Half Full at White Oak

We hear a great deal about disruption at the FDA. We hear almost nothing about the repair underneath it, which is the part that may outlast the noise

I. The two clinics

In the summer of 1865, the Hungarian obstetrician Ignaz Semmelweis was committed to an asylum in Vienna under circumstances that remain disputed and grim. Within two weeks he was dead, at forty-seven, of “blood poisoning,” an infection of nearly the same family as the one he had spent his life trying to prevent. The man who discovered how to stop women from dying of childbed fever died of sepsis, in confinement, largely disbelieved.

Two decades earlier he had been a junior physician at the Vienna General Hospital, which ran two maternity clinics side by side, the first staffed by physicians and medical students, the second by midwives. Women were admitted essentially at random, by the day of the week, and yet the two clinics produced wildly different outcomes. In the first, maternal mortality from puerperal fever hovered near one in ten, and in bad months worse; in the second, a few corridors away, it ran closer to one in twenty-five. The women knew, and they begged for the midwives’ clinic. Some preferred to give birth in the street.

Semmelweis worked the difference like an engineer, ruling out climate, crowding, delivery position, the route of the priest, every fashionable explanation in turn. What remained was the thing no one wanted to name: the physicians, unlike the midwives, performed autopsies and then walked from the dissection room to the delivery ward with nothing more than a cursory rinse. He ordered handwashing in chlorinated lime, and mortality in the first clinic collapsed toward one or two percent within months.

The data was overwhelming and the intervention nearly free, and still it did not spread, not for years, because accepting it meant accepting something intolerable: that the doctors were the vector, that the healers carried the disease from one bed to the next on their own hands. Being right was not enough. Against institutional inertia, it almost never is.

An institution adopts a change only when the change becomes legible in the terms it already uses to keep score. I have come to think this is the single most important thing to understand about any institution, the FDA at this moment included, and it is also what the current coverage least understands. The visible story is disruption; the consequential one is quieter, the conversion of a useful idea into an institutional obligation, the moment a thing that can be done becomes a thing the agency is responsible for doing.

II. One slide

The FDA is now narrated through rupture: reductions in force, reorganizations, senior departures, the accumulating evidence of an agency under strain. Read enough of it, and the conclusion begins to feel foreordained: that the agency is being hollowed out and alarm is the only honest posture. Some of that alarm is warranted, because a public health agency is not an abstraction, and its missteps can eventually reach the bedside.

But there is another account, harder to see because it leaves fewer public traces, and I want to make it from the inside, from the years I spent there, because that is where I learned how reform actually moves through a scientific bureaucracy: slowly, unevenly, and only when a working idea is translated into a form the institution can own.

Some years ago I gave an hour-long talk at the National Academies on the use of artificial intelligence in premarket safety surveillance, and for a subject that invites grand claims I had prepared none. I had one slide for a one-hour talk, a photograph of a computer monitor fringed on every side with yellow sticky notes.

This, I told the room, is how premarket safety is actually done at the FDA. There is no surveillance database behind it. The seven-day and fifteen-day expedited safety reports, the ones a sponsor is legally bound to file when something serious, suspected, and unexpected happens to a patient on an investigational drug, arrive as PDFs or by fax, and are read by a person and remembered, or not, on paper pressed to the edge of a screen. Before we can have a serious conversation about AI, I said, we have to get to data, just data, because the ability to draw a bar graph would already be a profound change.

The room laughed, because the line sounded like exaggeration. It was not.

Stay with that fact and it stops looking like inefficiency. At the investigational stage, before a drug is approved for anything, safety is the FDA’s central statutory authority; efficacy is the sponsor’s burden to prove later, at the NDA or BLA stage, if the program survives the valley of death where most INDs vanish. Safety is the lever the law hands the agency over a drug in human testing, the single hook it is empowered to act on, and behind that lever, for all of the agency’s modern history, sits no real surveillance at all. Sticky notes on a monitor, notes on paper, a spreadsheet someone started and never finished, a reviewer turning to the reviewer at the next desk to ask whether they had seen the same event and whether it meant anything: institutional memory carried in conversation, which is to say carried nowhere durable. What is remarkable is how well the reviewers did anyway, holding in trained judgment what the system gave them no instrument to hold. The deficit was never theirs.

Worse, the machine produced volume without proportionate knowledge. The oncology office was receiving thousands of expedited reports a year, and in an audit we published, we drew a random sample of 160 and read each against the law’s three-part test: serious, unexpected, a suspected reaction to the drug. Twenty-two qualified, fourteen percent; the other 86% were individual case reports that, stripped of any comparator or denominator, could neither raise a true alarm nor retire a false one. The system was at once overloaded and under-informed, activity in abundance and knowledge in deficit.

This is one of the things INFORMED, the data science incubator I founded at the FDA, set out to repair. We built the other version of premarket safety, structured and machine-readable and near real-time, a system that treated a safety report as a row in a dataset rather than a page to be filed and half-remembered, and it worked, not on a slide but on real reports, in conditions close enough to production that the result was a demonstration and not a promise.

Then I made the mistake some institutions teach you to stop making. I brought people at the FDA a number.

At full implementation, by our estimate, structured digital safety reporting would return to the agency at least 500 full-time-equivalent hours a month, five hundred hours of labor lifted off transcription and handed back to judgment. I thought the number would do the work for us, since it was, after all, large enough to seem self-evident.

It did very little.

It took our team an embarrassingly long time to understand why, and that understanding is among the most useful things I carried out of the building. Efficiency is not the FDA’s native currency. No one’s mandate there is measured in hours saved, and no career is made or ended by labor returned to the system or capital reallocated to taxpayers. The agency’s currency is caution, scientific defensibility, and above all the avoidance of the catastrophic miss, the approval that should never have happened, and I had walked in with a strong answer to a question almost no one in the room was paid, promoted, blamed, or remembered for asking.

We had brought Semmelweis’s basin to a room that had not yet been shown what was on its hands. It was not a failure of evidence, nor a failure of the people in it, but a failure of translation: we had shown the system worked in a pilot with large sponsors, but we had not yet made it legible as something the agency was responsible for owning.

III. Where good systems go to wait

A pilot can live on ingenuity, charisma, borrowed staff, and the temporary suspension of normal rules; infrastructure cannot. The moment a pilot must become infrastructure, it needs three things an incubator cannot grant: a permanent owner, a budget line that survives the next reorganization, and a mandate that crosses the boundary between offices with rival incentives. An innovation that belongs to everyone in general belongs to no one in particular, and that is where good ideas go to wait, not in a laboratory but in a gap in the org chart, the institutional form of forgetting.

We built several things that went there to wait: the structured safety system from that slide; the early scaffolding for an expedited IND process, meant to compress the dead time between an investigator’s readiness and an active application; real-world evidence pipelines; biosensor work, the first attempts to gather evidence closer to the patient and farther from the spreadsheet; AI infrastructure, in the pre-LLM era; the harmonization of the agency’s data into a single system. Each one worked, and some stalled the instant their champions left, for reasons that had nothing to do with technical merit and everything to do with custody.

This is why the present moment is more interesting than the headlines allow.

IV. Surgery on the living

Against the grain of the political temperament, I have begun to feel something close to optimism, and the reasons are not atmospheric but concrete: decisions, made by named people, in the last two years, to turn orphaned capabilities into assigned responsibilities.

Start with digital safety reporting, finally being implemented, not because the technology suddenly matured, since it never needed to, but because the only thing ever missing was at last supplied: someone with the authority, willing to spend their political capital, decided to own it and make it the standard across the agency. Once you know to look for that kind of decision, the pattern surfaces everywhere.

The agency’s leadership has lately been dismantling barriers that stood for years. In December 2025, it removed one of the oldest, issuing guidance that lets sponsors submit real-world evidence without first stripping and re-identifying patient data, a technical change with large consequences for the clinical registries and claims databases that had been sitting just out of reach. At nearly the same moment, and for the first time, the agency began to publish an honest accounting of what real-world evidence is actually entering its review pipeline, and the numbers, though modest and easy to over-read, point in a direction that is not in doubt. Protocols submitting real-world data to the drug center roughly tripled in a single year, from 11 to 31, and sponsors are beginning to file studies that use such evidence not merely to watch a drug after approval but to help establish that it works in the first place. Externally controlled designs, all but absent the year before, have started to appear, the approval packages of the decade’s end taking shape now, and the running tally of approvals informed at least in part by real-world evidence has climbed past a dozen.

ISTAND is the same story in a different register, the qualification pathway the agency built for tools that fit through no existing door: digital measures, wearables, AI methods, in silico models of human organs. Its first in silico submission, an AI model of the liver that predicts whether a drug candidate is likely to cause injury, was accepted not long ago, and this matters more than it sounds, because the reason real-world evidence submissions still show almost no contribution from digital health technologies is not that the sensors fail but that there has never been a qualified road from a wrist to a regulatory decision. ISTAND is that road, finally being paved.

An expedited IND initiative has resurfaced too, no longer an incubator sketch but a formal pilot, a rolling submission platform meant to shorten the path from drug identification to first-in-human study and to minimize the clinical holds that stall it. And there is the real-time clinical trial initiative, which I wrote about in The Ship and the Signal, that can reduce the latency between data and the regulator while leaving every safeguard in place.

None of this is disruption for its own sake; it is something harder, closer to surgery on a beating heart, the target moving under the hands while the stakes refuse to pause. That is the work underway at the FDA.

V. The bar that does not move

The agency today is working to modernize its substrate, the speed and structure with which evidence moves, the latency with which a signal is seen, the durability of the record on which judgment rests, while the judgment itself must remain as demanding as it ever was. The good version of these reforms makes the agency faster at being careful, not faster at being permissive.

Even those who concede the agency needs transformation will warn, reasonably, against throwing the baby out with the bathwater, and they are right that there is a baby. The agency’s scientific judgment, its institutional caution, its hard memory of every drug that looked good and was not, is precious and very nearly irreplaceable, and a careless hand could pour it out in a single season and fail to rebuild it in a generation.

But the idiom conceals its central premise, that the bathwater is inert, unpleasant perhaps but harmless in itself, and Semmelweis is the standing refutation, because in his wards the medium was not neutral. The contamination was the thing hurting the patients. The legacy substrate at the FDA, the fax and the PDF and the 86% of reports that are noise, is not merely old; it is a hazard to the very people the agency exists to protect, because a signal seen too late is not an administrative delay but potentially a patient harmed. To guard the bathwater in the name of the baby is a category error, and inaction is not prudence but a quieter way of choosing the greater risk.

The task was never to choose between the baby and the bathwater. It was to change the water without losing the child, and that is the work ahead, and the discipline it asks for: not razing the ward, not denying the fever, but operating on the living.

So I hold both halves of the glass, which is the only honest way to hold it. The disruption is real, and some of it may leave scars; the reinvention is also real, and a meaningful share of it is precisely the kind the agency needed and could not deliver on its own, for structural reasons that had little to do with money or talent. The question is whether the reinvention becomes durable before the disruption becomes the whole story.

VI. How an institution knows

Semmelweis had a system that worked, and the hard part was getting the institution to fold it into its own self-description: this is how we know, this is how we remember, this is how we will notice when reality begins to contradict us. That is the deepest meaning of modernization, not the substitution of software for judgment but the modernization of the way institutions know. A regulator that receives evidence as paper can deliberate only at the speed and fidelity of paper; a regulator that holds evidence as memory can forget; a regulator that receives evidence as data can still be wrong, but it can be wrong in ways that are visible, contestable, and correctable.

Semmelweis’s basin was never only a basin. It converted a moral and scientific fact into a routine, something a hospital performed every day without having to be persuaded again. The new instruments arriving today; AI, sensors, real-world data, real-time trials, earn their place only if they do the same work: forcing the institution to see its own contact with evidence more clearly, what it knows and what it is missing, where delay has become risk, where caution has curdled into concealment, where noise has been mistaken for vigilance.

Half full is the only honest reading, not because the glass is full, nor because the problem is solved, but because the agency has begun to take ownership of the instruments through which it sees the world. Semmelweis could not save himself, and was disbelieved to the end, yet the practice he could not make them accept outlived the person who showed them the stain, and that is the asymmetry worth betting on and the reason to do the work.

In public health, as in medicine, repair begins not with the claim that the hands are clean, but with the discipline that makes unclean hands impossible to ignore.