1 00:00:15,396 --> 00:00:22,036 Speaker 1: Pushkin from Pushkin Industries. This is Deep Background the show 2 00:00:22,076 --> 00:00:25,196 Speaker 1: where we explore the stories behind the stories in the news. 3 00:00:25,716 --> 00:00:28,996 Speaker 1: I'm Noah Feldman. A few weeks ago on the show, 4 00:00:29,276 --> 00:00:33,076 Speaker 1: I spoke to Nobel Prize me economist Paul Romer, and 5 00:00:33,196 --> 00:00:36,596 Speaker 1: Paul had what he considered a simple plan to reopen 6 00:00:36,636 --> 00:00:40,716 Speaker 1: the economy without risking people's health. All we need to 7 00:00:40,796 --> 00:00:44,556 Speaker 1: do is switch to a strategy where we're testing everybody 8 00:00:44,716 --> 00:00:48,156 Speaker 1: with regularity. As soon as we find somebody who's positive, 9 00:00:48,476 --> 00:00:52,596 Speaker 1: we need to isolate them without isolating lots of people 10 00:00:52,636 --> 00:00:55,676 Speaker 1: who could otherwise just go back to daily life and work. 11 00:00:55,956 --> 00:00:59,076 Speaker 1: Paul is not alone. Public health experts have been almost 12 00:00:59,196 --> 00:01:02,436 Speaker 1: unanimous in saying that we need a lot of tests 13 00:01:02,596 --> 00:01:06,036 Speaker 1: very soon in order to protect health and eventually reopen 14 00:01:06,076 --> 00:01:10,556 Speaker 1: the economy. And yet we are behind Germany, Canada, and 15 00:01:10,636 --> 00:01:14,116 Speaker 1: even Italy when it comes to per capita testing. And 16 00:01:14,276 --> 00:01:16,956 Speaker 1: as of now, less than one percent of the US 17 00:01:17,076 --> 00:01:21,596 Speaker 1: population has been tested for coronavirus. So what is the 18 00:01:21,636 --> 00:01:25,156 Speaker 1: hold up? What are the bottlenecks that stand between us 19 00:01:25,476 --> 00:01:29,756 Speaker 1: an effective testing? To learn more about coronavirus testing both 20 00:01:29,796 --> 00:01:32,836 Speaker 1: for diagnosis and then for antibody testing to see if 21 00:01:32,836 --> 00:01:36,156 Speaker 1: people have already had the disease. I'm joined by doctor 22 00:01:36,196 --> 00:01:40,796 Speaker 1: Ohmi Garner. He's the director of Clinical Microbiology Testing for 23 00:01:40,996 --> 00:01:44,316 Speaker 1: UCLA Health. His lab does more than one point five 24 00:01:44,556 --> 00:01:47,996 Speaker 1: million tests a year of all kinds, and so he 25 00:01:48,036 --> 00:01:51,596 Speaker 1: finds himself right in the thick of the question of 26 00:01:51,756 --> 00:01:57,196 Speaker 1: how we test for COVID. Oh my, I'm so grateful 27 00:01:57,236 --> 00:01:59,676 Speaker 1: to you for agreeing to talk to me. I want 28 00:01:59,716 --> 00:02:03,756 Speaker 1: to ask you to help guide us through the process 29 00:02:03,756 --> 00:02:08,796 Speaker 1: of just why testing takes so long to generate and 30 00:02:08,836 --> 00:02:12,916 Speaker 1: to cause to function. So start wherever you want. Maybe 31 00:02:12,956 --> 00:02:16,276 Speaker 1: start with the diagnostic tests first. What are the challenges 32 00:02:16,596 --> 00:02:19,956 Speaker 1: to having millions of diagnostic tests up and running on 33 00:02:19,956 --> 00:02:22,876 Speaker 1: a daily basis? You know, that's the million dollar question. 34 00:02:23,116 --> 00:02:26,956 Speaker 1: I think that there are lots of challenges for many ends, 35 00:02:27,476 --> 00:02:29,996 Speaker 1: and so just I think it's used to a little 36 00:02:29,996 --> 00:02:33,316 Speaker 1: bit walk through the process of getting a diagnostic test 37 00:02:33,796 --> 00:02:37,236 Speaker 1: for COVID nineteen by PRECR because it starts to then 38 00:02:37,316 --> 00:02:41,276 Speaker 1: outlay where the challenges are in the system. And so 39 00:02:41,476 --> 00:02:43,756 Speaker 1: the first part of the diagnostic test is the collection 40 00:02:43,796 --> 00:02:45,996 Speaker 1: of the sample. This is the part I think people 41 00:02:45,996 --> 00:02:48,916 Speaker 1: are most familiar with. You either go to your doctor's office, 42 00:02:48,996 --> 00:02:52,036 Speaker 1: or a hospital or a drive through location, and a 43 00:02:52,156 --> 00:02:56,476 Speaker 1: swab is inserted deep into nasal cavity and then that 44 00:02:56,676 --> 00:02:59,836 Speaker 1: sample is sent to a centralized testing lab. I think 45 00:02:59,836 --> 00:03:01,916 Speaker 1: there's a bit a little bit of confusion around this 46 00:03:02,396 --> 00:03:06,596 Speaker 1: because they call those locations testing locations, but no actual 47 00:03:06,636 --> 00:03:09,876 Speaker 1: testing happens there, and so I think people think, why 48 00:03:09,876 --> 00:03:12,076 Speaker 1: would it takes so long if the test happens right 49 00:03:12,076 --> 00:03:14,396 Speaker 1: where you collected it. So the sample needs to be 50 00:03:14,436 --> 00:03:17,876 Speaker 1: sent to a centralized laboratory like my laboratory where we 51 00:03:17,956 --> 00:03:21,876 Speaker 1: perform the PCR test, and the PCR test, depending on 52 00:03:21,916 --> 00:03:25,956 Speaker 1: which platform is used, can take anywhere from two to 53 00:03:25,996 --> 00:03:28,916 Speaker 1: six hours. And I think this is also something that's 54 00:03:28,916 --> 00:03:31,636 Speaker 1: not well known because if the test only takes two 55 00:03:31,636 --> 00:03:34,396 Speaker 1: to six hours, why are people waiting seven to fourteen 56 00:03:34,476 --> 00:03:36,876 Speaker 1: days to be able to get a test result right? 57 00:03:36,916 --> 00:03:41,596 Speaker 1: And I think one of the infrastructure challenges around this 58 00:03:41,676 --> 00:03:45,276 Speaker 1: particular outbreak and testing itself, is that there are just 59 00:03:45,436 --> 00:03:49,076 Speaker 1: not enough centralized laboratories that are able to do this 60 00:03:49,156 --> 00:03:51,996 Speaker 1: testing right now. And this starts to key in on 61 00:03:52,076 --> 00:03:55,436 Speaker 1: why we don't have testing across the country and a 62 00:03:55,436 --> 00:03:57,396 Speaker 1: lot of and we have labs, so it's not to 63 00:03:57,436 --> 00:04:01,556 Speaker 1: say that there aren't centralized clinical laboratories. There are centralized 64 00:04:01,556 --> 00:04:04,716 Speaker 1: clinical laboratories in almost every single city across this country. 65 00:04:05,156 --> 00:04:08,276 Speaker 1: The challenges that each one of those laboratories does not 66 00:04:08,436 --> 00:04:12,156 Speaker 1: have the equipment to be able to test for COVID nineteen, 67 00:04:12,596 --> 00:04:15,476 Speaker 1: and the labs that do have the equipment there is 68 00:04:15,516 --> 00:04:19,476 Speaker 1: such a shortage on they test themselves that many labs 69 00:04:19,476 --> 00:04:22,756 Speaker 1: that have the equipment still can't run the capacity of 70 00:04:22,796 --> 00:04:25,916 Speaker 1: tests they could run within a day. One of the 71 00:04:25,956 --> 00:04:29,796 Speaker 1: fascinating questions to me is is there some alternative technology 72 00:04:29,876 --> 00:04:33,316 Speaker 1: potentially in the pipeline they would make it easier to 73 00:04:33,356 --> 00:04:37,716 Speaker 1: collect samples by means other than the long swab that 74 00:04:37,756 --> 00:04:40,636 Speaker 1: goes deep into the nasal cavity. You know, Donald Trump 75 00:04:40,676 --> 00:04:42,596 Speaker 1: himself said it was a miserable experience for him to 76 00:04:42,596 --> 00:04:44,396 Speaker 1: have that done, And though I'm not super worried about 77 00:04:44,476 --> 00:04:47,676 Speaker 1: his own experience, it does mark the fact that we 78 00:04:47,716 --> 00:04:50,116 Speaker 1: need not only the swabs, that we need medical professionals 79 00:04:50,116 --> 00:04:52,036 Speaker 1: to do the swabbing, Whereas it might be a lot 80 00:04:52,036 --> 00:04:53,556 Speaker 1: faster and more efficient if people could do it at 81 00:04:53,596 --> 00:04:55,876 Speaker 1: home or there was just alive a test right now, 82 00:04:55,876 --> 00:04:57,596 Speaker 1: why is it the case that we can't do that? 83 00:04:58,116 --> 00:05:00,236 Speaker 1: I think that a lot of this is about clinical 84 00:05:00,276 --> 00:05:03,636 Speaker 1: sensitivity of what you're collecting. And when I say that, 85 00:05:03,716 --> 00:05:06,916 Speaker 1: I mean how likely is it for a false negative 86 00:05:06,956 --> 00:05:09,436 Speaker 1: to be given to a patient. So in the vironment 87 00:05:09,476 --> 00:05:11,996 Speaker 1: of COVID nineteen, we want to try our best to 88 00:05:12,036 --> 00:05:14,956 Speaker 1: avoid a false negative, and in order to do that, 89 00:05:15,436 --> 00:05:19,876 Speaker 1: you want to take the best possible specimen to increase 90 00:05:19,916 --> 00:05:24,036 Speaker 1: your likelihood of actually collecting virus. Now this is really 91 00:05:24,076 --> 00:05:26,716 Speaker 1: then the question is where is the virus? Right, Is 92 00:05:26,716 --> 00:05:28,956 Speaker 1: the virus out at the end of the nasal cavity, 93 00:05:29,116 --> 00:05:31,516 Speaker 1: Is the virus very very deep in the nasal cavity. 94 00:05:31,916 --> 00:05:34,436 Speaker 1: Is the virus in the throat? Is the virus in 95 00:05:34,516 --> 00:05:39,156 Speaker 1: different various oral fluid compartments. And the reason why nasal 96 00:05:39,156 --> 00:05:42,556 Speaker 1: pharyngeal collection was the first thing that was used is 97 00:05:42,596 --> 00:05:46,956 Speaker 1: because that's where we know other respiratory viruses live. And 98 00:05:46,996 --> 00:05:50,316 Speaker 1: so whether you're doing a PCR test for influenza or 99 00:05:50,356 --> 00:05:54,116 Speaker 1: a PCR test for something like respiratory sinciitio virus, the 100 00:05:54,316 --> 00:05:57,956 Speaker 1: best possible specimen, meaning the specimen that gives you the 101 00:05:58,036 --> 00:06:02,116 Speaker 1: highest likelihood for recovery of virus, is actually that really 102 00:06:02,236 --> 00:06:07,156 Speaker 1: deep nasal pharyngeal specimen. So then I think ultimately the 103 00:06:07,276 --> 00:06:09,676 Speaker 1: question is do you need to take the best possible 104 00:06:09,756 --> 00:06:14,236 Speaker 1: specimen or in this particular case, with this particular virus, 105 00:06:14,596 --> 00:06:17,276 Speaker 1: can you find an equal amount of virus in some 106 00:06:17,356 --> 00:06:21,356 Speaker 1: of these other specimens? And those studies are ongoing. I 107 00:06:21,396 --> 00:06:23,556 Speaker 1: agree with you if we could just use oral fluid, 108 00:06:23,596 --> 00:06:26,116 Speaker 1: I would change all of my test to oral fluid tomorrow. 109 00:06:26,356 --> 00:06:28,476 Speaker 1: But I won't do it if it's going to mean 110 00:06:28,556 --> 00:06:32,916 Speaker 1: we produce more false negatives. Now let's turn to the lab. 111 00:06:33,036 --> 00:06:35,276 Speaker 1: So you were saying the sample comes to you, it 112 00:06:35,316 --> 00:06:36,876 Speaker 1: reaches you in the lab, and you're going to perform 113 00:06:36,916 --> 00:06:39,876 Speaker 1: a PCR test. What is a PCR test. The test 114 00:06:39,996 --> 00:06:43,436 Speaker 1: is actually in two components, with PCR being the second component. 115 00:06:43,836 --> 00:06:47,716 Speaker 1: So the first component is really it's called RNA extraction. 116 00:06:48,196 --> 00:06:50,476 Speaker 1: And what happens is that when the sample comes in, 117 00:06:50,956 --> 00:06:54,396 Speaker 1: this first step actually takes out all the nucleic acid 118 00:06:54,476 --> 00:06:57,396 Speaker 1: from that sample. And so now what you have is 119 00:06:57,396 --> 00:06:59,396 Speaker 1: instead of the full sample from the patient, you just 120 00:06:59,436 --> 00:07:02,796 Speaker 1: have a pool of RNA and then you run the 121 00:07:02,836 --> 00:07:06,276 Speaker 1: PCR test. And so the PCR test is called an 122 00:07:06,396 --> 00:07:11,676 Speaker 1: rtPCR test. It's a reversed trend description polymerase chain reaction 123 00:07:12,076 --> 00:07:15,356 Speaker 1: that's that rt PCR, and what it does is because 124 00:07:15,356 --> 00:07:19,996 Speaker 1: we're looking for RNA, PCR is a technology that examines DNA. 125 00:07:20,116 --> 00:07:21,596 Speaker 1: So the first step is you have to turn the 126 00:07:21,716 --> 00:07:25,676 Speaker 1: RNA into DNA, and that's that reverse transcription. The second 127 00:07:25,716 --> 00:07:28,476 Speaker 1: test then is the polymerase chain reaction, and the polymerase 128 00:07:28,556 --> 00:07:33,396 Speaker 1: chain reaction is really a way to amplify a specific 129 00:07:33,556 --> 00:07:37,356 Speaker 1: target on DNA to see whether or not that target 130 00:07:37,476 --> 00:07:39,716 Speaker 1: is there. And of course the target we're looking for 131 00:07:40,316 --> 00:07:43,436 Speaker 1: is COVID nineteen, and so if some of that viral 132 00:07:43,596 --> 00:07:46,556 Speaker 1: RNA is there, it's been converted to DNA, and then 133 00:07:46,716 --> 00:07:49,876 Speaker 1: PCR can target to tell you whether or not that 134 00:07:49,996 --> 00:07:54,516 Speaker 1: viral RNA was originally in that specimen. And it's exquisitely sensitive. 135 00:07:54,516 --> 00:07:57,236 Speaker 1: The test that we're using in my laboratory get down 136 00:07:57,276 --> 00:08:01,916 Speaker 1: to about five hundred copies of virus per mill of fluid, 137 00:08:02,396 --> 00:08:04,276 Speaker 1: and so what I'd like to tell people is that 138 00:08:04,356 --> 00:08:07,116 Speaker 1: if the virus is in the sample, the test will 139 00:08:07,156 --> 00:08:10,556 Speaker 1: find it. That's super clarify and helpful. Now, you said 140 00:08:10,596 --> 00:08:14,756 Speaker 1: that there are enough laboratories in the United States to 141 00:08:14,796 --> 00:08:20,556 Speaker 1: handle even a substantial volume of testing, and that the 142 00:08:20,636 --> 00:08:23,836 Speaker 1: problem is that they don't have the necessary equipment in 143 00:08:23,916 --> 00:08:26,796 Speaker 1: a concrete sense, what is missing in these labs, because 144 00:08:26,796 --> 00:08:28,236 Speaker 1: if we could figure out what that is, maybe we 145 00:08:28,236 --> 00:08:31,316 Speaker 1: could talk about how we provide it. Sure So, there 146 00:08:31,356 --> 00:08:35,876 Speaker 1: are now I don't know somewhere around twelve FDA Emergency 147 00:08:35,996 --> 00:08:41,836 Speaker 1: Used Authorization approved PCR tests for COVID nineteen. The challenge 148 00:08:41,876 --> 00:08:45,236 Speaker 1: is that the manufactures of those tests need to get 149 00:08:45,316 --> 00:08:49,196 Speaker 1: those tests to those laboratories to be able to provide testing. So, 150 00:08:49,676 --> 00:08:52,876 Speaker 1: giving an example from my own laboratory, I actually run 151 00:08:53,116 --> 00:08:57,276 Speaker 1: four different FDA approved tests for COVID nineteen. And the 152 00:08:57,356 --> 00:08:59,596 Speaker 1: reason why I do that is because I can't get 153 00:08:59,756 --> 00:09:04,236 Speaker 1: one manufacturer to give me enough volume of test kits 154 00:09:04,916 --> 00:09:07,156 Speaker 1: to meet the need, so I actually have to bring 155 00:09:07,196 --> 00:09:09,276 Speaker 1: in four different tests to be able to do that. 156 00:09:09,556 --> 00:09:11,676 Speaker 1: You get a couple one hundred a day from one place, 157 00:09:11,716 --> 00:09:13,956 Speaker 1: you get a couple one hundred a day from another place, 158 00:09:14,196 --> 00:09:17,516 Speaker 1: and you combine all of that volume together and I 159 00:09:17,516 --> 00:09:20,396 Speaker 1: can get up around the thousand tests a day or 160 00:09:20,396 --> 00:09:23,356 Speaker 1: so that I can offer in my laboratory. This is 161 00:09:23,756 --> 00:09:28,316 Speaker 1: a significant challenge and the shortage by the manufacturers of 162 00:09:28,396 --> 00:09:32,356 Speaker 1: the diagnostic tests really is contributing to our inability to 163 00:09:32,476 --> 00:09:35,676 Speaker 1: have widespread testing. And I don't want to put the 164 00:09:35,716 --> 00:09:38,636 Speaker 1: blame on the manufacturers for this. What they've been asked 165 00:09:38,796 --> 00:09:41,916 Speaker 1: is very very difficult, which is to basically pivot their 166 00:09:42,076 --> 00:09:45,956 Speaker 1: entire operation. And these are diagnostic manufacturers that make all 167 00:09:46,036 --> 00:09:51,116 Speaker 1: kinds of diagnostic tests, HIV viral load tests, goneria, clamydia 168 00:09:51,236 --> 00:09:54,196 Speaker 1: PCR tests, and they're saying to them, Okay, we need 169 00:09:54,236 --> 00:09:57,716 Speaker 1: you to make a COVID nineteen test and ramp it 170 00:09:57,836 --> 00:10:01,276 Speaker 1: up a hundred times more the volume you would normally 171 00:10:01,356 --> 00:10:04,956 Speaker 1: make for testing. What do you think is slowing them 172 00:10:04,996 --> 00:10:07,556 Speaker 1: down in doing that? I mean, just at the most 173 00:10:07,636 --> 00:10:11,156 Speaker 1: basic level, picturing the factory where they make the tests, 174 00:10:11,476 --> 00:10:15,196 Speaker 1: and I'm picturing them shifting over the functionality they usually 175 00:10:15,196 --> 00:10:18,676 Speaker 1: have to produce other kinds of tests onto producing COVID 176 00:10:18,756 --> 00:10:23,076 Speaker 1: nineteen tests. What's the hold up for them that stops 177 00:10:23,076 --> 00:10:25,916 Speaker 1: them from doubling or tripling, to say nothing of going 178 00:10:25,996 --> 00:10:28,396 Speaker 1: up to one hundred times. So I think one of 179 00:10:28,396 --> 00:10:32,436 Speaker 1: the hold ups is just manufacturing capacity, because you can't 180 00:10:32,556 --> 00:10:35,636 Speaker 1: just stop making the other tests because people still have 181 00:10:35,716 --> 00:10:39,076 Speaker 1: those other diseases, and so it's almost like you need 182 00:10:39,116 --> 00:10:42,996 Speaker 1: to on top of what you were making before. Now 183 00:10:43,076 --> 00:10:47,396 Speaker 1: go ahead and produce one hundredfold times COVID nineteen testing, 184 00:10:47,756 --> 00:10:50,636 Speaker 1: and so you know, I really think it's a manufacturing bottleneck. 185 00:10:50,676 --> 00:10:53,756 Speaker 1: You can only do so many runs at a time 186 00:10:54,036 --> 00:10:58,276 Speaker 1: because you only have so much manufacturing capacity in that setting. 187 00:10:58,876 --> 00:11:02,316 Speaker 1: In speaking with the manufacturers, this is what I've been told. 188 00:11:02,676 --> 00:11:05,516 Speaker 1: The other part of the problem that we've discovered kind 189 00:11:05,516 --> 00:11:08,596 Speaker 1: of over time is that a lot of these manufacturers 190 00:11:08,716 --> 00:11:12,396 Speaker 1: rely on some of the same chemicals to make their 191 00:11:12,396 --> 00:11:17,236 Speaker 1: own proprietary test kits. And if one chemical, let's say 192 00:11:17,276 --> 00:11:22,316 Speaker 1: that multiple manufacturers use, is in shortage, that then stops 193 00:11:22,476 --> 00:11:25,876 Speaker 1: all of them from making more tests. So there's a 194 00:11:25,876 --> 00:11:29,156 Speaker 1: whole supply chain here of the chemicals that are necessary 195 00:11:29,196 --> 00:11:32,316 Speaker 1: to make this work. And so one has to go 196 00:11:32,356 --> 00:11:34,756 Speaker 1: back a further step and go to the chemical companies 197 00:11:34,756 --> 00:11:37,556 Speaker 1: and make sure the chemical companies are manufacturing more of 198 00:11:37,596 --> 00:11:40,756 Speaker 1: this in terms of stopping though the production of their 199 00:11:40,836 --> 00:11:44,996 Speaker 1: other tests can't. An argument be made that given the tremendous, 200 00:11:44,996 --> 00:11:48,716 Speaker 1: almost unimaginable cost of keeping our economy shut down, and 201 00:11:48,796 --> 00:11:51,916 Speaker 1: given the testing is so crucial to reopening, that they 202 00:11:51,916 --> 00:11:55,476 Speaker 1: actually should stop manufacturing the other tests rely on whatever 203 00:11:55,556 --> 00:12:00,356 Speaker 1: backlog they have and just prioritize COVID nineteen tests ahead 204 00:12:00,356 --> 00:12:03,996 Speaker 1: of everything else. I can agree with you there. You know, 205 00:12:04,036 --> 00:12:06,356 Speaker 1: I don't work for the companies. I can only speak 206 00:12:06,476 --> 00:12:09,836 Speaker 1: as an end user that's in an academic medical and 207 00:12:09,956 --> 00:12:13,596 Speaker 1: running these tests. That yes, I think that the pivot 208 00:12:13,636 --> 00:12:15,636 Speaker 1: needs to be fast. I think part of the challenge 209 00:12:15,636 --> 00:12:18,636 Speaker 1: as well, though, is that these companies aren't made to 210 00:12:18,756 --> 00:12:22,036 Speaker 1: pivot like that, and so you know, getting the either 211 00:12:22,156 --> 00:12:26,276 Speaker 1: federal support or whatever would be necessary to encourage them 212 00:12:26,316 --> 00:12:29,316 Speaker 1: to be able to do this is one of the challenges. 213 00:12:29,356 --> 00:12:32,196 Speaker 1: But yes, I will agree with you. Overall, to meet 214 00:12:32,276 --> 00:12:35,876 Speaker 1: this immediate need, there needs to be a shifting, and 215 00:12:35,916 --> 00:12:37,916 Speaker 1: I know a lot of companies are shifting. It's just 216 00:12:38,316 --> 00:12:40,916 Speaker 1: the scale of the shifting. You know, when we think 217 00:12:40,916 --> 00:12:44,076 Speaker 1: of clinical lab testing. You know, there has never been 218 00:12:44,116 --> 00:12:46,676 Speaker 1: a test in my laboratory where I need to do 219 00:12:46,756 --> 00:12:51,396 Speaker 1: two thousand tests a day. So the scale of this 220 00:12:51,556 --> 00:12:56,876 Speaker 1: is just it's mind boggling from an overall diagnostics perspective, 221 00:12:56,876 --> 00:12:59,636 Speaker 1: because I don't want to represent it as something like, well, 222 00:12:59,676 --> 00:13:02,236 Speaker 1: the manufacturers just should have shifted and this would have 223 00:13:02,276 --> 00:13:05,036 Speaker 1: been relatively easy for them to do, and they're negligent 224 00:13:05,076 --> 00:13:07,676 Speaker 1: to not do that. That's not what's going on. This 225 00:13:07,876 --> 00:13:11,556 Speaker 1: is really an unpress sedented shift that's being asked for, 226 00:13:11,876 --> 00:13:13,876 Speaker 1: Yet at the same time we have to be able 227 00:13:13,916 --> 00:13:17,276 Speaker 1: to do it in your lab. The PCR test, if 228 00:13:17,316 --> 00:13:20,196 Speaker 1: you have the equipment, can be run in two to 229 00:13:20,276 --> 00:13:23,956 Speaker 1: six hours. So what is driving the backlog that causes 230 00:13:23,996 --> 00:13:25,716 Speaker 1: people to have to wait seven to ten days for 231 00:13:25,756 --> 00:13:28,156 Speaker 1: a result. A lot of that is that every single 232 00:13:28,276 --> 00:13:32,596 Speaker 1: state doesn't even have large scale testing that's available. One 233 00:13:32,596 --> 00:13:37,556 Speaker 1: of our reference laboratories in California, Quest Diagnostics was receiving 234 00:13:37,676 --> 00:13:41,196 Speaker 1: samples from New York and New Jersey. Well, if you're 235 00:13:41,316 --> 00:13:44,356 Speaker 1: shipping samples across the country to be able to have 236 00:13:44,476 --> 00:13:46,636 Speaker 1: them tested at a facility, and then once they get 237 00:13:46,676 --> 00:13:49,956 Speaker 1: to that facility, if the queue or line is two 238 00:13:50,076 --> 00:13:53,636 Speaker 1: hundred thousand tests long, you can see that it just 239 00:13:53,836 --> 00:13:58,796 Speaker 1: increases exponentially the turnaround time, which is the expression that 240 00:13:58,796 --> 00:14:01,156 Speaker 1: we use in lab diagnostics for the amount of time 241 00:14:01,156 --> 00:14:04,076 Speaker 1: it takes from the sample to be collected all the 242 00:14:04,076 --> 00:14:07,116 Speaker 1: way to the person getting the result back. Is there 243 00:14:07,156 --> 00:14:11,796 Speaker 1: any in centralized national planning for where tests should go. 244 00:14:11,956 --> 00:14:15,196 Speaker 1: I mean, it seems very crazy that someone could be 245 00:14:15,236 --> 00:14:17,636 Speaker 1: tested in New York and then have their samples sent 246 00:14:17,716 --> 00:14:20,596 Speaker 1: to LA so that a lab there can do the work. 247 00:14:20,796 --> 00:14:22,676 Speaker 1: But I get that you have to send the test 248 00:14:22,716 --> 00:14:24,676 Speaker 1: where there's access. It sounds like the kind of thing 249 00:14:24,716 --> 00:14:28,396 Speaker 1: which would benefit from a centralized model. I agree with you. 250 00:14:28,476 --> 00:14:31,436 Speaker 1: I think a centralized model would be helpful. But you know, 251 00:14:31,476 --> 00:14:34,116 Speaker 1: I think that this is tied into our healthcare system, 252 00:14:34,356 --> 00:14:37,796 Speaker 1: and our healthcare system is not built around a centralized model. 253 00:14:37,876 --> 00:14:39,796 Speaker 1: And so I think this is why you see some 254 00:14:39,876 --> 00:14:43,356 Speaker 1: of the great disparity across the country is because there 255 00:14:43,476 --> 00:14:47,796 Speaker 1: is no centralized model, and thus individual areas some can 256 00:14:47,836 --> 00:14:50,716 Speaker 1: be very very fast, and some may not have access 257 00:14:50,756 --> 00:14:54,276 Speaker 1: to testing at all. What realistically is going to happen 258 00:14:54,476 --> 00:14:58,236 Speaker 1: in your view, if in the next few weeks, you know, 259 00:14:58,356 --> 00:15:01,196 Speaker 1: sort of like end of April, first few weeks of May, 260 00:15:01,796 --> 00:15:04,876 Speaker 1: we see an effort to get people back to work, 261 00:15:05,356 --> 00:15:08,516 Speaker 1: coupled with big companies trying to get tests done for 262 00:15:08,516 --> 00:15:13,236 Speaker 1: their employee eventually over the course of the summer, campuses 263 00:15:13,276 --> 00:15:16,236 Speaker 1: like university campuses trying to get people tested in a 264 00:15:16,236 --> 00:15:20,876 Speaker 1: systematic way is not at all realistically doable from your perspective, 265 00:15:21,156 --> 00:15:23,636 Speaker 1: Given where we stand, I mean, you're perfectly placed to 266 00:15:23,676 --> 00:15:26,036 Speaker 1: give a credible answer to this question because most people 267 00:15:26,076 --> 00:15:32,556 Speaker 1: are just speaking theoretically. Yeah, I'm optimistic. So within that optimism, 268 00:15:32,556 --> 00:15:35,836 Speaker 1: and again I talk to multiple manufacturers of these tests 269 00:15:35,836 --> 00:15:39,796 Speaker 1: on a daily basis. Everybody is ramping up. And as 270 00:15:39,836 --> 00:15:42,956 Speaker 1: everybody ramps up, I see more and more hospitals, even 271 00:15:42,996 --> 00:15:46,996 Speaker 1: just in the Los Angeles area, being able to provide testing. 272 00:15:47,436 --> 00:15:50,076 Speaker 1: And so I think we're moving in the right direction. 273 00:15:50,236 --> 00:15:52,756 Speaker 1: The question is are we moving in a direction fast 274 00:15:52,916 --> 00:15:55,796 Speaker 1: enough to match what we're going to do with changes 275 00:15:55,836 --> 00:16:00,636 Speaker 1: in social distancing policies? And that's a really difficult thing 276 00:16:00,756 --> 00:16:03,516 Speaker 1: to be able to predict because I think the two 277 00:16:03,596 --> 00:16:07,636 Speaker 1: need to be tethered together. As we increase our testing capacity, 278 00:16:07,676 --> 00:16:10,916 Speaker 1: I think that's one way for us to start in 279 00:16:10,956 --> 00:16:16,156 Speaker 1: a responsible way, opening back up, getting people back to work. 280 00:16:16,436 --> 00:16:17,956 Speaker 1: But you know, I think if you just flip the 281 00:16:17,956 --> 00:16:22,396 Speaker 1: switch on May fifteenth or whatever arbitrary day that said, 282 00:16:23,276 --> 00:16:27,596 Speaker 1: it's going to so outpace our pace of testing that 283 00:16:27,596 --> 00:16:30,236 Speaker 1: we're going to end up right back where we were. So, 284 00:16:30,316 --> 00:16:31,916 Speaker 1: you know, I think that states that are going to 285 00:16:31,956 --> 00:16:35,516 Speaker 1: be able to do this in a scientific and educated 286 00:16:35,596 --> 00:16:40,476 Speaker 1: way to meet the testing needs while you open up, 287 00:16:40,836 --> 00:16:43,516 Speaker 1: I think that we can be successful at it. We'll 288 00:16:43,556 --> 00:16:54,676 Speaker 1: be back in just a moment. So far, we've been 289 00:16:54,716 --> 00:16:57,956 Speaker 1: talking about PCR testing, which is to see if a 290 00:16:57,996 --> 00:17:01,036 Speaker 1: person from whom example has been taken has the virus now, 291 00:17:01,676 --> 00:17:05,956 Speaker 1: but part of opening up will also be extensive antibody testing. 292 00:17:06,556 --> 00:17:09,996 Speaker 1: Do you guys do that in your lab? So not yet. 293 00:17:10,116 --> 00:17:13,796 Speaker 1: I'm going through the validation process now, and so my 294 00:17:13,916 --> 00:17:16,756 Speaker 1: expectation is that we should go live at UCLA with 295 00:17:16,796 --> 00:17:20,796 Speaker 1: antibody testing, hopefully sometime early to mid next week. I 296 00:17:20,796 --> 00:17:23,356 Speaker 1: do want to make kind of a general comment about 297 00:17:23,356 --> 00:17:27,356 Speaker 1: the antibody testing compared to the PCR though, so I 298 00:17:27,436 --> 00:17:29,796 Speaker 1: said they were like nine to twelve manufacturer of the 299 00:17:29,836 --> 00:17:34,116 Speaker 1: PCR test. Ultimately they're using the exact same technology, even 300 00:17:34,156 --> 00:17:36,756 Speaker 1: though there are small differences between the tests, and so 301 00:17:36,796 --> 00:17:38,956 Speaker 1: you can really see those tests as the same tests. 302 00:17:39,636 --> 00:17:42,716 Speaker 1: So whether I offer a PCR test or hospital down 303 00:17:42,756 --> 00:17:44,796 Speaker 1: the street offers a PCR test, they're all going to 304 00:17:44,876 --> 00:17:48,996 Speaker 1: be kind of the equivalent sensitivity and high quality. Unfortunately, 305 00:17:49,076 --> 00:17:52,396 Speaker 1: that is not true for antibody testing at all, and 306 00:17:52,436 --> 00:17:54,596 Speaker 1: so the challenge of antibody testing is that it was 307 00:17:54,676 --> 00:17:57,716 Speaker 1: unregulated by the FDA to begin with, So there were 308 00:17:57,716 --> 00:17:59,916 Speaker 1: a lot of tests that flooded the market that were 309 00:18:00,276 --> 00:18:05,396 Speaker 1: very very low quality, and every single antibody test manufacturer, 310 00:18:05,436 --> 00:18:07,236 Speaker 1: because I'm now talked to five or six of them, 311 00:18:07,596 --> 00:18:10,596 Speaker 1: are using a different target on the virus to be 312 00:18:10,636 --> 00:18:14,596 Speaker 1: able to look for antibodies, and that distinctly affects whether 313 00:18:14,716 --> 00:18:17,476 Speaker 1: or not these tests are cross reactive, and they produce 314 00:18:17,556 --> 00:18:20,676 Speaker 1: false positives. And so unfortunately, what you're going to see 315 00:18:20,676 --> 00:18:24,076 Speaker 1: with antibody testing is that depending on the platform each 316 00:18:24,116 --> 00:18:28,396 Speaker 1: testing area uses, they could have vastly different results. And 317 00:18:28,556 --> 00:18:31,276 Speaker 1: this makes antibody testing then, in determining kind of what 318 00:18:31,316 --> 00:18:35,396 Speaker 1: it means, very very challenging. So how did you go 319 00:18:35,436 --> 00:18:37,916 Speaker 1: about the process of choosing the approach that you're going 320 00:18:37,956 --> 00:18:39,996 Speaker 1: to use in your lab? So I was looking for 321 00:18:40,036 --> 00:18:42,756 Speaker 1: the best test possible, right, I think the challenge with 322 00:18:42,756 --> 00:18:44,996 Speaker 1: antibody testing is that it needs to be of the 323 00:18:45,076 --> 00:18:48,396 Speaker 1: highest quality if we're going to have any chance of 324 00:18:48,436 --> 00:18:52,196 Speaker 1: trying to establish some level of immunity or even affect 325 00:18:52,316 --> 00:18:56,036 Speaker 1: behavior by having something like a positive test result. And 326 00:18:56,116 --> 00:18:58,596 Speaker 1: so in speaking with the companies, what I really wanted 327 00:18:58,596 --> 00:19:01,676 Speaker 1: to look at was the size of their validation data, 328 00:19:01,836 --> 00:19:05,636 Speaker 1: whether or not they proved non cross reactivity with something 329 00:19:05,676 --> 00:19:11,076 Speaker 1: like seasonal coronavirus, influenza, some other viruses that we all 330 00:19:11,156 --> 00:19:13,716 Speaker 1: have IgG four that you would not want to be 331 00:19:13,836 --> 00:19:18,236 Speaker 1: cross reactive in a COVID nineteen antibody test, And so 332 00:19:18,356 --> 00:19:21,476 Speaker 1: we did a long process of evaluation and then now 333 00:19:21,916 --> 00:19:24,676 Speaker 1: once we've chosen our company, we want to move forward 334 00:19:24,716 --> 00:19:28,556 Speaker 1: with I'm going to do an extensive in lab validation 335 00:19:28,636 --> 00:19:32,316 Speaker 1: with serum that I already have from COVID nineteen positive 336 00:19:32,316 --> 00:19:35,956 Speaker 1: patients and from patients with other viruses to prove that 337 00:19:35,996 --> 00:19:38,276 Speaker 1: it works before I go forward with a test for 338 00:19:38,356 --> 00:19:42,276 Speaker 1: my patients. So you're actually doubling up. First, you're choosing 339 00:19:42,276 --> 00:19:44,076 Speaker 1: what you think is the best test, and then you're 340 00:19:44,076 --> 00:19:46,556 Speaker 1: going to test it yourself in the lab to make 341 00:19:46,596 --> 00:19:48,756 Speaker 1: sure that you have confidence in it before you start 342 00:19:48,916 --> 00:19:51,236 Speaker 1: using it. Absolutely, I think it's the only way in 343 00:19:51,556 --> 00:19:53,876 Speaker 1: the current environment with the amount of anibody tests that 344 00:19:53,916 --> 00:19:56,316 Speaker 1: are out there. It's just I have to be sure 345 00:19:56,356 --> 00:19:59,196 Speaker 1: because clinical decisions are going to be made based on 346 00:19:59,276 --> 00:20:03,076 Speaker 1: these results. Personal decisions are going to be made based 347 00:20:03,116 --> 00:20:05,076 Speaker 1: on these results, and so you know, that's really the 348 00:20:05,156 --> 00:20:08,876 Speaker 1: role of a clinical lab director in choosing the best possible. 349 00:20:10,636 --> 00:20:13,756 Speaker 1: One of the things that has fascinated me is to 350 00:20:13,796 --> 00:20:17,076 Speaker 1: hear about scientists around the country trying to come up 351 00:20:17,076 --> 00:20:22,156 Speaker 1: with outside the box solutions to massively increase testing capacity. 352 00:20:22,556 --> 00:20:24,876 Speaker 1: And one of the most intriguing ones that I read 353 00:20:24,916 --> 00:20:28,196 Speaker 1: about was produced by a group at the Broad Institute 354 00:20:28,236 --> 00:20:30,276 Speaker 1: here in Cambridge, Massachusetts, which is where I'm based, not 355 00:20:30,316 --> 00:20:33,356 Speaker 1: at the Broad but in Cambridge, that was proposing, at 356 00:20:33,436 --> 00:20:38,236 Speaker 1: least theoretically, a massive throughput approach where they would bar code, 357 00:20:38,836 --> 00:20:45,036 Speaker 1: using a crisper like DNA technique, bar code samples so 358 00:20:45,076 --> 00:20:48,636 Speaker 1: that they could then run through sequencers hundreds of thousands 359 00:20:48,636 --> 00:20:51,276 Speaker 1: of tests at a single run. That's obviously a very 360 00:20:51,276 --> 00:20:54,676 Speaker 1: different technology, and it's using very different kinds of methods 361 00:20:54,676 --> 00:20:58,036 Speaker 1: than are used in most clinical labs. As someone who 362 00:20:58,196 --> 00:21:00,556 Speaker 1: does it the old fashioned way, as it were, what 363 00:21:00,636 --> 00:21:02,716 Speaker 1: do you think are the odds of success here? I mean, 364 00:21:02,836 --> 00:21:04,756 Speaker 1: it might be worth trying it even if the probability 365 00:21:04,756 --> 00:21:07,036 Speaker 1: of success is very low, because it will be great 366 00:21:07,036 --> 00:21:09,196 Speaker 1: to test so many people so quickly. What are the 367 00:21:09,196 --> 00:21:11,716 Speaker 1: big challenges that that approach faces in your view? Yeah, 368 00:21:11,716 --> 00:21:15,236 Speaker 1: So the scientists that run these approaches are very talented scientists, 369 00:21:15,276 --> 00:21:18,756 Speaker 1: you know, their research based scientists, and I think that 370 00:21:18,796 --> 00:21:23,316 Speaker 1: they will be able to successfully put together a system 371 00:21:23,356 --> 00:21:27,676 Speaker 1: that could theoretically do one hundred thousand samples. Part of 372 00:21:27,716 --> 00:21:31,156 Speaker 1: what differentiates a research test from a clinical test, something 373 00:21:31,156 --> 00:21:33,796 Speaker 1: that's allowed to be used on patients is that you 374 00:21:33,876 --> 00:21:38,036 Speaker 1: have to prove that it works before you can actually 375 00:21:38,356 --> 00:21:40,876 Speaker 1: use it clinically. And part of the challenge of a 376 00:21:40,876 --> 00:21:43,516 Speaker 1: system like this I lives literally having this exact same 377 00:21:43,556 --> 00:21:47,236 Speaker 1: conversation with some researchers at UCLA, is that in order 378 00:21:47,276 --> 00:21:49,956 Speaker 1: to prove that it works on scale, you need to 379 00:21:49,996 --> 00:21:54,956 Speaker 1: test fifty thousand samples one hundred thousand samples. And the 380 00:21:55,036 --> 00:21:57,356 Speaker 1: challenge of doing that is how do you get those 381 00:21:57,396 --> 00:22:01,876 Speaker 1: samples within a research setting under IRB approval and not 382 00:22:02,036 --> 00:22:05,196 Speaker 1: have it take nine months, a year, a year and 383 00:22:05,196 --> 00:22:07,876 Speaker 1: a half, which is typically what these sorts of things 384 00:22:07,876 --> 00:22:11,036 Speaker 1: would take before or you even began to have enough 385 00:22:11,156 --> 00:22:15,476 Speaker 1: data to submit to the FDA to get approval of 386 00:22:15,556 --> 00:22:18,636 Speaker 1: your new technique. And so, while I do think that 387 00:22:18,676 --> 00:22:21,196 Speaker 1: this could work, I don't know if it's going to 388 00:22:21,276 --> 00:22:25,396 Speaker 1: move in a time frame that's going to make it feasible. 389 00:22:26,076 --> 00:22:28,596 Speaker 1: There are other concerns that I have kind of wrapped 390 00:22:28,676 --> 00:22:31,356 Speaker 1: up in this. A lot of the challenges of let's say, 391 00:22:31,796 --> 00:22:34,316 Speaker 1: the paper that you had talked about, it doesn't use 392 00:22:34,716 --> 00:22:39,876 Speaker 1: rtPCR uses LAMP, which is a different nucleic acid amplification 393 00:22:39,956 --> 00:22:44,516 Speaker 1: technology that can have sensitivity issues. This is also part 394 00:22:44,516 --> 00:22:47,436 Speaker 1: of some other challenges when you pool large things together, 395 00:22:47,596 --> 00:22:51,836 Speaker 1: is that on an individual sample basis, sometimes you're just 396 00:22:51,956 --> 00:22:54,716 Speaker 1: not as good as the gold standard. And these would 397 00:22:54,716 --> 00:22:56,916 Speaker 1: be the things that these places would have to prove 398 00:22:56,956 --> 00:23:01,196 Speaker 1: to the FGA before they got approval to do massive testing. 399 00:23:01,836 --> 00:23:04,236 Speaker 1: In addition, you know, while I respect the fact that 400 00:23:04,276 --> 00:23:06,956 Speaker 1: you can run one hundred thousand samples at one time, 401 00:23:07,556 --> 00:23:11,236 Speaker 1: just collecting a hundred thousand samples, getting them sent to 402 00:23:11,316 --> 00:23:14,636 Speaker 1: one area and getting them processed to be able to 403 00:23:14,716 --> 00:23:19,316 Speaker 1: run is a phenomenal challenge that's wrapped up on the 404 00:23:19,356 --> 00:23:22,556 Speaker 1: pre analytical side, or kind of even before the testing begins. 405 00:23:23,156 --> 00:23:26,796 Speaker 1: So I am excited about this because I actually don't 406 00:23:26,836 --> 00:23:29,676 Speaker 1: think this is going to be our last pandemic. There 407 00:23:29,756 --> 00:23:32,716 Speaker 1: isn't anything to suggest it would be. And so if 408 00:23:32,756 --> 00:23:35,476 Speaker 1: we can get things online like this and really start 409 00:23:35,516 --> 00:23:38,596 Speaker 1: thinking about how the country when we need to, could 410 00:23:38,636 --> 00:23:42,236 Speaker 1: pivot to mass scale testing for a virus, that's a 411 00:23:42,276 --> 00:23:44,916 Speaker 1: really good thing to have in our back pocket. Is 412 00:23:44,956 --> 00:23:47,756 Speaker 1: this something that's going to work for COVID nineteen. I 413 00:23:47,756 --> 00:23:49,636 Speaker 1: don't know if the time scale is actually going to 414 00:23:49,716 --> 00:23:53,276 Speaker 1: meet up with the technology. If I could close our 415 00:23:53,276 --> 00:23:56,436 Speaker 1: conversation on a modestly lighter note, but it nevertheless an 416 00:23:56,476 --> 00:24:00,196 Speaker 1: important one. I read that you had said that watching 417 00:24:00,276 --> 00:24:03,476 Speaker 1: Cuba Gooding Junior in the nineteen ninety five film Outbreak 418 00:24:03,876 --> 00:24:06,196 Speaker 1: was one of the things that inspired your career path, 419 00:24:06,476 --> 00:24:07,956 Speaker 1: and of course a lot of us now feel like 420 00:24:07,956 --> 00:24:11,836 Speaker 1: we're living Outbreak the sequel. Yes, what does that feel 421 00:24:11,876 --> 00:24:13,876 Speaker 1: like for you personally to be, you know, on the 422 00:24:13,876 --> 00:24:17,276 Speaker 1: front lines here? It's interesting. So twenty fourteen, we had 423 00:24:17,316 --> 00:24:21,156 Speaker 1: our Ebola crisis in the United States and at UCLA, 424 00:24:21,236 --> 00:24:24,356 Speaker 1: I was part of the ebola treatment team, and so 425 00:24:24,476 --> 00:24:27,276 Speaker 1: in that setting, you know, as an ebola treatment a 426 00:24:27,356 --> 00:24:29,596 Speaker 1: person participating in the treatment of the patient, you have 427 00:24:29,636 --> 00:24:31,956 Speaker 1: to get fully suited up. So if you can imagine 428 00:24:32,036 --> 00:24:34,916 Speaker 1: Cuba getting Junior an outbreak in that yellow suit, that's 429 00:24:34,956 --> 00:24:38,236 Speaker 1: similar to what you wear when you're attempting to discern 430 00:24:38,276 --> 00:24:40,876 Speaker 1: whether or not somebody has ebola. So it was that 431 00:24:40,956 --> 00:24:44,316 Speaker 1: moment I really kind of had my outbreak moment. This 432 00:24:44,356 --> 00:24:47,156 Speaker 1: one I have felt it's a little bit strange because 433 00:24:47,996 --> 00:24:50,996 Speaker 1: until we kind of all moved forward with masking, it 434 00:24:51,076 --> 00:24:55,356 Speaker 1: was a pandemic but everything looked fine, So it was 435 00:24:55,436 --> 00:24:58,276 Speaker 1: kind of different from the outbreak scenario. It was like 436 00:24:58,596 --> 00:25:02,796 Speaker 1: a shift in what I thought a pandemic would look like. 437 00:25:03,396 --> 00:25:05,836 Speaker 1: And that's what I found to be the most surprising 438 00:25:05,836 --> 00:25:08,956 Speaker 1: of this whole thing. Hundreds of thousands to potentially millions 439 00:25:08,996 --> 00:25:12,236 Speaker 1: of people worldwide are going to die of this disease, 440 00:25:12,796 --> 00:25:17,396 Speaker 1: but it's not like running around in the biosafety level 441 00:25:17,436 --> 00:25:21,836 Speaker 1: four suits. All of the movies, TV shows, and so forth, 442 00:25:21,996 --> 00:25:24,516 Speaker 1: none of them has a scene where people say, well, 443 00:25:24,516 --> 00:25:26,516 Speaker 1: we should all suit up. Oh but wait a minute, 444 00:25:26,516 --> 00:25:28,836 Speaker 1: we don't have enough suits. You know, that's not a 445 00:25:28,876 --> 00:25:31,396 Speaker 1: plot detail that they've ever taken advantage of in the past, 446 00:25:31,396 --> 00:25:35,356 Speaker 1: though I suppose we'll see it going forward. Yes, thank you, Ohmi. 447 00:25:35,516 --> 00:25:41,036 Speaker 1: This was extraordinarily clarifying and helpful. I really hugely appreciate 448 00:25:41,116 --> 00:25:45,116 Speaker 1: your step by step patients in explaining what you do 449 00:25:45,516 --> 00:25:47,956 Speaker 1: every day to us. Thank you for doing the work 450 00:25:48,276 --> 00:25:51,236 Speaker 1: that you're doing, and we all appreciate it. Excellent. Thanks 451 00:25:51,236 --> 00:25:54,316 Speaker 1: for having me out. No, I appreciate it. Listening to 452 00:25:54,396 --> 00:25:59,316 Speaker 1: doctor Ohmi Garner. I had moments of optimism because he 453 00:25:59,436 --> 00:26:02,476 Speaker 1: himself said that he thinks we are scaling up our 454 00:26:02,516 --> 00:26:05,596 Speaker 1: capacities in a way that will facilitate a lot more 455 00:26:05,716 --> 00:26:09,716 Speaker 1: testing than we're doing at present. That was the good news. 456 00:26:10,196 --> 00:26:12,876 Speaker 1: On the other hand, Olmi also made it very clear 457 00:26:13,076 --> 00:26:16,356 Speaker 1: that there are significant limits to how many tests we 458 00:26:16,356 --> 00:26:20,036 Speaker 1: can do under current circumstances. We have the shortage of 459 00:26:20,116 --> 00:26:24,156 Speaker 1: chemicals in the existing tests, we have limited capacity, and 460 00:26:24,436 --> 00:26:27,436 Speaker 1: when it comes to antibody testing, we still don't really 461 00:26:27,476 --> 00:26:32,076 Speaker 1: know how well the various tests work. Last, but not least, 462 00:26:32,236 --> 00:26:35,716 Speaker 1: Although Omai thinks that some of the most fascinating experimental 463 00:26:35,756 --> 00:26:39,236 Speaker 1: techniques being proposed to test hundreds of thousands of people 464 00:26:39,276 --> 00:26:41,756 Speaker 1: at the same time have a good shot of working, 465 00:26:42,156 --> 00:26:44,996 Speaker 1: he's concerned that it may not be possible for that 466 00:26:45,116 --> 00:26:47,476 Speaker 1: kind of testing at that kind of scale to be 467 00:26:47,596 --> 00:26:51,236 Speaker 1: ramped up in time to help us address the COVID 468 00:26:51,316 --> 00:26:55,756 Speaker 1: nineteen epidemic as opposed to future epidemics. Above all, a 469 00:26:55,836 --> 00:26:58,236 Speaker 1: doctor Omai Garner is a kind of model of the 470 00:26:58,356 --> 00:27:02,076 Speaker 1: clear speaking, clear thinking scientist who can explain things to 471 00:27:02,196 --> 00:27:05,196 Speaker 1: all of us, and I feel very lucky that he's 472 00:27:05,236 --> 00:27:07,836 Speaker 1: at the helm of an important lab like the one 473 00:27:07,916 --> 00:27:10,556 Speaker 1: at UCLA. Until the next time I speak to you. 474 00:27:11,036 --> 00:27:16,116 Speaker 1: Be careful, be safe, and be well. Deep Background is 475 00:27:16,156 --> 00:27:19,796 Speaker 1: brought to you by Pushkin Industries. Our producer is Lydia Gencott, 476 00:27:20,076 --> 00:27:23,716 Speaker 1: with research help from Zooe Wynn. Mastering is by Jason 477 00:27:23,756 --> 00:27:27,756 Speaker 1: Gambrel and Martin Gonzalez. Our showrunner is Sophie mckibbon. Our 478 00:27:27,836 --> 00:27:30,916 Speaker 1: theme music is composed by Luis GERA special thanks to 479 00:27:30,916 --> 00:27:34,516 Speaker 1: the Pushkin Brass, Malcolm Gladwell, Jacob Weisberg, and Mia Lobel. 480 00:27:34,916 --> 00:27:37,796 Speaker 1: I'm Noah feld I also write a regular column for 481 00:27:37,876 --> 00:27:40,876 Speaker 1: Bloomberg Opinion, which you can find at Bloomberg dot com 482 00:27:40,876 --> 00:27:45,196 Speaker 1: slash feld To discover Bloomberg's original slate of podcasts, go 483 00:27:45,276 --> 00:27:48,996 Speaker 1: to Bloomberg dot com slash Podcasts. You can follow me 484 00:27:48,996 --> 00:27:53,036 Speaker 1: on Twitter at Noah R. Feldman. This is Deep Background.