Michael Mina: Rapid Testing, Viruses, and the Engineering Mindset

00:00:00.000 | The following is a conversation with Michael Mina.

00:00:02.520 | He's a professor at Harvard doing research

00:00:05.320 | on infectious disease and immunology.

00:00:08.120 | The most defining characteristic of his approach

00:00:10.680 | to science and biology is that of a first principles thinker

00:00:14.080 | and engineer focused not just on defining the problem,

00:00:17.860 | but finding the solution.

00:00:20.120 | In that spirit, we talk about cheap,

00:00:22.120 | rapid at home testing, which is a solution to COVID-19

00:00:26.280 | that to me has become one of the most obvious,

00:00:28.760 | powerful and doable solutions.

00:00:31.560 | That frankly should have been done months ago

00:00:33.800 | and still should be done now.

00:00:35.720 | As we talk about its accuracy,

00:00:37.720 | it's high for detecting actual contagiousness

00:00:40.400 | and hundreds of millions can be manufactured quickly

00:00:43.040 | and relatively cheaply.

00:00:44.720 | In general, I love engineering solutions like these,

00:00:47.620 | even if government bureaucracies often don't.

00:00:51.320 | It respects science and data, it respects our freedom,

00:00:54.960 | it respects our intelligence and basic common sense.

00:00:59.200 | Quick mention of each sponsor,

00:01:00.560 | followed by some thoughts related to the episode.

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00:01:26.840 | to get a discount and to support this podcast.

00:01:30.040 | As a side note, let me say that

00:01:31.680 | I've always been solution-oriented, not problem-oriented.

00:01:35.720 | It saddens me to see that public discourse

00:01:38.240 | disproportionately focuses on the mistakes of those

00:01:41.880 | who dare to build solutions

00:01:43.680 | rather than applaud their attempt to do so.

00:01:46.440 | Teddy Roosevelt said it well

00:01:48.320 | in his "The Man in the Arena" speech over 100 years ago.

00:01:52.280 | I should say that both the critic

00:01:54.600 | and the creator are important.

00:01:56.840 | But in my humble estimation,

00:01:59.180 | there are too many now of the former

00:02:01.800 | and not enough of the latter.

00:02:03.640 | So while we spread the derisive words

00:02:06.920 | of the critic on social media, making it viral,

00:02:10.260 | let's not forget that this world is built

00:02:13.080 | on the blood, sweat, and tears of those who dare to create.

00:02:18.040 | If you enjoy this thing, subscribe on YouTube,

00:02:20.360 | review it with the Five Stars on Apple Podcast,

00:02:22.400 | follow on Spotify, support on Patreon,

00:02:24.920 | or connect with me on Twitter @LexFriedman.

00:02:28.040 | And now, here's my conversation with Michael Mina.

00:02:31.540 | What is the most beautiful, mysterious, or surprising idea

00:02:36.480 | in the biology of humans or viruses

00:02:39.640 | that you've ever come across in your work?

00:02:41.720 | Sorry for the overly philosophical question.

00:02:43.720 | (Lex laughing)

00:02:45.280 | - Wow, well, that's a great question.

00:02:47.720 | You know, I love the pathogenesis of viruses,

00:02:50.320 | and one of the things that I've worked on a lot

00:02:55.320 | is trying to understand how viruses interact

00:02:59.880 | with each other.

00:03:00.760 | And so pre all this COVID stuff,

00:03:05.040 | I was really, really dedicated to understanding

00:03:09.000 | how viruses impact other pathogens.

00:03:15.000 | So how if somebody gets an infection

00:03:17.200 | with one thing or a vaccine,

00:03:19.560 | does it either benefit or harm you from other things

00:03:22.440 | that appear to be unrelated to most people?

00:03:26.920 | And so one system which is highly detrimental to humans,

00:03:31.920 | but what I think is just immensely fascinating is measles.

00:03:37.240 | And measles gets into a kid's body.

00:03:40.880 | The immune system picks it up

00:03:43.120 | and essentially grabs the virus

00:03:47.620 | and does exactly what it's supposed to do,

00:03:50.760 | which is to take this virus

00:03:52.240 | and bring it into the immune system

00:03:54.000 | so that the immune system can learn from it,

00:03:56.320 | can develop an immune response to it.

00:03:58.760 | But instead, measles plays a trick.

00:04:00.720 | It gets into the immune system,

00:04:03.000 | serves almost as a Trojan horse,

00:04:05.120 | and instead of getting eaten by these cells,

00:04:08.520 | it just takes them over,

00:04:10.040 | and it ends up proliferating in the very cells

00:04:12.200 | that were supposed to kill it.

00:04:15.400 | And it just distributes throughout the entire body,

00:04:17.940 | gets into the bone marrow,

00:04:19.100 | kills off children's immune memories.

00:04:22.580 | And so it essentially,

00:04:24.560 | what I've found and what my research has found

00:04:26.660 | is that this one virus was responsible

00:04:29.980 | for as much as half of all of the infectious disease deaths

00:04:33.360 | in kids before we started vaccinating against it,

00:04:36.380 | 'cause it was just wiping out children's immune memories

00:04:40.160 | to all different pathogens,

00:04:41.520 | which is, you know, I think just astounding.

00:04:45.060 | It's just amazing to watch it spread throughout bodies.

00:04:48.960 | We've done the studies in monkeys,

00:04:50.360 | and you can watch it just destroy

00:04:52.880 | and obliterate people's immune memories

00:04:54.800 | in the same way that some parasite

00:04:57.100 | might destroy somebody's brain.

00:04:58.800 | - Is that a evolutionary just coincidence,

00:05:03.440 | or is there some kind of advantage

00:05:04.960 | to this kind of interactivity between pathogens?

00:05:08.540 | - Oh, I think in that sense, it's just coincidence.

00:05:11.720 | It probably is a,

00:05:13.120 | it's a good way for measles to,

00:05:15.480 | it's a good way for measles to essentially

00:05:19.540 | be able to survive long enough to replicate in the body.

00:05:23.180 | It just replicates in the cells

00:05:25.180 | that are meant to destroy it.

00:05:26.480 | So it's utilizing our immune cells for its own replication,

00:05:31.480 | but in so doing, it's destroying the memories

00:05:34.520 | of all the other immunological memories.

00:05:37.180 | But there are other viruses,

00:05:38.780 | so a different system is influenza.

00:05:42.200 | And flu predisposes to severe bacterial infections.

00:05:47.200 | And that, I think, is another coincidence,

00:05:50.520 | but I also think that there are,

00:05:53.320 | that there are some evolutionary benefits

00:05:55.340 | that bacteria may hijack

00:05:57.340 | and sort of piggyback on viral infections.

00:05:59.400 | Viruses can, they just grow so much quicker than bacteria.

00:06:04.200 | They replicate faster, and so there's this system

00:06:06.700 | with viruses, with flu and bacteria,

00:06:09.200 | where the influenza has these proteins

00:06:12.640 | that cleave certain receptors.

00:06:14.780 | And the bacteria wanna cleave those same receptors,

00:06:18.140 | or wanna cleave the same molecules

00:06:19.640 | that gave entrance to those receptors.

00:06:22.800 | So instead, the bacteria found out,

00:06:24.960 | like, hey, we could just piggyback on these viruses.

00:06:28.040 | They'll do it 100 or 1,000 times faster than we can.

00:06:31.700 | And so then they just piggyback on,

00:06:33.860 | and they let flu cleave all these sialic acids.

00:06:37.040 | And then the bacteria just glom on in the wake of it.

00:06:39.880 | So there's all different interactions between pathogens

00:06:43.100 | that are just remarkable.

00:06:45.280 | - So does this whole system of viruses

00:06:48.220 | that interact with each other,

00:06:49.420 | and so damn good at getting inside our bodies,

00:06:52.100 | does that fascinate you or terrify you?

00:06:54.880 | - I'm very much a scientist,

00:06:56.320 | and so it fascinates me much more than it terrifies me.

00:07:00.520 | But knowing enough, I know just how well,

00:07:03.540 | you know, we get the wrong virus in our population,

00:07:08.380 | whether it's through some random mutation,

00:07:10.460 | or whether it's this same COVID-19 virus.

00:07:12.680 | And it, you know, these things are tricky.

00:07:14.600 | They're able to mutate quickly.

00:07:17.400 | They're able to find new hosts and rearrange

00:07:21.360 | in the case of influenza.

00:07:22.920 | So what terrifies me is just how easily

00:07:27.240 | this particular pandemic could have been so much worse.

00:07:29.760 | This could have been a virus

00:07:30.880 | that is much worse than it is.

00:07:34.000 | You know, same thing with H1N1 back in 2009.

00:07:37.360 | That terrifies me.

00:07:38.320 | If a virus like that was much more detrimental,

00:07:41.620 | you know, that would be, it could be much more devastating.

00:07:46.720 | Although it's hard to say, you know,

00:07:48.100 | the human species were, well,

00:07:52.280 | I hesitate to say that we're good at responding to things

00:07:56.120 | because there are some aspects that were,

00:07:58.680 | this particular virus, SARS-CoV-2 and COVID-19

00:08:01.760 | has found a sweet spot where it's not quite serious enough

00:08:06.680 | on an individual level that humans just don't,

00:08:08.880 | we haven't seen much of a useful response by many humans.

00:08:12.880 | A lot of people even think it's a hoax.

00:08:16.040 | And so it's led us down this path of,

00:08:18.160 | it's not quite serious enough to get everyone

00:08:21.680 | to respond immediately and with the most urgency,

00:08:24.960 | but it's enough, it's bad enough that, you know,

00:08:27.560 | it's caused our economies to shut down and collapse.

00:08:30.120 | And so I think, I know enough about virus biology

00:08:34.120 | to be terrified for humans that, you know,

00:08:37.120 | it can, it just takes one virus,

00:08:39.200 | just takes the wrong one to just obliterate us

00:08:42.080 | or not obliterate us,

00:08:43.640 | but really do much more damage than we've seen.

00:08:45.800 | - It's fascinating to think that COVID-19

00:08:47.520 | is a result of a virus evolving together with like Twitter,

00:08:52.520 | like figuring out how we can sneak past the defenses

00:08:55.560 | of the humans, so it's not bad enough.

00:08:58.800 | And then the misinformation, all that kind of stuff

00:09:01.400 | together is operating in such a way

00:09:03.640 | that the virus can spread effectively.

00:09:06.240 | I wonder, I mean, obviously a virus is not intelligent,

00:09:10.360 | but there's a rhyme and a rhythm

00:09:15.360 | to the way this whole evolutionary process works

00:09:18.240 | and creates these fascinating things

00:09:20.080 | that spread throughout the entire civilization.

00:09:23.000 | - Absolutely, it's, yeah, I'm completely fascinated

00:09:28.000 | by this idea of social media in particular,

00:09:33.640 | how it replicates, how it grows, you know,

00:09:36.600 | I've been, how it actually starts interacting

00:09:40.080 | with the biology of the virus, masks,

00:09:42.840 | who's gonna get vaccinated, politics,

00:09:45.000 | like these seem so external to virus biology,

00:09:49.280 | but it's become so intertwined

00:09:52.200 | and it's interesting, and I actually think

00:09:55.760 | we could find out that, you know,

00:09:57.120 | the virus actually becomes, obviously not intentionally,

00:10:02.120 | but, you know, we could find that choosing,

00:10:06.280 | people choosing not to wear masks,

00:10:07.880 | choosing not to counter this virus

00:10:10.960 | in a regimented and sort of organized way

00:10:14.280 | effectively gives the virus more opportunity to escape.

00:10:18.080 | We can look at vaccines, you know,

00:10:20.760 | we're about to have one of the most aggressive

00:10:24.200 | vaccination programs the world has ever seen,

00:10:26.760 | but we are unfortunately doing it

00:10:29.800 | right at the peak of viral transmission

00:10:32.120 | when millions and millions of people

00:10:34.040 | are still getting infected, and when we do that,

00:10:37.400 | that just gives this virus so many more opportunities,

00:10:40.560 | I mean, orders of magnitude more opportunity

00:10:43.680 | to mutate around our immune system.

00:10:46.400 | Now, if we were to vaccinate everyone

00:10:48.280 | when there's not a lot of virus,

00:10:50.680 | then there's just not a lot of virus,

00:10:52.120 | and so there's not going to be as many,

00:10:54.760 | you know, I don't even know how many zeros

00:10:56.280 | are at the end of however many viral particles

00:10:58.440 | there are in the world right now,

00:10:59.560 | you know, more than quadrillions, you know,

00:11:02.760 | and so if you assume that at any given time,

00:11:05.460 | somebody might have trillions of virus in them

00:11:07.360 | on any given individual, so then, you know,

00:11:09.760 | multiply trillions by millions,

00:11:11.360 | and you know, you get a lot of viruses out there,

00:11:13.480 | and if you start applying pressure,

00:11:15.800 | ecological pressure to this virus,

00:11:19.200 | that when it's not abundant,

00:11:22.000 | God, the opportunity for a virus to sneak around immunity,

00:11:25.920 | especially when all the vaccines are identical, essentially.

00:11:29.360 | - It takes one to mutate, and it jumps, oh.

00:11:33.480 | - Takes one, takes one in the whole world,

00:11:35.560 | you know, and we have to not forget

00:11:37.680 | that this particular virus was one.

00:11:40.400 | It was one opportunity, and it has spread across the globe,

00:11:43.560 | and there's no reason that can't happen tomorrow,

00:11:45.720 | I knew, you know, it's scary.

00:11:49.020 | - I have a million other questions in this direction,

00:11:51.380 | but I'd love to talk about one of the most exciting aspects

00:11:56.100 | of your work, which is testing, or rapid testing.

00:12:00.700 | You wrote a great article in Time on November 17th,

00:12:04.900 | so this is like a month ago, about rapid testing,

00:12:08.820 | titled "How We Can Stop the Spread of COVID-19 by Christmas."

00:12:13.420 | Let's jot down the fact that this was a month ago,

00:12:15.700 | so maybe your timeline would be different,

00:12:17.940 | but let's say in a month.

00:12:19.460 | So you've talked about this powerful idea

00:12:21.380 | for quite a while, throughout the COVID-19 pandemic.

00:12:25.380 | How do we stop the spread of COVID-19 in a month?

00:12:28.100 | - Well, we use tests like these.

00:12:32.940 | You know, so the only reason the virus continues spreading

00:12:36.980 | is because people spread it to each other.

00:12:39.380 | This isn't magic.

00:12:41.060 | - Yes.

00:12:42.140 | - And so there's a few ways to stop the virus

00:12:45.700 | from spreading to each other,

00:12:47.980 | and that is you either can vaccinate everyone,

00:12:51.980 | and vaccinating everyone is a way

00:12:54.420 | to immunologically prevent the virus

00:12:56.220 | from growing inside of somebody and therefore spreading.

00:12:58.760 | We don't know yet, actually, if this vaccine,

00:13:01.220 | if any of these vaccines are going

00:13:02.620 | to prevent onward transmission,

00:13:05.260 | so that may or may not serve to be one opportunity.

00:13:10.060 | Certainly, I think it will decrease transmission,

00:13:12.680 | but the other idea that we have at our disposal now,

00:13:16.240 | we had it in May, we had it in June,

00:13:18.540 | July, August, September, October, November,

00:13:21.120 | and now it's December.

00:13:22.680 | We still have it, we still choose not to use it

00:13:25.300 | in this country and in much of the world,

00:13:28.160 | and that's rapid testing.

00:13:29.320 | That is giving, it's empowering people

00:13:31.600 | to know that they are infected

00:13:34.560 | and giving them the opportunity to not spread it

00:13:36.880 | to their loved ones and their friends

00:13:38.980 | and neighbors and whoever else.

00:13:41.880 | We could have done this, we still can.

00:13:44.740 | Today, we could start.

00:13:46.360 | We have millions of these tests.

00:13:48.520 | These tests are simple paper strip tests.

00:13:51.800 | They are, inside of this thing

00:13:54.660 | is just a little piece of paper.

00:13:56.440 | Now, and I can actually open it up here.

00:14:00.360 | There we go.

00:14:01.520 | So this, this is how we do it, right here.

00:14:05.260 | We have this little paper strip test.

00:14:07.280 | This is enough to let you know if you're infectious.

00:14:11.160 | With somewhere around the order of 99% sensitivity,

00:14:14.680 | 99% specificity, you can know

00:14:18.080 | if you have infectious virus in you.

00:14:20.840 | If we can get these out to everyone's homes,

00:14:23.240 | build these, make 10 million, 20 million,

00:14:25.200 | 30 million of them a day.

00:14:26.800 | You know, we make more bottles of Dasani water every day.

00:14:30.500 | We can make these little paper strip tests.

00:14:33.520 | And if we do that, and we get these into people's homes

00:14:36.680 | so that they can use them twice a week,

00:14:39.040 | then we can know if we're infectious.

00:14:41.960 | You know, is it perfect?

00:14:43.140 | Absolutely not.

00:14:44.060 | But is it near perfect?

00:14:45.120 | Absolutely.

00:14:46.360 | You know, and so if we can say,

00:14:48.520 | hey, the transmission of this is, you know,

00:14:51.360 | for every 100 people that get infected right now,

00:14:54.720 | they go on to infect maybe 130 additional people.

00:14:58.000 | And that's exponential growth.

00:14:59.160 | So 100 becomes 130.

00:15:01.360 | A couple days later, that 130 becomes another 165 people

00:15:06.360 | have now been infected.

00:15:08.640 | And you know, go over three weeks,

00:15:10.400 | and 100 people become 500 people infected.

00:15:13.920 | Now, it doesn't take much to have those 100 people

00:15:17.080 | not infect 130, but infect 90.

00:15:19.760 | All we have to do is remove, say, 30, 40% of new infections

00:15:24.520 | from continuing their spread.

00:15:26.280 | And then instead of exponential growth,

00:15:28.040 | you have exponential decay.

00:15:30.040 | So this doesn't need to be perfect.

00:15:32.000 | We don't have to go from 100 to zero.

00:15:34.120 | We just have to go and have those 100 people infect 90.

00:15:37.280 | And those 90 people infect, you know, 82,

00:15:40.600 | whatever it might be.

00:15:41.800 | And you do that for a few weeks, and boom,

00:15:43.720 | you have now gone, instead of 100 to 500,

00:15:45.760 | you've gone from 100 to 20.

00:15:47.720 | - Yes. - It's not very hard.

00:15:49.720 | And so the way to do that is to let people know

00:15:53.200 | that they're infectious.

00:15:55.280 | I mean, we're a perfect example right now.

00:15:58.200 | I, this morning, I used these tests

00:16:01.840 | to make sure that I wasn't infectious.

00:16:03.640 | Is it perfect?

00:16:04.480 | No, but it reduced my odds 99%.

00:16:06.880 | I already was at extremely low odds

00:16:08.600 | because I spend my life quarantining these days.

00:16:11.480 | - Well, the interesting thing with this test,

00:16:13.720 | with testing in general,

00:16:15.000 | which is why I love what you've been espousing,

00:16:17.360 | and it's really confusing to me

00:16:18.600 | that this has not been taken on,

00:16:20.880 | is it's one, an actual solution

00:16:24.640 | that's been available for a long time.

00:16:28.720 | There doesn't seem to have been solutions proposed

00:16:33.720 | at a large scale.

00:16:35.360 | And a solution that it seems like a lot of people

00:16:37.640 | would be able to get behind.

00:16:38.840 | There's some politicization or fear of other solutions

00:16:43.840 | that people have proposed, which is like lockdown.

00:16:47.120 | And there's a worry,

00:16:48.280 | especially in the American spirit of freedom,

00:16:50.760 | like you can't tell me what to do.

00:16:52.640 | The thing about tests is it empowers you

00:16:57.000 | with information, essentially.

00:16:59.080 | So like, it gives you more information

00:17:03.840 | about your role in this pandemic,

00:17:08.000 | and then you can do whatever the hell you want.

00:17:10.680 | It's all up to your ethics and so on.

00:17:13.000 | So it's obvious that with that information,

00:17:16.800 | people would be able to protect their loved ones

00:17:19.520 | and also do their sort of, quote unquote,

00:17:23.240 | duty for their country, right?

00:17:25.000 | Is protect the rest of the country.

00:17:26.800 | - That's exactly right.

00:17:27.840 | I mean, it's just, it's empowerment.

00:17:30.320 | But this is a problem.

00:17:32.240 | We have not put these into action in large part

00:17:35.280 | because we have a medical industry

00:17:37.880 | that doesn't wanna see them be used.

00:17:40.200 | We have a political and a regulatory industry

00:17:44.160 | that doesn't wanna see them be used.

00:17:45.640 | That sounds crazy.

00:17:46.520 | Why wouldn't they want them to be used?

00:17:48.840 | We have a very paternalistic approach

00:17:51.200 | to everything in this country.

00:17:52.640 | Now, despite this country kind of being founded

00:17:55.500 | on this individualistic ideal,

00:17:58.360 | pull yourself up from your bootstraps, all that stuff.

00:18:01.760 | When it comes to public health,

00:18:03.240 | we have a bunch of ivory tower academics who want data.

00:18:08.240 | They want to see perfection.

00:18:12.360 | And we have this issue of letting perfection

00:18:15.900 | get in the way of actually doing something at all,

00:18:19.280 | doing something effective.

00:18:21.520 | And so we keep comparing these tests, for example,

00:18:25.080 | to the laboratory-based PCR test.

00:18:28.000 | And sure, this isn't a PCR test,

00:18:30.800 | but this doesn't cost $100

00:18:32.480 | and it doesn't take five days to get back,

00:18:34.780 | which means in every single scenario,

00:18:36.800 | this is the more effective test.

00:18:38.900 | And we have, unfortunately, a system

00:18:41.720 | that's not about public health.

00:18:42.980 | We have entirely eroded any ideals of public health

00:18:47.980 | in our country for the biomedical complex,

00:18:51.560 | this medical industrial complex, which overrides everything.

00:18:55.300 | And that's why I'm just,

00:18:56.960 | can I swear on this podcast?

00:18:59.800 | - Yes. (both laughing)

00:19:02.680 | - I'm just so fucking pissed that these tests don't exist.

00:19:06.200 | Meanwhile, and everyone says,

00:19:08.480 | oh, we couldn't make these, that we could never do it.

00:19:11.220 | That would be such a hard, a difficult problem.

00:19:14.400 | Meanwhile, the vaccine gets,

00:19:16.280 | we have, at the same time that we could have gotten

00:19:18.760 | these stupid little paper strip tests out to every household,

00:19:22.060 | we have developed a brand new vaccine.

00:19:25.320 | We've gone through phase one, phase two, phase three trials.

00:19:28.000 | We've scaled up its production.

00:19:30.000 | And now we have UPS and FedEx

00:19:31.880 | and all the logistics in the world,

00:19:33.840 | getting freezers out to where they need to be.

00:19:35.880 | We have this immense, we see when it comes to medicine,

00:19:40.080 | something you're injecting into somebody,

00:19:42.400 | then all of a sudden people say, oh, yes, we can.

00:19:45.560 | But you say, oh no, that's too simple a solution,

00:19:48.680 | too cheap a solution.

00:19:49.760 | No way could we possibly do that.

00:19:52.180 | It's this faulty thinking in our country,

00:19:54.040 | which frankly is driven by big money,

00:19:58.000 | big, the only time when we actually think

00:20:00.800 | that we can do something that's maybe aggressive

00:20:03.520 | and complicated is when there's billions and billions

00:20:05.680 | and billions of dollars in it.

00:20:07.160 | - I mean, on a difficult note,

00:20:09.200 | because this is part of your work from before the COVID,

00:20:12.240 | it does seem that I saw a statistic currently

00:20:15.880 | is that 40% would not be taken,

00:20:18.400 | of Americans would not be taking the vaccine,

00:20:20.200 | some number like this.

00:20:21.800 | So you also have to acknowledge that

00:20:23.480 | all the money that's been invested,

00:20:25.720 | like there doesn't appear to be a solution

00:20:27.920 | to deal with the fear and distrust that people have.

00:20:32.240 | I bet, I don't know if you know this number,

00:20:34.680 | but for taking a strip, like a rapid test like this,

00:20:38.300 | I bet you people would say,

00:20:41.100 | like the percentage of people that wouldn't take it

00:20:43.040 | is in the single digits probably.

00:20:45.240 | - I completely think so.

00:20:46.840 | And there's a lot of people

00:20:48.060 | who don't wanna get a test today.

00:20:50.400 | And that's because it gets sent to a lab,

00:20:53.100 | it gets reported, it has all this stuff.

00:20:55.800 | And we're a country which teaches people

00:20:58.880 | from the time they're babies,

00:21:01.080 | to keep their medical data close to them.

00:21:04.480 | We have HIPAA, we have all these,

00:21:05.920 | we have immense rules and regulations

00:21:07.720 | to ensure the privacy of people's medical data.

00:21:11.560 | And then a pandemic comes around

00:21:13.000 | and we just assume that all that the average person

00:21:15.560 | is gonna wipe all of that away and say,

00:21:17.600 | oh no, I'm happy giving out, not just my own medical data,

00:21:20.560 | but also to tell the authorities,

00:21:22.940 | everyone who I've spent my time with,

00:21:24.340 | so that they all get a call

00:21:26.020 | and are pissed at me for giving up their names.

00:21:28.300 | So people aren't getting tested

00:21:30.100 | and they're definitely not giving up their contacts

00:21:33.020 | when it comes to contact tracing.

00:21:34.900 | And so for so many reasons, that approach is failing.

00:21:37.780 | Not to even mention the delays in testing

00:21:41.100 | and things like that.

00:21:41.940 | And so this is a whole different approach,

00:21:44.560 | but it's an approach that empowers people

00:21:47.020 | and takes the power a bit away from the people in charge.

00:21:51.580 | And that's what's really grating on,

00:21:54.340 | I think public health officials who say,

00:21:56.100 | no, we need the data.

00:21:57.460 | So they're effectively saying, if I can't have the data,

00:22:00.580 | I don't want the individuals,

00:22:02.220 | I don't want the public to have their own data either.

00:22:04.760 | Which is a terrible approach to a pandemic

00:22:06.680 | where we can't solve a public health crisis

00:22:09.860 | without actively engaging the public.

00:22:12.860 | It just doesn't work.

00:22:14.900 | And that's what we're trying to do right now,

00:22:17.460 | which is a terrible approach.

00:22:19.180 | - So first of all, you have a really nice,

00:22:21.700 | informative website, rapidtest.org,

00:22:23.900 | with information on this.

00:22:24.940 | I still can't believe this is not more popular.

00:22:26.940 | It's ridiculous.

00:22:27.780 | Okay, but one of the FAQs you have is,

00:22:32.780 | are rapid tests too expensive?

00:22:35.160 | So can cost be brought down?

00:22:38.300 | Like I take a weekly PCR test

00:22:41.800 | and I think I pay 160, 170 bucks a week.

00:22:46.140 | - No, I mean, it's criminal.

00:22:47.380 | Absolutely, we can get costs.

00:22:49.340 | This thing right here, costs less than a dollar to make.

00:22:53.220 | With everything combined, plus the swabs,

00:22:56.060 | maybe it costs a dollar 50.

00:22:58.020 | Could be sold for, frankly, it could be sold for $3

00:23:02.580 | and still make a profit if they wanna sell it for five.

00:23:04.740 | This one here, this is a slightly more complicated one,

00:23:08.920 | but you can see it's just got

00:23:10.980 | the exact same paper strip inside.

00:23:13.740 | This is really, it doesn't look like much,

00:23:15.740 | but it's kind of the cream of the crop

00:23:17.020 | in terms of these rapid tests.

00:23:19.320 | This is the one that the US government bought

00:23:20.860 | and it is doing an amazing job.

00:23:23.220 | It has a 99.9% sensitivity and specificity.

00:23:27.580 | So it's really good.

00:23:29.500 | And so essentially the way it works is you just,

00:23:31.820 | you use a swab, you put the,

00:23:34.140 | once you kind of use the swab on yourself,

00:23:36.140 | you put the swab into these little holes here,

00:23:39.020 | you put some buffer on it and you close it,

00:23:41.460 | and a line will show up if it's positive

00:23:43.900 | and a line won't show up if it's negative.

00:23:45.780 | It takes five, 10 minutes.

00:23:48.500 | This whole thing, this can be made so cheap

00:23:51.980 | that the US government was able to buy them,

00:23:54.680 | buy 150 million of them from Abbott for $5 a piece.

00:23:59.680 | So anyone who says that these are expensive,

00:24:03.240 | we have the proof is right here.

00:24:05.140 | This one at its, it was,

00:24:07.740 | Abbott did not lose money on this deal.

00:24:10.340 | They got $750 million for selling 150 million of these

00:24:14.820 | at five bucks a piece.

00:24:15.940 | All of these tests can do the same.

00:24:20.460 | So anyone who says that these should be,

00:24:22.500 | unfortunately what's happening though is the FDA

00:24:24.620 | is only authorizing all of these tests as medical devices.

00:24:28.380 | So what happens when you, if I'm a medical company,

00:24:32.340 | if I'm a test production company

00:24:34.580 | and I wanna make this test,

00:24:36.460 | and I go through and the FDA,

00:24:38.580 | at the end of my authorization, the FDA says,

00:24:42.060 | okay, you now have a medical device,

00:24:45.180 | not a public health tool, but a medical device,

00:24:47.880 | and that affords you the ability

00:24:49.820 | to charge insurance companies for it.

00:24:52.060 | Why would I ever as a,

00:24:55.980 | in our capitalistic economy and sort of infrastructure,

00:25:00.980 | why would I ever not sell this for $30

00:25:03.540 | when insurance will pay for it, or $100?

00:25:06.260 | Might only cost me 50 cents to make,

00:25:09.340 | but by pushing all of these tests

00:25:12.020 | through a medical pathway at the FDA,

00:25:14.660 | what extrudes out the other side

00:25:17.280 | is an expensive medical device

00:25:18.940 | that's erroneously expensive.

00:25:20.380 | It doesn't need to be inflated in cost,

00:25:22.900 | but the companies say, well, I'd rather make fewer of them

00:25:27.100 | and just sell them all for $30 a piece

00:25:30.340 | than make tens of millions of them, which I could do,

00:25:34.020 | and sell them at a dollar marginal profit.

00:25:39.020 | And so it's a problem with our whole medical industry

00:25:43.740 | that we see tests only as medical devices.

00:25:46.420 | And what I would like to see is for the government,

00:25:49.340 | in the same way that they bought

00:25:50.500 | 150 million of these from Abbott,

00:25:52.920 | they should be buying all of these tests,

00:25:56.820 | they should be buying 20 million a day

00:25:59.140 | and getting them out to people's homes.

00:26:00.700 | This virus has cost trillions of dollars

00:26:03.060 | to the American people.

00:26:05.020 | It's closed down restaurants and stores,

00:26:07.740 | and obviously the main streets across America

00:26:09.820 | have shuttered.

00:26:11.820 | It's killing people, it's killing our economy,

00:26:14.460 | it's killing lifestyles and lives.

00:26:17.900 | - This is an obvious solution.

00:26:19.260 | To me, this is exciting.

00:26:20.340 | This is a solution.

00:26:21.800 | I wish in April or something like that

00:26:25.700 | to launch the largest scale

00:26:28.880 | manufacturing deployment of tests.

00:26:33.340 | Doesn't matter what tests they are.

00:26:35.220 | It's obviously the capitalist system

00:26:37.060 | would create cheaper and cheaper tests

00:26:39.020 | that would be hopefully driving down to $1.

00:26:42.380 | So what are we talking about?

00:26:43.980 | In America, there's, I don't know,

00:26:46.100 | 300 plus million people.

00:26:49.180 | So that means you wanna be testing regularly, right?

00:26:54.140 | So how many do you think is possible to manufacture?

00:26:57.500 | What would be the ultimate goal to manufacture per month?

00:27:00.780 | - Yep, so if we wanna slow this virus

00:27:03.940 | and actually stop it from transmitting,

00:27:05.660 | achieve what I call herd effects,

00:27:07.360 | like vaccine herd immunity,

00:27:09.940 | herd effects are when you get that R value below one

00:27:13.160 | through preventing onward transmission.

00:27:14.700 | If we wanna do that with these tests,

00:27:15.940 | we need about 20 million to 40 million of them every day,

00:27:19.040 | which is not a lot.

00:27:21.580 | - In the United States? - In the United States.

00:27:23.540 | So we could do it.

00:27:24.500 | There's other ways.

00:27:25.320 | You can have two people in a household

00:27:27.180 | swab each other, swab themselves rather,

00:27:31.060 | and then mix, put the swabs into the same tube

00:27:33.500 | and onto one test.

00:27:34.320 | You can pool.

00:27:35.380 | So you can get a two or three X gain in efficiency

00:27:40.300 | through pooling in the household.

00:27:42.340 | Could do that in schools or offices too,

00:27:44.260 | where everyone just uses swab.

00:27:45.540 | You have those two people.

00:27:47.740 | I mean, even if it's just standing in line

00:27:50.220 | at a public testing site or something,

00:27:52.580 | you could just say, okay,

00:27:53.780 | these two are the last people to test or swab themselves.

00:27:56.980 | They go into one thing.

00:27:58.580 | And if it comes back positive,

00:27:59.900 | then you just do each person and it's rapid.

00:28:02.100 | So you can just say to the people,

00:28:03.700 | one of you is positive, let's test you again.

00:28:06.600 | So there's ways to get the efficiency gains much better.

00:28:10.500 | But let's say, I think that the optimal number right now

00:28:13.660 | that matches sort of what we can produce more or less today

00:28:16.740 | if we want it is 20 million a day.

00:28:19.020 | Right now, one company that,

00:28:20.540 | I don't have their test here,

00:28:21.700 | but one company is already producing

00:28:23.460 | five million tests themselves and shipping them overseas.

00:28:27.780 | It's an American company based in California called Inova,

00:28:30.920 | and they are giving five million tests to the UK every day.

00:28:34.960 | Not to the, you know, and this is just because there's no,

00:28:39.060 | the federal government hasn't authorized these tests.

00:28:42.180 | - So without the support of the government.

00:28:44.660 | So yeah, so essentially,

00:28:46.260 | if the government just put some support behind it,

00:28:49.220 | then yeah, you can get 20 million probably easy.

00:28:53.980 | - Oh yeah, this, I mean,

00:28:54.860 | just here I have three different companies.

00:28:57.500 | These, they all look similar.

00:28:58.660 | Well, this one's closed,

00:28:59.500 | but these are three different companies right here.

00:29:02.220 | This is a fourth, Abbott.

00:29:04.020 | Now this is a fifth.

00:29:05.580 | This is a sixth.

00:29:07.060 | These two are a little bit different.

00:29:08.620 | - Do you mind if in a little bit,

00:29:10.020 | would you take some of these or?

00:29:11.620 | - Yeah, let's do it.

00:29:12.820 | We can absolutely do them.

00:29:15.500 | - So you have a lot of tests in front of you.

00:29:17.820 | Could you maybe explain some of them?

00:29:20.060 | - Absolutely.

00:29:21.260 | So there's a few different classes of tests

00:29:24.340 | that I just have here.

00:29:25.340 | And there's more tests.

00:29:26.180 | There's many more different tests out in the world too.

00:29:28.860 | These are one class of test.

00:29:31.420 | These are rapid antigen tests

00:29:33.660 | that are just the most bare bones paper strip tests.

00:29:36.740 | These are, this is the type that I wanna see produced

00:29:41.740 | in the tens of millions every day.

00:29:43.920 | It's so simple.

00:29:45.420 | You know, you don't even need the plastic cartridge.

00:29:47.460 | You can just make the paper strip

00:29:52.180 | and you could have a little tube like this

00:29:55.340 | that you just dunk the paper strip into.

00:29:57.660 | You don't actually need the plastic,

00:30:00.140 | which I'd actually prefer

00:30:01.300 | because if we start making tens of millions of these,

00:30:03.460 | this becomes a lot of waste.

00:30:05.340 | So I'd rather not see this kind of waste be out there.

00:30:07.460 | And there's a few companies,

00:30:08.700 | Quidel is making a test called the QuickView,

00:30:11.580 | which is just this.

00:30:13.060 | They've gotten rid of all the plastic.

00:30:16.540 | - And for people who are just listening to this,

00:30:18.420 | we're looking at some very small tests

00:30:20.500 | that fit in the palm of your hand.

00:30:22.300 | And they're basically paper strips

00:30:24.340 | fit into different containers.

00:30:26.380 | And that's hence the comment about the plastic containers.

00:30:29.660 | - These are just injection molded, I think.

00:30:32.180 | And they can build them at high numbers,

00:30:36.920 | but then they have to like place them in there appropriately

00:30:38.980 | and all this stuff.

00:30:39.820 | So it is a bottleneck

00:30:41.460 | or somewhat of a bottleneck in manufacturing.

00:30:44.340 | The actual bottleneck,

00:30:45.940 | which the government I think

00:30:47.300 | should use the Defense Productions Act to build up

00:30:49.900 | is there's a nitrocellulose membrane,

00:30:52.780 | a laminated membrane on this that allows the material,

00:30:57.220 | the buffer with the swab mixture to flow across it.

00:31:02.220 | So the way these work, they're called lateral flow tests.

00:31:05.220 | And you take a swab, you swab the front of your nose,

00:31:10.080 | you dunk that swab into some buffer,

00:31:12.940 | and then you put a couple of drops of that buffer

00:31:15.580 | onto the lateral flow.

00:31:17.500 | And just like a paper,

00:31:19.080 | if you dip a piece of paper into a cup of water,

00:31:21.860 | the paper will pull the water up through capillary action.

00:31:25.020 | This actually works very similarly.

00:31:26.380 | It flows through somewhat a capillary action

00:31:29.740 | through this nitrocellulose membrane.

00:31:32.300 | And there's little antibodies on there.

00:31:33.900 | These little proteins that are very specific,

00:31:36.180 | in this case for antigens or proteins of the virus.

00:31:39.420 | So these are antibodies similar

00:31:41.460 | to the antibodies that our body makes

00:31:44.500 | from our immune system,

00:31:45.700 | but they're just printed on these lateral flow tests.

00:31:48.420 | And they're printed just like a little line.

00:31:50.620 | So then you slice these all up into individual ones.

00:31:54.620 | And if there's any virus on that buffer,

00:31:56.700 | as it flows across, the antibodies grab that virus,

00:32:00.100 | and it creates a little reaction with some colloids in here

00:32:03.240 | that cause it to turn dark.

00:32:04.920 | Just like a pregnancy test, one line means negative.

00:32:08.900 | It means a control strip worked.

00:32:11.540 | And two lines mean positive.

00:32:13.100 | Means, you know, if you get two lines,

00:32:16.100 | it just means you have virus there.

00:32:17.140 | You're very, very likely to have virus there.

00:32:18.620 | And so they're super simple.

00:32:20.980 | This is, it is the exact same technology as pregnancy tests.

00:32:23.940 | It's the technology, this particular one from Abbott,

00:32:27.980 | this has been used for other infectious diseases

00:32:31.060 | like malaria.

00:32:32.500 | And actually a number of these companies

00:32:34.340 | have made malaria tests that do the exact same thing.

00:32:37.520 | So they just co-opted the same form factor

00:32:41.280 | and just changed the antibodies

00:32:43.380 | so it picks up SARS-CoV-2 instead of other infections.

00:32:46.620 | - Is it also the Abbott one, is it also a strip?

00:32:48.780 | - Yep, yeah, this Abbott one here is,

00:32:51.060 | there's the, in this case,

00:32:52.180 | instead of being put in a plastic sheath,

00:32:53.740 | it's just put in a cardboard thing and literally glued on.

00:32:56.940 | I mean, it looks like nothing.

00:32:58.540 | You know, it's just, it looks like a,

00:33:01.380 | like, I mean, it's just the simplest thing

00:33:03.900 | you could imagine.

00:33:04.740 | - The exterior packaging looks very Apple-like, it's nice.

00:33:07.600 | - It does, yeah, yeah.

00:33:09.440 | Yeah, so it's nice and it comes in a,

00:33:11.840 | this is the, this is how they're packaged.

00:33:14.600 | You know, so, and they don't have to,

00:33:17.600 | you know, these are coming in individual packages,

00:33:19.960 | again, because they're really considered

00:33:21.960 | individual medical devices,

00:33:24.200 | but you could package them in, you know,

00:33:25.840 | bigger packets and stuff.

00:33:27.040 | You wanna be careful with humidity

00:33:28.760 | so they all have a little,

00:33:30.280 | one of those humidity-removing things

00:33:33.600 | and oxygen-removing things.

00:33:35.080 | So that's, this is one class, these antigen tests.

00:33:39.980 | - If we could just pause for a second, if it's okay,

00:33:42.620 | and could you just briefly say what is an antigen test

00:33:47.620 | and what other tests there are out there,

00:33:49.580 | like categories of tests?

00:33:50.980 | - Sure.

00:33:51.820 | - Just really quick.

00:33:52.740 | - So the testing landscape is a little bit complicated,

00:33:55.220 | but it's, but I'll break it down.

00:33:56.940 | There's really just three major classes of tests.

00:34:00.080 | We'll start with the first two.

00:34:02.820 | The first two tests are just looking for the virus

00:34:06.320 | or looking for antibodies against the virus.

00:34:10.100 | So we've heard about serology tests,

00:34:12.580 | or maybe some people have heard about it.

00:34:14.600 | Those are a different kind of test.

00:34:15.900 | They're looking to see, has somebody in the past,

00:34:19.260 | does somebody have an immune response against the virus,

00:34:21.500 | which would indicate that they were infected

00:34:23.280 | or exposed to it.

00:34:24.780 | So we're not talking about the antibody tests.

00:34:26.780 | I'll just leave it at that.

00:34:27.860 | Those, they actually can look very similar to this

00:34:31.780 | where they can be done in a laboratory.

00:34:35.420 | Those are usually done from blood

00:34:37.620 | and they're looking for an immune response to the virus.

00:34:40.620 | So that's one.

00:34:41.780 | Everything I'm talking about here

00:34:43.060 | is looking for the virus itself,

00:34:44.720 | not the immune response to the virus.

00:34:46.960 | And so there's two ways to look for the virus.

00:34:49.140 | You can either look for the genetic code of the virus,

00:34:51.340 | like the RNA, just like the DNA of somebody's human cells,

00:34:55.520 | or you can look for the proteins themselves,

00:34:57.460 | the antigens of the virus.

00:34:59.800 | So I like to differentiate them.

00:35:02.420 | If you were a PCR test that looks for RNA in,

00:35:07.420 | let's say if we made it against humans,

00:35:10.980 | it would be looking for the DNA inside of our cells.

00:35:13.100 | That would be actually looking for our genetic code.

00:35:15.700 | The equivalent to an antigen test is sort of a test

00:35:21.020 | that like actually is looking for our eyes or our nose

00:35:23.500 | or physical features of our body that would delineate,

00:35:27.180 | okay, this is Michael, for example.

00:35:30.300 | And so you're either looking for a sequence

00:35:33.640 | or you're looking for a structure.

00:35:35.980 | The PCR tests that a lot of people have gotten now

00:35:38.640 | and they're done in labs usually

00:35:40.640 | are looking for the sequence of the virus, which is RNA.

00:35:43.640 | This test here by a company called Detect,

00:35:46.960 | this is one of Jonathan Rothberg's companies.

00:35:49.360 | He's the guy who helped create modern day sequencing

00:35:54.200 | and all kinds of other things.

00:35:56.080 | So this Detect device, that's the name of the company,

00:35:58.860 | this is actually a rapid RNA detection device.

00:36:02.000 | So it's almost like a PCR-like test

00:36:04.160 | and we could even do it here.

00:36:06.120 | It's really, it's a beautiful test in my opinion.

00:36:09.140 | Works exceedingly well.

00:36:10.980 | It's gonna be a little bit more expensive

00:36:12.420 | so I think it could confirm,

00:36:14.200 | could be used as a confirmatory test for these.

00:36:16.480 | - Is there a greater accuracy to it?

00:36:18.280 | - Yes, I would say that there is a greater accuracy.

00:36:21.800 | There's also a downfall though of PCR

00:36:23.980 | and tests that look for RNA,

00:36:26.480 | they can sometimes detect somebody

00:36:29.960 | who is no longer infectious.

00:36:32.380 | So you have the RNA test

00:36:33.920 | and then you have these antigen tests.

00:36:35.800 | The antigen tests look for structures

00:36:37.920 | but they're generally only going to turn positive

00:36:40.600 | if people have actively replicating virus in them.

00:36:43.620 | And so what happens after an infection dissipates,

00:36:48.940 | you have, you've just gone from having sort of a spike.

00:36:51.980 | So if you get infected, maybe three days later,

00:36:54.240 | the virus gets into exponential growth

00:36:56.900 | and it can replicate to trillions of viruses inside the body.

00:37:01.520 | Your immune system then kind of tackles it

00:37:03.560 | and beats it down to nothing.

00:37:05.600 | But what ends up in the wake of that,

00:37:07.860 | you just had a battle.

00:37:08.760 | You had this massive battle that just took place

00:37:11.000 | inside your upper respiratory tract.

00:37:12.800 | And because of that,

00:37:14.680 | you've had trillions and trillions of viruses

00:37:17.640 | go to zero essentially.

00:37:19.720 | But the RNA is still there.

00:37:21.600 | It's just, it's these remnants.

00:37:23.100 | In the same way that if you go to a crime scene

00:37:24.900 | and blood was sort of spread all over the crime scene,

00:37:28.900 | you're gonna find a lot of DNA.

00:37:30.820 | There's tons of DNA.

00:37:31.660 | There's no people anymore,

00:37:33.420 | but there's a lot of DNA there.

00:37:35.300 | Same thing happens here.

00:37:36.420 | And so what's happening with PCR testing

00:37:38.740 | is when people go and use these exceedingly

00:37:41.260 | high sensitivity PCR tests,

00:37:44.140 | people will stay positive for weeks or months

00:37:46.880 | after their infection has subsided,

00:37:49.780 | which has caused a lot of problems in my opinion.

00:37:51.600 | It's problems that the CDC and the FDA

00:37:54.240 | and doctors don't wanna deal with.

00:37:56.840 | But I've tried to publish on it.

00:37:58.180 | I've tried to suggest that this is an issue

00:38:01.720 | both to New York Times and others.

00:38:03.040 | And now it's unfortunately kind of taken on a life of its own

00:38:05.600 | of conspiracy theorists thinking.

00:38:07.120 | - Oh no.

00:38:07.960 | (laughs)

00:38:08.800 | - They call it a case demic.

00:38:10.080 | They say, oh, PCRs,

00:38:12.240 | it's detecting people who are false positive.

00:38:16.040 | They're not false positives.

00:38:17.360 | They're late positives, no longer transmissible.

00:38:20.780 | - I think the way you,

00:38:22.180 | like what I saw on rapidtest.org,

00:38:25.140 | I really liked the distinction

00:38:26.260 | between diagnostic sensitivity

00:38:27.860 | and contagiousness sensitivity.

00:38:30.100 | That's so,

00:38:32.160 | that website is so obvious that it's painful

00:38:37.420 | 'cause it's like, yeah,

00:38:38.260 | that's what we should be talking about

00:38:40.020 | is how accurately is a test able to detect

00:38:44.180 | your contagiousness?

00:38:46.300 | And you have different plots that show

00:38:47.800 | that actually there's,

00:38:49.580 | that antigen test,

00:38:52.800 | the test we're looking at today like rapid tests,

00:38:55.580 | actually really good at detecting contagiousness.

00:38:58.480 | - Absolutely.

00:38:59.320 | It all mixes back with this whole idea

00:39:01.660 | that of the medical industrial complex.

00:39:04.740 | In this country and in most countries,

00:39:07.580 | we have almost entirely defunded

00:39:10.940 | and devalued public health, period.

00:39:14.620 | We just have.

00:39:15.700 | And what that means is that we don't even,

00:39:20.060 | we don't have a language for it.

00:39:22.140 | We don't have a lexicon for it.

00:39:23.360 | We don't have a regulatory landscape for it.

00:39:25.900 | And so the only window we have to look at a test today

00:39:30.160 | is as a medical diagnostic test.

00:39:32.820 | And that becomes very problematic

00:39:36.420 | when we're trying to tackle a public health threat

00:39:40.140 | and a public health emergency by definition.

00:39:43.300 | This is a public health emergency that we're in.

00:39:45.980 | And yet we keep evaluating tests

00:39:48.900 | as though the diagnostic benchmark is the gold standard.

00:39:52.860 | Where if I'm a physician, I am a physician,

00:39:55.740 | so I'll put on that physician hat for a moment.

00:39:59.340 | And if I have a patient who comes to me

00:40:01.820 | and wants to know if their symptoms

00:40:04.660 | are a result of them having COVID,

00:40:08.660 | then I want every shred of evidence that I can get

00:40:11.060 | to see does this person currently

00:40:12.940 | or did they recently have this infection inside of them?

00:40:17.420 | And so in that sense, the PCR test is the perfect test.

00:40:21.380 | It's really sensitive.

00:40:23.100 | It will find the RNA if it's there at all

00:40:25.280 | so that I could say, you know,

00:40:26.900 | yeah, you have a low amount of RNA left.

00:40:29.000 | You might've been,

00:40:30.140 | you said your symptoms started two weeks ago.

00:40:32.560 | You probably were infectious two weeks ago

00:40:36.260 | and you have lingering symptoms from it.

00:40:39.180 | But that's a medical diagnosis.

00:40:41.740 | It's kind of like a detective recreating a crime scene.

00:40:44.780 | They wanna go back there and recreate the pieces

00:40:48.620 | so that they can assign blame or whatever it might be.

00:40:53.060 | But that's not public health.

00:40:54.020 | In public health, we need to only look forward.

00:40:56.220 | We don't wanna go back and say, well,

00:40:57.780 | was this person, are there symptoms

00:40:59.740 | because they had an infection two weeks ago?

00:41:01.980 | In public health, we just wanna stop the virus

00:41:05.020 | from spreading to the next person.

00:41:06.460 | And so that's where we don't care

00:41:09.100 | if somebody was infected two weeks ago.

00:41:11.820 | We only care about finding the people

00:41:13.780 | who are infectious today.

00:41:16.060 | And unfortunately, our regulatory landscape

00:41:19.980 | fails to apply that knowledge

00:41:24.060 | to evaluate these tests as public health tools.

00:41:26.300 | They're only evaluating the tests as medical tools.

00:41:29.420 | And therefore, we get all kinds of complaints

00:41:32.860 | that say this test, which detects 99 plus,

00:41:37.500 | you know, 99.8% of current infectious people,

00:41:41.620 | by the FDA's rubric, they'll say, no, no,

00:41:45.940 | that's, it's only 50% sensitive.

00:41:48.660 | And that's because when you go out into the world

00:41:50.660 | and you just compare this against PCR positivity,

00:41:53.820 | most people who are PCR positive in the world right now

00:41:57.020 | at any given time are post-infectious.

00:42:00.700 | They're no longer infectious

00:42:01.860 | because you might only be infectious for five days,

00:42:05.140 | but then you'll remain PCR positive

00:42:06.900 | for three or four or five weeks.

00:42:09.380 | And so when you go and just evaluate these tests

00:42:11.540 | and you say, okay, this person's PCR positive,

00:42:14.180 | does the rapid antigen test detect that?

00:42:17.340 | More often than not, it's no.

00:42:19.220 | But that's because those people don't need isolation.

00:42:22.460 | You know, they're post-infectious.

00:42:24.260 | And this is a, it's become much more of a problem

00:42:27.980 | than I think even the FDA themself is recognizing

00:42:31.500 | because they are unwilling at this point

00:42:33.740 | to look at this as a public health problem

00:42:37.340 | requiring public health tools.

00:42:39.060 | - We'll definitely talk about this a little bit more

00:42:41.300 | because the concern I have is that like

00:42:43.580 | a bigger pandemic comes along,

00:42:45.580 | what are the lessons we draw from this

00:42:47.340 | and how we move forward?

00:42:48.300 | Let's talk about that in a bit.

00:42:50.300 | But so can we discuss further the lay of the land here

00:42:55.300 | of the different tests before us?

00:42:57.180 | - Absolutely.

00:42:58.020 | So I talked about PCR tests and those are done in the lab

00:43:01.140 | or they're done essentially with a rapid test like this

00:43:05.420 | that detect, and we can even try this in a moment.

00:43:08.060 | It goes into a little heater.

00:43:09.640 | So you might have one of these in a household

00:43:11.580 | or one of these in a nursing home or something like that

00:43:14.660 | or in an airport, or you could have one

00:43:17.500 | that has a hundred different outlets.

00:43:19.580 | This is just to heat the tube up.

00:43:21.560 | These are the rapid tests.

00:43:22.820 | They are super simple, no frills.

00:43:25.820 | You just swab your nose and you put the swab into a buffer

00:43:31.060 | and you put the buffer on the test.

00:43:32.380 | So we can use these right now if you want.

00:43:34.540 | We can try it out.

00:43:35.380 | - And all the tests we're talking about,

00:43:37.020 | they're usually swabbing the nose.

00:43:40.100 | Like that's the--

00:43:41.420 | - That's still the main, yeah.

00:43:43.420 | There are some saliva tests coming about

00:43:46.140 | and these can all work potentially with saliva.

00:43:48.380 | They just have to be recalibrated.

00:43:50.380 | But these swabs are really not bad.

00:43:52.920 | This isn't the deep swab that goes like way back

00:43:57.380 | into your nose or anything.

00:43:58.580 | This is just a swab that you do yourself

00:44:02.100 | like right in the front of your nose.

00:44:04.020 | So if you wanna do it--

00:44:04.860 | - Yeah, do you mind if I--

00:44:05.780 | - Sure, yeah.

00:44:07.020 | Yeah, why don't we start with this one?

00:44:08.320 | 'Cause this is Abbott's BinexNOW test

00:44:10.860 | and it's really, it's pretty simple.

00:44:12.780 | - This is the swab from the Abbott test.

00:44:15.940 | - That's correct.

00:44:16.780 | That's the swab from the Abbott test.

00:44:18.620 | So what I'm gonna do to start

00:44:21.700 | is I'm going to take this buffer here,

00:44:24.180 | which is, this is just the buffer that goes onto this test.

00:44:28.140 | So this is a brand new one.

00:44:29.000 | I just opened this test out.

00:44:31.020 | I'm gonna just take six drops of this buffer

00:44:35.020 | and put it right onto this test here.

00:44:37.120 | - Two, three, four, five, six.

00:44:43.740 | - Okay, and now you're gonna take that swab, open it up.

00:44:47.100 | Yep, and now just wipe it around inside the,

00:44:51.140 | into the front of your nose.

00:44:52.580 | Do a few circles on each nostril.

00:44:55.940 | (sniffing)

00:44:58.500 | That looks good.

00:44:59.340 | - This always makes me wanna sneeze.

00:45:05.580 | - Yeah. (laughs)

00:45:07.300 | Okay, now I'm gonna have you do it yourself.

00:45:09.740 | - I'm getting emotional.

00:45:13.700 | - Hold it parallel to the test.

00:45:15.140 | So put the test down on the table.

00:45:16.460 | Yep, and then go into that bottom hole.

00:45:19.220 | Yep, and push forward

00:45:20.380 | so that you can start to see it in the other hole.

00:45:23.060 | There you go.

00:45:23.900 | And then turn, if it's, once it hits up against the top,

00:45:26.700 | just turn it three times, one, two, three, and sort of,

00:45:30.780 | yep, and now you just close.

00:45:33.220 | So pull off that adhesive sticker there.

00:45:35.540 | And now you just close the whole thing.

00:45:39.340 | - And.

00:45:43.060 | - And that's it.

00:45:44.220 | - That's it.

00:45:45.060 | - Now what we will see is we will see a line form.

00:45:51.420 | What's happening now is the buffer that you put in there

00:45:55.420 | is now moving up onto the paper strip test

00:46:00.420 | and it has the material from the swab in there.

00:46:04.980 | And so what we'll see is a line will form

00:46:07.500 | and that's gonna be the control line.

00:46:09.380 | And then we'll also see the,

00:46:13.020 | ideally we'll see no line for the actual test line.

00:46:17.540 | And that's because you should be negative.

00:46:20.140 | So one line will be positive and two lines will be negative.

00:46:24.140 | - It's very cool.

00:46:24.980 | There's this purple thing creeping up

00:46:27.260 | onto the control line.

00:46:30.340 | - That's perfect.

00:46:32.460 | That's what you wanna be seeing.

00:46:34.020 | So you want to see that,

00:46:36.700 | so right now you essentially want to see

00:46:41.100 | that that blue line turns pink or purple-y color.

00:46:45.780 | There's a blue line that's already there, printed.

00:46:49.260 | It should turn sort of a purple-pink color.

00:46:52.660 | And ideally there will be no additional line for the sample.

00:46:57.660 | - And if there is, that's the 99 point whatever percent

00:47:04.900 | accuracy on, that means I have, I'm contagious.

00:47:09.140 | - That would mean that you're likely contagious

00:47:11.180 | or you likely have infectious virus in you.

00:47:14.260 | What we can do, because one of the things

00:47:16.380 | that my plan calls for is because sometimes

00:47:20.980 | these tests can get false positive results, it's rare.

00:47:24.580 | Maybe 1% or in the case of this BinaxNOW,

00:47:27.620 | this Abbott test, 0.1%.

00:47:30.140 | So one in a thousand, one in 500,

00:47:31.940 | something like that can be falsely positive.

00:47:34.380 | What I recommend is that when somebody is positive

00:47:38.020 | on one of these, you turn around

00:47:40.020 | and you immediately test on a different test.

00:47:42.340 | You could either do it on the same,

00:47:43.380 | but for as good measure, you want to use a separate test

00:47:48.180 | that is somewhat orthogonal,

00:47:51.340 | meaning that it shouldn't turn falsely positive

00:47:54.140 | for the same reason.

00:47:56.060 | This particular test here, this detect test,

00:47:59.620 | because it is looking for the RNA and not the antigen,

00:48:03.540 | this is an amazingly accurate test.

00:48:05.700 | And it's sort of a perfect gold standard

00:48:09.380 | or confirmatory test for any of these antigen tests.

00:48:12.740 | So one of the recommendations that I've had,

00:48:14.780 | especially if people start using antigen tests

00:48:17.780 | before you get onto a plane,

00:48:19.740 | or as what I call entrance screening,

00:48:22.820 | if somebody's positive, you don't immediately tell them,

00:48:26.340 | you're positive, go isolate for 10 days.

00:48:28.700 | You tell them, let's confirm on one of these,

00:48:31.940 | on a detect test, that is because it's completely orthogonal,

00:48:36.620 | it's looking for the RNA instead of the antigen.

00:48:40.380 | There's no reason, no biological reason,

00:48:43.540 | that both of these should be falsely positive.

00:48:46.300 | So if one's falsely positive and the other one is negative,

00:48:50.500 | especially because this one's more sensitive,

00:48:52.740 | then I would trust this as a confirmatory test.

00:48:56.900 | If this one's negative, then the antigen test

00:49:00.380 | would be considered falsely positive.

00:49:02.180 | - It does look like there's only a single line,

00:49:04.140 | so this is very exciting news.

00:49:05.540 | - That's right, yep. (laughs)

00:49:07.580 | It says wait 15 minutes to see both lines,

00:49:10.900 | but in general, if somebody's really gonna be positive,

00:49:14.060 | that line starts showing up within a minute or two.

00:49:17.140 | So you wanna keep the whole,

00:49:18.180 | we'll keep watching it for the whole 15 minutes

00:49:20.340 | as it's sitting there, but I would say you're,

00:49:23.580 | knowing that you've had PCR tests recently and all that.

00:49:26.860 | - The odds are pretty good. - The odds are very good.

00:49:28.780 | - The packaging, very iPhone-like.

00:49:30.780 | I'm digging the sexy packaging.

00:49:33.660 | I'm a sucker for good packaging, okay.

00:49:36.020 | So then there's this test here, which is,

00:49:38.340 | this is another, it's funny,

00:49:41.540 | let me open this up and show you.

00:49:42.900 | This is a really nice test.

00:49:44.340 | It's another antigen test.

00:49:45.660 | Works the exact same way as this, essentially.

00:49:48.260 | But what you can see is it's got lights in it

00:49:51.140 | and a power button and stuff.

00:49:52.260 | This is called an Ellume test, which is fine,

00:49:57.260 | and it's a really nice test, to be honest,

00:50:00.060 | but it has to pair with an iPhone.

00:50:04.340 | And so it's good as a, I think that this is gonna become,

00:50:07.540 | there's a lot of use for this from a medical perspective,

00:50:11.740 | where you want good reporting.

00:50:13.020 | This can, because it pairs with an iPhone,

00:50:15.900 | it can immediately send the report to a department of health,

00:50:20.420 | whereas these paper strip tests, they're just paper.

00:50:23.340 | They don't report anything unless you wanna report it.

00:50:26.580 | Okay, so I'm gonna just pick it apart.

00:50:28.860 | And so you can see is there's fluorescent readers

00:50:32.180 | and little lasers and LEDs and stuff in there.

00:50:34.700 | You can actually see the lights going off.

00:50:37.100 | And there's a paper strip test right inside there,

00:50:39.380 | but you can see that there's a whole circuit board

00:50:41.380 | and all this stuff, right?

00:50:44.380 | And so this is the kind of thing

00:50:48.100 | that the FDA is looking for,

00:50:50.420 | for home use and things like that,

00:50:54.780 | because it's kind of foolproof.

00:50:56.380 | You can't go wrong with it.

00:50:58.340 | It pairs with an iPhone, so you need Bluetooth,

00:51:00.540 | so it's gonna be more limited.

00:51:01.780 | It's a great test, don't get me wrong.

00:51:03.180 | It's as good as any of these.

00:51:05.220 | But when you compare this thing with a battery

00:51:08.420 | and a circuit board and all this stuff,

00:51:10.900 | it's got its purpose, but it's not a public health tool.

00:51:14.080 | I don't wanna see this made in the tens of millions a day

00:51:17.020 | and thrown away.

00:51:17.940 | - But FDA likes that kind of stuff.

00:51:20.420 | - FDA loves this stuff,

00:51:22.020 | 'cause they can't get it out of their mind

00:51:23.980 | that this is a public health crisis.

00:51:26.020 | We need, I mean, just look at the difference here.

00:51:29.380 | - Something with flashing lights

00:51:30.540 | is essential. - Yeah.

00:51:32.060 | It's got batteries, it's got a Bluetooth thing.

00:51:34.020 | It's a great test, but to be honest,

00:51:36.620 | it's not any better than this one.

00:51:39.780 | And so I want this one.

00:51:42.440 | It's nice and all.

00:51:44.340 | The form factor is nice,

00:51:46.420 | and it's really nice that it goes to Bluetooth.

00:51:48.980 | - But it goes against the principle

00:51:50.460 | of just 20 million a day.

00:51:52.620 | - Exactly. - The easy solution.

00:51:53.900 | Everybody has it.

00:51:54.860 | You can manufacture, and probably,

00:51:57.580 | you could have probably scaled this up

00:51:58.980 | in a couple of weeks.

00:52:00.060 | - Oh, absolutely.

00:52:00.900 | These companies, I mean, the rest of the world has these.

00:52:04.220 | They can be scaled up.

00:52:05.300 | They already exist.

00:52:06.700 | You know, SD biosensors,

00:52:08.100 | one company's making tens of millions a day,

00:52:10.460 | not coming to the United States,

00:52:11.860 | but going all over Europe,

00:52:13.420 | going all over Southeast Asia and East Asia.

00:52:16.980 | So they exist.

00:52:17.900 | The US is just, you know,

00:52:18.980 | we can't get out of our own way.

00:52:21.100 | - I wonder why somebody,

00:52:22.380 | I don't know if you were paying attention,

00:52:23.620 | but somebody like an Elon Musk type character,

00:52:26.900 | so he was really into doing some, like,

00:52:28.980 | obvious engineering solution.

00:52:30.580 | Like, this at-home rapid test

00:52:33.980 | seems like a very Elon Musk thing to do.

00:52:37.220 | - I don't know if you saw,

00:52:38.140 | but I had a little Twitter conversation with Elon Musk.

00:52:41.820 | - Does he not like, what is he,

00:52:43.420 | do you know what his thoughts are on rapid testing?

00:52:45.500 | - Well, he was using a slightly different one,

00:52:47.180 | one of these, but that requires an instrument

00:52:49.180 | called the BD Veritor,

00:52:50.860 | and he got a false positive.

00:52:52.020 | Or no, I shouldn't say,

00:52:53.020 | he didn't necessarily get a false positive.

00:52:54.580 | He got discrepant results.

00:52:55.920 | He did this test four times.

00:52:57.900 | He got two positives, two negatives.

00:52:59.740 | But then he got a PCR test,

00:53:02.340 | and it was a very low positive result.

00:53:05.080 | So I think what happened

00:53:06.580 | is he just tested himself at the tail end of an,

00:53:09.140 | this was actually right before he was about to send those,

00:53:11.140 | it was the day of, essentially,

00:53:12.220 | that he was sending the astronauts

00:53:13.420 | up to the space station the other day.

00:53:15.140 | So he was using these rapid tests

00:53:17.820 | 'cause he wanted to make sure that he was good to go in,

00:53:20.100 | and he got discrepant results.

00:53:23.140 | Ultimately, they were correct.

00:53:25.220 | But, you know, two were negative, two were positive,

00:53:26.900 | but what really happened,

00:53:28.540 | once he got his, he shared his PCR results,

00:53:30.740 | and they were very low positive.

00:53:32.860 | So really what was happening is,

00:53:34.580 | my guess is he found himself

00:53:36.140 | right at the edge of his positivity, of his infectiousness.

00:53:39.940 | And so, you know, the test worked

00:53:41.500 | how it was supposed to work.

00:53:42.540 | It, probably had he used it two days earlier,

00:53:45.820 | it would have been screaming positive.

00:53:47.260 | You know, he wouldn't have gotten discrepant results.

00:53:49.500 | But he found himself right at the edge

00:53:51.180 | by the time he used the test.

00:53:52.800 | So the PCR would always pick it up

00:53:55.100 | 'cause it's still, 'cause it will still stay positive

00:53:57.340 | then for weeks potentially.

00:53:59.100 | But the rapid antigen test was starting to falter,

00:54:02.660 | not in a bad way, but just,

00:54:04.960 | he probably was really no longer particularly infectious.

00:54:07.860 | And so it was kinda,

00:54:09.080 | when it gets to be a very low viral load,

00:54:10.940 | it becomes stochastic.

00:54:12.740 | - It's fascinating, this duality.

00:54:14.380 | So one, you can think from an individual perspective,

00:54:18.440 | it's unclear when you take four and half

00:54:20.780 | are positive, half are negative,

00:54:23.860 | like what are you supposed to do?

00:54:25.660 | But from a societal perspective,

00:54:28.120 | it seems like if just one of them is positive,

00:54:30.900 | just stay home for a couple of days, for a while.

00:54:34.580 | So when you're a CEO of a company

00:54:36.220 | and launching astronauts to space,

00:54:38.020 | you may not want to rely absolutely on the antigen test

00:54:43.020 | as a thing by which you steer your decisions

00:54:47.380 | of like 10,000 plus people companies.

00:54:50.420 | But us individuals just living in the world,

00:54:53.780 | if it comes up positive,

00:54:56.140 | then you make decisions based on that.

00:54:59.340 | And then that scales really nicely

00:55:00.860 | to an entire society of hundreds of millions of people.

00:55:03.620 | And that's how you get that virus to stop spreading.

00:55:07.420 | - That's exactly right.

00:55:08.300 | You don't have to catch every single one.

00:55:10.420 | And the nice thing is that these will,

00:55:12.720 | these will catch the people who are most infectious.

00:55:15.740 | So with Elon Musk,

00:55:16.940 | generally that test, we don't have the counterfactual.

00:55:20.420 | We don't have his results from three days earlier

00:55:23.260 | when he was probably most infectious.

00:55:25.180 | But my guess is the fact that it was catching two

00:55:30.020 | out of the four, even when he was down at a CT value,

00:55:33.220 | a really, really very, very low viral load on the PCR test,

00:55:36.740 | suggests that it was doing its job.

00:55:38.640 | And you just wanna, and the nice thing is

00:55:42.220 | because these can be produced at such scale,

00:55:44.580 | getting one positive doesn't immediately have to mean

00:55:49.140 | 10 days of isolation.

00:55:51.760 | That's the CDC's more conservative stance to say,

00:55:55.660 | if you're positive on any test,

00:55:57.620 | stay home for 10 days and isolate.

00:55:59.220 | But here, people would just have more tests.

00:56:01.780 | So the recommendation should be test daily.

00:56:04.620 | If you turn positive, test daily

00:56:06.940 | until you've been negative for 24, 48 hours,

00:56:09.260 | and then go back to work.

00:56:10.240 | And the nice thing there is,

00:56:12.340 | now right now people just aren't testing

00:56:14.020 | 'cause they don't wanna take 10 days off.

00:56:15.740 | They're not getting paid for it.

00:56:16.980 | So they can't take 10 days off.

00:56:18.580 | - Do you know what Elon thinks about this idea

00:56:21.840 | of rapid testing for everybody?

00:56:23.400 | So I understood, I need to look at that whole Twitter thread.

00:56:26.680 | So I understand his perhaps criticism of,

00:56:29.780 | he had like a conspiratorial tone from my vague look at it

00:56:34.720 | of like, what's going on here with these tests?

00:56:37.920 | But what does he actually think about this very practical

00:56:41.560 | to me engineering solution

00:56:43.040 | of just deploying rapid tests to everybody?

00:56:45.120 | It seems like that's a way to open up the economy in April.

00:56:48.560 | - Well, to be honest,

00:56:49.400 | I've been trying to get in touch with him again.

00:56:51.480 | I think take somebody like Elon Musk

00:56:54.920 | with the engineering prowess within his ranks

00:56:57.720 | to easily, easily build these at the tens of millions a day.

00:57:02.720 | He could build the machines from scratch.

00:57:07.120 | A lot of the companies,

00:57:08.200 | they buy the machines from South Korea or Taiwan, I believe.

00:57:12.840 | We don't have to, we can build these machines.

00:57:15.080 | They're simple to build.

00:57:17.000 | Put somebody like Elon Musk on it,

00:57:20.160 | take some of his best engineers and say,

00:57:21.960 | "Look, the US needs a solution in two weeks.

00:57:26.840 | "Build these machines, figure it out."

00:57:29.080 | He'll do it, he could do it.

00:57:30.100 | This is a guy who is literally,

00:57:33.080 | he has started multiple entirely new industries.

00:57:36.860 | He has the capital to do it without the US government

00:57:40.820 | if he wanted to.

00:57:41.880 | And you know what, it would,

00:57:43.480 | the return on investment for him would be huge.

00:57:47.480 | But frankly, the return on investment in the country

00:57:50.400 | would be hundreds of billions of dollars

00:57:52.600 | because it means we could get society open.

00:57:55.580 | So I know that he,

00:57:57.440 | his first experience with these rapid tests was confusing,

00:58:01.600 | which is how I ended up having this Twitter

00:58:04.320 | kind of conversation with him very briefly.

00:58:07.000 | But I think that if he understood sort of a little bit more,

00:58:10.360 | and I think he does, I really love to talk to him about it

00:58:13.320 | 'cause I think he could totally change

00:58:14.960 | the course of this pandemic in the United States,

00:58:17.360 | single-handedly.

00:58:18.200 | You know, he loves grand things.

00:58:20.000 | - Yeah, I think out of all the solutions I've seen,

00:58:24.680 | this is the obvious engineering solution

00:58:29.680 | to at least a pandemic of this scale.

00:58:33.440 | - I love that you say the engineering solution.

00:58:35.840 | So this is something I've been really trying to,

00:58:38.640 | I'm an engineer, my previous history was all engineering,

00:58:43.200 | and that's really how I think.

00:58:45.160 | I then went into medicine and PhD world,

00:58:47.360 | but I think that the world,

00:58:52.680 | like one of the major catastrophes

00:58:54.440 | or one of the major problems is that we have physicians

00:58:57.480 | making the decisions about public health and a pandemic

00:59:01.320 | when really we need engineers.

00:59:03.320 | This is an engineering problem.

00:59:05.240 | And so what I've been trying to do,

00:59:06.620 | I actually really want to start a whole new field

00:59:10.540 | called public health engineering.

00:59:12.880 | And so I've been, eventually I want to try to bring it

00:59:15.640 | to MIT and get MIT to want to start a new department

00:59:18.080 | or something.

00:59:18.920 | - It's a doubly awesome idea.

00:59:21.620 | (laughing)

00:59:23.880 | I love this.

00:59:25.840 | I love every aspect.

00:59:26.700 | I love everything you're talking about.

00:59:29.840 | A lot of people believe,

00:59:30.960 | because vaccines started being deployed currently,

00:59:34.520 | that we are no longer in need of a solution.

00:59:39.480 | We're no longer in need of slowing the spread of the virus.

00:59:44.480 | To me, as I understand it,

00:59:46.640 | it seems like this is the most important time

00:59:49.760 | to have something like a rapid testing solution.

00:59:52.560 | Can you kind of break that apart?

00:59:54.680 | What's the role of rapid testing in the next,

00:59:58.040 | what is it, three, four months maybe?

01:00:01.760 | - Even more.

01:00:03.000 | The vaccine rollout isn't gonna be as peachy

01:00:05.680 | as everyone is hoping.

01:00:07.680 | And I hate to be the Debbie Downer here,

01:00:09.440 | but there's a lot of unknowns with this vaccine.

01:00:13.600 | You've already mentioned one,

01:00:14.660 | which is there's a lot of people

01:00:16.120 | who just don't want to get the vaccine.

01:00:18.080 | I hope that that might change as things move forward

01:00:21.440 | and people see their neighbors getting it

01:00:23.120 | and their family getting it and it's safe and all.

01:00:25.640 | We don't know how effective the vaccine is gonna be

01:00:27.640 | after two or three months.

01:00:28.680 | We've only measured it in the first two or three months,

01:00:30.960 | which is a massive problem,

01:00:33.200 | which we can go into biologically,

01:00:35.160 | 'cause there's reasons to,

01:00:36.960 | very good reasons to believe that the efficacy

01:00:39.080 | could fall way down after two or three months.

01:00:41.580 | We don't know if it's gonna stop transmission.

01:00:44.600 | And if it doesn't stop transmission,

01:00:47.000 | then we're not, then there's, you know,

01:00:48.400 | herd immunity is much, much more difficult to get

01:00:50.880 | because that's all based on transmission blockade.

01:00:53.600 | And frankly, we don't know how easily

01:00:57.640 | we're going to be able to roll it out.

01:00:58.920 | Some of the vaccines need really significant cold chains,

01:01:01.640 | have very short half-lives outside of that cold chain.

01:01:04.640 | We need to organize massive numbers of people

01:01:10.360 | to be able to distribute these.

01:01:11.520 | Most hospitals today are saying that they're not equipped

01:01:14.840 | to hire the right people to be even administering

01:01:17.940 | enough of these vaccines.

01:01:19.240 | And then a lot of the hospitals are frustrated

01:01:20.880 | 'cause they're getting much smaller allocations

01:01:23.320 | than they were expecting.

01:01:24.920 | So I think right now, like you say,

01:01:28.940 | right now is the best time, you know,

01:01:31.840 | besides three or four or five or six months ago,

01:01:34.520 | right now is the best time to get these rapid tests out.

01:01:38.080 | And we need to, I mean, the country has the capacity

01:01:41.680 | to build them.

01:01:42.520 | We have, we're shipping them overseas right now.

01:01:45.380 | We just need to flip a switch, get the FDA to recognize

01:01:48.520 | that there's more important things than diagnostic medicine,

01:01:51.480 | which is the effectiveness of the public health program

01:01:54.880 | when we're dealing with a pandemic.

01:01:57.320 | They need to authorize these as public health tools,

01:02:00.540 | or, you know, frankly, the president could.

01:02:04.200 | You know, there's a lot of other ways to get these tests

01:02:08.540 | to not have to go through the normal FDA authorization

01:02:11.260 | program, but maybe have the NIH and the CDC

01:02:14.460 | give a stamp of approval.

01:02:15.940 | And if we could, we could get these out tomorrow.

01:02:19.860 | And that's where that article came from, you know,

01:02:21.620 | how we can stop the spread of this virus by Christmas.

01:02:24.960 | We could, you know, now it's getting late.

01:02:27.620 | And so we have to keep updating that timeframe,

01:02:30.860 | maybe putting Christmas in the title wasn't,

01:02:32.740 | I should have said how we can stop the spread

01:02:34.620 | of this virus in a month.

01:02:36.220 | It would be a little bit more timeless,

01:02:37.840 | but we could do it.

01:02:39.700 | You know, we really could do it.

01:02:41.300 | And that's the most frustrating part here is that

01:02:44.380 | we're just choosing not to, as a country,

01:02:46.460 | we're choosing to bankrupt our society

01:02:48.820 | because some people at the FDA and other places

01:02:52.960 | just can't seem to get their head around the fact

01:02:54.980 | that this is a public health problem,

01:02:56.460 | not a bunch of medical problems.

01:02:58.160 | - Is there a way to change that policy-wise?

01:03:00.500 | So this is a much bigger thing that you're speaking to,

01:03:03.260 | which I love in terms of the MIT engineering approach

01:03:08.260 | to public health.

01:03:11.500 | Is there a way to push this?

01:03:13.260 | Is this a political thing, like where some Andrew Yang

01:03:16.780 | type characters need to like start screaming about it?

01:03:20.420 | Is it more of an Elon Musk thing

01:03:24.360 | where people just need to build it

01:03:26.320 | and then on Twitter start talking crap

01:03:28.760 | to politicians for not doing it?

01:03:31.320 | What are the ideas here?

01:03:34.840 | - I think it's a little of both.

01:03:37.160 | I think it's political on the one hand,

01:03:38.880 | and I've certainly been talking to Congress a lot,

01:03:41.120 | talking to senators.

01:03:42.440 | - Are they receptive?

01:03:43.400 | - Oh yeah.

01:03:44.240 | I mean, that's the crazy thing.

01:03:45.360 | Everyone but the FDA is receptive.

01:03:47.880 | I mean, it's astounding.

01:03:49.240 | I mean, I advise, informally I advise the president

01:03:53.380 | and the president-elect's teams.

01:03:55.740 | I talk to Congress, I talk to senators, governors,

01:03:59.840 | and then all the way down to mayors of towns and things.

01:04:05.020 | And I mean, months ago I held a round table discussion

01:04:08.900 | with Mayor Garcetti, who's the mayor of LA.

01:04:12.120 | And I brought all the companies who make these things.

01:04:15.320 | This was in like July or August or something.

01:04:17.140 | I brought all the companies to the table and said,

01:04:18.800 | "Okay, how can we get these out?"

01:04:21.200 | And unfortunately it went nowhere

01:04:23.560 | because the FDA won't authorize them as public health tools.

01:04:27.200 | The nice thing is that this is one of the,

01:04:30.800 | nice and frustrating things,

01:04:32.080 | this is one of the few bipartisan things that I know of.

01:04:35.200 | And like you said, it's a real solution.

01:04:38.380 | Lockdowns aren't a solution.

01:04:40.280 | They're an emergency Band-Aid to a catastrophe

01:04:45.280 | that's currently happening.

01:04:47.000 | They're not a solution.

01:04:48.200 | And they're definitely not a public health solution

01:04:51.080 | if we're taking a more holistic view of public health,

01:04:53.280 | which includes people's wellbeing,

01:04:55.760 | includes their psychological wellbeing,

01:04:57.480 | their financial wellbeing.

01:04:59.640 | Just stopping a virus,

01:05:00.880 | if it means that all those other things

01:05:02.360 | get thrown under the bus, is not a public health solution.

01:05:05.720 | It's a myopic or very tunnel-visioned approach

01:05:10.720 | to a virus that's spreading.

01:05:14.520 | This is a simple solution with essentially no downfall.

01:05:19.520 | There is nothing bad about this.

01:05:22.080 | It's just giving people a result.

01:05:25.560 | And it's bipartisan.

01:05:27.640 | The most conservative and the most liberal people,

01:05:30.560 | everyone just wants to know their status.

01:05:32.560 | Nobody wants to have to wait in line for four hours

01:05:35.760 | to find out their status on Monday,

01:05:38.480 | a week later on Saturday.

01:05:40.880 | It just doesn't make any sense.

01:05:42.000 | It's a useless test at that point.

01:05:43.720 | And everyone recognizes that.

01:05:45.480 | - So why do you think, like the mayor of LA,

01:05:49.440 | why do you think politicians are going for these,

01:05:52.380 | from my perspective, like kind of half-assed lockdowns?

01:05:57.840 | So I have seen good evidence

01:06:01.480 | that a complete lockdown can work.

01:06:04.760 | But it's just like communism in theory can work.

01:06:08.600 | Theoretically speaking, but it just doesn't,

01:06:12.160 | at least in this country, we don't,

01:06:14.760 | I think it's just impossible to have a complete lockdown.

01:06:17.240 | And still, politicians are going for these kind of lockdowns

01:06:21.940 | that everybody hates,

01:06:24.080 | that's really hurting small businesses.

01:06:27.340 | Like why are they going for that?

01:06:29.320 | - And big businesses.

01:06:30.840 | - Yeah, all businesses.

01:06:32.760 | But like basically not just hurting,

01:06:35.720 | they're destroying small businesses, right?

01:06:38.840 | Which is going to have potentially, I mean--

01:06:42.760 | - Very long-lasting consequences.

01:06:43.600 | - Yeah, I've been reading, as I don't shut up about,

01:06:47.760 | the rise and fall of the Third Reich.

01:06:49.760 | And there's economic effects that take a decade to,

01:06:54.760 | there's going to be long-lasting effects

01:06:58.940 | that may be destructive to the very fabric of this nation.

01:07:02.440 | So why are they doing it

01:07:04.520 | and why are they not using this solution?

01:07:06.280 | Is there an intuition?

01:07:07.680 | I mean, you've said the FDA has a stranglehold, I guess,

01:07:11.680 | on this whole public health problem.

01:07:14.800 | Is that all it is?

01:07:16.280 | - That's, honestly, it's pretty much all it is.

01:07:20.080 | The companies, so the, somebody like Mayor Garcetti

01:07:23.720 | or Governor Baker, Cuomo, Newsom, any of these,

01:07:28.640 | DeWine, I've talked to a lot of governors

01:07:31.860 | in this country at this point.

01:07:33.360 | And of course the federal government,

01:07:36.720 | including the president's own teams,

01:07:40.360 | and the heads of the NIH, the heads of the CDC about this.

01:07:44.860 | The problem is the tests don't exist in this country

01:07:50.080 | at the level that we need them to right now

01:07:52.480 | to make that kind of policy, to make that kind of program.

01:07:57.200 | They could, but they don't.

01:07:59.200 | And so what that means is that when Mayor Garcetti says,

01:08:03.000 | "Okay, what are my actual options today?"

01:08:06.720 | Despite these sounding like a great idea,

01:08:08.600 | he looks around and he says, "Well, they're not authorized.

01:08:11.640 | "They don't exist right now for at-home use."

01:08:15.320 | And from his perspective, he's not about to pick that fight

01:08:18.120 | with the FDA, and it turns out nobody is.

01:08:20.980 | - Why are people afraid of,

01:08:22.600 | it seems like an easy, strong fight.

01:08:25.160 | It's like-- - Well, it's not a,

01:08:27.000 | so they don't see it as a fight.

01:08:28.240 | They think that the FDA is the end-all, be-all.

01:08:31.640 | Everyone thinks the FDA is the end-all, be-all.

01:08:34.640 | And so they just defer, everyone is deferential,

01:08:37.720 | including the heads of all the other government agencies,

01:08:40.780 | because that is their role.

01:08:42.360 | But what everyone is failing to see

01:08:44.960 | is that the FDA doesn't even have a mandate or a remit

01:08:48.600 | to evaluate these tests as public health tools.

01:08:50.800 | So they're just falling in this weird gray zone

01:08:53.840 | where the FDA is saying, "Look, we evaluate medical products.

01:08:57.860 | "That's the only thing that I meant."

01:08:59.440 | Like Tim Stenzel, head of in vitro diagnostics at the FDA,

01:09:02.720 | he's doing what his job is, which is to evaluate public,

01:09:06.480 | which is to evaluate medical tools.

01:09:08.240 | Unfortunately, this is where I think

01:09:11.720 | the CDC has really blundered.

01:09:13.760 | They haven't made the right distinction to say,

01:09:16.040 | "Look, okay, the FDA is evaluating these

01:09:19.360 | "for doctors to use and all that,

01:09:21.640 | "but we're the CDC and we're the public health agency

01:09:24.720 | "of this country, and we recognize that these tools

01:09:27.880 | "require a different authorization pathway

01:09:30.000 | "and a different use, not prescriptions."

01:09:31.600 | - A difference between medical devices and public health.

01:09:34.920 | I guess FDA is not designed for this public health,

01:09:38.520 | especially in emergency situations.

01:09:40.680 | - And they actually explicitly say that.

01:09:43.800 | I mean, when I go and talk to Tim,

01:09:45.560 | he's a very reasonable guy, but when I talk to him,

01:09:50.120 | he says, "Look, we don't, we just do not

01:09:54.660 | "evaluate a public health tool.

01:09:55.920 | "If you're telling me this is a public health tool,

01:09:57.440 | "great, go and use it."

01:10:00.680 | And so I say, "Okay, great, we'll go and use it."

01:10:03.800 | And then the comment is, "But does it give a result

01:10:07.360 | "back to somebody?"

01:10:08.800 | I say, "Well, yes, of course it gives a result

01:10:10.980 | "back to somebody, it's being done in their home."

01:10:13.320 | He says, "Oh, well then it's defined as a medical tool,

01:10:15.220 | "you can't use it."

01:10:16.440 | So it's stuck in this gray zone where we,

01:10:19.160 | unfortunately there's this weird definition

01:10:20.860 | that any tool, any test that gives a result back

01:10:24.480 | to an individual is defined by CMS,

01:10:27.880 | Centers for Medicaid Services, as a medical device,

01:10:32.000 | requiring medical authorization.

01:10:34.920 | But then you go and ask, it gets crazier,

01:10:36.920 | 'cause then you go and ask Seema Verma, the head of CMS,

01:10:41.920 | okay, can these be authorized as public health tools

01:10:47.360 | and not fall under your definition of a medical device?

01:10:50.120 | So then the FDA doesn't have to be the ones

01:10:52.220 | authorizing it as a public health tool.

01:10:54.720 | And Seema Verma says, "Oh, well, we don't have

01:10:58.120 | "any jurisdiction over point of care

01:11:02.040 | "and sort of rapid devices like this,

01:11:04.540 | "we only have jurisdiction over lab devices."

01:11:07.440 | So it's like nobody has ownership over it,

01:11:10.360 | which means that they just keep,

01:11:11.680 | they stay in this purgatory of not being approved.

01:11:15.280 | And so this is where I think, frankly, it needs a president.

01:11:18.480 | It needs a presidential order to just unlock them,

01:11:21.040 | to say this is more important than having a prescription.

01:11:25.920 | And in fact, I mean, really what's happening now,

01:11:28.240 | because there is this sense that tests

01:11:31.280 | are public health tools,

01:11:32.760 | even if they're not being defined as such,

01:11:35.120 | the FDA now is pretty much,

01:11:37.100 | not only are they not authorizing these

01:11:39.080 | as public health tools,

01:11:41.120 | what they're doing by authorizing

01:11:43.680 | what are effectively public health tools as medical devices,

01:11:47.480 | they're just diluting down the practice of medicine.

01:11:50.600 | I mean, his answer right now, unfortunately, is,

01:11:54.160 | "Well, I don't know why you want these

01:11:56.420 | "to be sort of available to everyone without a prescription.

01:11:58.840 | "We've already said that a doctor

01:12:00.760 | "can write a whole prescription

01:12:01.920 | "for a whole college campus."

01:12:04.800 | It's like, well, if you're going in that direction,

01:12:06.400 | then that's no longer medicine.

01:12:08.640 | Having a doctor write a prescription for a college campus,

01:12:11.560 | for everyone on the campus to have repeat testing,

01:12:14.360 | now we're just in the territory of eroding medicine

01:12:18.800 | and eroding all of the legal rules and reasons

01:12:21.400 | that we have prescriptions in the first place.

01:12:23.840 | So it's just everything about it is just destructive,

01:12:27.160 | instead of just making a simple solution,

01:12:29.920 | which is, these are okay as public health tools

01:12:32.980 | as long as they meet X and Y metrics,

01:12:35.520 | go and CDC can put their stamp of approval on them.

01:12:38.160 | - Well, what do you think, sorry if I'm stuck on this,

01:12:41.160 | your mention of MIT and public health engineering, right?

01:12:47.280 | I mean, it has a sense of,

01:12:49.120 | I talked to competition biology folks.

01:12:51.400 | It's always exciting to see computer scientists

01:12:54.160 | start entering the space of biology.

01:12:56.160 | And there's actually a lot of exciting things

01:12:58.120 | that happen because of that,

01:12:59.800 | trying to understand the fundamentals of biology.

01:13:03.080 | So from the engineering approach to public health,

01:13:07.440 | what kind of problems do you think can be tackled?

01:13:09.680 | What kind of disciplines are involved?

01:13:11.600 | Like, do you have ideas in this space?

01:13:14.240 | - Oh yeah.

01:13:15.080 | I mean, I can speak to one of the major activities

01:13:19.600 | that I wanna do.

01:13:20.440 | So what I normally do in my research lab

01:13:22.180 | is develop technologies that can take a drop

01:13:26.260 | of somebody's blood or some saliva

01:13:27.940 | and profile for hundreds of thousands

01:13:30.560 | of different antibodies against every single pathogen

01:13:33.300 | that somebody could be possibly exposed to.

01:13:36.360 | So this is all new technology that we've been developing

01:13:39.200 | more from a bioengineering perspective.

01:13:43.040 | But then I use a lot of the mathematics tools

01:13:47.680 | to A, interpret that.

01:13:49.360 | But what I really wanna do, for example,

01:13:51.000 | to kind of kick off this new field

01:13:52.640 | of what I consider public health engineering

01:13:55.220 | is to create, maybe it's a little ambitious,

01:13:57.600 | but create a weather system for viruses.

01:14:02.220 | I want us to be able to open up our iPhones,

01:14:06.060 | plug in our zip code and get a better sense,

01:14:08.800 | get a probability of why my kid has a runny nose today.

01:14:11.660 | Is it COVID?

01:14:13.000 | Is it a rhinovirus, an adenovirus, or is it flu?

01:14:16.440 | And we can do that.

01:14:17.960 | We can start building the rules of virus spread

01:14:21.060 | across the globe, both for pandemic preparedness,

01:14:24.240 | but also for just everyday use.

01:14:28.280 | In the same way that people used to think

01:14:30.280 | that predicting the weather was gonna be impossible.

01:14:33.160 | Of course we know that's not impossible now.

01:14:34.840 | Is it always perfect?

01:14:35.700 | No, but does it offer, does it completely change

01:14:39.480 | the way that we go about our days?

01:14:42.240 | Absolutely.

01:14:43.140 | I envision, for example, right now,

01:14:46.860 | we open up our iPhone, we plug in a zip code,

01:14:50.080 | and if it tells us it's gonna rain today,

01:14:51.880 | we bring an umbrella.

01:14:53.400 | So in the future, it tells us,

01:14:56.120 | hey, there's a lot of SARS-CoV-2 in your community.

01:14:59.640 | Instead of grabbing your umbrella, you grab your mask.

01:15:02.520 | We don't have to have masks all the time,

01:15:05.280 | but if we know the rules of the game

01:15:07.360 | that these viruses play by,

01:15:09.320 | we can start preparing for those.

01:15:10.800 | And every year, we go into every flu season

01:15:15.120 | blindfolded with our hands tied behind our back,

01:15:17.440 | just saying, I hope this isn't a bad flu season this year.

01:15:21.200 | I mean, this is, we're in the 21st century.

01:15:26.280 | I mean, we have the tools at our disposal now

01:15:31.120 | to not have that attitude.

01:15:32.680 | This isn't like 1920s.

01:15:34.960 | We can just say, hey, this is gonna be

01:15:39.060 | a bad flu season this year.

01:15:40.440 | Let's act accordingly and with a targeted approach.

01:15:44.720 | Now, we don't, for example,

01:15:47.000 | we don't just use our umbrellas all day long

01:15:50.240 | every single day in case it might rain.

01:15:53.560 | We don't board up our homes every single day

01:15:55.560 | in case there's a hurricane.

01:15:56.640 | We wait, and if we know that there's one coming,

01:15:58.880 | then we act for a small period of time accordingly,

01:16:03.360 | and then we go back, and we've prepared ourselves

01:16:05.720 | in like these little bursts to not have it ruin our days.

01:16:09.160 | - I can't tell you how exciting that vision of the future is.

01:16:13.120 | I think that's incredible,

01:16:14.520 | and it seems like it should be within our reach.

01:16:16.920 | Just these weather maps of viruses

01:16:22.360 | floating about the earth, and it seems obvious.

01:16:26.000 | It's one of those things where right now

01:16:28.720 | it seems like maybe impossible,

01:16:31.960 | and then looking back 20 years from now,

01:16:34.800 | we'll wonder why the hell this hasn't been done

01:16:38.320 | way earlier, though one difference between weather,

01:16:42.240 | I don't know if you have interesting ideas in this space,

01:16:45.320 | the difference between weather and viruses

01:16:47.920 | is it includes the collection of the data

01:16:51.080 | includes the human body potentially,

01:16:54.400 | and that means that there is some,

01:16:58.440 | as with the contact tracing question,

01:17:01.100 | there's some concern about privacy.

01:17:03.440 | There seems to be this dance that's really complicated.

01:17:07.400 | You know, with Facebook getting a lot of flack

01:17:11.160 | for basically misusing people's data,

01:17:13.560 | or just whether it's perception or reality,

01:17:17.480 | there's certainly a lot of reality to it too,

01:17:19.880 | where they're not good stewards of our private data.

01:17:24.280 | So there's this weird place where it's like obvious

01:17:28.880 | that if we collect a lot of data about human beings

01:17:35.120 | and maintain privacy and maintain all basic respect

01:17:40.120 | for that data, just honestly common sense respect

01:17:42.960 | for the data, that we can do a lot of amazing things

01:17:45.800 | for the world, like a weather map for viruses.

01:17:48.920 | Is there a way forward to gain trust of people

01:17:52.720 | or to do this well?

01:17:55.720 | Do you have ideas here?

01:17:56.780 | How big is this problem?

01:17:58.560 | - I think it's a central problem.

01:18:00.760 | There's a couple central problems that need to be solved.

01:18:02.720 | One, how do you get all the samples?

01:18:05.600 | That's not actually too difficult.

01:18:07.080 | I have a pilot project going right now

01:18:10.120 | with getting samples from across all the United States.

01:18:13.320 | Tens of thousands of samples every week

01:18:16.140 | are flowing into my lab and we process them.

01:18:19.200 | - So it's taking like one of the,

01:18:22.280 | basically there's biology here and chemistry

01:18:26.320 | and converting that into numbers.

01:18:27.920 | - That's exactly right.

01:18:28.760 | So what we're doing, for example,

01:18:30.080 | is a lot of people who go to the hospital every day,

01:18:33.000 | a lot of people who donate blood, people who donate plasma.

01:18:36.280 | So one of the projects that I have,

01:18:38.520 | I'll get to the privacy question in a moment,

01:18:40.280 | but this, so what I wanna do is the name

01:18:42.440 | that I've given this is a global immunological observatory.

01:18:46.800 | You know, there's no reason not to have that.

01:18:48.480 | - Good name.

01:18:49.440 | - I've said, you know, instead of saying,

01:18:50.960 | well, how do we possibly get enough people on board

01:18:53.560 | to send in samples all the time?

01:18:56.000 | Well, just go to the source.

01:18:57.480 | You know, so there's a company in Massachusetts

01:18:59.680 | that makes 80% of all the instruments

01:19:02.240 | that are used globally to collect plasma

01:19:04.960 | from plasma donors.

01:19:07.120 | So I went to this company, Hemanetics,

01:19:10.400 | and said, you know, is there a way,

01:19:12.980 | you have 80% of the global market on plasma donations,

01:19:17.640 | can we start getting plasma samples

01:19:21.480 | from healthy people that use your machines?

01:19:24.200 | So that hooked me up with this company called OctoPharma,

01:19:26.680 | and OctoPharma has a huge reach

01:19:28.720 | and offices all over the country

01:19:30.880 | where they're just collecting people's plasma.

01:19:32.800 | They actually pay people for their plasma,

01:19:35.480 | and then that gets distributed to hospitals

01:19:37.120 | and all this stuff as anonymous plasma.

01:19:39.380 | So I've just been collecting anonymous samples,

01:19:41.720 | and we're processing them, in this case,

01:19:45.140 | for COVID antibodies to watch from January

01:19:48.360 | up through December, we're able to watch

01:19:51.460 | how the virus entered into the United States

01:19:54.240 | and how it's transmitting every day,

01:19:56.480 | you know, across the US.

01:19:58.800 | So we're getting those results organized now,

01:20:02.480 | and we're gonna start putting them publicly online soon

01:20:06.080 | to start making at least a very rough map of COVID.

01:20:09.100 | But that's the type of thinking that I have

01:20:12.840 | in terms of like, how do you actually capture

01:20:14.720 | huge numbers of specimens?

01:20:17.080 | You can't ask everyone to participate on sort of a,

01:20:20.200 | I mean, you maybe could if you have the right tools,

01:20:23.040 | and you can offer individuals something in return

01:20:25.400 | like 23andMe does.

01:20:26.840 | You know, that's a great way to get people

01:20:29.040 | to give specimens and they get results back.

01:20:31.060 | So with these technologies that I've been building,

01:20:34.520 | along with some collaborators at Harvard,

01:20:36.140 | we can come up with tools that people might actually want.

01:20:39.960 | So I can offer you your immunological history.

01:20:43.280 | I can say, give me a drop of your blood on a filter paper,

01:20:47.120 | mail it in, and I will be able to tell you

01:20:49.880 | every infectious disease you've ever encountered,

01:20:52.060 | and maybe even when you encountered it, roughly.

01:20:55.060 | I could tell you, do you have COVID antibodies right now?

01:20:58.780 | Do you have Lyme disease antibodies right now?

01:21:00.580 | Flu, triple E, and all these different viruses.

01:21:03.700 | Also peanut allergies, you know, milk allergies, anything.

01:21:07.020 | You know, if your immune system makes a response to it,

01:21:11.260 | we can detect that response.

01:21:13.220 | So all of a sudden we have this very valuable technology

01:21:17.640 | that on the one hand gives people maybe information

01:21:19.960 | they might want to know about themselves,

01:21:21.980 | but on the other hand becomes this amazingly rich

01:21:25.020 | source of big data, you know,

01:21:26.740 | to enter into this global immunological observatory

01:21:29.860 | sort of mathematical framework to start building these maps,

01:21:33.460 | these epidemiological tools.

01:21:34.820 | But you asked about privacy,

01:21:36.740 | and absolutely that's essential to keep in mind,

01:21:40.360 | first and foremost.

01:21:41.900 | So privacy can be, you can keep these samples 100% anonymous.

01:21:46.900 | They are just, when I get them, they show up with nothing.

01:21:49.320 | They're literally just tubes.

01:21:51.340 | I know a date that they were collected

01:21:52.880 | and a zip code that they're collected from,

01:21:54.620 | or even just sort of a county level ID.

01:21:59.020 | With an IRB and with ethical approval

01:22:02.300 | and with the people's consent,

01:22:03.740 | we can maybe collect more data,

01:22:05.100 | but that would require consent.

01:22:07.320 | But then there's this other approach

01:22:09.560 | which I'm really excited about,

01:22:10.980 | which is certainly going to gain some scrutiny, I think.

01:22:14.460 | But we'll have to figure out where it comes into play.

01:22:17.900 | But I've been recognizing that we can take

01:22:20.240 | somebody's immunological profile

01:22:22.860 | and we can make a biological fingerprint out of it.

01:22:25.700 | And it's actually stable enough

01:22:27.300 | so that I could take your blood.

01:22:28.540 | Let's say I don't know who you are,

01:22:30.460 | but you sent me a drop of blood a year ago,

01:22:34.300 | and then you sent me a drop of blood today.

01:22:36.540 | I don't know that those two blood spots

01:22:38.300 | are coming from the same person.

01:22:39.740 | They're just showing up in my lab.

01:22:41.440 | But I can run our technology over,

01:22:46.500 | and it just gives me your immunological history.

01:22:49.820 | But your immunological history is so unique to you

01:22:52.340 | and the way that your body responds to these pathogens

01:22:55.380 | is so unique to you that I can use that

01:22:58.260 | to tether your two samples.

01:22:59.620 | I don't know who you are.

01:23:00.560 | I know nothing about you.

01:23:01.820 | I only know when those samples came out of a person.

01:23:06.600 | But I can say, oh, these two samples a year apart

01:23:09.120 | actually belong to the same person.

01:23:10.940 | - Yeah, so there's sufficient information

01:23:12.340 | that immunological history to match the samples.

01:23:16.060 | Or from a privacy perspective, that's really exciting.

01:23:18.540 | Does that generally hold for humans?

01:23:20.220 | So you're saying there's enough uniqueness to match?

01:23:23.780 | - Yeah, because it's very stochastic, even twins.

01:23:25.980 | So this, I believe, we haven't published this yet.

01:23:28.220 | We will soon.

01:23:29.380 | - You have a twin, too, right?

01:23:30.540 | - I do have a twin.

01:23:31.380 | I have an identical twin brother,

01:23:32.540 | which makes me interested in this.

01:23:34.620 | He looks very much like me.

01:23:36.460 | - Oh, is that how that works?

01:23:37.660 | (both laughing)

01:23:38.940 | - And DNA can't really tell us apart.

01:23:42.580 | But this tool is one of the only tools in the world

01:23:45.580 | that can tell twins apart from each other.

01:23:48.040 | Could still be accurate enough to say this blood,

01:23:51.340 | you know, it's like 99.999% accurate

01:23:55.580 | to say that these two blood samples

01:23:58.020 | came from the same individual.

01:24:00.420 | And it's because it's a combination,

01:24:01.940 | both of your immunological history,

01:24:04.140 | but also how your unique body responds to a pathogen,

01:24:09.140 | which is random.

01:24:10.900 | The way that we make antibodies is, by and large,

01:24:14.200 | it's got an element of randomness to it.

01:24:17.540 | How the cells, when they make an antibody,

01:24:19.480 | they chop up the genetic code to say,

01:24:22.500 | okay, this is the antibody that I'm gonna form

01:24:24.240 | for this pathogen.

01:24:26.200 | And you might form, if you get a coronavirus, for example,

01:24:29.760 | you might form hundreds of different antibodies,

01:24:31.960 | not just one antibody against the spike protein,

01:24:33.940 | but hundreds of different antibodies

01:24:35.720 | against all different parts of the virus.

01:24:38.300 | So that gives us really rich resolution of information

01:24:42.200 | that when I then do the same thing

01:24:43.640 | across hundreds of different pathogens,

01:24:45.360 | some of which you've seen, some of which you haven't,

01:24:48.320 | it gives you an exceedingly unique fingerprint

01:24:50.600 | that is sufficiently stable over years and years and years

01:24:54.920 | to essentially give you a barcode.

01:24:57.760 | And I don't have to know who you are,

01:24:59.600 | but I can know that these two specimens

01:25:01.400 | came from the same person somewhere out in the world.

01:25:04.520 | - It's so fascinating that there's this trace,

01:25:07.080 | your life story in the space of viruses,

01:25:11.200 | in the space of pathogen,

01:25:13.560 | like these, you know, 'cause there's this entire universe

01:25:18.560 | of these organisms that are trying to destroy each other.

01:25:22.320 | And then your little trajectory through that space

01:25:25.960 | leaves a trace.

01:25:27.680 | And then you can look at that trace.

01:25:29.460 | That's fascinating.

01:25:30.380 | And that, I mean, there's, okay,

01:25:33.160 | that data period is just fascinating.

01:25:35.560 | And the vision of making that data universally connected

01:25:40.240 | to where you can make, like infer things.

01:25:43.600 | And just like with the weather is really fascinating.

01:25:47.440 | And there's probably artificial intelligence applications

01:25:50.480 | there to start making predictions, start finding patterns.

01:25:53.120 | - Exactly, we're doing a lot of that already.

01:25:54.920 | And that's how, how do we have this going?

01:25:57.280 | You know, I've been trying to get this funded for years now.

01:26:00.360 | And I've spoken to governments.

01:26:02.540 | Now everyone says, "Cool idea, not gonna do it."

01:26:05.480 | You know, why do we need it?

01:26:07.240 | - Oh, really?

01:26:08.080 | The why do you need it?

01:26:09.280 | - The why do you need it?

01:26:10.280 | And of course now, you know,

01:26:11.880 | I mean, I wrote in 2015 about this,

01:26:14.380 | why we would, why this would be useful.

01:26:18.160 | And of course now we're seeing why it would be useful.

01:26:21.240 | Had we had this up and running in 2019,

01:26:25.560 | had we had it going, we were drawing blood from,

01:26:28.520 | you know, we're getting blood samples from hospitals

01:26:30.760 | and clinics and blood donors from New York City,

01:26:32.800 | let's just say.

01:26:34.200 | Now that could have, we didn't run the first PCR test

01:26:39.000 | for coronavirus until probably a month and a half

01:26:42.720 | or two months after the virus started transmitting

01:26:45.680 | in New York City.

01:26:46.920 | - So it's like with the rain,

01:26:48.000 | we didn't start wearing umbrella or taking out umbrellas.

01:26:52.280 | - Exactly, for two months.

01:26:53.120 | - It was getting wet.

01:26:54.000 | - But different than the rain,

01:26:55.120 | we couldn't actually see that it was spreading, you know?

01:26:57.960 | And so Andrew Cuomo had no choice

01:27:00.520 | but to leave the city open.

01:27:02.160 | You know, there were hints that maybe the virus

01:27:03.800 | was spreading in New York City,

01:27:05.320 | but you know, he didn't have any data to back it up.

01:27:07.880 | No data.

01:27:08.700 | And so it was just week on week and week.

01:27:11.320 | And he didn't have any information to really go by

01:27:17.120 | to allow him to have the firepower to say,

01:27:19.000 | "We're closing down the city.

01:27:20.440 | "This is an emergency.

01:27:21.320 | "We have to stop spread before it starts."

01:27:23.420 | And so they waited until the first PCR tests

01:27:28.360 | were coming about.

01:27:29.200 | And then the moment they started running a PCR test,

01:27:30.680 | they find out it's everywhere, you know?

01:27:32.600 | And so that was a disaster because of course,

01:27:35.040 | New York City, you know, was just hit so bad

01:27:38.480 | because nobody was, you know, we were blind to it.

01:27:41.700 | We didn't have to be blind to it.

01:27:43.020 | And the nice thing about this technology is

01:27:45.680 | we wouldn't have, with the exact same technology

01:27:47.980 | we had in 2017, we could have detected

01:27:51.600 | this novel coronavirus spreading in New York City in 2020.

01:27:56.360 | Not because we changed,

01:27:57.740 | not because we are actually actively looking

01:27:59.800 | for this novel coronavirus,

01:28:01.600 | but because we would see,

01:28:03.140 | we would have seen patterns in people's immune responses

01:28:05.580 | using AI or just frankly using our,

01:28:08.220 | just the raw data itself.

01:28:10.560 | We could have said, "Hey, it looks like there's

01:28:13.160 | "something that looks like known coronavirus

01:28:15.720 | "is spreading in New York, but there's gaps."

01:28:18.340 | You know, there's, for some reason,

01:28:19.840 | people aren't developing an immune response

01:28:21.720 | to this coronavirus that seems to be spreading

01:28:23.540 | to these normal things that, you know,

01:28:25.660 | and it just looks, the profile looks different.

01:28:28.340 | And we could have seen that and immediately,

01:28:31.640 | especially since we had an idea

01:28:33.180 | that there was a novel coronavirus circulating

01:28:36.940 | in the world, we could have very quickly

01:28:39.020 | and easily seen, "Hey, clearly we're seeing a spike

01:28:42.200 | "of something that looks like a known coronavirus,

01:28:44.280 | "but people are responding weirdly to it."

01:28:46.980 | Our AI algorithms would have picked it up

01:28:49.660 | and just our basic, heck, you could have put it

01:28:52.780 | in an Excel spreadsheet, we would have seen it.

01:28:55.060 | So--

01:28:56.660 | - And basic visualization would have shown it.

01:28:58.260 | - Exactly, we would have seen spikes

01:28:59.860 | and they would have been kind of like off,

01:29:02.040 | you know, immune responses that the shape

01:29:04.220 | of them just looked a little bit different,

01:29:06.340 | but they would have been growing and we would have seen it

01:29:08.500 | and it could have saved tens of thousands

01:29:10.620 | of lives in New York City.

01:29:12.300 | - So to me, the fascinating question,

01:29:14.020 | everything we've talked about,

01:29:15.020 | so both the huge collection of data at scale,

01:29:18.060 | just super exciting, and then the kind of obvious

01:29:22.560 | at scale solution to the current virus

01:29:26.320 | and future ones is the rapid testing.

01:29:30.180 | Can we talk about the future of viruses

01:29:34.420 | that might be threatening our very existence?

01:29:39.420 | So do you think like a future natural virus

01:29:44.140 | can have an order of magnitude greater effect

01:29:49.140 | on human civilization than anything we've ever seen?

01:29:52.240 | So something that either kills all humans

01:29:56.200 | or kills, I don't know, 60, 70% of humans.

01:30:01.200 | So something we can't even imagine.

01:30:06.520 | Is that something that you think is possible?

01:30:09.360 | Because it seems to have not have happened yet.

01:30:11.760 | So maybe like the entirety, whoever the programmer is

01:30:16.760 | of the simulation that sort of launched the evolution

01:30:20.040 | for the Big Bang seems to not wanna destroy us humans.

01:30:24.700 | Or maybe that's a natural side effect

01:30:26.320 | of the evolutionary process that humans are useful.

01:30:30.280 | But do you think it's possible that the evolutionary process

01:30:32.600 | will produce a virus that will kill all humans?

01:30:35.720 | - I think it could.

01:30:36.960 | I don't think it's likely.

01:30:38.080 | And the reason I don't think it's likely is,

01:30:40.240 | well, on the one hand, it hasn't happened yet,

01:30:43.620 | in part because mobility is a recent phenomena.

01:30:50.080 | People weren't particularly mobile.

01:30:53.600 | Until fairly recently.

01:30:56.860 | Now, of course, now that we have people flying back

01:30:59.380 | and forth across the globe all the time,

01:31:01.440 | the chances of global pandemics

01:31:06.060 | has escalated exponentially, of course.

01:31:08.900 | And so on the one hand,

01:31:10.780 | that's part of why it hasn't happened yet.

01:31:12.700 | We can look at things like Ebola.

01:31:15.020 | Now Ebola, we haven't generally had major Ebola epidemics

01:31:20.020 | in the past, not because Ebola wasn't transmitting

01:31:23.080 | and infecting humans, but because it was largely affecting

01:31:27.100 | and infecting humans in disconnected communities.

01:31:30.860 | So you see in rural parts of Africa, for example,

01:31:35.820 | in Western Africa,

01:31:36.740 | you might end up having isolated Ebola outbreaks,

01:31:40.660 | but there weren't connections that were fast enough

01:31:43.740 | that would allow people to then spread it into the cities.

01:31:46.480 | Of course, we saw back in 2014, 15,

01:31:52.540 | massive Ebola outbreak that wasn't

01:31:57.540 | because it was a new strain of Ebola,

01:31:59.340 | but it was because there's new inroads and connections

01:32:02.460 | between the communities and people got it to the city.

01:32:05.900 | And so we saw it start to spread.

01:32:08.300 | So that should be a little bit for foreshadowing

01:32:12.100 | of what's to come.

01:32:13.740 | And now we have this pandemic.

01:32:15.420 | We had 2009, we have this.

01:32:17.240 | There is a benefit,

01:32:21.580 | or there is sort of a natural check.

01:32:23.780 | And this is a kind of Latke-Voltaire,

01:32:26.380 | predator-prey dynamic kind of systems,

01:32:28.700 | ecological systems in mathematics

01:32:30.580 | that if you have something that's so deadly,

01:32:34.580 | people will respond more, maybe with a greater panic,

01:32:39.580 | greater sense of panic, which alone could destroy humanity.

01:32:43.660 | But at the same time, we now know that we can lock down.

01:32:47.820 | We know that that's possible.

01:32:49.180 | And so if this was a worse virus

01:32:50.820 | that was actually killing 60% of people as infecting,

01:32:53.860 | we would lock down very quickly.

01:32:55.980 | My biggest fear though, is let's say that was happening.

01:32:59.580 | You need serious lockdowns

01:33:01.020 | if you're gonna keep things going.

01:33:03.060 | So the only reason we were able to keep things going

01:33:05.340 | during our lockdowns is because it wasn't so bad

01:33:08.540 | that we were still able to have people work

01:33:10.180 | in the grocery stores,

01:33:13.440 | still have people work in the shipping

01:33:14.700 | to get the food onto the shelves.

01:33:16.700 | So on the one hand,

01:33:17.860 | we could probably figure how to stop the virus.

01:33:21.220 | But can we stop the virus without starving?

01:33:24.380 | I'm not sure that that,

01:33:26.540 | if this was another acute respiratory virus

01:33:30.260 | that say had a slightly, say it transmitted the same way,

01:33:34.100 | but say it actually did worse damage to your heart,

01:33:36.380 | but it was like a month later

01:33:38.060 | that people started having heart attacks in mass.

01:33:41.700 | It's like not just one-offs, but really severe.

01:33:45.660 | Well, that could be a serious problem for humanity.

01:33:50.100 | So in some ways, I think that there are lots of ways

01:33:53.740 | that we could end up dying at the hand of a virus.

01:33:56.860 | I mean, we're already seeing it.

01:33:57.900 | Just, I mean, my fear is still,

01:34:00.100 | I think coronaviruses have demonstrated a keen ability

01:34:03.420 | to destroy or to create outbreaks

01:34:06.580 | that can potentially be deadly to large numbers of people.

01:34:10.340 | Flu strains though are still by and large my concern.

01:34:14.580 | - So you think the bad one might come from the flu,

01:34:17.620 | the influenza?

01:34:18.780 | - Yeah, their replication cycle,

01:34:20.780 | they're able to genetically recombine

01:34:22.460 | in a way that coronaviruses aren't.

01:34:24.380 | They have segmented genomes,

01:34:25.940 | which means that they can just swap out

01:34:27.540 | whole parts of their genomes, no problem, repackage them.

01:34:31.180 | And then boom, you have a whole antigenic shift,

01:34:34.060 | not a drift.

01:34:35.580 | What that means is that on any occasion,

01:34:38.160 | any day of the year, you can have, boom,

01:34:40.820 | a whole new virus that didn't exist yesterday.

01:34:44.500 | And now with farming and industrial livestock

01:34:48.620 | and we're seeing animals and humans

01:34:51.060 | come into contact much more,

01:34:53.460 | just the opportunities for an influenza strain

01:34:58.460 | that is unique and deadly to humans increases

01:35:01.820 | all the while transmission and mobility has increased.

01:35:05.860 | It's just a matter of time, in my opinion.

01:35:08.880 | - What about from immunology perspective

01:35:12.900 | of the idea of engineering a virus?

01:35:16.340 | So not just the virus leaking from a lab

01:35:18.140 | or something, but actually being able to understand

01:35:22.300 | the protein, like everything about what makes a virus

01:35:26.100 | enough to be able to figure out ways

01:35:29.500 | to maybe targeted or untargeted attack biology.

01:35:34.500 | - Subvert immunity.

01:35:38.060 | - Yeah.

01:35:38.900 | - Yeah.

01:35:39.740 | - Is that something, obviously that's somewhere

01:35:43.060 | on the list of concerns, but is that anywhere close,

01:35:48.300 | of the top 10 highlights along with nuclear weapons

01:35:51.140 | and so on that we should be worried about?

01:35:53.180 | Or is the natural pandemic really the one

01:35:55.620 | that's much greater concern?

01:35:58.120 | - I would say that the former, that man-made viruses

01:36:02.180 | and genetically engineered viruses should be

01:36:07.180 | right up there with the greatest concerns

01:36:09.340 | for humanity right now.

01:36:10.640 | We know that the tools, for better or worse,

01:36:15.220 | the tools for creating a virus are there.

01:36:18.780 | We can do it.

01:36:20.560 | I mean, heck, the human species is no longer vaccinated

01:36:26.780 | against smallpox.

01:36:28.120 | I didn't get a smallpox vaccine.

01:36:29.580 | You didn't get a smallpox vaccine, at least I don't think.

01:36:32.480 | So if somebody wanted to make smallpox

01:36:36.700 | and distribute it to the world in some way,

01:36:41.060 | it could be exceedingly deadly.

01:36:44.500 | And detrimental to humans.

01:36:47.140 | And that's not even sort of using your imagination

01:36:52.180 | to create a new virus.

01:36:53.140 | That's one that we already have.

01:36:54.940 | Unlike the past when smallpox would circulate,

01:36:58.100 | you had large fractions of the community

01:37:01.140 | that was already immune to it.

01:37:02.620 | And so it wouldn't spread or it would spread

01:37:05.380 | a little bit slower.

01:37:06.220 | But now we have essentially in a few years,

01:37:07.960 | we'll have a whole global population that is susceptible.

01:37:11.500 | Let's look at measles.

01:37:13.740 | We have an entire, I mean, measles.

01:37:15.920 | I have, you know, there are some researchers

01:37:20.200 | in the world right now, which for various reasons

01:37:22.540 | are working on creating a measles strain

01:37:25.500 | that evades immunity.

01:37:27.420 | It's not for bioterrorism.

01:37:28.900 | At least that's not the expectation.

01:37:30.420 | It's for using measles as an oncolytic virus to kill cancer.

01:37:34.280 | And the only way you can really do that

01:37:37.460 | is if your immune system doesn't, you know,

01:37:39.580 | if you take a measles virus and there's,

01:37:41.860 | we don't have to go into the details of why it would work,

01:37:43.820 | but it could work.

01:37:44.900 | Measles likes to target potentially cancer cells.

01:37:48.180 | But to get your immune system not to kill off the virus,

01:37:51.780 | if you're trying to use the virus to target it,

01:37:53.340 | you maybe want to make it blind to the immune system.

01:37:57.540 | But now imagine we took some virus like measles,

01:38:00.220 | which has an R naught of 18, transmits extremely quickly.

01:38:04.220 | And now we have essentially,

01:38:05.740 | let's say we had a whole human race

01:38:07.540 | that is susceptible to measles.

01:38:10.340 | And this is a virus that spreads orders of magnitude easier

01:38:14.620 | than this current virus.

01:38:16.060 | Imagine if you were to plug something toxic

01:38:20.900 | or detrimental into that virus and release it to the world.

01:38:25.020 | - So it's possible to be both accidental and intentional.

01:38:29.340 | - Absolutely.

01:38:30.180 | Yeah, and so Mark Lipsitch,

01:38:31.460 | who's a good colleague of mine at Harvard,

01:38:33.600 | we're both in the, he's the director of the Center

01:38:36.960 | for Communicable Disease Dynamics where I'm a faculty member.

01:38:40.800 | He's spoken very, very forcefully

01:38:42.960 | and he's very outspoken about the dangers

01:38:47.160 | of gain-of-function testing,

01:38:49.400 | where in the lab we are intentionally creating viruses

01:38:53.400 | that are exceedingly deadly under the auspices

01:38:57.760 | of trying to learn about them.

01:38:59.200 | So that if the idea is that if we kind of accelerate

01:39:02.800 | evolution and make these really deadly viruses in the lab,

01:39:07.080 | we can be prepared for if that virus ever comes about

01:39:11.200 | naturally or through unnatural means.

01:39:14.560 | The concern though is, okay, that's one thing,

01:39:17.440 | but what if that virus got out on somebody's shoe?

01:39:20.900 | Just what if?

01:39:21.740 | If the effects of an accident are potentially catastrophic,

01:39:29.800 | is it worth taking the chances just to be prepared

01:39:33.640 | a little bit for something that may or may not ever

01:39:35.900 | actually develop?

01:39:36.740 | And so it's a serious ethical quandary we're in,

01:39:40.360 | how to both be prepared but also not

01:39:44.320 | cause a catastrophic mistake.

01:39:48.860 | - As a small tangent, there's a recent really exciting

01:39:53.660 | breakthrough of Alpha Fold 2, solving protein folding

01:39:58.660 | or achieving state-of-the-art performance

01:40:00.920 | on protein folding.

01:40:02.640 | And then I thought proteins have a lot to do with viruses.

01:40:07.640 | It seems like being able to use machine learning

01:40:14.100 | to design proteins that achieve certain kinds of functions

01:40:19.540 | will naturally allow you to use, maybe down the line,

01:40:22.860 | not yet, but allow you to use machine learning

01:40:26.380 | to design basically viruses, maybe like measles for good,

01:40:31.220 | which is like to attack cancer cells, but also for bad.

01:40:36.220 | Is that a crazy thought, or is this a natural place

01:40:41.500 | where this technology may go?

01:40:46.480 | I suppose all technologies can, which is for good

01:40:49.400 | and for bad.

01:40:52.020 | Do you think about the role of machine learning in this?

01:40:54.060 | - Oh yeah, absolutely.

01:40:55.640 | I mean, Alpha Fold is amazing.

01:40:59.420 | It's an amazing algorithm, series of algorithms.

01:41:03.540 | And it does demonstrate, to me it demonstrates

01:41:08.220 | just how powerful, everything in the world has rules.

01:41:12.540 | We just don't know the rules.

01:41:13.960 | We often don't know them, but our brain has rules,

01:41:17.160 | how it works.

01:41:18.000 | Everything is plus and minus.

01:41:19.220 | There's nothing in the world that's really not

01:41:21.200 | at its most basic level, positive, negative.

01:41:25.260 | It's all, obviously, it's all just charge.

01:41:28.180 | And that means everything, you can figure it out

01:41:31.580 | with enough computational power and enough.

01:41:33.820 | In this case, I mean, machine learning and AI

01:41:36.260 | is just one way to learn rules.

01:41:40.060 | It's an empirical way to learn rules,

01:41:42.600 | but it's a profoundly powerful way.

01:41:44.940 | And certainly, now that we are getting to a point

01:41:51.380 | where we can take a protein and know how it folds,

01:41:56.460 | given its sequence, we can reverse engineer that

01:42:00.100 | and we can say, okay, we want a protein to fold this way.

01:42:04.020 | What does the sequence need to be?

01:42:06.000 | We haven't done that yet so much,

01:42:08.740 | but it's just the next iteration of all of this.

01:42:11.940 | So let's say somebody wants to develop a virus.

01:42:15.020 | It's gonna start with somebody wanting to develop a virus

01:42:17.620 | to defeat cancer, something good.

01:42:20.900 | And so it would start with a lot of money

01:42:23.060 | from the federal government.

01:42:26.000 | For all the positives that will come out of it.

01:42:28.420 | But we have to be really careful

01:42:32.220 | because that will come about.

01:42:34.540 | There's no doubt in my mind that we will develop,

01:42:37.420 | we're already doing it.

01:42:38.260 | We engineer molecules all the time for specific uses.

01:42:41.700 | Oftentimes, we take them from nature and then tweak them.

01:42:44.540 | But now we can supercharge it.

01:42:47.300 | We can accelerate the pace of discovery

01:42:50.840 | to not have it just be discovery.

01:42:52.460 | We have it be true ground-up engineering.

01:42:55.780 | - Let's say you're trying to make a new molecule

01:43:00.060 | to stabilize somebody with some retinal disease.

01:43:03.580 | So we come up with some molecule

01:43:06.480 | that can improve the stability of somebody

01:43:10.220 | with retinal degeneration.

01:43:12.140 | Just a small tweak to that to say,

01:43:16.680 | make a virus that causes the human race to become blind.

01:43:19.940 | I mean, it sounds really conspiracy theory-ish,

01:43:22.260 | but it's not.

01:43:25.660 | We're learning so much about biology

01:43:27.420 | and there's always nefarious reasons.

01:43:28.740 | I mean, heck, look at how AI and just Google searches,

01:43:33.740 | those can be, they are every single day

01:43:37.740 | being leveraged by nefarious actors

01:43:39.900 | to take advantage of people, to steal money,

01:43:43.140 | to do whatever it might be.

01:43:44.840 | Eventually, probably to create wars

01:43:48.260 | or already to create wars.

01:43:50.380 | And I mean, I don't think there's any question at this point

01:43:53.660 | behind disinformation campaigns.

01:43:55.460 | And so it's being leveraged.

01:43:56.860 | This thing that could be wholly good

01:43:59.740 | is always going to be leveraged for bad.

01:44:02.220 | And so how do you balance that as a species?

01:44:04.540 | I'm not quite sure.

01:44:06.260 | - The hope is, as you mentioned previously,

01:44:08.260 | that there's some, that we're able

01:44:10.460 | to also develop defense mechanisms.

01:44:12.300 | And there's something about the human species

01:44:14.060 | that seems to keep coming up with ways to,

01:44:18.700 | just like on the deadline, just at the last moment,

01:44:22.780 | figuring out how to avoid destruction.

01:44:26.380 | I think I'm like eternally optimistic

01:44:29.900 | about the human race not destroying ourselves,

01:44:32.740 | but you could do a lot of things that would be very painful.

01:44:36.040 | - Yes.

01:44:36.900 | Well, we're doing it already.

01:44:37.900 | You know, just, I mean, we are seeing

01:44:40.140 | how our regulation today.

01:44:42.940 | We did this thing, it started as a good thing,

01:44:45.800 | regulation of medical products,

01:44:48.020 | but now it is, you know, unwillingly

01:44:52.420 | and unintentionally harming us.

01:44:54.980 | Our regulatory landscape,

01:44:57.180 | which was developed wholly for good in our country,

01:45:00.500 | is getting in the way of us deploying a tool

01:45:04.020 | that could stop our economies

01:45:06.860 | from having to be sort of sputteringly closed,

01:45:11.000 | that could stop deaths from happening

01:45:12.900 | at the rate that they are.

01:45:14.580 | And it's, you know, I think we will come to a solution,

01:45:19.300 | of course, now we're gonna get the vaccine

01:45:21.040 | and it's gonna make people lose track

01:45:23.160 | of like why we even bother testing, which is a bad idea.

01:45:25.880 | But we're already seeing that we have this amazing capacity

01:45:29.780 | to both do damage when we don't intend to do damage

01:45:34.780 | and then also to pull up when we need to pull up

01:45:38.980 | and, you know, stop complete catastrophe.

01:45:41.420 | And so we are an interesting species in that way,

01:45:46.060 | that's for sure.

01:45:47.540 | - So there's a lot of young folks, undergrads,

01:45:50.740 | grads, they're also young, listen to this.

01:45:54.140 | So is there, you've talked about a lot of fascinating stuff

01:45:57.500 | that's like, there's ways that things are done

01:46:01.900 | and there's actual solutions

01:46:03.540 | and they're not always like intersecting.

01:46:05.860 | Do you have advice for undergraduate students

01:46:09.300 | or graduate students or even people in high school now

01:46:12.980 | about a life, about a career,

01:46:15.900 | of how they might be able to solve real big problems

01:46:19.460 | in the world, how they should live their life

01:46:22.140 | in order to have a chance to solve big problems

01:46:24.180 | in the world?

01:46:25.460 | - It's hard, I struggle a little bit sometimes

01:46:27.740 | to give advice because the advice that I give

01:46:30.060 | from my own personal experience is necessarily distinct

01:46:32.900 | from the advice that would make other people successful.

01:46:36.580 | I have unending ambitions to make things better, I suppose.

01:46:41.580 | And I don't see barricades where other people

01:46:45.540 | sometimes see barricades.

01:46:48.300 | Now even just little things like when this virus started,

01:46:51.740 | I'm a medical director at Brigham and Women's Hospital

01:46:54.420 | and so I oversee or helped oversee

01:46:56.180 | molecular virology diagnostics.

01:46:58.100 | So when this virus started, wearing my epidemiology hat

01:47:02.220 | and wearing my sort of viral outbreak hat,

01:47:04.580 | I recognized that this was gonna be a big virus

01:47:06.720 | that was important at a global level.

01:47:08.780 | Even if the CDC and WHO weren't ready to admit

01:47:11.060 | that it was a pandemic, it was obvious in January

01:47:13.380 | that it was a pandemic.

01:47:15.020 | So I started trying to get a test built at the Brigham,

01:47:19.060 | which is one of Harvard's teaching hospitals.

01:47:21.380 | The first encounters I had with the upper administration

01:47:26.900 | of the hospital were pretty much no, why would we do that?

01:47:29.700 | That's silly, who are you?

01:47:31.740 | And I said, well, okay, don't believe me, sure.

01:47:35.120 | But I kept pushing on it.

01:47:37.020 | And then eventually I got them to agree.

01:47:39.820 | It was really only a couple of weeks

01:47:41.820 | before the Biogen conference happened.

01:47:44.140 | We started building the test.

01:47:45.660 | I think they started looking abroad and saying,

01:47:47.260 | okay, this is happening, sure.

01:47:49.020 | Maybe he was right.

01:47:51.620 | But then I went a step further and I said,

01:47:53.940 | we're not gonna have enough tests at the hospital.

01:47:57.860 | And so my ambition was to get

01:48:00.420 | a better testing program started.

01:48:02.860 | And so I figured what better place to scale up testing

01:48:06.620 | than the Broad Institute?

01:48:08.160 | Broad Institute is amazing, very high throughput,

01:48:10.700 | high efficiency research institute

01:48:12.740 | that does a lot of genomic sequencing, things like that.

01:48:15.620 | So I went to the Broad and I said,

01:48:17.440 | hey, there's this coronavirus

01:48:19.540 | that's obviously gonna impact our society greatly.

01:48:23.100 | Can we start modifying your high efficiency instruments

01:48:27.460 | and robots for coronavirus testing?

01:48:30.180 | Everyone in my orbit in the hospital world

01:48:35.180 | just said, that's ridiculous.

01:48:37.780 | How could you possibly plan to do that?

01:48:39.700 | It's impossible.

01:48:41.980 | And to me, it was like the most dead simple thing to do.

01:48:45.760 | But the higher ups and the people who think about,

01:48:50.220 | I think one of the most important things

01:48:51.540 | is to recognize that most people in the world

01:48:54.100 | don't see solutions, they just see problems.

01:48:56.020 | And it's 'cause it's an easy thing to do.

01:48:58.420 | Thinking of problems and how things will go wrong

01:49:02.660 | is really easy 'cause you're not coming up

01:49:05.540 | with a brand new solution.

01:49:07.220 | And this to me was just a super simple solution.

01:49:09.440 | Hey, let's get the Broad to help build tests.

01:49:11.940 | Every single hospital director told me no,

01:49:14.980 | like it's impossible.

01:49:15.820 | My own superiors, the ones I report to in the hospital,

01:49:18.900 | said, Mike, you're a new faculty member.

01:49:22.060 | Your ideas probably would be right,

01:49:25.660 | but you're too naive and young to know that it's impossible.

01:49:29.860 | Obviously now the Broad is the highest throughput laboratory

01:49:33.620 | in the country.

01:49:34.460 | And so I think my recommendation to people

01:49:39.260 | is as much as possible,

01:49:40.740 | get out of the mode of thinking about things as problems.

01:49:45.060 | Sometimes you piss people off.

01:49:46.720 | I could probably use a better filter sometimes

01:49:49.540 | to try to be not so upfront with certain things,

01:49:53.660 | but it's just so crucial to always just see,

01:49:57.020 | to just bring it, think about things in new ways

01:49:59.860 | that other people haven't.

01:50:01.740 | 'Cause usually there's something else out there.

01:50:03.740 | And one of the things that has been most beneficial to me,

01:50:06.460 | which is that my education was really broad.

01:50:10.200 | It was engineering and physics.

01:50:12.700 | And well, and then I became a Buddhist monk for a while.

01:50:15.900 | And so that gave me a different perspective.

01:50:18.540 | But then it was medicine and immunology.

01:50:20.820 | And now I've brought all of it together

01:50:23.100 | from a mathematics and biology and medicine perspective

01:50:27.780 | and policy and public health.

01:50:29.100 | And I think that I'm not the best

01:50:30.900 | in any one of these things.

01:50:32.980 | I recognize that there are gonna be geniuses out there

01:50:36.100 | who are just worlds better than me

01:50:37.680 | at any one of these things that I try to work on.

01:50:41.660 | But my superpower is bringing them all together

01:50:44.220 | and just thinking.

01:50:45.060 | And that's, I think, how you can really change the world.

01:50:48.580 | I don't know that I'll ever change the world

01:50:51.500 | in the way that I hope.

01:50:53.780 | - But that's how you can have a chance.

01:50:55.300 | - Yeah, that's how you can have a chance, exactly.

01:50:57.060 | And I think it's also what,

01:51:00.820 | this to me, this rapid testing program,

01:51:02.780 | this is the most dead simple solution in the world.

01:51:06.180 | - And this literally could change the world.

01:51:07.580 | - It could change the world.

01:51:08.420 | And it is.

01:51:09.600 | There's countries that are doing it now.

01:51:11.160 | The US isn't, but I've been advising many countries on it.

01:51:13.960 | And I would say that some of the early papers

01:51:18.160 | that we put out earlier on,

01:51:19.860 | a lot of the things actually are changing.

01:51:22.280 | You don't always, unless you really look hard,

01:51:24.160 | you don't know where you're actually having an effect.

01:51:26.720 | Sometimes it's more overt than other times.

01:51:29.600 | In April, I published a paper that was saying,

01:51:33.240 | hey, with the PCR values from these tests,

01:51:36.580 | we need to really focus on the CT values,

01:51:38.560 | the actual quantitative values of these lab-based PCR tests.

01:51:42.560 | At the time, all the physicians and laboratory directors

01:51:46.000 | told me that was stupid.

01:51:47.240 | Why would you do that?

01:51:48.160 | They're not accurate enough.

01:51:49.520 | And of course, now it's headline news that in Florida,

01:51:53.380 | they just mandated reporting out the CT values of these tests

01:51:56.840 | 'cause there's a real utility of them.

01:51:58.960 | You can understand public health from it.

01:52:00.520 | You can understand better clinical management.

01:52:03.800 | That was a simple solution to a pretty difficult problem.

01:52:07.460 | And it is changing the way that we approach

01:52:11.180 | all of the lab testing in this country.

01:52:12.660 | It's starting to, it's taken a few months,

01:52:14.660 | but it's starting to change because of that.

01:52:16.620 | And that was just me saying,

01:52:19.380 | hey, this is something we should be focusing on.

01:52:21.580 | Got some other people involved and other people,

01:52:24.100 | and now people recognize, hey, there's actual value

01:52:27.260 | in this number that comes out of these lab-based PCR tests.

01:52:30.220 | So sometimes it does grow fairly quickly.

01:52:34.060 | But I think the real answer, my only answer,

01:52:37.740 | I don't know what, I recognize that everyone,

01:52:40.340 | some people are gonna be really focused on

01:52:42.540 | and have one small but deep skillset.

01:52:46.100 | I go the opposite direction.

01:52:47.340 | I try to bring things together.

01:52:49.860 | But the biggest thing I think is just don't see barriers.

01:52:55.540 | Like just see, like there's always a solution to a barrier.

01:52:59.220 | If there's a barrier, that literally means

01:53:00.780 | there's a solution to it.

01:53:02.420 | That's why it's called a barrier.

01:53:03.560 | - And just like you said, most people will just present to,

01:53:07.240 | or only be thinking about it and present to you

01:53:09.240 | with barriers, and so it's easy to start thinking

01:53:11.940 | that's all there is in this world.

01:53:13.840 | - And just think big.

01:53:14.720 | I mean, God, there's nothing wrong with thinking big.

01:53:18.320 | Elon Musk thought big, and then thinking big builds

01:53:22.320 | on itself, you know?

01:53:23.160 | You get a billion dollars from one big idea,

01:53:26.280 | and then that allows you to make three new big ideas.

01:53:28.880 | - And there's a hunger for it if you think big

01:53:31.000 | and you communicate that vision with the world,

01:53:33.320 | all the most brilliant and passionate people will just like,

01:53:37.500 | you'll attract them, and they'll come to you.

01:53:39.840 | And then it makes your life actually really exciting.

01:53:42.500 | The people I've met at like Tesla and Neuralink,

01:53:46.340 | I mean, there's just like this fire in their eyes.

01:53:48.280 | They just love life, and it's amazing, I think,

01:53:51.220 | to be around those people.

01:53:53.360 | I have to ask you about what was the philosophy,

01:53:58.900 | the journey that took you to becoming a Buddhist monk,

01:54:02.180 | and what did you learn about life?

01:54:07.180 | What did you take away from that experience?

01:54:09.100 | How did you return back to Harvard

01:54:12.340 | and the world that's unlike that experience, I imagine?

01:54:17.340 | - Yeah, well, I was at Dartmouth at the time.

01:54:19.680 | Well, I went to Sri Lanka.

01:54:23.380 | I was already pretty interested in developing countries

01:54:25.820 | and sort of under-resourced areas,

01:54:27.460 | and I was doing a lot of engineering work,

01:54:30.700 | and I went there, but I was also starting to think

01:54:33.420 | maybe health was something of interest.

01:54:35.760 | And so I went to Sri Lanka

01:54:40.840 | because I had a long interest in Buddhism as well,

01:54:43.540 | just kind of interested in it as a thing.

01:54:46.660 | - Which aspect of the philosophy attracted you?

01:54:49.200 | - I would say that the thing that interested me most

01:54:52.540 | was really this idea of kind of a butterfly effect

01:54:57.080 | of like what you do now has ripple effects

01:55:02.080 | that extend out beyond what you can possibly imagine,

01:55:06.280 | both in your own life and in other people's lives.

01:55:10.620 | And in some ways, Buddhism has, not in some ways,

01:55:13.140 | in a pretty deep way, Buddhism has that

01:55:14.960 | as part of its underlying philosophy in terms of rebirth

01:55:19.820 | and sort of your actions today propagate to others,

01:55:25.340 | but also propagate to sort of what might happen

01:55:30.000 | in your circle of what's called samsara and rebirth.

01:55:32.600 | And I don't know that I subscribe fully

01:55:36.600 | to this idea that we are reborn,

01:55:39.840 | which always was a little bit of a debate internally,

01:55:44.840 | I suppose, when I was a monk.

01:55:46.300 | But it has always been, it was that,

01:55:50.440 | and then it was also meditation.

01:55:52.520 | At the time I was a fairly elite rower,

01:55:55.400 | I was rowing at the national level,

01:55:57.840 | and rowing to me was very meditative.

01:56:01.600 | It was just, even if you're in a boat with other people,

01:56:06.600 | I mean, on the one hand, it's like the extreme

01:56:09.520 | of like a team sport, but it's also the extreme

01:56:13.120 | sort of focus and concentration that's required of it.

01:56:16.720 | And so I was always really into just meditative

01:56:18.840 | type of things, I was doing a lot of pottery too,

01:56:20.840 | which was also very meditative.

01:56:22.400 | And so Buddhism just kind of really,

01:56:25.680 | there are a lot of things about meditating

01:56:28.400 | that just appealed.

01:56:30.600 | And so I moved to Sri Lanka,

01:56:32.280 | planning to only be there for a couple of months.

01:56:34.740 | But then I was shadowing in this medical clinic,

01:56:37.720 | and there was this physician who was just really,

01:56:40.340 | I mean, it's just kind of a horrible situation, frankly.

01:56:43.400 | This guy was trained decades earlier,

01:56:46.000 | he was an older physician, and he was still just practicing

01:56:49.560 | like these fairly barbaric approaches to medicine,

01:56:52.480 | 'cause he was a rural town,

01:56:55.520 | and he just didn't have a lot of,

01:56:57.160 | he didn't have any updated training, frankly.

01:57:00.640 | And so I just remember this girl came in

01:57:03.640 | with shrapnel in her hand,

01:57:05.880 | and his solution was to air it out.

01:57:08.720 | And so he was like, without even numbing her hand,

01:57:12.400 | he was cutting it open more,

01:57:15.920 | with this idea that the more oxygen and stuff,

01:57:20.040 | and it just, I think there was something about all of this,

01:57:23.000 | and I was already talking to these monks at the time,

01:57:25.520 | I would be in this clinic in the morning,

01:57:27.240 | and I'd go, and my idea was to teach English

01:57:31.520 | to these monks in the evening.

01:57:33.060 | Turned out I'm a really bad English teacher.

01:57:37.080 | So they just taught, they allowed me

01:57:39.320 | just to sit with them and meditate,

01:57:41.260 | and they were teaching me more about Buddhism

01:57:42.960 | than I could have possibly taught them about English,

01:57:44.800 | or being an American or something.

01:57:48.000 | And so I just slowly, I just couldn't take,

01:57:52.800 | I couldn't handle being in that clinic.

01:57:55.240 | So more and more, I just started moving,

01:57:57.320 | spending more and more time at this monastery.

01:57:59.440 | And then after about two months,

01:58:00.760 | I was supposed to come back to the States,

01:58:02.200 | and I decided I didn't want to.

01:58:04.160 | So I moved to this monastery in the mountains,

01:58:06.460 | primarily because I didn't have the money

01:58:09.180 | to just keep living.

01:58:11.200 | So living in a monastery is free.

01:58:13.540 | And so I moved there, and just started meditating

01:58:16.240 | more and more, and then months went by,

01:58:17.640 | and I just really gravitated.

01:58:22.120 | I gravitated to the whole notion of it.

01:58:24.800 | I mean, it became, it sounds strange,

01:58:28.400 | but meditating almost, just like anything

01:58:30.680 | that you put your mind to, became exciting.

01:58:34.560 | It became like there weren't enough hours

01:58:36.480 | in the day to meditate.

01:58:38.100 | And I would do it for 18 hours a day, 15 hours a day.

01:58:43.160 | Just sit there, and I mean, I hate sleeping anyway,

01:58:48.160 | but I wouldn't want to go to sleep

01:58:49.880 | because I felt like I didn't accomplish

01:58:51.440 | what I needed to accomplish in meditation that day,

01:58:54.120 | which is so strange, 'cause there is no end.

01:58:56.280 | But it was always, but there are these steps

01:59:01.480 | that happen during meditation

01:59:02.800 | that are very prescribed in a way.

01:59:05.160 | Buddha talked about them,

01:59:06.680 | and these are ancient writings, which exist.

01:59:08.720 | I mean, the writings are real.

01:59:09.840 | They're thousands of years old now.

01:59:11.240 | And so whether it was Buddha writing them or whoever,

01:59:16.240 | there are lots of different people

01:59:17.760 | who have contributed to these writings over the years.

01:59:20.560 | But they're very prescribed,

01:59:23.520 | and they tell you what you're gonna go through.

01:59:26.880 | And I didn't really focus too much on them.

01:59:29.040 | I read a little bit about them,

01:59:31.240 | but your mind really does.

01:59:32.420 | When you actually start meditating at that level,

01:59:35.160 | like not an hour here and there,

01:59:36.440 | but truly just spending your day as meditating,

01:59:39.560 | it becomes kind of like this other world

01:59:42.320 | where it becomes exciting,

01:59:43.920 | and you're actively working, you're actively meditating,

01:59:49.380 | not just kind of trying to quiet things.

01:59:51.200 | That's sort of just the first stage

01:59:53.360 | of trying to get your mind to focus.

01:59:54.940 | Most people never get past that first stage,

01:59:56.780 | especially in our culture.

01:59:58.680 | - Could you briefly summarize what's waiting

02:00:01.760 | beyond the stage of just quieting the mind?

02:00:03.980 | It's hard for me to imagine that there's something

02:00:08.320 | that could be described as exciting there.

02:00:12.400 | - Yeah, it's an interesting question.

02:00:14.640 | So I would say, so the first thing,

02:00:18.140 | the first step is truly just to be able to close your eyes,

02:00:22.080 | focus on your breath,

02:00:23.080 | and not have other thoughts enter into your mind.

02:00:26.280 | That alone is just so hard to do.

02:00:28.240 | I couldn't do it now if I wanted, but I could then.

02:00:35.520 | But once you get past that stage,

02:00:38.520 | you start entering into all these other,

02:00:41.600 | you go through a kind of,

02:00:42.440 | I went through this pretty trippy stage,

02:00:44.640 | which is a little bit euphoric,

02:00:46.280 | where you just kind of start not hallucinating.

02:00:49.800 | I mean, it wasn't like some crazy thing

02:00:51.440 | that would happen in a movie,

02:00:53.080 | but definitely just weird.

02:00:55.320 | You start getting to the stage

02:00:56.720 | where you're able to quiet your mind for so long,

02:01:01.720 | for hours at a time, that,

02:01:04.280 | for me, I started getting really excited

02:01:07.640 | about this idea of mindfulness,

02:01:09.640 | which is part of Buddhism in general,

02:01:11.760 | but it's part of Theravada Buddhism in particular

02:01:13.760 | for this, in this way, which was,

02:01:15.640 | you take, you start focusing on your daily activities,

02:01:21.600 | whether that's sipping a cup of tea,

02:01:23.960 | or walking, or sweeping around.

02:01:28.960 | I lived on this mountainside in this cottage thing,

02:01:32.360 | it was built into the rock,

02:01:33.420 | and so every morning I would wake up early

02:01:36.280 | and sweep around it and stuff,

02:01:37.600 | 'cause that's just what we did.

02:01:39.100 | And you start to, you meditate on all those activities,

02:01:44.000 | and one of the things that was so exciting,

02:01:46.240 | which sounds completely ridiculous now,

02:01:48.720 | was just almost learning about your daily activities

02:01:53.720 | in ways that you never would have thought about before.

02:01:56.880 | So what is, what's involved

02:02:00.480 | with picking up this glass of water?

02:02:02.900 | You know, if I said, okay, I'm just gonna pick,

02:02:05.140 | I'm gonna take a drink of water,

02:02:06.820 | to me right now, it's a single activity, right?

02:02:09.500 | You just, but during meditation,

02:02:14.500 | it's not a single activity,

02:02:16.340 | it's a whole series of activities,

02:02:18.160 | of like little engineering feats and feelings,

02:02:21.940 | and it's gripping the water,

02:02:24.240 | and it's feeling that the glass is cold,

02:02:25.960 | and it's lifting, and it's moving,

02:02:27.940 | and dragging, and dragging,

02:02:29.280 | and you start to learn a whole new language of life.

02:02:34.200 | And that, to me, was like this really exhilarating thing,

02:02:37.540 | that it was an exhilarating component of meditation,

02:02:41.320 | that there was never enough time,

02:02:43.680 | it's kind of like learning a new computer language,

02:02:46.360 | like it gets really exciting when you start coding

02:02:48.280 | and all these new things you can do.

02:02:50.480 | - You learn how to much,

02:02:53.200 | to experience life in a much richer way,

02:02:55.400 | and so you never run out of ways

02:02:57.000 | to go deeper, and deeper, and deeper in the way

02:02:59.140 | you experience just the drinking of the glass of water.

02:03:02.340 | - That's exactly right,

02:03:03.260 | and what becomes kind of exhilarating is,

02:03:05.860 | you start to be able to predict things that you never,

02:03:09.040 | or I don't even know if prediction's the right word,

02:03:11.180 | but I always think of the Matrix,

02:03:12.420 | you know, or I forget who it was,

02:03:15.180 | somebody was shooting at Neo,

02:03:17.900 | and he like leans backwards,

02:03:19.700 | and he dodges the bullets.

02:03:21.080 | You know, in some ways,

02:03:23.460 | when you start breaking every little action

02:03:25.380 | that your hands do, or that your feet do,

02:03:26.940 | or that your body does,

02:03:27.820 | down into all these little actions

02:03:29.520 | that make up one, what we normally think of as an action,

02:03:33.340 | all of a sudden, you can start to see things

02:03:35.360 | almost in slow motion.

02:03:37.100 | I like to think of it very much like language.

02:03:40.280 | The first time somebody hears a foreign language,

02:03:42.720 | it sounds really fast, usually.

02:03:45.980 | You don't hear the spaces between words,

02:03:48.980 | and it just sounds like,

02:03:52.180 | just like a stream of conscious,

02:03:54.020 | and it just sounds like a stream of noises,

02:03:55.680 | if you've never heard the language before.

02:03:57.060 | And as you learn the language,

02:03:58.740 | you hear clear breaks between words,

02:04:01.220 | and it starts to gain context,

02:04:02.820 | and all of a sudden, like that,

02:04:04.340 | what once sounded very fast,

02:04:06.740 | slows down, and it has meaning.

02:04:10.160 | That's our whole life.

02:04:11.420 | Well, there's this whole language happening

02:04:13.060 | that we don't speak, generally.

02:04:15.540 | But if you start to speak it,

02:04:17.140 | and if you start to learn it,

02:04:18.340 | and you start to say,

02:04:19.860 | hey, I'm picking up this glass

02:04:21.060 | is actually 18 little movements,

02:04:24.060 | then all of a sudden, it becomes extremely exciting,

02:04:27.260 | and exhilarating to just breathe.

02:04:29.460 | Breathing alone, and the rise and fall of your abdomen,

02:04:31.640 | or the way the air pushes in and out of your nose,

02:04:34.100 | becomes almost interesting.

02:04:36.640 | And what's really neat is the world

02:04:39.520 | just starts slowing down.

02:04:41.520 | And I'll never forget that feeling.

02:04:44.120 | And if there was one euphoric feeling from meditation

02:04:47.140 | I want to gain back,

02:04:48.940 | but I don't think I could

02:04:49.880 | without really meditating like that again,

02:04:52.140 | and I don't think I will.

02:04:54.340 | Was this slow motion of the world.

02:04:56.980 | It was finding the spaces between all the movements

02:05:01.380 | in the same way that the spaces

02:05:02.480 | between all the words happen.

02:05:04.620 | And then it almost gives you

02:05:05.860 | this new appreciation for everything.

02:05:07.860 | You know, it was really amazing.

02:05:10.100 | And so I think it came to an abrupt end, though,

02:05:14.180 | when the tsunami hit.

02:05:15.380 | I was there when the Indian Ocean tsunami hit in 2004.

02:05:18.580 | And it was like this dichotomy of being a monk,

02:05:22.140 | and just meditating in this extraordinary place.

02:05:26.600 | And then the tsunami hits and kills 40,000 people

02:05:30.660 | in a few minutes on the coast

02:05:32.220 | of this really small little country in Sri Lanka.

02:05:34.900 | And then I,

02:05:37.380 | it like my whole world of being a monk came crashing down

02:05:41.700 | when I go to the coast.

02:05:46.140 | And I mean, that was just a devastating

02:05:51.780 | visual sight and emotional sight.

02:05:54.460 | But the strangest thing happened,

02:05:56.500 | which was that everyone just wanted me to stay as a monk.

02:05:59.580 | Now people in that culture, they wanted to,

02:06:02.460 | the monks largely fled from the coastlines,

02:06:06.540 | those, you know, and so then there I was,

02:06:09.700 | and people wanted me to be a monk.

02:06:11.260 | They wanted me to stay on the coast,

02:06:12.260 | but be a monk and not help,

02:06:14.380 | like not help in the way that I considered helping.

02:06:17.660 | They wanted me just to keep meditating

02:06:20.520 | so that they could bring me dana, like offerings,

02:06:23.340 | and have their sort of karmic responsibilities

02:06:26.940 | attended to as well.

02:06:29.300 | And so that was really bizarre to me.

02:06:32.460 | It was like, how could I possibly just sit around

02:06:36.340 | while all these people,

02:06:37.380 | half of everyone's family just died?

02:06:40.220 | And so in any case, I stopped being a monk,

02:06:43.980 | and I moved to this refugee camp

02:06:45.460 | and lived there for another six months or so,

02:06:47.340 | and just stayed there, not as a monk,

02:06:52.340 | but tried to raise some money from the US

02:06:56.560 | and tried to like, I didn't know what I was doing.

02:06:58.840 | Frankly, I was 22.

02:07:01.560 | And I don't think I appreciated at the time

02:07:06.080 | how much of a role I was having in that community's life.

02:07:09.940 | But it's taken me many years to process all of this

02:07:14.600 | since then, but I would say

02:07:16.680 | it's what put me into the public health world,

02:07:19.160 | living in that refugee camp.

02:07:21.060 | And that difference that happened from being a monk

02:07:23.720 | to being in this devastating environment

02:07:26.880 | just really changed my whole view

02:07:30.120 | of what sort of why I was existing, I suppose.

02:07:34.640 | - Well, so there's this richness of life

02:07:39.640 | in a single drink of water that you experience,

02:07:42.640 | and then there's this power of nature

02:07:46.160 | that's capable to take the lives of thousands of people.

02:07:50.040 | So given all that, the absurdity of that,

02:07:52.480 | let me ask you, and the fact that you study things

02:07:58.140 | that could kill the entirety of human civilization,

02:08:01.200 | what do you think is the meaning of this all?

02:08:03.800 | What do you think is the meaning of life,

02:08:05.540 | this whole orchestra we've got going on?

02:08:08.040 | Does it have a meaning?

02:08:09.960 | And maybe from another perspective,

02:08:15.040 | how does one live a meaningful life if such is possible?

02:08:19.120 | - Well, from what I've seen,

02:08:24.540 | I don't think there's a single answer to that by any stretch.

02:08:29.080 | One of the most interesting things about Buddhism to me

02:08:32.280 | is that the human existence is part of suffering,

02:08:35.840 | which is very different from Judeo-Christian existence,

02:08:40.940 | which is that human existence is something to be,

02:08:45.940 | is a very different, it's something to,

02:08:50.220 | there's a richness to it.

02:08:51.680 | In Buddhism, it's just another one of your lives,

02:08:55.400 | but it's your opportunity to attain nirvana

02:08:59.620 | and become a monk, for example,

02:09:01.580 | and meditate to attain nirvana.

02:09:03.480 | Else you kind of just go back into the samsara,

02:09:06.820 | the cycle of suffering.

02:09:09.140 | And so, when I look at, I mean, in some ways,

02:09:14.140 | the notion of life and what the purpose of life is,

02:09:17.900 | they're kind of completely distinct,

02:09:20.900 | this sort of Western view of life,

02:09:22.940 | which is that this life is the most precious thing

02:09:27.180 | in the world versus this is just another opportunity

02:09:30.420 | to try to get out of life.

02:09:33.260 | I mean, the whole notion of nirvana and in Buddhism,

02:09:36.060 | getting out of this sort of cycle of suffering is to vanish.

02:09:41.060 | If you could attain nirvana throughout this life,

02:09:45.620 | the idea is that you don't get reborn.

02:09:48.620 | And so, when I look at these two,

02:09:51.300 | on the one hand, you have Christian faith

02:09:55.060 | and other things that want to go to heaven

02:09:57.120 | and live forever in heaven.

02:09:58.900 | Then you have this other whole half of humans

02:10:01.220 | who want nothing more than to get out of the cycle

02:10:05.700 | of rebirth and just poof, not exist anymore.

02:10:09.060 | - The cycle of suffering, yeah.

02:10:10.260 | - Yeah, and so, how do you reconcile those two?

02:10:12.460 | And I guess--

02:10:13.580 | - Do you have both of them in you?

02:10:15.700 | Do you basically oscillate back and forth?

02:10:17.980 | - I don't think I, I think I just,

02:10:19.820 | I look at us in a, I think we're just a bunch of proteins

02:10:22.940 | that we form and they work in this really amazing way.

02:10:29.580 | And they might work in a bigger scale.

02:10:31.380 | There might be some connections

02:10:33.820 | that we're not really clear about,

02:10:35.380 | but they're still biological.

02:10:36.580 | I believe that they're biological.

02:10:38.340 | - How do these proteins become conscious

02:10:40.580 | and why do they want to help civilization

02:10:43.600 | by having at home rapid tests at scale?

02:10:47.640 | - Well, I think, I don't have an answer to that one,

02:10:50.860 | but I really do believe that it's just,

02:10:54.740 | you know, this is just an evolution of consciousness.

02:10:59.140 | I don't personally think is,

02:11:02.460 | my feeling is that we're a bunch of pluses and minuses

02:11:05.420 | that have just gotten so complex

02:11:07.160 | that they're able to make rich feelings, rich emotions.

02:11:10.900 | And I do believe, though, you know,

02:11:13.040 | on the one hand, I sometimes wake up some days,

02:11:15.760 | my fiance doesn't always love it,

02:11:18.700 | but I kind of think we're all just a bunch of robots

02:11:20.780 | with pretty complicated algorithms that we deal with.

02:11:24.260 | And in that sense, like, okay,

02:11:28.620 | if the world just blew up tomorrow

02:11:30.940 | and nothing existed the day after that,

02:11:35.340 | it's just another blip in the universe, you know?

02:11:37.900 | But at the same time, I don't know.

02:11:40.100 | So that's kind of probably my most core basic feeling

02:11:42.460 | about life is like, we're just a blip

02:11:45.500 | and we may as well make the most of it

02:11:47.340 | while we're here blipping.

02:11:48.640 | - It's one hell of a fun blip, though.

02:11:52.300 | - It is, it's an amazing, you know,

02:11:55.900 | blink of an eye in time.

02:11:59.160 | - Michael, this is, you're one of the most

02:12:01.000 | interesting people I've met,

02:12:02.060 | one of the most interesting conversations,

02:12:03.960 | important ones now.

02:12:05.320 | I'm going to publish it very soon.

02:12:07.440 | I really appreciate taking the time.

02:12:09.760 | I know how busy you are.

02:12:10.920 | It was really fun.

02:12:12.940 | Thanks for talking today.

02:12:14.120 | - Well, thanks so much.

02:12:15.080 | This was a lot of fun.

02:12:16.480 | - Thanks for listening to this conversation

02:12:19.440 | with Michael Mina, and thank you to our sponsors.

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02:12:45.400 | to get a discount and to support this podcast.

02:12:48.960 | If you enjoy this thing, subscribe on YouTube,

02:12:51.420 | review it with Five Stars on Apple Podcasts,

02:12:53.800 | follow us on Spotify, support it on Patreon,

02:12:56.360 | or connect with me on Twitter @LexFriedman.

02:12:59.640 | And now, let me leave you with some words

02:13:01.960 | from Teddy Roosevelt.

02:13:03.840 | "It is not the critic who counts,

02:13:05.920 | not the man who points out how the strong man stumbles,

02:13:10.200 | or where the doer of deeds could have done them better.

02:13:13.640 | The credit belongs to the man who actually is in the arena,

02:13:17.880 | whose face is marred by dust and sweat and blood,

02:13:21.280 | who strives valiantly, who errs,

02:13:24.520 | who comes short again and again,

02:13:27.200 | because there's no effort without error and shortcoming,

02:13:30.720 | but who does actually strive to do the deeds,

02:13:33.800 | who knows great enthusiasms, the great devotions,

02:13:37.480 | who spends himself in a worthy cause,

02:13:40.280 | who at the best knows in the end

02:13:42.980 | that triumph of high achievement,

02:13:44.880 | and who at the worst, if he fails,

02:13:47.400 | at least fails while daring greatly,

02:13:50.600 | so that his place shall never be

02:13:53.240 | with those cold and timid souls

02:13:55.480 | who neither know victory nor defeat."

02:13:58.160 | Thank you for listening, and hope to see you next time.

02:14:01.920 | (music)

02:14:03.920 | (music)

02:14:05.920 | [BLANK_AUDIO]

Michael Mina: Rapid Testing, Viruses, and the Engineering Mindset | Lex Fridman Podcast #146

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