The Future of Healthcare

– We’re going to welcome Global Markets editor ^and host of Opening Bell and Sunday Morning Futures ^for Fox Business Network, Maria Bartiromo. ^Maria? ^(applause) – Thank you so much. Hi everybody, great to see you. ^I would just add one thing to say ^we actually do have someone in the room ^who’s gonna make a pretty good prediction coming up, and that is our next speaker, because you said “Who knows what happens with innovation?” I believe our next guest does have an idea so without further ado, let me welcome to the stage world-renowned genome scientist and entrepreneur, Dr. J. Craig Venter. Dr. Venter… (applause) ^started a firm called Human Longevity, Inc. ^- Yes. ^- And we’re gonna talk about that. ^Great to see you, Craig. ^- Nice to see you. – Thank you so much for being here and I’m thrilled to talk with you, founder, executive chairman and CEO, J. Craig Venter Institute. Co-founder, chairman and co-chief scientist, Synthetic Genomics. You know, I’ve been looking forward to this because I feel like it has become, all of a sudden, mainstream about longevity and that we’re living longer. You mapped the genome 15-plus years ago, and when you did it, it was a really, really big deal, it was really expensive, and I want to ask you what has happened since. – It’s a great question. Mostly, technology changes. I think we all thought a lot more was gonna fall out of having the first genomes, and how it was gonna change medicine. It’s changed the pharmaceutical industry, giving all the targets and things, but it hasn’t done as much as I think most people anticipated, but the nice thing is, technology has changed very dramatically. So when you covered things 15 years ago, the first genome cost $100 million, took us nine months to do, took two giant buildings, one for a $50 million computer that would now fit in your laptop, and the other for 350 machines. Now we have these machines, each one is 1,350 equivalents of what we did 15 years ago. We have dozens of those. Computing technology has changed. We built the third largest computer in the world 15 years ago for $50 million, and now it wouldn’t even rank in the top multiple thousand. We have cloud computing, and we have the modern tools of machine learning and artificial intelligence. So it’s a very different world. Now we’re doing what we wanted to do 15 years ago but the technology wasn’t ready. – I want to talk about what you’re doing right now and let me just point out that over the last 15 years, Dr. Venter has been collecting data from the mapping of the genome, and one of the reasons you’re here today, I wanted to mention this in the intro. One of the reasons you’re here today is because back in the day, when you were not this unbelievable entrepreneur genius scientist, you were working your way there, the American Heart Association gave you your first grant. – They gave me my very first research grant. That’s why I decided to come today to pay it back. (applause) – So for all of those people in the audience that are wondering, you know, “Should I be there? “Should I be supporting?” The American Heart Association supported Craig’s work early on and look what he has been able to do in the last 15 years. It’s pretty extraordinary. – That was 1976, so… – 1976! – You’re either a lot younger than I certainly was, and… (laughter) but it was, it’s important, it was a great start, so happy to do a little bit of payback today. – Thank you, and we’re thrilled that you’re here. So, back in the day, when you first mapped the genome, you said it cost $100 million. How much does it cost today, and are you seeing individuals want to map their genome to try to get ahead of disease? What are you seeing in terms of the perception out there and what people are doing? Then I want to ask you about the data you’ve collected. – Okay, so it’s now about $1,500 is the actual cost to sequence a genome. – $1,500? – Big change over $100 million. We’re trying to scale up to do 100,000 a year. So instead of one a year, we’re now trying to 100,000 a year. We’re still ramping up to that scale. But it’s not just the genome. We’re collecting phenotype and clinical information on every single person in our database, because it’s important to compare the phenotype to the genotype. In fact, we’re setting it up with the machine learning. We talked earlier, we hired Franz Och out of Google. He built Google Translate. He’s translated now 90 languages into each other using machine learning and artificial intelligence. A small team doing that seems overwhelming, but we gave him a bigger challenge and said he has to help translate the human genome. We’re using these modern tools of computing instead of hiring tens of thousands of people to do this. We’re hoping the new computer tools will allow us to make great discoveries. We’re setting it up so if you can measure something in the phenotype accurately, we can find the genetic determinants for that. – It’s massive amounts of data. What have you learned so far. What have been the most important breakthroughs that you’ve learned as a result of gathering this data over the last decade and a half? – Well, we’ve just started collecting at this new scale, because this technology only became available a little over a year ago. But the last two or three years has seen a big change, particularly in cancer chemotherapy by sequencing the genome of the tumor, or most people just sequence a few gene or exomes, looking for driver mutations with cancer. That dictates which drugs can be used. Best example is lung cancer. Phizer had a drug that they did a large phase three clinical trial for lung cancer and it totally failed. The retrospective analysis found a gene called ALK with a translocation occurs in about 4% of lung cancer patients. If you have that translocation, the Phizer drug works incredibly well on shrinking tumors in over 60% of those patients. I know the last panel talked a little bit about this, of doing genetic selection to get subgroups for drug approval. Now if you know the genetic subgroup, if Phizer had known just that 4% ahead of time, they could have gotten the drug approved probably in less than a year, with doing as few as 100 patients. It changes the entire paradigm. It changes the cost. Our view is there should be no failed phase three trials going forward, at least failing for efficacy, because we can find the right population. It’s not just cancer. It’s across the board. – Is that precision medicine? Is that what – – It’s part of the definition of precision medicine. It used to be called personalized medicine. People got confused and they thought people were going to make a drug specifically for you, versus by understanding your genetic code, we know which drug to select for your specific condition. Victor McKusick, who started this whole field, used to call it individualized medicine. But it is now trying to get much more precise on the target. President Obama announcing it as precision medicine probably will help drive the terminology in that direction. – I’m glad you mentioned what happened in terms of lung cancer. False starts is really where I’m going. because there has been this consumerism taking place in healthcare where you’re seeing individuals go into a Rite-Aid and go and sit there and try to get all of their fluids checked and do things on their own. Do you like what’s happening in terms of consumerism in healthcare? Or do you think that we’re doing things that we don’t understand, and that could lead to negative outcomes? – I think it’s really an exciting trend. The faster it goes, the better, as long as the right safeguards are in place. I think Theranos just got approval in Arizona for doing their broad array of blood tests, now over the counter in Arizona. They can do it on a micro liter of blood, so it changes the scale and the cost. With Genomics, we’re working through physicians and through genetic counselors right now because so much of the information is new and it’s going to be pretty powerful. The medical community has to learn how to sort it out. Angelina Jolie made a lot of press with first getting her breasts removed because of risk for breast cancer. People think if they have genetic risk and they go out and have double mastectomies, that’s not the best outcome. We’ve talked before about how if you have BRCA1 and BRCA2 gene changes, only 60% of women with those changes actually develop breast cancer. Physicians used to tell their patients it was close to 100%. It is close to 100% if every every woman in your family, your mother, your grandmother, your aunts, have breast cancer. and you have those genetic changes, then your odds are very high of getting breast cancer. That was, I think, Angelina Jolie’s case. But just because you have those positive gene changes isn’t a prescription to go out and have a double mastectomy. We need to get the right understanding out there before people go and do radical things based on not understanding the information completely. – Which is why I brought up the false starts. Because there is this consumerism going on, and you have a company like a 23andMe, not to pick on them, but they came out and said, “Look, you can spit in a cup. “We want to get your DNA, and we’ll tell you “what you’re susceptible for.” Then, of course, very soon into it the FDA said, “You’ve got to shut this down,” because of this very reason. – Initially they use a gene chip, so they don’t actually measure the genome. They just measure a number of known alleles. It was great when they were measuring like traits of family history, genealogy, etc. As soon as they moved into trying to determine risk for Alzheimer’s disease, or breast cancer, they moved into the diagnostic arena, and these chips have a very high false negative rate as well as a false positive rate. As a diagnostic, it’s not a good medium for doing things, so I think the FDA did the right thing in telling them to stop doing diagnostic tests. On the same time, the over-the-counter, people getting direct access to that information was a good start of a movement, that if we can get it so it’s accurate information and the medical community rises to the occasion to give the right information to go with it, then it can be very powerful. Most physicians are getting their training from their patients now, who read about new things. So if they go in with their genome sequenced, most physicians won’t have a clue what to do with that information. – That’s a good point. How important has technology been? Because today you see stories about Watson working with doctors and being able to digest so much medical information instantaneously so the doctors can cross off things that may be the issues. How has technology changed the game? – I think it’s early on in how it’s going to change it, but the scale of the information is tremendous. From about 10,000 human genomes, it’s over a petabyte of A’s, C’s, G’s, and T’s. That’s a lot of data just from 10,000. That doesn’t include the clinical records. An MRI, a single brain MRI, is about 2 gigabytes of data. So the amount of data
– [Maria] Wow. – and the quantity of information is going to be massive. As we get machine learning approaches that sort it out accurately and we can trust those, it’s going to be a tremendous tool set for the medical community and for individuals. – You have been studying organs recently, and I want to talk about what you’re doing in terms of human organs, versus organs of pigs. Tell us what you’re working on. – United Therapeutics made a major investment in my other company, Synthetic Genomics, where we’re rewriting the genetic code. It’s where we made the first synthetic cell writing the complete genetic code. But we’re in the process of trying to rewrite the pig genome to humanize it, so we can get pig organs for transplantation, so hearts, lungs, kidneys, liver. United Therapeutics is mostly interested in lungs. It’s the most difficult part. But slightly humanized pig hearts, just changing four or five genes, those hearts last well over a year in baboons. The heart is the right size and the right structure. If we change more of the antigens, more of the immune system, we think we can get those lasting a very long time. – Wow. Why pigs? Is that the closest to a human? – It’s the closest in terms of the size and the structure of the organs. They’re about the right size, the right overall function because of the size and the body mass. All mammals are only about 10% different from each other in the genetic code. But those differences are obviously important, as people know with tissue typing for any kind of transplantation. It’s a huge task. We have a large team working on it, because there’s very early rejection. There’s intermediate rejection pathways, and there’s long-term rejection. Immune therapy or immune suppression has been a big part of this. But we want to get it so you can do it without massive immune suppression. – Fascinating. – There’s about a million people that die in the U.S. from the lack of organs for transplantation. – Okay. We have done a lot of study as a country on heart disease. The biggest killer is still heart disease. We’ve done a lot of work on cancer. You mentioned cancer. What about the brain? What have you learned about the brain and what leads to autism or Alzheimers? Are you seeing discoveries or breakthroughs there that you can share? – It’s early, but now we have new tools for measurement. There’s nice quantitative algorithms developed by a team at UCSD that take this complex 2 gig MRI brain image. The algorithm converts that into volumes of different brain regions. In fact, the algorithm is much better than any pathologist at scoring minor changes in the brain. If you’re developing dementia, we could take brain scans as soon as three months apart and see differences. But it also gives us ability to find the genetic association between, for example, hippocampal size or changes. We’re doing this as a test with faces. We’re taking 3D photographs. We’re up to about a thousand students who are doing this. It generates 30,000 unique measurements from somebody’s face. We’re taking that into the machine learning algorithms. The goal is to predict an absolute good picture of you straight from your genetic code. We’re also trying to do this with voice. Perfect pitch is a genetic trait. The cadence that people speak at is a genetic trait. We’re more confident about the photos than we are about voice. It’s early on with the voice studies. But it shows people how personal this information is. You cannot de-identify your genetic code because it truly does describe you physically and structurally. We’re starting with those kind of measurements. But to get back to the brain, as the MRI imaging and other things get more precise, we know in rats, for example, the neurons show up in the same exact place in every inbred rat down to a few microns. So it’s clearly a genetic trait. If we can start to get those measurements in the brain, or the heart, or any other organ, we can work out the exact genetics associated with building that brain pattern. So we should be able to predict in advance the types of brain structures and functions, whether it’s a photographic memory, or whether it’s autism, the types of autism, or other major brain disorders. It’s early on, but this is where the future’s going to take us. – Is the medical community keeping up with what you’re seeing and working on in terms of the science? Doctors today, hospitals today, are we equipped to actually keep up with some of the advances that you’re talking about? – I have trouble keeping up, and I’m running the program. – I know. – Widespread word is not out about this data. I think as it gets converted from these massive data sets into very clear cut, actionable events that physicians can do and patients can do, I think they’ll rapidly become part of medical practice. Disseminating the information to the medical community is probably one of the biggest challenges in changing anything. It’s a conservative community, in fact, because you don’t want people changing therapy every time a new idea comes along and if it’s not proven. At the same time, when we get to this level, we want to change things very quickly. As powerful as the gene measurements in cancer are, still only a small percentage of cancer patients in the U.S. have the genes measured, even though it probably could save the lives of a very large number of people. – And what about the FDA? Are they keeping up? – The FDA is actually more forward-looking in this space now than we thought they might be, and we’re trying to work directly with the FDA. In fact, from their point of view, approving new drugs, we make their lives very easy. Right now people have to do huge clinical trials, and they use statistics to tell you whether the drug is going to work or not. Looking at specific genetic populations, there’s been cases where there are very small clinical trials, as few as 100. It’s kind of a yes/no answer. Does it work? In some cases, these trials, 100% of the patients respond. You don’t need a statistician to tell you whether to approve it or not. It makes it very easy for the FDA to make those decisions. They want to learn from our database, and learn from this approach. We have a major deal with Genentech and Roche to do all the patients in their clinical trials going forward. We’re talking to lots of other pharma companies about the same thing. I think it could totally change the way drugs are taken through clinical trial and approved. The industry’s been afraid of this in the past, for the reason that, with this ALK translocation, it says only 4% of lung cancer patients can now get that drug. But it’s about $100,000 a year per patient. The insurance companies are paying it, because they’d rather pay to have 4% get it that are really going to benefit, than the other 96% get it that could even do harm to. That’s the precision part of this as we go forward. It’s going to be a dramatic change. – I love this whole consumerism going on in healthcare right now. I want to get your take on something that Paul Jacobs told me recently. He, of course, was the CEO of Qualcom. Qualcom makes all the chips for our phones, our devices. They’re trying to get further into healthcare. He’s backing a clinical trial, hear me out here for a second, where you insert a sensor into your bloodstream, and then your phone will call you two weeks before you’re going to have a heart attack and tell you, “Go to the doctor. “You’re going to have a heart attack.” – Means you’ve got to keep your battery charged, right? – I mean, explain this
– You don’t want to get – clinical trial.
– a wrong number or a busy signal. – Yeah, exactly. Can you talk a bit about – Do you know of this clinical trial? – Yes. – Tell me about it. – The sensor field is just exploding, and there’s going to be a lot of these, of implantable sensors to measure your blood sugar, blood pressure, all kinds of things. It’s an exciting space. The measurement of these things on a continuous basis. People have been trying to do this. For blood pressure or arrhythmias, people wear halters, and they wear these bizarre devices around the clock. If you get a small, implantable device you can get continuous recording. The challenge is, again, what do you do with all the data and how do you sort out what’s useful, versus this massive onslaught of data that we’re going to get from these devices? – I’ve been following Craig’s work for about 20 years. But just recently I saw this headline, and I had to ask him about it. That is something you probably all have seen. It’s Time Magazine. It says, “This baby could live to be 142 years old.” – That’s my photo predicted from my genetic code. (laughter) – Is that true. – No. – No, no, no. I’m not saying is that you. Is it true that this baby could live until 142 years old is what I’m asking. – I don’t know about 142, but the odds of living into a second century are greatly increasing. We have an increasing number of centenarians and supercentenarians. We’re trying to look at their genetic code to see what’s unique about them. The studies thus far haven’t revealed anything. I think it’s more the absence of disease. That’s what human longevity goal is. We’re not trying to find a magic elixer, or magic drug that helps us live longer. If we can help prevent heart disease, if we can help prevent cancer, and we can find early predictions that allow us to prevent Alzheimer’s disease, we’re going to change the statistics pretty dramatically. It’s more then absence of disease than treating or curing of disease. I think it’s going to be preventing them and understanding them in advance that’s going to move the average up quite a bit, at least in the advanced developed world. – And some of the things that have gotten us here are very basic, like cleaner sewers, or cleaning up your neighborhood. You could actually say, and correct me if I’m wrong, that most disease happens either because of genetics, number one, or number two, behavior. That includes where you live, if you’re near the – So tell us about that. How some very basic things –
– Well, sanitation – The biggest changes in longevity in history have been from improving sanitation. The development of antibiotics. The development of antivirals. We’re a little bit in danger of going the other way. There’s now more people dying in the U.S. from drug-resistant microbes than from car accidents. So it’s a big change in the medical community. Because of the over-use and misuse of antibiotics we’re now running out of some of our arsenal. In the end, a lot of people still die from infectious disease. They die from pneumonia or some other type agent. We still have to work on infectious agents. We can’t ignore that as part of modern medicine. Right now it’s becoming a bigger problem instead of a smaller problem. We have to look at humans across the board. That’s what we’re looking at with the genome. About half your genome goes to making your brain structures. This was a real problem early on. Back when we first met I was in the Neurology Institute at NIH. They were upset that I was making discoveries outside of neurology. It turns out there’s not a chromosome that codes for the brain or for the heart. It’s the integration of this information across our genome, and we have to look at thousands of factors working together to change these things. It’s going to be a big challenge, and that’s why the computation is such an important part. – Craig is willing to take a few questions from the audience so think about that if you have any. But as people get ready, Craig, let me as you this. If you had to look out the next 15 years, do you think that you will find the biggest breakthroughs in cancer, in diabetes, in brain function? Where do you believe you’re really targeting or putting your finger on what’s going to be the most explosive stuff out there. – I think the answer is yes. – All of the above. – I think there’s going to be more breakthroughs in the next decade than in the past 100 years, because we’ll have information that wasn’t even remotely possible to get up until just last year. It’s going to be an exciting ride for the next 10 years. – Is there a way to protect all that data? This is also one of the big issues in healthcare. – We take database security very seriously. Even though HIPPA regulations allow you to “de-identify” the genetic code, obviously if we can generate your picture from your genome you can’t really de-identify it. We’re creating very highly secure databases. We have some of the top experts in the world working on database security. We’re using parts of the Amazon cloud. Database security is probably one of the most important things for the whole health industry going forward. You can’t just have this data out on the internet with all the predictions that will be possible going forward. – We have about five minutes for questions. Yes, sir. Right over here. You’re getting a microphone. If you could just tell us where you’re from that would be helpful. – [Audience Member] Yeah, I’m from New Jersey. (laughter) Is that good enough? No? – What do you think? – [Jeff] No, my name is Jeff Voigt, V-O-I-G-T. – Thank you. – [Jeff] There was a book that came out a couple years ago. It was by actually a comedian named Albert Brooks. The book was “2030.” I don’t know if anyone’s ever read the book. It’s a real fascinating take on – So you’re talking about human longevity. One of the main themes of the book is the character in the book has solved – has cured cancer. Okay? So this creates a situation where people are living really a long time. All right? He looks at, in the book, which makes it really fascinating, he looks at the political ramifications of people living that long. In the book what happens is you have the Youngs versus the Olds. The Youngs are really pissed off at the Olds because they have to care for and pay for the Olds as they continue to live, and pay for all these healthcare dollars. My question to you is – And by the way, I’m for what you’re doing. Have you ever thought of the – Actually the character of the book, too, has a mark on his head. He’s won the Nobel Prize for curing cancer. The Youngs want to kill him. – So it’s the ramifications of – – [Jeff] So the ramifications of what you’re trying to do. Have you thought about that, and how it affects society as a whole? – It’s an important question. Thank you for that. – Basically what you described is the current state of healthcare. – That’s right. – Right? _ We’re living till 85. – That’s not some science fiction future story. What we’re trying to do is to change that. We’re more interested in having you live a normal life span without disease, than necessarily extending life span. But as a result of eliminating disease, it will extend normal healthy life span. It’s not the goal to extend diseased life span, or people that are incapacitated and just require large dollars to maintain. I think this data will have the biggest chance of lowering healthcare costs than raising it. It’s going to make us old people younger again, so we can out-compete the young people without as much money. – But I think what you’re tapping into is really important, and one of the things that you said on my show when we talked about this, when I said, “How are we going to pay for this?” You said, “One idea is to, at a minimum we need to “increase the age that we collect Social Security.” – Just change the retirement age to 75. – The retirement age, the retirement age, from 65 to 75. – It solves all the entitlement issues right now. But then congress wouldn’t know what to do and fight over. – They would have to take another vacation. Yes, sir, in the back. – [Barry] Barry Tiko from Phizer. You have data now and you’re accumulating data on thousands of people. What’s your ethical obligation when you find a mutation in their genome that could have health implications for them? Are you obligated to go and notify them that they now have an increased risk of prostate cancer or whatever? – It’s a very important question. Depends on whether they’re part of a clinical study, a clinical trial from one of the pharmaceutical companies, or whether they’re an individual that’s come to us to get their genome analyzed and more information. If you come and get your genome done by us, you’ll set up as a lifelong learning thing, that every time there’s a new discovery you will get that instantaneously. Actually, a more problematic ethical issue that’s arising out of this, from a study that Tom Kaske did at Baylor just using the Young Presidents Organization, that many of them had very significant genetic risk. When it’s your genetic risk, guess what? It extends to your siblings, your children. The social obligation to me means you notify those people immediately. About a third of these people with significant genetic risk for disease did not want their family members to know. Where the moral obligation starts and stops is going to be a real problem for society. I think once that information exists, the family members have a right to know that. You can’t keep it secret. But it’s not our obligation to notify the family members. We’re letting the primary person know what we find. – But then again, that tells me that you think – If it’s my information, it’s my information. I own that information. – But you shared your genetic code. – I just shared it with you. – No you shared your genetic code with your offspring. – Right. – They have half your genome, and at the very least, they should be tested to see if they have that same exact risk. – So that raises the question if I want to share my information with you. Because then you might tell somebody I don’t want to know. – We won’t tell somebody, but we think you should tell somebody. – That’s the dilemma, the ethical dilemma. This is a very important question. Thank you for that. I promised him, and we have time for two more questions after this. – [Alexander] Alexander von Perfle, Royalty Pharma. Maria, thank you for honoring us with your presence. It’s always a pleasure to hear you moderate, and today’s no exception. Mr. Venter, do you recall the amount of your original American Heart Association grant in 1976? What is the combined or cumulative R&D budget of your efforts today, and your views on the funding of this research? Specifically the question of in this changing funding environment, how are we going to fund this, and what are some of the viable pathways to provide funding where funding is needed to advance the science? – A good combination question. I don’t remember the exact amount. Today you wouldn’t take the grant seriously. In the ’70s, I think it was something like $20,000 a year. – At the time it’s what you needed. – At the time that covered a couple people. Today it wouldn’t even cover a graduate student. If the American Heart Association wants to count return on investment from that one grant, you can claim it’s in the multi billions of dollars that have followed on from there. – Isn’t that great?
– In research funding. – That is so great. That is so great. (applause) – So I was grateful to get the grant. – Question right here. – [Ali] Hi. Ali Hartmann from K. Cairn. Everybody’s heard me talk a lot, but I really wanted to ask you this question. On the one hand you talked about people living into their hundreds, and on the other hand we’ve heard the statistic that this generation is likely to live five less years than their parents. So we seem to have a pretty big disconnect between what medicine can do and what behavior is leading towards. It causes me in my head to think about, if we can use the genome to cure people’s cancer, but they’re still consuming resources, whether on an environmental level, or a health behavior level, that aren’t good for themselves and for the planet, then are we putting a Band-Aid on overall an unhealthy situation, and are we also limiting, because this is so cost prohibitive, this to the few versus addressing the problems of the many? – There are about 15 convoluted questions in there. I’ll pick the one that I want to answer. – [Ali] That’s fine. That’s fine. Fair enough. It’s almost cocktail time. – Yes, it would be irresponsible just to try and increase the length of life span, when we have overused resources on this planet with the close to 8 billion people that we will soon have. So we have to solve all these problems simultaneously. As I said, trying to live a healthy life span is different than just trying to live to 120 under normal circumstances. There are lots of choices that people make. We’re talking to one major insurance company. By offering lower premiums to a group that follows healthy guidelines, by age 65, there’s an 8 year differential in life span. So the choices we make, the behavior things, will be important. You can use your genome to tell you the degree that those will impact things. Some people will be very heavily impacted, and some will be lesser impacted. Some people carry a mutation in a gene that if they smoke they come out about a hundred times worse than other people who smoke. Smoke is clearly a behavioral attribute. Everybody likes to refer to Aunt Millie who is 82 and smokes three packs a day and drinks six quarts of liquor every day. “So she did it and survived, that must be okay for me.” We, number one, want to sequence her genome. But that’s the beauty of this. It is precise. It is individualized. What works even for your siblings and family members won’t necessarily work for you. But how you carry out your life is going to be equally important, and what you do with the information will matter. What you do and how you live and what you consume out of the environment, we have to solve that as a society, or we won’t want to live a whole lot longer. – What’s the biggest challenge that you face right now in terms of your work? – I think our biggest actual challenge is trying to cope with all the data, integrate it, and interpret it. Nobody’s had this much data at this level before and tried to make real sense out of it. We’re trying to build all the pipelines so it really works. It’s very technical, but these are real challenges. If we don’t do it with the highest standards, our motto is “Garbage in and garbage out.” That’s what the story of the genome field has been. You mentioned 23andMe. If you can’t measure things very completely, you just get noise out of it. It’s a huge challenge with these computes, but it’s an exciting challenge at the same time. – Craig, thank you so much for your work. – It’s always fun. Thank you so much. – Dr. Craig Venter. – Thank you.

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