Eric Topol on the Creative Destruction of Medicine
Apr 1 2013

Eric Topol of the Scripps Research Institute and the author of The Creative Destruction of Medicine talks with EconTalk host Russ Roberts about the ideas in his book. Topics discussed include "evidence-based" medicine, the influence of the pharmaceutical industry, how medicine is currently conducted for the "average" patient, the potential of genomics to improve health care and the power of technology, generally, to transform medicine.

Eric Topol on the Power of Patients in a Digital World
We're in the middle of a healthcare revolution but it's about more than marvelous life-saving and life-enhancing apps on our smartphone. Eric Topol of the Scripps Translational Science Institute and author of The Patient Will See You Now argues that...
Eric Topol on Deep Medicine
Cardiologist and author Eric Topol talks about his book Deep Medicine with EconTalk host Russ Roberts. Topol argues that doctors spend too little face-to-face time with patients, and the use of artificial intelligence and machine learning is a chance to...
Explore audio transcript, further reading that will help you delve deeper into this week’s episode, and vigorous conversations in the form of our comments section below.


Apr 1 2013 at 9:55am

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Greg G
Apr 1 2013 at 10:25am

Evidence based medicine has the potential to provide us with many badly needed benefits. But even if it can do everything that is claimed for it here (and I think it can) not everyone will agree that it increases their liberty.

Certainly those who recognize that they got better medical outcomes and saved money are likely to agree. But others will experience it as a reduction in the options available to them.

Vast numbers of people today sell and purchase ineffective treatments of all kinds. Evidence based medicine will, and should, result in both government and private insurance supporting a more limited range of treatments to deal with a given set of medical facts.

In many cases the people selling and receiving ineffective treatments will disagree with the consensus interpretation of the evidence. The policy disputes will continue but, in my opinion, this podcast is a step in the right direction towards helping us make better policy decisions. Thank you Russ and Eric.

Apr 1 2013 at 12:45pm

This conversation between Eric and Russ brought out a brief discussion of the profound weaknesses of the discipline of Macroeconomics. Russ summarized it with his statement, “Complexity is not our strong suit statistically.” Eric replied that supercomputers and large amount of data might produce solutions to our difficulty understanding and predicting outcomes in large multi-variable systems.

It strikes me that Eric might be correct. If computers were given relevant data on each person in a system (past patterns of behavior, gender, age, education, occupations, family roles, genome, etc.) along with the environmental data each person will encounter (information, incentives, obstacles, competition, weather, etc) AND that data was run through Micro-economic models, then it might be possible to approximate each individual’s Micro-economic decisions. Each of those Micro-economic decisions could then be added together to produce a fairly reliable Macro-economic prediction. This is precisely how weather is predicted with supercomputers– albeit with far fewer variables and far less complexity. This kind of summative analysis would be a huge improvement over the currently [cough] worthless field of Macro-economics since it builds on the rather robust foundations of Micro-economics. Descent macro-economic predictions might–finally–empower human beings to recognize the cause and effect relationship between bad policy decisions and the horrible outcomes they produce years or even decades later.

Apr 1 2013 at 9:17pm

Topol’s emphasis on personalized medicines and treatments is interesting. What puzzles me is that such an approach implies a variability of human genetic “assets” larger than you would expect, given other statements about little our genome differs from other species.

Ken P
Apr 2 2013 at 1:05am

Ok, I don’t think I’ve ever commmented on a poodcast prior to listening.

SaveyourSelf writes: “If computers were given relevant data…”

One could ask who decides what is relevant, but the thing is that most “big data” approaches, don’t worry about that. They feed what they have to the computer and let it make a wide choice of weighting and variable combinations, resulting in an equation that works well under the training set and the validation set.

Ex.) Seemingly irrelevant data like car-color and tire-type may actually be important in predicting the likelihood of a credit default. The real world is pretty unpredictable. Machine learning algorithms actually do a pretty good job of predicting in an unpredictable environment.

My respect fo Russ’ opinion has caused me to constantly rethink the potential for the “singularity”. The skeptical challenge to my extreme optimism is a good thing. As a result, my opinion on that varies over time more than on any other concept.

If you picture the complex way our human brains work, I don’t think “relevance” is something “chosen”, but instead, something that “emerges”. I think “Big Data” shares that kind of complexity.

Apr 2 2013 at 9:39am

I am waiting for a study that concludes that smoking one (or two or …) cigarettes a day allows some people to live longer, have more productive lives (and so on and so on …) (… I also know that there is a better chance that water will freeze in h^%l before anyone is ALLOWED to even study that – given that “We have decided that tobacco is bad for you”)

The age of personalized medicine is indeed close – within the next decade I’d say – it is not just the availability of sequence information that is driving this – but our ability to make some sense from all the data – sequence leads to postulates of mechanisms to someone testing such mechanisms and refining the postulates … On surface, it may appear that what Topol talked about is like the relationship between micro- and macro-economics – where with sufficient computing power, we may yet understand the consequences of micro- on macro.

The problem with economics is at level of the raw data itself – how such data was acquired and the bias that is often inherent in economic data sets – Genetic data, information do not have such biases – yes, there could be errors in sequencing – or even interpretations – but all such errors can indeed be fixed because the rules are objective and over time, we can indeed converge to the “truth” – and supercomputers will help us achieve that …

Apr 2 2013 at 9:55am

Ken P

I often have the same reaction after listening to “too much” Econtalk. I think the problem of who is deciding what data to collect, how to analyze it, etc. is a much bigger problem than people realize.

However, it is interesting to hear a statement like this one:

This inane idea that there’s two types of diabetes, when there’s more than 20 types. When you look at it from a molecular basis–which genes, which pathways. So what I’m coming back to you now is that we are now starting to understand this pathway approach, and I think we can break this thing down.

Going from 2 to 20 based on real science of understanding an order of magnitude more information about our medical conditions is possible. Hopefully that will bring benefits and not more iatrogenic treatments.

As far as the mention of Vitamin D, My own level is slightly low, and my doctor told me that over the past 20 years she’s seen the tested levels drop to the point where about 80% of her patients are low according to the test. It’s an interesting trend, and as the podcast mentioned, some diseases/illnesses take years to develop. What will the long-term trend of “low” vitamin D be for the population? Do we have to wait 20 years to find out, or will new technology emerge to tell us more conclusively that we should or shouldn’t supplement? My suggestion is simply to get outside for 15 minutes at lunch every day when it’s sunny outside. At worst, you’ll be more relaxed, and it should provide some protective effects.

Apr 2 2013 at 9:55am

Markbres writes:What puzzles me is that such an approach implies a variability of human genetic “assets” larger than you would expect, given other statements about little our genome differs from other species.

It is indeed true that there is very little difference between our genomes and chimpanzees (and many others) – this is when you compare the entire sequences – the tiny, small differences can result in fairly large “visual” and in other ways – In many cases, simply knowing the sequence (while necessary) is not sufficient – because we do not understand what the control mechanisms are – Not ALL differences are significant – there are benign mutations and mutations that are not benign and cause disease – quite complicated – but many of the pieces are indeed falling into place

Cancer treatment is perhaps one area where “genetics” has indeed changed the way patients are being treated – many of the treatment approaches are tailored (to some extent) to the specific genetic profile (presence of specific variants for example) … Herceptin is perhaps a very good example of a drug that works very well when given to patients that have a specific genetic profile

Carl Pearson
Apr 2 2013 at 10:06am

One note following up the question of human vs other genetic diversity. The early geneticists weren’t lying when they made those statements, but they were measuring the wrong numbers (with some mix of naiveté and disingenuousness).

The sequence data they compared doesn’t account for differences in copy number and folding (typically called epigenetics), which we are beginning to discover are very important to making predictions based on genetics.

Ken P
Apr 2 2013 at 9:41pm

Krishnan writes:

Herceptin is perhaps a very good example of a drug that works very well when given to patients that have a specific genetic profile

This may be splitting hairs, but it’s actually a “tumor specific genetic profile” that is required. My point is that having your genome sequenced would not typically help in this case. Investigating the genetic profile of a tumor, does. There is also an immunological method (no genetics necessary) which can detect the over-expression of the HER2 receptor. Herceptin is definitely a great example of patient specific treatment.

@Rufus, I liked the point about 20 types of diabetes, as well.

After listening to the podcast, I came up with a couple examples to explain the point I made about big data and machine learning techniques. Eric talks about the difficulty in teaching the art of listening to heart rhythms. That’s because it is experiential learning and requires lots of examples (data sets) to learn. It’s more of an art. I would guess that the inflammation in the ear example is the same way. Just like facial recognition. What variables explain how you know person x is person x? You were just trained by experience and so is a machine learning algorithm.

Apr 2 2013 at 10:15pm

As a data miner, this is a great step forward by taking a realistic look at data. There is also another (much bigger) piece of data can augment this approach: our immediate “environment” i.e. the microbes which live within us. There is already some interests in studies of the genomics and classification of microbes which resides in the colon and stomach. The best example is the treatment of C. Difficiles by fecal transplant. How do they play a role in our well being using Dr. Topol’s approach?

Zooko Wilcox-O'Hearn
Apr 3 2013 at 11:43am

This is great so far! (I’m at minute 13.)

Fact check: I think Dr. Topol said something to the effect that there was a 1/1000 risk of Stevens-Johnson syndrome if you take carbamazepine. That sounds high to me. Here’s the first reference I could dig up:

“The risk of these events is estimated to be about 1 to 6 per 10,000 new users in countries with mainly Caucasian populations. However, the risk in some Asian countries is estimated to be about 10 times higher.”

By the way, carbamazepine and oxcarbazepine are used to suppress seizures. It turns out that a very-low carb diet is at least as effective—and probably more effective—for that, without the dangerous side-effects. Probably it is sufficient to practice a diet not much different from the low-carb diet that Russ has been using to lose excess body fat.

Here are some notes I wrote about that:

my script:


Zooko Wilcox-O'Hearn
Apr 3 2013 at 12:13pm

While waiting for my comment here to be approved by the moderator, I posted it on G+. ☺

I also added this further comment:

Ah, so that explains why, as Dr. Topol mentioned, a screen for Stevens-Johnson-syndrome-likelihood is required in Taiwan but not in USA. It’s because almost in Taiwan the risk really maybe around 1/1000.

Carl Petersen
Apr 3 2013 at 9:49pm

Thank you for another great podcast! I would have liked to hear the guest’s response to how insurance companies would view and price individuals who get their genome mapped. And there was a brief discussion of pharma companies but I would have liked to hear more about what components of the guest’s vision for the future are patentable, and therefore more likely to replace the way pharma companies make money.

Apr 4 2013 at 1:13am

I agree with many of the important ideas presented here. Most importantly, the analysis of the implications of “evidence-based” medicine, producing an average outcome ( no better, no worse), often at great expense and with danger and discomfort is much appreciated.

As a medical practitioner (I am a Hematologist and Oncologist), “evidence-based” medicine comes to me as algorithms and guidelines (like those of the National Cancer Center Network). In this context it is interesting to me that, ultimately, Dr. Topol advocates a machine algorithm as the ultimate product of personalized medicine. Presumably, with enough data an algorithm will work.

But I think that a most important neglected capability is not emphasized enough… the ability to gather an organize vast amounts of data about response to therapy. This is a difficult issue that includes questions of (the illusion of) privacy. This is a technology that is actually in use in an area that exceeds macroeconomics… It is used to make money through directed advertising. It is through data mining and better methods of collecting and organizing data that we will begin to understand the millions of variations in the human genome and what treatments work for specific, multifactorially ( genomically, proteomically, microbiomically, and clinically) defined cancers.

The collection of these data will require a new, democratized approach to the collection and sharing of medical information. Once that happens, patients will benefit.

Adam Hickey
Apr 4 2013 at 12:04pm

Great podcast,

I’m not sure how relevant it is to this discussion, but has anyone else read about science based medicine? There is a slight difference between science and evidence based medicine as described here

They argue when determining whether a medical finding is true not only depends on the results of a clinical trial, but also on the prior chance of the result being true. It’s a slight difference but can have drastic implications for the direction of modern medicine.

John Berg
Apr 4 2013 at 12:31pm

This podcast produced a refreshing uplift–the first since November 2012! As an optimist, created by much Science Fiction reading in the 40s, I found myself identifying and comparing with several insights learned over a life time in the computer industry.

But first some questions:

Is any work being done on reading and writing to an subdermal chip?

The point was made that the best use of genomes would result from access to three or more siblings (Trianglizaton?). Must the siblings be alive? Could a vial of blood be preserved indefinitely into the future? Would a “transcript” of the genome be used into the future?

I can see the resistance to use of genomic evidence by my local health provider if I consider the investments they have made in modern medical equipment. How can I encourage the use of “predictive” evidence a well as “probative” evidence?

John Berg

Joseph Kash
Apr 4 2013 at 7:47pm

The sequencing of the complete human genome (which as pointed out is still not completed)has great potential benefits. The real benefit to individuals is less convincing at this time however. I sense that Dr. Topol has both a researcher’s bias that his passion for this topic will lead to results. I also sense that Dr. Topol might possibly have some financial skin in the game.

It would have been nice if Russ had asked him concerning any financial conflict of interest in regards to his supposedly objective opinions.

Apr 6 2013 at 8:31pm

Interesting discussion. . . doctors are very uncreative and our training stamps out any creativity we may have at one time had. . . plus we’re terrible with technology, as my husband is constantly complaining.

But one thing I am sure of, Russ, stop asking your doctor for antibiotics! Unless you have a UTI (rare in continent men, which I trust you are!) or xray proven pneumonia, every other bronchitis or sinusitis you have is viral, nearly guaranteed. Even the ones that last weeks. Your doctor isn’t trying to make money by making you come in (altho docs aren’t reimbursed for phone work, a problem), he/she is probably just hoping you’ll go away and get better on your own.

I’ve been doing some primary care moonlighting lately and am struck by how much of my time is spent denying medications, tests, and procedures to the ‘worried well’. “You don’t need that cat scan/MRI/antibiotic/colonoscopy, you don’t have anything serious”.

I am excited by genomics. In my hospice work there are new studies showing people metabolize morphine differently, some fast and others slow. It explains how two people can get my morphine and one is nearly comatose while the other is still screaming in pain. It’d be great to be able to know who is who ahead of time.

I am troubled by how to use free market ideas in medicine. I know in some ways it’s good, but there seems so much duplication of services, inefficiency, fraud in this wild west private practice world I know work in. What about interviewing the CEO of Kaiser? It’s a closed system with less choice where docs are salaried and it works well. Kaiser is my own health insurance currently.

Lastly, my economist husband had a good analogy. Consumer choice in medicine is like allowing your students to take whatever classes they want with whatever professors they choose. . . or granting tenure based solely on your rating. . . so many profs who are lazy and don’t make students work just as many doctors who let their patients have whatever tests they want are also popular but bad doctors in the eyes of their peers. . .

Thanks again, as always, thought provoking. If you want proof of the antibiotics thing, let me know and I can send you the papers. . .


John Berg
Apr 7 2013 at 11:14am

In honor of “perky Becky” let’s test the suggestion in the podcast to reward only successful encounters with MDs. (Although I’m in an immediate quandary with a hospice doctor.) Following the lead of the Federal government, the most likely service I would seek is a gun-shot wound. The second problem I found is determing who would construct for me an a priori contract. Certainly neither the doctor nor I would enter into a transaction without one. (It’s a litigious world!) The third problem stopped me dead. And how do I deal with this new world of Obamacare?

John Berg

Apr 7 2013 at 2:26pm

Re: rebecca

Consumer choice in medicine is like allowing your students to take whatever classes they want with whatever professors they choose

There is indeed something to be said to allow student choice – It is not as if the professors/departments/universities have thought well about what does constitute a “good curriculum” – other than making college easier and more enjoyable for those that can pay …

. . .

or granting tenure based solely on your rating


yea, bizarre – then again, when people are granted tenure with publications that have 500 authors and in journals that no one cares about or whatever – then, yea, I suppose ratemyprofessor may have some value more than the “value” being ascribed to the current process …

. . so many profs who are lazy and don’t make students work

yes, a problem caused in part by subsidies to education that has made college administration fat and happy and content to let things be – because the monies roll in and before the implosion happens, the people with their fingers on the money button have collected and gone onto bigger/better things (i.e. higher paying admin positions far away so they cannot be held accountable)

just as many doctors who let their patients have whatever tests they want are also popular but bad doctors in the eyes of their peers. . .

If people had control over their monies – if they knew that THEY had to pay for tests, medicine – office visits – and not imagine “someone else” will pay for it – everything will get better

There is nothing intrinsically special about medicine or schooling – it is about the messaging system and what information people can get or allowed to get about the products they may purchase with their own monies – Medicine, schooling are protected cartels and have always been very inefficient – allowing for a few to benefit at the expense of many (OK, that is a bit harsh – but there is a lot of truth in that) (And sure, I have physicians, educators who indeed help heal me, educate me and so on …)

Apr 7 2013 at 6:44pm

I am a cancer doctor with a data background (biostats, PhD Epidemiology) and have found it odd that the podcasts I have liked the least have been the ones by Drs.

First, Dr Topol was a little hyperbolic about alot of things, but he was wrong in some of his comments about PSA screening and mammogram screening. He said something along the lines of “all the data show these screenings are always harmful”, which is totally false. There is some controversy regarding testing – particularily PSA, but the highest level of evidence we can create (randomized controlled trials with thousands of participants) show PSA testing saves lives. I would strongly recommend people continue PSA testing and mammograms – the data is robust and you can save your or your mom or wife’s life.

Doctors who speak in the public press or who are leaders in the field tend to take an overly negative view of the current state of evidence in medicine. We certainly need more data, but a great deal of what doctors currently do is evidenced based (again, not nearly everything). And though the data is for the “average” person, human biology is on the whole very similar and our pathologies, even when genetically different, have similar pathways that respond to common medications. That is why despite the possibility there are actually 20 types of diabetes, it is unlikely that we will have 20 distinct therapies since most of them will end in a common pathway that respond to the same medications.

I am hopeful that many of the “personalized” medicine advances Dr. Topol sees on the futute will eventually be realized. They have been on the horizon for awhile. I do think Dr. Topol over sells their benefit since their gains are likely to be marginal – as nearly all gains in medicine are marginal now. We already have entered the era of personalized cancer therapies based on the tumor genetic profile, but the gains for patients are still relatively modest compared to the previous therapies. Overtime all the marginal therapies add up and we continue to improve survival.

I think the more interesting changes for medicine are likely the computational power to replace physicians in the future and the data anylysis that we will be able to do. But the field so tightly regulated that innovation in delivery will be slowed incredibly.

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Podcast Episode Highlights
0:33Intro. [Recording date: March 20, 2013.] Russ: Your book is about the digital revolution and how it's transforming medicine--a little bit so far and perhaps a lot more to come. I want to start with the example you give of how much of medicine today, particularly clinical trials and the efficacy of various drugs, looks at the average person rather than the individual. So, what do you mean by that? How is it changing now? And how might it ultimately change down the road? Guest: Well, unfortunately, because we didn't have the tools until now to define each individual, the default mode has been: Treat everybody the same. Have everybody come in for screening, whether it's a mammogram for women or prostate specific antigen (PSA) for men, have everybody come for an annual physical exam, and also give the same drug to all patients with the same condition. Medicine has been terribly dumbed down. Russ: And the same dose. Guest: That's right. And the same drug that doesn't work in lots of people. So, we've got a real problem and that is this waste and imprecise use of all our treatments and our procedures. It's a mess. Finally we have a time when we can rise above that. Russ: How? How's is that happening now? You give some examples in the book of how recent genetic discoveries have improved our understanding. But how might it go even further down the road? Guest: Well, it basically is so pervasive, how this can be rolled out, it's why I call it the creative destruction or complete re-do, rebooting of how medicine is practiced. So, you pick an area of interest--let's say, cancer. So, in cancer, last year in 2012 there were 12 new drugs approved by the Food and Drug Administration (FDA). A banner year for that. And 11 of the 12, the cost of the drugs were over $100,000--per treatment. And that's pretty characteristic of most of the relatively new cancer drugs. But the way cancer drugs are given--well, you have a disease of a particular organ, like prostate or lung, and you get a drug based on that. Well, that of course doesn't work very well. Not only is it a profound waste, but beyond that we can now sequence the tumor relatively inexpensively compared to the cost of the drugs, because they are usually used in multiple combinations. Sequence a tumor, find out what is the driver, causative mutation, and then go ahead and treat this in a very biologically based genome-guided way. That's just one example. I can just go on and on. Russ: But, the kind that I found exciting in the book is that a lot of times drugs are ineffective or worse have side effects that are harmful to fatal, and yet we are starting to learn some of the genetic descriptions of individuals that would allow us to avoid that kind of mistake. Guest: That's right. But unfortunately, Russ, a lot of this information is not used in medical practice today. So, giving you an example of that: A drug that's commonly used, called Carbamazepine, also known as Tegretol, that drug is given for a variety of conditions, neurologic conditions, seizures, depression, neuropathy. Anyway, that drug has got a 1 in 1000 chance, which we can accurately predict, of who is going to have a potentially fatal side effect, so-called Stevens Johnson syndrome. But we don't screen for that, even with that knowledge in hand. Whereas in Taiwan, for example, you can't get a prescription for the drug unless you have a genotype first. So, there's information that's well secured but not being used. And that is really unfortunate. And that's just the genomic side. We haven't started getting into sensors. Russ: Well, some of the reason we don't do those kind of tests is cultural. We talk a lot about the conservatism of the medical profession; we'll come back to that later. Some of it presumably is cost. What does it cost to do that kind of genotyping you are talking about? Guest: Well, if we were to get with it and have hospitals do their own certified, so-called CLIA[?] labs, they could do this for a few dollars. The actual genotype, once you know where to look, in fact it could be done for less than a dollar, the actual test. It's so inexpensive. But also as a cultural way, that everybody had their drug genomic profile defined, we wouldn't have to--if you gave a prescription it would already be cataloged. And it would be stored in people's homes or somewhere on their personal website, electronic record, or whatever. So, we don't have that mindset right now. We're not embracing genomics and we're not even--no less making more discoveries, which is happening, but we're not even taking the ones that have been made and implementing them into daily care of patients. Russ: So, the digital side of this would be the equivalent of the bracelet that I might wear if I were allergic to some treatment or something so that I would be able to advertise to health care professionals something about me that's unique. But ideally that should come about just through my entering into the health care system, which of course doesn't happen right now, right? Guest: That's right. That's a pretty fair analogy. I'm thinking that a lot of this would be stored on one's cell phone because that's usually very much connected to each individual; but a bracelet, a chip, whatever. This information should be available for everyone. Russ: My cat could have that chip. Guest: Yeah, sure. We've got more chips for our pets than we have for our people. Russ: Well, for obvious reasons. They make people a little bit uneasy, for cultural reasons. We'll talk about that later.
7:02Russ: I want to come back to what you said a second ago about PSAs and mammograms. One of the interesting tensions in your book is between individuals having a lot of information about ourselves--not enough versus a little. And usually we'd say more information is better. But there are a lot of false positives with PSAs and mammograms. And you give a very chilling and powerful story in your book of the guy whose wife gives him some kind of imaging test as a birthday present and as a result his life gets turned upside down. Talk about those tests: why they are not always a good idea. And what are some of the consequences when there are all these mistakes. Guest: Yeah. You've touched on many concepts with that question. So, on the one hand when you have recommendations that all people should have a PSA or a woman should have a mammogram--all the data show that that induces net harm, because it's not suitable for mass medicine. But the other thing you brought up is all the unnecessary things that are done. Like, in that example, you mentioned the spouse--she got her husband a calcium score, a CT scan, which indicated that he had a lot of calcium somewhere around the arteries of his heart. Which is a common problem in American medicine. And then that just led to this express train ride that went through getting an angiogram and then having all these stents put in to multiple arteries. And this fellow had no symptoms. Which is quite common, by the way. And so you have--you've brought up both the unnecessary procedures as well as the ones that are driven because of our inability to differentiate one individual compared with the next. So, we got a lot of problems with this population-dumb-down medicine approach that are now, finally--there's a solution in sight. Russ: And the other example I think is strictly fascinating and I think relates to a lot of previous conversations on this program is the power of evidence--so called evidence-based medicine. And one of the challenges--I wouldn't call it a challenge. I guess I'd call it a mistake. One of the mistakes we've made in trying to make medicine more scientific is using, say, various tests as our goal of lowering a score on a cholesterol exam. When it may not be correlated with heart attacks. But, quote, "it's the best we can do." So we do it anyway. We've had Gary Taubes on this program, who is very skeptical about the role of fat, say, in heart attacks--which is what we care about, not so much in cholesterol scores. So, what's your thought about what we know so far in those issues? Where are we? Guest: Well, we don't have a good body of evidence. Our evidence-based medicine is--it's a nice buzz word, but a lot of it is eminence-based medicine, where a bunch of people sit around in a room, these experts, and they just make an opinion about what everyone should do. All patients with this diagnosis should have such-and-such. And that doesn't work. Russ: And then you can measure that. You can grade a hospital on what proportion get that drug within that amount of time. Guest: Yeah. Appropriate example that you just brought up was the LDL-bad cholesterol. And what a mistake--what a misadventure that has been. Because basically, the benefit of taking a statin for people who don't have heart disease but have a high cholesterol blood test--this is just fixing the blood test, which of course that works very well--but in terms of reducing heart attacks or preventing deaths, we only benefit 1 or 2 people out of 100. We then medicate these people. The whole idea of making a nice lab test--98 out of 100 are taking the medicine just for that. And that's the most--the statin drug class is the most successful drug class in the history of the pharmaceutical industry. So that just shows you how bad our approaches have been. That's one of the most--evident. But the evidence is scant. One to two per hundred, statistically significant. And people talk about the 33% reduction in heart attacks. But that's going from 3 to 2 per hundred. So this is an unacceptable--even when there is evidence, it's not evidence that's strong. We need to have overwhelming evidence. That's what we should be seeking. Because that's going to make everything much more precise. And economically attractive. No less better outcomes for patients. Russ: So I want to come back to that PSA example because as I was reading your book a couple of days ago I came across an article, I think it was in a British newspaper, of three urologists in their late 50s who all got prostate cancer and two of them found it soon enough that they're probably going to be okay. The third one has a short period of time left to live. And all three were discovered they had--I have to be careful, not all three--a PSA test played a role in their diagnosis and their discovery. Are you suggesting that that's a small sample and that ignores the other people who take that exam, have their prostates removed, say, for no good reason, deal with the side effects of that--you said there was a net harm to that exam? So are you saying we should not take that exam, if you are over the age of 50, say? You should not take a mammogram? Guest: That's right. PSAs should not be done. And the data for that are that there are 250,000 men each year in the United States alone that have a false positive PSA. And they undergo serial biopsy. Not just one, but multiple biopsies, which are not only extensive but painful. And then there turned out that there would be a false positive. So all those men who are harmed along the way, no less the emotional hardship of dealing with this abnormal PSA, and they don't even have prostate cancer. And that greatly overrides the few men that are picked up relatively early for successful treatment. So, if you look at it from a population level we're doing harm by using that test. And similarly, from mammography, the data shows no benefit. That has been reviewed recently and published in a journal--we continue to keep doing mammography even though there is an overall lack of benefit. But the answer there and recommended by the authors of the New England Journal paper was: We need a better, more precise strategy--a family history of breast cancer, for example, genomic risk of breast cancer, for example. Those women should get mammography, whether it's every year or even a more sensitive test. And the women who have no family history or have no genomic sensibility. Maybe they get a test but only once a decade. Or not at all. But we don't have that sort of individualized approach today. Russ: I think the other challenge for most of us is a temptation to then say: oh, thank goodness; I don't have to get any more tests any more because they scare me. But that is not the lesson. The lesson is that some tests are good and some tests are not worth it, right? At least on average. Guest: Sure. The problem is everybody's been average. And that is wrong. We couldn't be distinct. There are not even identical twins on this planet that are the same. And so we have got to move in that direction. And we couldn't do it before. But with sequencing and sensors and all the other tools that we have at our disposal it's time to do that.
15:36Russ: Let's move on to some of the innovations that have happened in genetics so far and what might be coming. Learning more about one's own genetic makeup is very scary to some people, partly for privacy reasons but partly because I think for some people it makes them feel like they are losing their free will. They are getting too much of an advance--a preview of the future. They'd rather be left in the dark about their likelihood of getting some disease and having that hang over them. Talk about that phenomenon and then some of your own experiences, which are quite interesting. Guest: One of the things at the moment--I've had my genome sequenced and I'm pretty healthy; and I wouldn't recommend that now, to have your genome sequenced if you are healthy. I did it more out of academic curiosity. But if you are sick, if you have a serious illness which has not been diagnosed, you could make a good case today for going to sequencing a lot earlier than has ever been done before. The so-called 'diagnostic odysseys'--they are individuals who typically go from one medical center to the next, to the supreme-court place of medicine; and they still don't have a diagnosis. And we just had one that we presented at our genomic medicine meeting here in La Joya, and in fact had been to ten such medical centers. But when we did the sequence--this was a 16-year old girl with a pretty severe neurologic abnormality, condition, we were able to find exactly the two gene mutations that were causative. The root cause of her illness, that she'd gone 16 years and millions of dollars in the odyssey. So there is an easy one. And in fact even insurers are starting to say: Maybe we should go to sequencing much earlier in the saga. Russ: What does it cost right now and how has that changed in the last ten years? Guest: Oh, wow. It's reduced more than a millionth-fold. The cost of sequencing for an individual would be about $4000 today. But in order to understand that individual you need siblings or parents, so you really need a trio of three. So you are talking about sequencing costs of somewhere, by the end of the year well less than $10,000, but it's in the $12-15,000 at this point with all the analysis. So, it's pretty inexpensive compared to millions of dollars spent trying to get a diagnosis through the old way of practicing medicine. Russ: Is the price coming down? Guest: And the price is coming down; it's expected by year end to start to get pretty darn close to--well, less than $2000 and maybe closer to $1000 per whole genome sequence. Russ: Now, help me with the science. A genome sequence is say about $4000 right now. There's something else that's about $400. What is that other thing? Guest: Oh. Well, if you do a scan of the common variants in a genome, which is really almost becoming not useful--so you can get that now for $99 through There aren't many of those consumer-genomic companies still standing. That's certainly the main one. It was $400; it's just come down over time to now $99. That gets you a peek into the genome. It does get, by the way, going back to our discussion earlier about the drug interactions, it gets you something like 25-30 major drug interactions about you. So, just that alone is a bargain in my view. But it doesn't get you every single letter of your genome sequence. There you are just getting hundreds of thousands rather than 6 billion. Russ: Why are they going out of business? Do you know? Guest: Oh, the other companies? Well, DeepCode, Navigenics, there's been a few of them--they were charging a lot more, well over $400, and they could not get enough people to buy into that. And 23andMe brought the price down to $99 and that's starting to get a lot of interest and support. Initially when Navigenics came out a few years ago it was $1500 for this limited genomic information of common variants. And that just wasn't going to fly. They had bad expectations about how much people would pay for what was minimal information. Russ: And what do you mean by 'drug interactions'? What's an example? Guest: So, the 23andMe panel that anyone can get for a saliva kit sent to them, that gets interactions with drugs like Plavix, like various cancer drugs. Caffeine, even. A whole list of drugs. Warfarin, the blood thinner. I don't remember all 27 of them offhand, but it has a lot of useful commonly used drugs with very strong data to support the variant in one's genome. Russ: But the interactions you are talking about are not between drugs, but between the drug and you. Guest: Yes. Exactly. So, let's say you are prescribed to take Warfarin, blood thinner. Well here you'd know the dosage you should be taking. I mean, I know that the average person takes between 5 and 7 milligrams. I know from having that that I should only take 2 milligrams. Otherwise I'd have a lot of bleeding. I don't have to take that drug but it sure is nice to know that well in advance, if it ever was prescribed. Some people have to take 20 milligrams to get the effect of their blood thinned. That's just the kind of example of the kind of information you get from that. Russ: So that's a saliva test, which is pretty pleasant. If you want your full genomic code, the $4000 thing, what do you have to do? Cut off a limb? Lock of hair? Half your hair? Guest: No. Russ: Fingernail? Or just saliva? Guest: You could do saliva but really to do it right you want one tube of blood. That's much better. I mean, it can be done, whole sequencing from saliva, but I think blood is superior. Since you want this to be as good as it gets, because this is your sequence. You only really want to do this once in your life. Why not do it right? And a tube of blood is pretty straightforward.
22:34Russ: So, when you did it, you learned about your proclivity to get a bunch of different diseases and where you were more likely than the average person, less likely. You say you didn't do it because you were worried; it was because it was interesting. Guest: Right. Because I work in this space; I have tremendous curiosity. It was an opportunity. Russ: So having done it, how did it change your behavior, feelings, sensitivity to the psychological aspects of that kind of knowledge? Guest: Well, it's on my iPad, and whenever I get bored I can study my 3.4 million variants from the reference genome to see what is going on there. So, it's a lot of information to try to digest. But, with respect to--I know every possible drug interaction that exists today just by looking things up. And every week when something comes out, whether it's a rare variant for this or that condition, I can look it up now. I don't think it's so valuable today as it will be in 2 or 3 years. Because we are going to have millions of people sequenced, and we'll have so much of the whole of our knowledge filled in. But, did it change anything for me? On an immediate basis? No. It just provided lots of information. That's why I don't recommend it at this juncture. Because the price point isn't there. And also the knowledge of millions of people getting sequenced. I don't think it's prudent to do it now. But I think it's going to be great a few years from now. It will be much cheaper and much more informative. Russ: Well, my wife just got an iPad, and she asked me, naively, how many apps I have. I didn't tell her, by the way, because I didn't want to depress her. I think she thought it would be like 5 or 6. But I said it's maybe 100. I don't know the answer. I buy lots of things for my iPad that I just think are beautiful, and for 99 cents or $3.99, I just like the idea of them. I don't use them very often. Or maybe just once. But somebody did something beautiful or extraordinary, and I have to say even though I have no plans to get the genomic map for myself, there's something magnificent about the human enterprise being able to do that. For a mere $4000. It's a lot of money. It's quote "not worth it" to me--I won't do it. I'm healthy. But it is an extraordinary thing. It's a beautiful thing. Guest: Yeah. And you know what's interesting about that is you can go ahead and download an iPad app called My Genome, 99 cents. It's not your genome, even though it's called "my genome"--it will have a person's genome and you can basically find out what it's like to look up every variant in a genome. It's fascinating; just using your fingers to explore a human genome. So it's made for people who are not genomically literate. It gives you a feel. Russ: It reminds me of the story you tell about the thrill, and then not so thrilling, about when you were able to do an ultrasound on your heart. Tell that story. There's a lot of information there. Guest: Yeah. That was pretty wild. So, I was able to get my hands on the first high resolution ultrasound, Vscan device; and what I did when I got it was of course test it on myself, to see what was going on with my heart. And I didn't think I had any heart condition. I'd had a previous echocardiogram to see and whatnot. But when I did it everything looked okay, but I had this really big leak in my mitral valve. I said, Oh my gosh. It didn't make any sense. And then I went back to the old relic, my stethoscope, and I said: Well, I hear a little something, but not a lot of leak in this valve. And so I unfortunately started doing this late on an afternoon, evening, and I basically had a troubled night thinking: Where should I go to have my valve repaired with open heart surgery? But then I had made an appointment the next day to actually go through the normal full echocardiogram and that showed that I didn't have any significant leak. I had a small amount. Which I thought was the case. So, then I checked with the manufacturer of this device, and they had a--because I was almost like an alpha tester of this, they had a software problem. And the problem that I had-- Russ: Oops. Guest: And so that got fixed, and now that's not an issue any more. But I had a scare, just because of having an immature technology. One of the many lessons out of that is: You don't want to be using these things until they've been fully tested and vetted and proven that they don't have glitches in them, like I had. I've had a couple of things like that. The other one in the book was when I first got my very first Navigenics report, again one of the early ones, and it said I had a 108% risk of a heart attack. How could I have 108% risk? And I joked in the book--I called my wife and said I won't be coming home for dinner. Russ: And actually you probably weren't even talking to her then. You'd been dead for days. Guest: I know--more than 100% risk of a heart attack, that's really bad! These things really happened. It's scary. So you want to wait a while. That's another reason to wait to get your genome sequenced, even if you are healthy. Wait till we get a lot of the bugs out. There's still parts of the genome that don't get sequenced, or don't get sequenced accurately. So if you are going to go for it, wait. It'll be less than $1000 in the next couple of years, and it will be much more useful. Russ: One of the things that amaze me about that story of the heart image is how much of medicine until very recently--until the x-ray to start, and then the advances we've made in other types of imaging--how much of medicine was listening, both to what the patient had to say, and how the heart sounded with a stethoscope. That was what you had. It was an art. Guest: Yes. You know what gets me about that--funny you mention it. So, 1816, the stethoscope--we listen so indirectly to lub-dub for the heart, or for bowel sounds in the abdomen. Sound. Whereas now you can see everything. That is such a dramatic difference. I just can hardly adequately express that. And I used to be one of the big proponents of the nude doc students learning all the heart sounds, all the intricacies; and I used to spend hours--I'm afraid to think how many hours I spent at the bedside teaching that. And it's dinosaur stuff. It's all obsolete. Russ: Yeah. Well, thank God. Sorry. Guest: Not generally though, because of issues of reimbursement, because of the unwillingness of the medical profession to change, it isn't like it's been a shift where it should be. It will take time. Russ: But that kind of creative destruction, of your knowledge becoming useless in many cases, that's a good thing usually. Guest: I think so. Some people will argue with it, but I think you are right.
30:43Russ: So, you mention in the book that the--I don't know what the right term is--the biogenomic, biological sciences revolution, it started with such promise in the mapping of the human genome. A lot of people argue that it's been very disappointing. And you remain both cheerful about the present--you've given some examples already--but also very optimistic about the future. You just said, for example--I don't remember this being in the book--in two or three years it'll probably be worth it. What's going to change to make the payoff so dramatic? Because one of the lessons I got from the book--I'm not an expert in this field at all; I'm pretty illiterate--but it's striking to me how complicated the genetic map is relative to what we thought. That's the impression I got from your book. So, given that that's true, why are we going--why are you so cheerful about the future? Guest: Well, I'm so cheerful because we have this amazing digital infrastructure, which has not been harnessed in medicine to a significant extent yet. And just by having the broadband, the connectivity, the social network capability--all that stuff. And then you've got these sequences of the genome--not just the DNA sequence. But you can sequence the RNA. All the proteins, all the metabolites, all the so-called epigenome, which is the side-chains of the DNA. And not just of an individual but let's say of a bacteria or virus that's infecting an individual. We have such potent tools now. And we have these sensors that can come up with data in real time on virtually any physiologic metric, anything that makes us tick. So, when you have all this together, you know, this term I use about the 'superconvergence' the likes of which we've never had in our history, this sets off this unique time, this true great inflection of medicine. Which I think we're just getting started with now. Russ: Well, we see it in so many areas outside of medicine. So the obvious question is: Why not medicine? And the answer isn't because we're not learning more. The answer is the industry is not very well suited to deal with innovation of that kind. What do you think is going to change with prevention? You bemoan the fact we spend a lot of resources in medicine, of course, reacting to changes in our health. But we don't do very much for prevention. In fact, I'd say for most of us the biggest thing we do that's preventive is, we exercise some. Which, I like the idea that it helps me but I'm not so sure the science is there. We can probably do a lot better. What are some areas that you think are coming that might help us be more successful in preventing disease rather than find a cure? Guest: Well, I think that's where we're working pretty hard on kind of the futuristic notion. Again, just saying you should eat this and you should exercise that and everybody getting the same prescription, that's got to be wrong. Because that doesn't take into account different nutritional, different types of exercise for an individual. Lifestyle the same for all people is another poor notion. But to truly prevent illnesses that people will be destined to get, even if they have a healthy lifestyle, we've got to get much more information. And that might not from wearable sensors. So that's why we've put a lot into our program at Scripps where we actually are using nanosensors that can pick up a genomic signal. So whether that be from a free cancer DNA, before a cancer has really taken form, whether it's from a cancerous cell that's gotten into the blood, or for the immune system that's been activated, again, that signature in the blood; or a cell that's coming off of the lining of an artery that's going to be the beginning of what would be a crack or heart attack and hooking that up to a sensor that talks to your smart phone. That's when we can really get into the big time prevention. Or an asthma sufferer. To prevent the even first asthma attack--and you probably know, Russ, in children this is the number one cause for going to the emergency room, asthma attacks; and they can be deadly. We don't want any child to have an asthma attack, no less die of one. But we can predict that now with various metrics, predictive analytics, through a cell phone. And that could be not just with the child, but obviously also with the parent. So, being able to prevent things like an asthma attack or heart attack, or cancer--this is really where this newfound, granular information, panoramic information on each individual, can help. Some day, that will click. Russ: Well, some of it's already there, right? Some of that sensor technology has been approved by the FDA, if I remember correctly. Guest: The heart cardiogram, yes. The digitized pills, yes. But we've got a long ways to go to get these embedded now sensors in the blood. There isn't an asthma--there's an asthma sensor approved that's to tell you hot spots for asthma attacks in a community, geographical location. But there isn't one to tell from your own metrics yet that you're heading towards an asthma attack. And we're talking about before anyone has wheezing or shortness of breath, to know they are going to have an asthma attack. We're in the early stages. Russ: You think we are really going to find out that for some people lying on the couch and eating french fries is really what's good for them? Because you say that having lifestyle similarities is absurd. I'm sympathetic to that claim. But we do have lots of things in common, so you'd think that there would be some general rules. Eating broccoli, say, or whatever it is. Even though we should be skeptical about average medicine, there are likely some things that are, on average, good. Guest: Yeah. You're right. I'm not debating everything. But I don't think everybody has to do the same type of exercise and eat the same food. Russ: The same length of time. It's 27 minutes of your heart at this level, and then you are not going to die. Congratulations. Guest: Yeah. No, I think that some people are better suited to live their life really thing. Because even a little extra weight will have a lot of extra issues [?] for that. Whereas some people don't need to exercise their brain out. They just need to do walking. This whole idea of prescribing the same everything overall, I have a problem with that. It transcends lifestyle. I mean, I think we're talking about: How do you prevent a specific illness? Like, you have a risk for melanoma, you really have to gear up for sun protection. If you don't do that you are really going to change your odds of having that. We need to know that at the earliest possible time so that when kids are growing up, these, most chronic illnesses have their roots during childhood and adolescence, if not even before. So that's why we really have a new power of prevention.
38:44Russ: You mentioned sun exposure. So, I'm going to have to ask you: I'm very Vitamin D deficient. Which, my physician said I should take megadoses of Vitamin D. Which I did not. A common phenomenon in the world, as you mention--many people do not take their meds. I thought it was not such a good tradeoff. Do we know anything about Vitamin D? Because a lot of people now spend a lot of time sitting in an office, not getting any sun exposure, not going outside, lathering on sunscreen and they are not getting any Vitamin D from the sun. Is it a crisis? You hear that it is. What's your reading? Guest: Oh, it's been terribly overhyped. There are some relatively unusual circumstances where Vitamin D should be taken. But the levels for an individual are not really known. There is a natural Vitamin D activation from being outside that isn't necessarily used, but most people are not Vitamin D deficient. And this has been kind of a frenzied thing whereby a lot of studies recently have really shot that down as to whether it's important. We've been kind of going through this Vitamin D fad of taking it and testing it and whatnot. So, that's just one on a long, long list of things that need to be individualized. Russ: Another example that comes to mind that I don't think you talk about in the book is hormesis, the idea that most things that might kill you are good for you in small doses. So, wine being an obvious example; at least some people argue that a glass of red wine is good for your heart, a glass a day. Certainly a cask of red wine a day will kill you, most of us. But I wonder, since we don't know where that level is for most of us--you should probably stay away from arsenic, lead, other things that are clearly toxic in fairly small doses--but it does raise the possibility, this individual medicine idea, that some day I'll know better where my threshold might be. Is that imagineable? So that therefore I could take my arsenic pills in the morning, because they help me think better-who knows what the benefits might be--but most things that are toxic are helpful in small doses. Is it possible we'll get to that point, where I'd learn where my cutoff is and take a chance? Guest: Yeah. Eventually. It's going to take a while because it's not on the high priority list to define it. But no question. This will be worked out some day. A good example is mercury exposure through seafood. There are a lot of different seafoods that people eat. And some people, if they get a level of that, any level, could be really deleterious. Whereas others, they are going to be fine. There's many examples of these things. Radiation is a great example. Some people, you could send them for scans, CT scans, PET scans, nuclear scans--they could go every week and they'll never get a cancer. Whereas other people are exquisitely sensitive. And we need to know who they are. I'm not suggesting that some people should have scans frequently--in fact, that's one of my pet peeves, that we overcook that. That whole controversy with do cell phones cause brain cancer? I suspect that they do in the rare individual who is already exquisitely genomically sensitive. But it's so rare that we haven't endeavored to find it. So this whole thing about toxicity, whether it's things that we ingest or are exposed to in our environment, we need to work on that.
42:46Russ: Let me bring this around to an economics example that we've talked about before on the program when I talked to Gary Taubes. We talked about the strange parallels between macroeconomics and epidemiology, which are that you have a very complex system, you have a lot of causal agents, and it's very hard to tease out the independent effect. And I think some of the hype of so-called 'big data' is overly optimistic about our ability to single our or measure with any precision these kind of effects that might be of concern to us. So, just to take an example, Taubes has advanced the view that there's a nexus between insulin production, diabetes, heart failure, obesity--that those are not three separate problems; they are one problem, they all come from insulin miscalibration, etc. It's an interesting idea; it's provacative. I think all of us as human beings have an urge to know. So we say: That could be it. Of course, it could not be it, too. So, I'm curious. Where do you think are the limits to these kind of advances that we are talking about? Or do you see any at all? Because I wonder. Guest: Yeah. I don't really--let's go back on your question for a second because I'm just blanking on a response. Russ: Let me try to rephrase it. There are a lot of things that we'd like to know about, say, the relationship between exercise and longevity. Between diet and longevity. Between--those things and quality of life. And it's nice to think that given enough time and enough data we'll figure that out, not just for the average person but for each of us. But a part of me says: You know, we've been trying to do this in economics for about 80 years, and I don't think we've gotten very far. Complexity is not our strong suit statistically. And maybe we should be more realistic about what we are going to understand. Guest: Well, yeah. But going back to the kind of Taubes concept that all these diseases are linked--I think that in part that's true. But what we are learning is that in any given individual--let's pick diabetes, for example. This inane idea that there's two types of diabetes, when there's more than 20 types. When you look at it from a molecular basis--which genes, which pathways. So what I'm coming back to you now is that we are now starting to understand this pathway approach, and I think we can break this thing down. And you alluded to this 'big data'--well, obviously we have an enormity, a torrent of data like we've never had before, but we have supercomputers, we have analytical capabilities, predictive analytics and machine learning like we never had before and just getting better every day. So I actually think we can get into the nitty gritty here, and override some of the inability that you are getting at in the future. I'm quite optimistic about that. No one would ever have thought you could sequence a whole genome with 6 billion--to do it 40 times, 240 billion data points--and be able to analyze that in minutes? Who would have thought that would be possible? Russ: It's very cool. But again, we're human beings. We have a problem with hubris and overconfidence. I look at the financial sector where people build all these complicated models and they actually think they know what they are doing. I don't think they are incentivized to know what they are doing. And that could be a problem in medicine also. I look at the examples that you give in the book of evidence-based medicine, where people--they think they are doing science, but they are doing what Hayek called 'scientism'. It's--they are fooling themselves. Guest: Yeah, you are making a very good point there. And time will tell whether we can override those concerns. I think it's a legitimate issue and only when we have proof can we really respond to that concern.
47:10Russ: So, one of the problems--and this is a huge topic so we'll just touch on it because I have other things I want to talk to you about--I think in medicine is the lack of competition. It's hard to start a hospital. Very hard. John Cochrane on a recent episode of this program talked about--you, I think you started a medical school. Which is hard to do. Guest: Yes. Russ: Incredibly hard to do. The system is designed to make it difficult on purpose. Now, there's good reasons used to justify this; but there are some really bad reasons. Like preserving one's own well-being in the face of creative destruction. So, you talk in the book very eloquently about how archaic some medical school curriculum is, how resistant medical school curriculum is to introducing topics like the ones we are talking about. Do you see any hope that these phenomena could be made more competitive? Or maybe more realistically that we could somehow do it end around? As some patients do around the system--they teach themselves, they don't rely on the doctor. Guest: Yeah. You have hit on another biggie here. What I'm banking on because the systems are hard to change, and the medical school--you bring up a major painful point there. And at that time--this is back in 2002--there hadn't been a new medical school in over 20 years in this country. Now there's a whole bunch of them. But the issue is that the power of the people is greater than the people in power. Right? Russ: No. Guest: And so we do have an opportunity now. Yeah, yeah. We have an opportunity like never before of, in the social networking era--when you go back and you think: Look what happened in HIV. Talk about a difficult problem of people dying. And it was activism. We didn't have social network systems then. It was just people parading and storming into Congressional offices. And that led to definitive treatments and maybe even we are talking about cures and vaccines now. Tremendous progress. Not a fatal disease by any means. Well, if we had that across the board in medicine, wouldn't that be extraordinary? We can take activism now, it's exponentially more powerful. So, if we could get people activated--that's actually why I did the book, is because I thought that if everybody knew about this who was willing to delve into the book and get activated, maybe we could rally and undo some of the problems we have of making these very deeply seated, difficult-to-change systems, make them much more maleable and progressive. Russ: Let me ask you about one of them. A little trivial, somewhat trivial, but maybe it's symptomatic of the problem in general. My doctor, and I'm sure this is not uncommon, seems less eager to prescribe antibiotics than I am to take them. I'll call him, or sometimes I have to go see him about a problem I have; and it's one maybe I've had before. I'm pretty sure I know what it is. If I'm on the road he'll sometimes phone in an antibiotic, but sometimes he'll make me come in. Now is that because I'm ignorant? I think antibiotics work better than they do? And he's protecting the public from overexposure, our public health system from overexposure? Is he trying to keep me coming in so he can make the money from the call? That whole system is weird. We don't do that anywhere else. If I go and I think I need a new something for my car, I just go do it. If I'm capable. But it's a strange world. Guest: Right. It is a strange world. And there's a lot of answers to your question. One of them, of course, it is incumbent on physicians to be less promiscuous with antibiotics because that's what led to all sorts of problems of resistance. We've now learned in recent years how it's had drastic influence on our microbiomes, and that has its own risk for diseases, no less intrinsic DNA. But the other thing you are getting at is the self-care of the future. And that is, as we have data that's widely accessible, and information, to the consumer, to the individual. And let's say you could validate what infection you had and what it was, and what antibiotics it was resistant or sensitive to, prove whether it was an infection with a dipstick thing. Or whatever it was. An ear infection, you name it. You could then have an algorithm that goes right to your phone that tells you what to take, and that, once it's validated, should give you the leeway to be in charge. And you should have full access to whatever that medicine should be. And I think that's where we want to be. We want to fully democratize. The day is out there, once we prove that is the right way to go, better model of medicine, that's how I see going forward. Russ: That's a beautiful idea. So, I guess the analogy would be, when I have the earache, I hold my cell phone up to my ear. I put this little attachment in, maybe, and he gets to look on the screen in his office to see how inflamed it is or whatever else might give him information, and then he's comfortable letting me have the antibiotic. Or, I don't have to go to him. Guest: You don't have to go to him. It could be your child, too, more likely to have the ear infection. You get a tenfold high-resolution image of that eardrum, which is through that addin to your phone. That goes to an algorithm, and you get a text back, yes or no on the ear infection question. And then you could either call and say I have a confirmed ear infection, where physicians some day trust that without having to see you or your child and call in the prescription. Or someday, going a little step beyond that where that algorithm is so good and this is down pat that you just get a ticket to get the prescription. In fact, not only do you get the text back that there's an infection but you also have the medication--either you are downloading it directly from the Internet or it's already available to pick up from your local pharmacy. Russ: Yeah, well I interviewed Doc Searles a couple of weeks ago about what he calls the 'intention economy.' So, I'd send out the picture of my ear and then a bunch of pharmacies would offer me some good deals on the best drug for it. I wouldn't even have to search. Guest: It's coming.
54:28Russ: You've spent a lot of, played a lot of different roles in the pharmaceutical industry's discovery process, been on panels evaluating drug efficacy. You got entangled in the Vioxx controversy, which we might talk about in a minute. We had Marcia Angell on this program a while back and she sees the industry as basically totally corrupt. In fact not just pharmaceuticals and drug approval, but the entire nexus betweeen physicians and the drug device and pharmaceutical industry. What are your thoughts on that, those tensions there? Guest: I think Marcia is an extremist. I know her and I respect her, but I believe that there is an imperiled pharmaceutical industry because of lack of innovation, lack of individualized medicine embracement. I think they will start to get on this now because the whole blockbuster model of mass medicine, those days are over for good. So I'm seeing a real transition, a real notable change in the attitude toward using genomics, sensors, other tools to develop new drugs that are much more effective, that aren't helping 2% of those who take it, but hopefully most people. I, in the book, wrote about I want to see a guarantee to succeed model. I mean, you made the analogy of buying something as a consumer and if it didn't work, you take it back. You want your money back. I want to see that for drugs. I want to see: It doesn't work, then I'm not paying for it. That's where we need to be. And especially with the costs of these drugs. You know, there is a drug that's now a million dollars a treatment? There are drugs that are hundreds of thousands of dollars per treatment. Per year. Cystic fibrosis--if you are fortunate enough to be a child with a specific mutation that is sensitive to the new drug Kalydeco, it costs $294,000. A year, for the rest of the person's life, till something better comes along. I mean, this is ridiculous, these costs. That should be guaranteed to succeed, and even then it's too expensive. Russ: There's a complicated set of issues there about regulation, property rights, patents, FDA approval stuff. Guest: There's one thing, I can make it simple: somebody's making a lot of money out of that. Russ: That's true. But I think what your example, your description of the pharmaceutical industry moving away from mass medicine, I have two thoughts, which echo your opening chapters. One is: That's like cable TV. Instead of three channels producing shows that are on average popular, we get 100 channels producing shows that a lot more people love. And then the other example is the long tail, that Chris Anderson insight. He's been a guest on this program, talking about that. And you refer to it at the beginning of your book. In the digital world, very small niche markets get served magnificently which would never have been served in the physical world. Isn't one of the barriers to that in the drug industry the cost of approval and the requirement to prove efficacy? Which you point out isn't so efficacious for a lot of people? It's not a very good system. So, that's my rant. You can react to it or you can say what you would do to make it better. Guest: I think that the drug development woes were when there was trying to develop a drug that you could essentially give to everyone. Put in the water supply. But when you are developing a drug for a specific mutation, that's a whole different look. Now you've got the biologic basis and it can be done precisely and quickly. And it can also be fast-tracked through the FDA. So your time to market is reduced; your time, the number of patients needed to show overwhelming efficacy is trivial. And in addition, if you have overwhelming efficacy, if there happens to be a side effect, the benefit-risk ratio there is so favorable. So, my response to that is we are the long tail of pharmaceutical development that you are kind of getting at, is well suited--it could be an ideal model. And what's fascinating is once you have a drug that works on a specific pathway and mutation for something rare, it could turn out that it helps a lot more people than the ones who have that rare mutation. So, I think this is a model that's going to start getting popular. It's very different than the way we all conceive of pharma in the past. Russ: The system is not designed to make that easy. And it's partly not designed to make that easy because big pharma likes the current system. They are really good at compliance; they are really good at FDA testing, and they have something of an oligopoly because small competitors can't absorb those large fixed costs that FDA approval requires. So we are going to have to move, to get to your world of innovation, to get to a world of much more tolerance in that industry. Guest: That's right. I totally agree with you.
1:00:25Russ: Well, we're out of time. Let's close with a little bit of poetry--not the literal kind but the kind that makes your heart feel good. And I don't mean your physical heart--I meant your spiritual one. Your book is an incredible catalog of both the current state of medicine and where it might go. What gets Eric Topol the most excited out of all that? It's an incredible time to be in your field. I've got an 18 year old son who has got scientific leanings; I'm encouraging him and have been for a while, partly because of your book, lately, but also because of previous conversations--Freeman Dyson said if he were a young man he wouldn't go into physics, he would go into biology. Because that's where the action is; and he thinks most people feel that way; they might be wrong. But for you, what do you think is the most exhilarating part that's yet to come? Guest: That's a great question. I do think--I wish I could go back and be an 18 year old or be a medical student now. The most exciting time is of course going to be in the future. The thing I've worked on most in my life, from a research standpoint, has been preventing--treating heart attacks. But the dream of being able to prevent one, the sense that it was coming days or weeks before and gearing up so it doesn't happen, that to me as a singular project is the most exciting. But as an overall landscape, the idea that we will finally be able to recognize each human being, digitize what makes them tick, and render specific treatments and preventions for that individual at the doctor level, at the life science industry level--that to me is exhilarating. I can't think of a more ideal way to move forward and transition from this kind of horrible mess economically and with respect to the overall benefit/risk balance we're in today versus where we are going to go when the future, which will be so much more precise. Eventually we will get there. It just is a matter of time.

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