instantly, run real-time sensitivity analyses for pricing and regulatory changes, and link demand, supply, and P&L in a single unified environment. Scenario modeling that once took weeks now happens in days.
The IRA is an ongoing process. CMS will select additional drugs each year, renegotiate existing MFPs, and expand the program to Part B drugs beginning in 2028. Pharmaceutical finance teams require infrastructure that can accommodate these ongoing changes without regular model reconstruction. Investing in scenario planning capabilities is essential as the regulatory environment evolves.
The Bottom Line
Volume increases will not offset IRA price cuts for most drugs. Price elasticity is too low, the reductions are substantial, and adherence improvements are limited.
Potential mitigating factors include discount exemptions for drugs with significant catastrophic-phase utilization, organic Medicare enrollment growth, and modest adherence improvements from the $2,000 cap. Together, these may offset 20-40% of the revenue loss for favorably positioned products. For others, particularly specialty drugs with low existing rebates, the offset will be closer to 10%.
Pharmaceutical finance teams should model offsets accurately, identify drugs with favorable exemption calculations, and develop scenario infrastructure to manage ongoing regulatory changes. Volume increases should be viewed as a minor cushion rather than a primary recovery strategy.
FAQ
No—at least not for most drugs. Pharmaceuticals are generally price-inelastic, meaning demand does not increase proportionally when prices fall. With typical elasticity estimates between –0.10 and –0.20, even a 50% price reduction would likely produce only a 5–10% increase in volume. That modest gain cannot compensate for large negotiated price reductions.
Beginning in 2025, manufacturers must pay 10% discounts in the initial coverage phase and 20% in the catastrophic phase under the redesigned Part D benefit. However, drugs selected for IRA negotiation are exempt from these discounts.
For high-cost drugs with significant catastrophic-phase utilization, avoiding the 20% discount can materially offset revenue losses. This is not a volume-driven recovery but a liability reduction mechanism that must be modeled carefully by benefit-phase distribution.
While CMS announced list price discounts ranging from 38% to 79%, the more relevant comparison is to pre-IRA net prices (after rebates). Analyses show:
- Round 1: ~22% average reduction from pre-IRA net price
- Round 2: ~44% average reduction from pre-IRA net price
The financial impact depends heavily on a drug’s pre-IRA rebate structure. Products with smaller existing rebates will generally experience larger net revenue declines.
The new $2,000 annual cap should improve adherence and reduce patient financial burden. However, research suggests utilization increases are modest—often in the 1–3% range for drugs where cost was a barrier.
While beneficial for patients, adherence gains are unlikely to materially offset 40–50% price reductions.
Finance teams should prioritize:
- Quantifying avoided Manufacturer Discount Program liability
- Using realistic elasticity assumptions (–0.10 to –0.20)
- Modeling adherence gains separately to avoid double counting
- Benchmarking against true pre-IRA net prices
- Including baseline Medicare enrollment growth
- Running structured best/base/worst-case scenarios
Volume growth should be treated as a secondary cushion—not a primary recovery strategy.
