For three days, Alex Jofriet drank one 8-ounce glass of milk per day. This was a big deal because he hadn’t touched the stuff in years. Jofriet has Crohn’s disease, a poorly understood chronic inflammation of the intestine. Eat the wrong thing, or even too much of the right thing, and he would pay the price: hours in the bathroom wracked with stomach pain, gas and diarrhea.

But Jofriet took the risk. He and his doctor, Shehzad Saeed, decided to set up an experiment, and Jofriet would be the only subject. For those three days, he would drink milk like he wasn’t afraid, like he hadn’t spent the past eight years negotiating a careful truce with his digestive system. He would drink milk and record how he felt on those days. How many bowel movements did he have? Was there blood in his stool? Did he have stomach pain and bloating? Then Saeed would statistically compare Jofriet’s health on the days he drank milk with the days he didn’t.

This is the basic outline of a randomized control clinical trial — the gold standard of medical research and the basis of most of the medical facts we hear from doctors and read in magazines like this one. It’s the best way we know of to learn about how our bodies work (and don’t work) and what it takes to fix them.

One way to correct for the gaps the gold standard leaves in our knowledge is the “N of 1” trial, where the number of participants (N) is one instead of hundreds or thousands of volunteers. That one person works with the doctor to test a narrow hypothesis — for example, “I think drinking milk will make me feel sick. Am I right?” There are still controls. Ideally, there are still placebos. But at the end, what you get is a patient-specific, individualized answer. It’s a process shown — by controlled clinical trials, no less — to improve patient outcomes. And scientists working with these studies today, including Saeed, are almost invariably enthusiastic about N of 1’s potential.

What makes a great idea such a flop in practice? Saeed and other researchers think they’ve figured out the problems. And this time, instead of fading away yet again, N of 1 is here to stay.

Trust but Verify

Alex Jofriet was always a picky eater. But somewhere around fourth grade, he got sick, and the casual pickiness — the “wake up in the morning and decide bologna is gross today” kind of pickiness — turned into something else. His stomach began to hurt. He spent hours on the toilet, suffering recurrent bouts of diarrhea.

Between that and throwing up much of what he ate, it was just easier not to eat. By the time everyone realized this was more than just a fussy distaste for a few foods or a bad stomach flu, Jofriet had lost 20 pounds and was so exhausted that he had to sit down on the shelves at the grocery store to rest. At age 10, the calcium-deficient bones in his back cracked and fractured.

Today, at 18, he’s enjoying the best health he’s had since grade school. Nobody is exactly sure why his illness flared up in horrible ways throughout junior high and high school, but after some experimentation with his doctor, he’s finally found a medication that keeps his Crohn’s under control. And that has left Jofriet in an awkward position. Increasingly healthy, he doesn’t want to do anything that could jeopardize that health. It’s not unusual for Crohn’s patients in his situation to experiment informally, jumping mostly by instinct into fad diets, supplements, new foods and alternative therapies.

That kind of experimentation isn’t limited to Crohn’s patients. Everybody has tried one-person experiments at some point. You want to lose weight, so you try the low-carb diet you keep hearing about on the news. You have arthritis, and you think acupuncture might relieve your pain better than medication. Your kid has a cold, and taking a friend’s advice, you give him some zinc. In that way, N of 1 trials are nothing new.

This distinguishes formal N of 1 experiments from basic, everyday decision-making about health. Some are more formalized than others, but the best have three important elements that don’t exist when patients, or patients and their doctors, are just trying things out, says Naihua Duan, a retired Columbia University biostatistician and part of a team of experts convened by the federal Agency for Healthcare Research and Quality that recently published a user’s guide to N of 1 experiments.

Psychologists have been running one-person experiments, using some of these basic principles, since the mid-20th century. But the idea of single-subject research didn’t really make the leap to medicine of the body until the early 1980s when Gordon Guyatt, a Canadian physician now known as a founder of evidence-based medicine, began working in an interdisciplinary department at McMaster University in Ontario, with psychologists, biostatisticians, ethicists and clinical epidemiologists all working together.

At the time, he was dealing with a lot of patients whose health experiences didn’t match up with the results of large randomized clinical trials. One of those was an asthmatic septuagenarian whose three prescribed medications didn’t seem to be helping. N of 1, Guyatt realized, could solve that problem.

Guyatt published the results in The New England Journal of Medicine in 1986. “To definitively establish whether or not something works in an individual is kind of a thrill,” he says. “A trial of 1,000 people is a long-term process. Even just recruitment can take three years. There’s a lot of slogging. But N of 1 gets you answers quickly.”

While the improvements in N of 1 patients aren’t always as dramatic, research over the past 20-plus years has produced solid support for the idea that these studies really can help doctors and patients work together to make better decisions. That’s especially true when it comes to chronic illness.

In 1990, when Guyatt and his team published the first review of their work, these were the kind of results they were looking for — experiments that answered a question and changed a patient’s treatment plan. Of the 70 N of 1 experiments they’d done at that point, 50 led to a definitive answer, and 39 percent of those answers led to a change in treatment. Later studies found similar benefits of N of 1 trials.

Today, few people have even heard of N of 1 experiments. When Richard Kravitz, co-vice chair of research in the department of internal medicine at the University of California, Davis, does focus groups to see what doctors think about N of 1 trials, he usually has to start by explaining what an N of 1 trial is.

First and foremost: It’s just plain complicated to do an N of 1 trial. Most doctors have neither the time nor the tools, administrative help or extra funding they’d need to make it work. And in most trials, you also need a placebo, or sugar pill, and the placebo and the drug would need to be disguised so that neither the patient nor doctor would know which was being taken when.

That’s more complicated than it sounds, says Paul Glasziou, who used to run a service that helped doctors design N of 1 experiments at the University of Queensland in Brisbane, Australia.  Despite their simple ingredients, placebos aren’t cheap. “[It] means getting pharmaceutical companies to shut down the usual production system and put in inert powder instead,” he says. For a simple one-off experiment, you could go to a compounding pharmacist to make capsules that hide either the active drug or a placebo, but those pharmacies aren’t common, and they rarely work in bulk. That’s a problem if you’re trying to set up a service where, ideally, lots of doctors would come to get placebos or capsules for hundreds of patients.

Bureaucracy is the second challenge that looms over N of 1. Any time scientists want to do an experiment on a human, they have to get the plan approved by an Institutional Review Board (IRB). N of 1 trials don’t fit into that established bureaucracy in a clearly defined way. The trials aren’t exactly research: Nobody is using them to figure out whether a drug works or is safe before it’s released to the general public. This is just doctors taking approved drugs and figuring out whether they work for specific patients.

When interest in N of 1 experiments began to rebound in the last decade, proponents had to deal with the same problems. Sunita Vohra runs the N of 1 service at the University of Alberta, Canada. Although she got her funding in 2004, she couldn’t launch the service until 2006. The intervening years were filled with prolonged negotiations to convince the university that N of 1 experiments were primarily about improving patient care, not doing research on how drugs and other treatments worked.

Finding Workarounds

But Cincinnati Children’s also streamlined the N of 1 process by discarding placebos and blinding. For instance, when Jofriet did the experiment to see whether drinking milk would make him sick, he and his doctors didn’t create fake “milk” — they knew when Jofriet was drinking milk and when he wasn’t.

Think back to Jofriet’s milk trial. The point of that experiment wasn’t just to see what happened when he drank milk, Saeed says. It was also about emotional and psychological reassurance. Jofriet hadn’t eaten a normal diet in years. Trying milk was the first step toward that. He needed to see himself drinking the milk, just like he needed to see the results: that it wasn’t hurting him.

That’s why N of 1 experiments are worth doing, even if you can’t do them perfectly, says Michael Seid, director of health outcomes and quality of care research at Cincinnati Children’s Hospital. From Seid’s perspective, the personalization offered by N of 1 experiments is not only a cheaper and lower-tech way to achieve personalized medicine, it is even better than the personalization you get with the high-tech tools.

Single-subject trials allow you to personalize the outcome, not just the treatment. With the help of N of 1 experiments, Jofriet could decide that “being able to drink milk” was the desired outcome, and he and his doctor could figure out how to make that happen.

That’s changing, Duan says. Over the last decade, medical researchers have begun to put more of an emphasis on doing research that serves patients’ needs directly. Some of that happens in the form of large placebo-controlled clinical trials aimed at answering questions such as which of two existing treatments for the same disease produces the best results for the least money. The trend toward patient-centered research is reshaping the way medical studies are done. In 2008, the movement got its own journal, The Patient: Patient Centered Outcomes Research. In 2010, the Affordable Care Act established the Patient Centered Outcomes Research Institute.

N of 1 experiments fit neatly into this shift in thinking, and this could be the catalyst that makes these experiments succeed where they had once failed. Duan certainly hopes so, and he’s using the opportunity to make sure more people learn about N of 1 experiments and what they can do. This summer, he and Kravitz began an ambitious study comparing N of 1 experiments with standard medical treatment in almost 250 patients. The study represents one of the first times that N of 1 has gone head to head with traditional health care. Depending on what Duan and Kravitz learn, the study could lead to a world with more Alex Jofriets — and more opportunities for people to improve their health, one patient at a time.

[This article originally appeared in print as "Singled Out."]