Could lowering the prices of drugs covered by Medicare prevent the discovery of a cure for cancer or Alzheimer’s disease?

For the first time, the federal government has negotiated directly with drug companies on prices for several drugs. The new prices, announced in mid-August, will go into effect in January 2026 and help the Medicare program limit the amount individual patients spend out-of-pocket on prescriptions each year to $2,000.

This historic policy, which has been around for decades, long faced opposition from Big Pharma until Democrats in Congress passed and President Joe Biden signed the Inflation Reduction Act of 2022.

Drug companies have tried to stave off the bargaining policy in the courts after it became law. Their concerns—namely, that these “price controls” would stifle innovation—have resonated with Republicans and political commentators with the recent finalization of negotiated prices. With less profit, companies like Pfizer and Merck say, it will be harder to hire scientists, invest in lab space and organize clinical trials to test future drugs.

It’s a terrifying proposition: that by trying to control drug prices for 67 million Medicare patients, we may be unwittingly preventing the development of future drugs that could save lives. That means, if we’re not explicitly saying so, that we’re jeopardizing a cure for cancer, Alzheimer’s or some other terminal illness.

But we have good reason to believe that the current policy won’t have such a compromise anytime soon. First, pharmaceuticals are incredibly profitable, and these negotiated prices, while potentially reducing profit margins, shouldn’t completely undermine the incentive to innovate, according to several key industry studies. Second, if we’re concerned about future innovation, we should focus on making drug development cheaper—and that’s one area where AI shows promise. By identifying the best candidates for potential treatments early in the research process, we could speed development and continue to drive down costs—without losing out on tomorrow’s breakthroughs.

The argument against reducing profits usually goes like this: Drug companies spend a lot of money developing drugs, including drugs that never make it to market because they don’t prove effective. Once they have a new, effective drug to sell, they have to make a lot of money to cover their development costs, and even more so they can take the profits and invest more money in research and development for the next generation of drugs.

Most other wealthy countries, such as Australia and the United Kingdom, use the central role of government in the health care system to negotiate lower prices while also supporting their own sectors of medical innovation. But in the U.S., before the IRA became law, prices were more left 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 obscured and increased the prices of drugs for Americans. As a result, the U.S. pays by far the highest drug costs in the world.

As a result of what we pay, Americans usually have priority access to new drugs. But this early access is only useful if patients can afford the drugs. Too often, they can’t.

But the whole point is that the whole premise is flawed. When the Congressional Budget Office reviewed the bill before it passed, its analysts said they didn’t expect it would have a significant impact on future drug development. The need to cover research and development costs doesn’t explain, at least not entirely, America’s high drug costs, according to a 2017 analysis published by Health mattersa scientific journal devoted to health care research.

The study—by Nancy Yu, Zachary Helms, and Peter Bach of Memorial Sloan Kettering Cancer Center—determined the excess prices paid in the U.S. compared with other wealthy countries. They called this price the U.S. “premium” for R&D. They then calculated how much revenue this premium generated for the world’s 15 largest drugmakers and compared it to the R&D spending of each company.

They found that in other countries, the average prices of drugs on the list were 41 percent of the net prices paid in the U.S. Big Pharma made $116 billion a year from these excess U.S. prices. That same year, drugmakers spent $76 billion on research and development. These figures suggest that drug companies can afford to avoid such a premium. “There are billions of dollars left over even after global research budgets are met,” the authors wrote.

At some point, the expectation of lower revenues could start to make the industry less willing to invest in new drugs and take riskier bets with potentially large payoffs. But are we close to that point? Whatever objections these companies may raise, it may be more telling to look at what they do than what they say.

Last year, Richard Frank and Ro Huang of the Brookings Institution looked at the business decisions drugmakers have made since the bargaining rules became law. The researchers took into account mergers and acquisitions, another way that big pharma companies discover new drugs (usually by buying a promising start-up that has already done the research and development).

Frank and Huang found little evidence that drug companies were expecting a big hit to their revenues from the changes in the negotiation process. If anything, they found increased deals for drugs in both early- and late-stage trials. Total M&A spending was not noticeably affected, and some recent earnings reports expressed optimism about the future.

That makes sense: The IRA stipulated that Medicare’s negotiating authority would be limited and phased in gradually. For the first year, Medicare could select 10 drugs to negotiate. The program could add another 15 next year, and another 15 the year after that.

We have good reason to believe that we can afford to pay lower prices for more drugs. But it would still be nice if we could develop drugs faster and therefore cheaper. That could naturally lower prices while still getting new drugs to people in need. Win-win.

There may be ways to simplify the approval process and criteria for more drugs. Writer Matt Yglesias discussed several options in his newsletter that Congress and the FDA should consider, including being more open to data from clinical trials conducted in other countries (where studies can often be done at lower cost).

But science is the biggest hurdle for new drugs. It can take scientists years to figure out how diseases work, what their biological underpinnings are, and thus develop hypotheses about potential candidates for intervention. It can take decades to go from basic research that uncovers those building blocks to clinical trials that secure FDA approval. The FDA only considers something that actually works. That’s why big pharma spends so much on acquisitions; even with all their resources, there’s no guarantee that internal scientists will find a promising treatment candidate before an outsider does.

The best way to maximize our R&D resources, to get the most bang for our buck when we’re doing expensive human trials, is to identify the most promising candidates early on. But we’re dealing with a huge amount of information: the library of genetics that every human carries around. So drugmakers are turning to AI to help sort through it.

Leading antibiotic resistance researchers have taught computers to hunt everywhere, even in extinct animal DNA, for molecules that might hold promise in treating bacteria that have become difficult to treat with conventional drugs. Longevity advocates have similar faith in AI. New startups like Recursion Pharmaceuticals, profiled by STAT, have built their entire businesses around using AI to find potential drug candidates, including ones that sit on Big Pharma shelves and could be repurposed to treat new conditions.

Whether these AI aspirations will pay off remains to be seen. But they are yet another reason for optimism.

Too often, the conversation about drug prices is framed as either/or. Either lower prices or new drugs, not both. That’s a false choice.