Health Economics for Builders and Backers, October 2026

What’s New and What Matters this Month

Is the unmet need in the primary prevention of cardiovascular disease still large enough for novel therapeutics to be worth it to society?

In a new analysis, we quantified the gaps in health-adjusted life expectancy, caregiver requirements, medical costs, and workforce participation between someone at high risk for cardiovascular disease (CVD) and a comparable person from the general US population. We then estimated how much societal value could be created if innovation was able to close those gaps.

We calculated a 1.5-year gap in health-adjusted life expectancy between those at high-risk for CVD and the general population. Fully closing this gap could create approximately $650,000 to $2,100,000 in value per person at high risk for CVD. Beyond improving health, closing the gaps could free up approximately $1,300 worth of disease-related caregiver time, avoid approximately $90,000 in CVD-related healthcare costs, and generate more than $23,000 in additional labor production per person at high risk for CVD. These estimates should not be interpreted as a price for a CVD primary prevention therapy, but rather the magnitude of the unmet need and the potential value of closing it.

We created an infographic to summarize this opportunity for innovation in the primary prevention of CVD and it can be found here.

For builders and backers: Safe and effective therapeutics for the primary prevention of CVD could still create enormous societal value. The societal value a therapeutic could create would extend far beyond its exclusivity period and would continue to generate societal returns long after its “high” price tag.

What evidence drives the value proposition of a drug for the primary prevention of CVD and should be collected as part of the evidence package?

The primary clinical endpoint that supports the pharmacoeconomic value proposition is the treatment’s effectiveness reducing the first major adverse cardiovascular event (MACE). Although this clinical endpoint is already commonly included in the evidence package, it is the baseline risk of experiencing a first MACE and the downstream consequences of a MACE (e.g., mortality, quality of life decrement, health system costs) that drive the health economic value proposition. Therefore, evidence on the cost, quality of life, and mortality associated with each of these events, in addition to the baseline risk of each event, is necessary to support the value proposition.

For builders and backers: Some evidence to support the value proposition will likely come from outside the trial such as the health and economic impacts of each of these cardiovascular events. The clinical evidence package can be supplemented with evidence from the literature, claims databases, and real-world evidence to gather data to support market access activities in addition to evidence for regulatory approval.

How big is 340B and should biotech care?

In this month’s episode of Perspectives by the Leerink Center for Pharmacoeconomics, I was joined by Sabrina Aery of Aery Policy & Access Partners for a 340B 101. The whole episode is worth a listen. Sabrina shared some data at the very beginning of the episode about the size of the 340B program and why it matters for biotech executives and investors. She noted that in 2025, 340B purchases reached $100 billion (at the discounted 340B prices) and the program has grown 22% year over year. She also cited estimates put out recently by the Berkeley Research Group that 340B prescriptions represent more than 25% of the total prescription market. 

For builders and backers: 340B is large enough to impact commercial assumptions. Any outpatient covered drug can be a 340B drug. The 340B ceiling price is calculated similarly to the Medicaid price.

How does 340B impact the economics of a drug?

Primarily by the discount off the list price for the 340B drug which translates to the net price ultimately received by the drug’s manufacturer. Sabrina estimated that 340B discounts now represent around 20% of the drug manufacturers’ gross-to-net outlays. She also cited another estimate put out recently by the Berkeley Research Group that the average 340B discount was 57% off the list price. Importantly, 340B can apply to any covered outpatient drug. Exposure may be particularly significant for oncology drugs, immunology drugs, and anti-infectives as suggested by a recent Congressional Budget Office report identifying therapeutic areas with a high volume of 340B purchases.

For builders and backers: The 340B ceiling price is calculated similarly to the Medicaid price and thus is priced at a substantial discount to the list price and impacts the net price ultimately received by the drug’s manufacturer. As the program has grown, likely so has its portion of the drug manufacturers’ gross-to-net outlays.

Why is 340B exposure difficult to estimate?

There are challenges estimating the size of the discount, the growth of the program, and which utilization is subject to the program. Because 340B eligibility may be determined after a prescription is dispensed, manufacturers might have to triangulate across multiple different data sets to understand exposure. A related issue Sabrina discussed throughout the episode was the potential for unintended duplicate discounts/rebates. Sabrina provided three questions that can be asked to assess 340B exposure: What data are available on prescribing and dispensing locations? What 340B growth rate is assumed in long-term forecasts? And can rebate invoices be overlaid with 340B transactions to identify potential unintended duplicate discounts/rebates?

For builders and backers: Assessing 340B exposure may be more complicated than simply coming up with what 340B percentage is realistic to assume. Understanding what that assumption is based on, how it is expected to change over time, and what data will eventually be available to validate it may be necessary. Data quality and gross-to-net modeling become increasingly important to understand the economics of a product.

How does 340B interact with other drug pricing policies?

The branded drug pricing framework in the US is complex and increasing in complexity over time. Drug manufacturers now also need to consider how 340B interacts with maximum fair prices established through Medicare Drug Price Negotiation and with emerging Most Favored Nation models while also attempting to reduce multiple discounts or rebates inadvertently paid on the same utilization. At the end of the podcast episode with Sabrina, she highlighted HRSA’s pilot of a 340B rebate model for the drugs with maximum fair prices as one example of policymakers attempting to reconcile these overlapping obligations.

For builders and backers: As you decipher the impacts and economics of new drug pricing policies, you also have to consider how they interact with 340B. As the US branded drug pricing system becomes even more complicated and interconnected, how 340B factors into these new policies and proposals must be considered.

How quickly does FDA approval turn into broad insurance coverage for rare disease drugs?

A poster presented at this month’s NORD Breakthrough Summit by Ivy Leong and researchers at the National Pharmaceutical Council examined commercial health insurance coverage patterns one year after FDA approval for select orphan drugs. Their sample included 50 orphan drugs (single-indication, non-oncology) that received FDA approval from January 2019 to June 2025. On average, it took nearly 8 months for insurance coverage to start and 12 months for coverage to extend to more than half of the covered lives. Here is the key finding from their poster: “By 12 months after approval, 66.6% (33/50) of drugs achieved coverage for at least 50% of covered lives, and 32% (16/50) achieved coverage for at least 80% of covered lives.” They found that rare disease drugs that received Priority Review and rare disease drugs that did not have therapeutic competition were quicker to gain coverage within one year of regulatory approval.

For builders and backers: FDA approval does not translate into immediate or broad market access. Even for rare disease drugs, the time between regulatory approval and insurance coverage can be lengthy. This has implications for how uptake is estimated after launch. The lag between regulatory approval and broad coverage may be shorter for rare disease products that have received FDA Priority Review or that do not have therapeutic competition.