John Ioannidis, M.D., D.Sc.: Why most biomedical research is flawed, and how to improve it

**Peter Attia** (0:11)
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Now, without further delay, here's today's episode.
I guess this week is John Ioannidis. John is by all estimates a polymath. He's a physician scientist, a writer, and a Stanford University professor. He has extensive training in mathematics, medicine, epidemiology. He's just generally one of the smartest people I've ever met and I've had the luxury of knowing John for probably about nine years. And anytime I get to interact with him, whether it's over a meal or more formally through various research collaborations, it's just always an incredible pleasure. John studies scientific research itself, a process known as meta research, primarily in clinical medicine, but also somewhat in the social sciences. He's one of the world's foremost experts on the credibility of medical research. He's the co-director of the Meta Research Innovation Center at Stanford. In this episode, we talk about a lot of things. We talk about his journey from Greece to the United States, but we talk a lot about some of his seminal papers. You're going to see me reference a number of papers, beginning with, I think, one of the most famous papers he's written, although by citation, it turns out to not be the most famous. There's actually papers that even exceed it, which is an amazing paper where he describes, through a mathematical model, why most published research in the biomedical field is incorrect, which is obviously out of the gate, a staggering statement. We go on to discuss a number of his other seminal papers and then really kind of tackle some of the hard issues in medical research, including my favorite topic, nutritional epidemiology.
As always, John is candid and full of insight, so I'm just going to leave it at that and hope that you trust me and make time to listen to this one. So please, without further delay, enjoy my discussion with John Ioannidis.
John, this is really exciting for me to be as close to sitting down with you as I can be during this time. I've been wanting to interview you for as long as I've had a podcast, and obviously we've known each other for probably close to 10 years now. Of course, you first came on my radar in 2005 with a paper that we're going to spend a lot of time discussing today. But before we get to that, how would you describe yourself to people because you have such a unique background?

**John Ioannidis** (3:09)
I think that it's very difficult to know yourself, and I've been struggling on that front for a long time. So I'm trying to be a scientist. I think that this is not an easy job. It means that you need to reinvent yourself all the time.
You need to search for new frontiers, for new questions, for new ways to correct errors and to correct your previous self in some way. So under that denominator of scientists in the works, probably it would be a good place to put my whereabouts.

**Peter Attia** (3:48)
Now, your background is also in mathematics, and I think that's part of my appreciation for you is the rigor with which you bring mathematics to the study of science. And in particular, we're going to discuss some of your work and how you use mathematical models as tools to create frameworks around this. Now, you were born in the US but grew up in Greece, is that correct?

**John Ioannidis** (4:08)
Indeed, I was born in New York, in New York City, but I grew up in Athens.
And I always loved mathematics. I think that mathematics are the foundation of so many things and they can really transform our approach to questions that without mathematics, it would be very difficult to make much progress.

**Peter Attia** (4:29)
How did you navigate your studies? Because you were obviously very prolific in mathematics. If I recall reading somewhere in one of your bios, you even won the highest honor that a graduating college student could win in mathematics in Greece at the time.