The Peter Attia Drive - #393 ‒ AMA #85: A guide to medications and supplements: determining what to take, what to skip, and how to know if they're working for you

Episode Date: May 25, 2026

View the Show Notes Page for This Episode Become a Member to Receive Exclusive Content Sign Up to Receive Peter's Weekly Newsletter In this "Ask Me Anything" (AMA) episode, Peter explores how to think critically about medications and supplements by focusing not on whether an intervention is inherently "good" or "bad," but on whether it makes sense for a specific person with a specific problem. He explains why clearly defining the problem matters more than choosing the intervention itself, how the intended purpose of a medication or supplement should influence the standard of evidence required, and why mechanistic reasoning alone is rarely enough to justify taking something. Peter also examines how baseline risk shapes the true benefit of an intervention, why relative risk statistics can be misleading without proper context, and how to weigh not only side effects, but also cost, inconvenience, and opportunity cost when deciding whether something is worth taking. Additionally, he discusses practical ways to evaluate whether a supplement is actually having a meaningful effect, how to think about discontinuing therapies, why supplements deserve far more skepticism than they often receive, and the small group of over-the-counter supplements he believes may offer a reasonable risk-reward trade-off. If you're not a subscriber and are listening on a podcast player, you'll only be able to hear a preview of the AMA. If you're a subscriber, you can now listen to this full episode on your private RSS feed or our website at the AMA #85 show notes page. If you are not a subscriber, you can learn more about the subscriber benefits here. We discuss: How to properly define health problems before considering medications or supplements [1:45]; How the intended purpose of an intervention should determine evidence standards and risk tolerance [5:00]; Understanding the hierarchy of evidence for medications and supplements and avoiding the mistake of treating weak evidence as clinical proof [9:00]; Why mechanistic explanations can be misleading when evaluating longevity interventions [13:15]; How baseline risk—and the distinction between relative and absolute risk reduction—changes the real-world benefit of medications and supplements [18:15]; Thinking beyond side effects: the many forms of downside associated with medications and supplements [22:45]; Why medications and supplements require different standards of trust and evidence [26:00]; How to structure meaningful self-experiments with medications and supplements to determine if it's they're working [30:30]; How to monitor the effects of medications and supplements without fooling yourself [32:30]; How to periodically reevaluate and potentially discontinue medications and supplements [35:15]; The biggest risks and failure modes of over-the-counter supplements: efficacy, poor quality control, contamination, interactions, toxicity, and marketing-driven overuse [38:30]; Why the US supplement regulatory system creates unreliable products [41:45]; A practical framework for evaluating medications and supplements [46:30]; Over-the-counter supplements with the best balance of evidence and low downside risk [48:00]; and More. Connect With Peter on Twitter, Instagram, Facebook and YouTube

Hey everyone, welcome to a sneak peek, Ask Me Anything or AMA episode of the Drive podcast. I'm your host, Peter Atia. At the end of this short episode, I'll explain how you can access the AMA episodes in full, along with a ton of other membership benefits we've created. Or you can learn more now by going to peteratia md.com forward slash subscribe. So without further delay, here's today's sneak peek of the Ask Me Anything episode. Welcome to Ask Me Anything, AMA, episode 85. Today we're talking about medications and supplements.

This is one of the topics I get asked about more than almost anything else, and I think it's also one of the easiest areas to go wrong. People tend to ask me whether something is good or bad, whether they should take it or not, but those are, I think, kind of the wrong questions. The right question is whether a specific intervention makes sense for a specific person with a specific problem, and that's what I'm going to try to get to today. So in this episode, we'll cover why defining the problem matters more than picking the intervention. The different jobs a medication or supplement can do and why the evidence bar should move depending on the job.

How to tell strong evidence from weak evidence and why mechanism alone isn't enough. Why baseline risk changes everything and how relative risk can mislead you. How to think about the real downside of taking something. Side effects, yes, but also cost, hassle and opportunity cost. How to determine whether the supplement you're taking is having any real effect, how to stop taking something, why supplements specifically deserve a lot more skepticism than people give them. And finally, the short list of over-the-counter supplements that I think are probably worth the risk-reward trade-off. So without further delay, I hope you enjoy AMA number 85.

Peter. Welcome to another AMA. How you doing? Very well. Thanks. Good. We will get right into it today on AMA all around medications and supplements. So first question, before someone takes any medication or supplement, how do you think that they should define what the problem is in a way that increases the odds that they look for and pick interventions that actually benefit them and reduce risk, opposed to at best waste money and at worse cause other harm that they don't know about. You know, I think this is actually one of the biggest challenges from a sort of mental model standpoint is plaguing most people when they think about supplements in particular, but I think also, frankly, pharmaceuticals.

So people are, I think, typically defining the problem at the wrong level of abstraction. So they'll say things like, I want to be healthier or I want more energy or I want to pursue better longevity. And that challenge is that those are not really actionable problem definitions. They're vague, difficult to measure, very difficult to falsify and things like that. So I would suggest that we reframe this discussion around what would be actionable metrics or actionable parts, right? So one would be a metric that can be studied. Two would be a threshold against which you would measure.

And then I think a third potential one would be a time horizon. So what am I measuring? What level tells me that there's a problem and by extension a solution? And when do I expect that to happen? And so if you can't come up a priori with some sense of those things, you're probably not in a good spot to start anything. So for example, let's use a tangible example. Instead of saying my cholesterol is bad, you would say my APOB is 130 milligrams per deciliter. I want to get it below 60 milligrams per deciliter. And I'd like to do. that in the next six months. Instead of saying, you know, my sleep is bad, you might say it takes me 60 minutes to fall asleep on, you know, four or five nights a week. And I want to make that under 10 minutes to fall asleep within two months. So that's a real problem definition. The next question is the counterfactual. What happens if I do nothing? Does this problem meaningfully increase risk, reduce quality of life, or create some downstream consequence? So I think this question is important because it separates real problems from things that merely, you know, feel actionable.

And it matters because poor problem definition almost guarantees some sort of false positive. So if the problem is vague, almost anything can look like it helped. You sleep a little better one week. Your energy is a little better on Tuesday. One lab improves a little. And now you're telling yourself a story. And we all do this. I mean, we're storytelling machines. And I think that's how people end up taking things for years without ever knowing if they've solved anything real. So I think the rule here could be pretty simple, right? Do not start with the molecule.

Start with the problem. Define tightly enough that you could actually be proven wrong. So if you can't state the metric, the threshold, and the timeline, and even the consequences of doing nothing, you're not really making an intervention decision. You're probably impulse shopping on, you know, your favorite website. And when looking at different medications and supplements, how do you think about and maybe classify the quote-unquote job that they would do? And based on that classification, does it change the evidence threshold you like to see and how much risk you're willing to tolerate? Well, once the problem is defined, I think the next question is asking, okay, what is the purpose of that intervention? And again, it matters because it requires different standards.

So if you don't classify this job as you describe it correctly, you're very likely going to apply the wrong evidence threshold and accept the wrong amount of risk. So I think we could put these into four buckets, disease treatment, symptom relief, risk reduction. And I hate the term, but I think we just need to use it and it's optimization. So they might sound sort of similar on the surface, but they're actually quite, quite different. So if the quote unquote job is disease treatment, the bar is high, right? Does this improve the disease in a meaningful way?

And of course here, you would be willing to accept more downside because the underlying problem is serious and the counterfactual is strong. Presumably if you have a disease and you do nothing, the disease will get significantly worse. But at the same time, you're going to want stronger evidence, ideally hard outcome trials, or at least some well-validated surrogate endpoint, not just a compelling story. Now, if the job is symptom relief, the question is a bit different. Does the person actually feel or function better? And here we're dealing with something that's subjective.

You may be willing to, frankly, tolerate placebo risk, because if the symptoms meaningfully improve and the downside is low, that could still be a reasonable trade-off. If the job is risk reduction, you're treating something that a person can't, can't feel almost by definition. So the evidence bar again here needs to be pretty high. That usually means hard outcomes when available or again, at least a very validated surrogate marker.

And again, not all biomarkers are equal here. ApoB is a very well validated surrogate biomarker, whereas, you know, some vague inflammatory marker or heavy metal is not necessarily going to be in that category as you're, you know, someone's pontificating about detoxification. or something like that. If the job is optimization, then I think skepticism should go up, right? This is where error rates are highest. The person is usually starting from a relatively healthy baseline, and the expected effect is often small. The claims are usually made in a mechanistic way, and there's generally no objective way to determine whether the supplement or medication is

benefiting you, making your ability to basically fool yourself enormous. So I think the challenge and probably the reason we're even doing this episode is in part because most of the longevity interventions are really optimizations masquerading as risk reductions. They kind of borrow the language of prevention, aging, health span, resilience, longevity, but the actual evidence that they put forth looks much more like speculative optimization interventions rather than true risk reduction. And I think this distinction really matters, right? this classification should change both your evidence threshold and your risk tolerance. I think the more serious and concrete the problem, the more downside you may be willing to keep, as I said, and the more speculative the goal, the less downside you should be willing to tolerate. So I guess to summarize that, if you're looking at disease treatment, you want to demand strong

evidence, but you'll accept more risk. If you're looking at symptom relief, you prioritize the actual lived benefit, but watch for placebo and noise and factor in the unknowns about safety. risk reduction, you're going to have to look at validated surrogates or hard outcomes, although the latter tends to be challenging. And if it's about optimization, you're going to default into a skeptical state, especially around safety. So, Peter, let's double click on one of the things you briefly mentioned there, which is kind of evidence when looking at medications and supplements. So when people are evaluating how they're thinking about a medication supplement for themselves, what are common ways that you see people confuse the different tiers of that? evidence and how can people prevent that in practice? So how can people be a little bit more aware so when they're looking at various claims, they start to understand how good those claims are.

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