For the first time, the federal government has negotiated directly with pharmaceutical companies over the prices for a handful of drugs. The new prices, which were announced mid-August, take effect in January 2026, and they will help the Medicare program cap what individual patients spend out of pocket on their prescriptions in a year at $2,000.
The historic policy, which has been floating around for decades, was long opposed by “Big Pharma” until Democrats in Congress passed and President Joe Biden signed the Inflation Reduction Act in 2022.
Pharma tried to stop the negotiation policy in courts after it became law. Their concerns — namely, that these “price controls” will stifle innovation — have been echoed by Republicans and policy commentators with the recent finalization of the negotiated prices. With less profit, companies like Pfizer and Merck argue, it will be harder to hire scientists, invest in laboratory space, and set up clinical trials to test the medications of the future.
Sign up here to explore the big, complicated problems the world faces and the most efficient ways to solve them. Sent twice a week.
It is a harrowing proposition: that in trying to control drug prices for 67 million Medicare patients now, we might inadvertently prevent the development of future drugs that could save lives. Implied, if not stated outright, is that we’re putting a cure for cancer or Alzheimer’s or some other intractable disease in jeopardy.
But we have good reasons to believe that the current policy won’t have such a trade-off any time soon. For one, pharma is hugely profitable, and these negotiated prices, while potentially chipping away at profit margins, should hardly entirely dampen the incentive to innovate, according to a couple of key studies of the industry. Two, if we are worried about future innovation, we should be focused on making it cheaper to develop drugs – and this is actually one area where AI is showing promise. By identifying the best candidates for possible treatments early in the research process, we could speed up development and continue to reduce costs — without losing out on tomorrow’s breakthroughs.
The argument against reducing profits usually goes like this: The drug companies spend a lot of money developing drugs, including some drugs that never make it to market because they don’t prove to be effective. When they do have a new, effective drug to sell, they need to make a lot of money to cover their development costs and then some, so they can take the profits and invest more money into research and development for the next generation of medicines.
Most other wealthy countries, like Australia and the UK, use the government’s central role in their health care system to negotiate lower prices while also fostering their own medical innovation sectors. But in the US, before the IRA’s provisions became law, prices were left more to the free market and the individual negotiating positions of manufacturers, private insurers, the government, and pharmacy benefit managers. Various rebates, kickbacks, and other financing mechanisms often obfuscated and increased Americans’ drug prices. As a result, the US pays by far the highest costs for medications in the world.
As a result of how much we pay, Americans generally get first dibs on new cures. But that early access is only useful if patients can afford the drugs. Too often, they can’t.
But here’s the thing: This whole premise is faulty. When the Congressional Budget Office evaluated the bill before it passed, its analysts said they did not expect a major effect on future drug development. The need to cover R&D costs does not actually explain, at least not entirely, the high costs for medications charged in America, according to a 2017 analysis published by Health Affairs, a health care research journal.
The research — from Memorial Sloan Kettering Cancer Center’s Nancy Yu, Zachary Helms, and Peter Bach — determined the excess price paid in the US compared to other wealthy nations. They called this price the American R&D “premium.” They then calculated how much revenue said premium generated for the top 15 drug manufacturers in the world and compared it to the companies’ respective R&D spending.
They concluded other countries had average drug list prices that were 41 percent of the net prices paid in the US. Big Pharma reaped $116 billion in revenue in one year from these excess American prices. In the same year, drug makers spent $76 billion on R&D. These numbers suggest drug companies can afford avoiding such a premium. “There are billions of dollars left over even after worldwide research budgets are covered,” the authors wrote.
At a certain point, the expectation of lower revenues could start to reduce the industry’s willingness to invest in new drugs and make riskier bets with potentially big payoffs. But are we anywhere near that point? Whatever objections these companies might be raising, it may be more telling to examine what they do rather than what they say.
Last year, Richard Frank and Ro Huang at the Brookings Institution looked at the business decisions drug makers had made since negotiation provisions became law. The researchers specifically considered mergers and acquisitions, the other means by which big drug companies discover new drugs (usually by buying a promising start-up that has already done R&D).
Frank and Huang detected little evidence that the drug companies were expecting a massive blow to their revenues because of changes to the negotiation process. If anything, they found increased transactions for drugs at both the early and late trial stages. Overall M&A spending was not noticeably altered and some recent earnings reports had expressed optimism about the future.
This makes sense: the IRA stipulated that Medicare’s negotiating authority be limited and gradually phased in. For the first year, Medicare was permitted to pick 10 drugs for negotiations. Next year, the program can add another 15 and another 15 the year after that.
We have a sound basis to think we can afford lower prices for more drugs. But still, it would be nice if we could develop drugs more quickly and therefore more cheaply. That could naturally lower prices while still delivering new medicines to people in need. Win-win.
There may be ways to simplify the approval process and the approval criteria for more drugs. Writer Matt Yglesias covered some options for Congress and the FDA to consider in his newsletter, including being more receptive to data from clinical trials conducted in other countries (where trials can often be done at less expense).
But science is the most daunting obstacle to new drugs. It can take years for researchers to even figure out how diseases work, their biological basis, and thereby hypothesize possible candidates for interventions. Moving from the basic research that reveals those building blocks to the clinical trials that secure FDA approval can take decades. The FDA only factors in once you’ve figured out something that actually works. That’s why big drug companies do spend so much on acquisitions; even with all their resources, there’s no guarantee the in-house scientists will find a promising treatment candidate before an outside researcher does.
The best way to maximize our R&D resources, to get the most bang for our buck when we set up expensive human trials, is to identify the most promising candidates at the start. But we are dealing with an enormous amount of information: the library of genetics that every human being carries. This is why drug developers are turning to AI for help in sorting through it.
Leading researchers on antibiotic resistance have trained computers to hunt everywhere, even in extinct animal DNA, for molecules that could be promising in treating bacteria that have become difficult for conventional medicines to treat. Longevity proponents put a similar faith in artificial intelligence. New start-ups, such as Recursion Pharmaceuticals, profiled by STAT, have based their entire business on using AI to find potential drug candidates, including among those sitting on the shelves of Big Pharma that could be repurposed for new conditions.
Whether those AI aspirations will pay off is still unknown. But they provide another reason for optimism.
Too often, the drug pricing conversation is framed as an either/or. Either lower prices or new cures, but not both. It’s a false choice.
