In the early 1990s, Katalin Karikó was obsessed with an idea most of her fellow scientists dismissed: Could messenger RNA, or mRNA, a genetic molecule that helps cells synthesize proteins, be harnessed to create new kinds of treatments?
She believed that if used correctly, mRNA could instruct cells to produce their own medicines, transforming how we fight diseases. But grant after grant was rejected. Reviewers at the National Institutes of Health were skeptical of her work. Her career stalled. She was demoted. Yet she kept going through sheer grit and some timely lifelines from colleagues. Her research changed the course of the Covid-19 pandemic — and she won a Nobel Prize — but only after being delayed by a decade because our system was so risk-averse.
Scientists have been complaining for years that the way we fund science is flawed. Researchers are too often waiting up to 20 months for grant funding, an eternity in fast-moving fields like genetic engineering. Project leaders report that nearly 50 percent of their time is spent doing paperwork and other administrative tasks. The average age at which scientists receive their first traditional N.I.H. grant is 43.
Earlier this month, thousands of scientists marched on Washington to defend science from Elon Musk’s Department of Government Efficiency, as staff reductions at the N.I.H. and National Science Foundation and steep cuts to biomedical funding roiled the scientific establishment. But it’s difficult to fully defend the status quo, which made it hard for a scientist like Karikó to pursue her visionary work.
At the same time, I fear this administration’s current approach will make things worse. The N.I.H.’s new policy to cap what it pays universities to cover “indirect costs” on grants (for things like utility bills, research facilities and administrative staff) to 15 percent will amount to a $4 billion cut in biomedical funding per year if it holds up in court. It could force universities to lay off researchers and shutter labs. Some universities have already frozen hiring, and important long-term studies have been cut short.
Right now, DOGE is treating efficiency as a simple cost-cutting exercise. But science isn’t a procurement process; it’s an investment portfolio. If a venture capital firm measured efficiency purely by how little money it spent, rather than by the returns it generated, it wouldn’t last long. We invest in scientific research because we want returns — in knowledge, in lifesaving drugs, in technological capability. Generating those returns sometimes requires spending money on things that don’t fit neatly into a single grant proposal.
While it’s true that indirect costs serve an important function, they can also create perverse incentives: When the government promises to cover expenses, expenses tend to go up. But instead of slashing funding indiscriminately, we should be thinking about how to get the most out of every dollar we invest in science.
That means streamlining research regulations. Universities are drowning in bureaucracy. Since 1990, there have been 270 new rules that complicate how we conduct research. Institutional Review Boards, intended to protect people from being unethically experimented on in studies, now regularly review low-risk social science surveys that pose no real ethical concerns. Researchers generate reams of paperwork in legally mandated disclosures of every foreign contract and collaboration, even for countries such as the Netherlands that present no geopolitical risk.
We must also rethink how we select scientific research to fund. The Trump administration’s nominee to run the N.I.H., Jay Bhattacharya, has written about how the agency isn’t funding cutting-edge science at the rate it once did. He’s right. The current grant process is far too slow, rigid and risk-averse. We should experiment with rapid-turnaround projects and “golden tickets” — which allow grant reviewers to greenlight unconventional ideas — and implement a streamlined review system that starts with a two-page pitch instead of a 50-page proposal.
Much of that cutting-edge science is now coming from outside of traditional academic labs, and the N.I.H. is struggling to support it. Organizations like Janelia Research Campus, the Arc Institute and a whole class of nonprofit start-ups called focused research organizations are instead using philanthropic dollars to build tools that could accelerate scientific progress. The Arc Institute, which does not get funding from the N.I.H., just released an artificial intelligence model called Evo 2, which is trained on DNA the way ChatGPT is trained on language. Evo 2 can predict if specific genetic mutations are harmful or help design new gene-editing systems, which could treat disorders including cystic fibrosis.
Projects like Evo 2 are increasingly the future of science, and they require infrastructure at a scale that traditional N.I.H. grants were never designed to support: massive computing clusters, specialized machine learning engineers and multimillion-dollar lab equipment.
The N.I.H. should pioneer a new funding mechanism to support scientific organizations with the flexibility to build that kind of infrastructure. In other words, the future of scientific discovery will likely require more spending on certain kinds of indirect costs, and less on others. Researchers should spend less time writing grant reports and more time exploring unconventional hypotheses.
Dr. Karikó’s story should force us to rethink what efficiency really means in science. It isn’t primarily about the dollars we could save — it’s about the breakthroughs we could be missing.
The post American Science Should Take a Lot More Risks appeared first on New York Times.
