WEBVTT 00:00:00.602 --> 00:00:04.160 The first patient to ever be treated with an antibiotic 00:00:04.160 --> 00:00:05.693 was a policeman in Oxford. 00:00:05.693 --> 00:00:07.800 On his day off from work, 00:00:07.800 --> 00:00:11.173 he was scratched by a rose thorn while working in the garden. 00:00:11.173 --> 00:00:14.848 That small scratch became infected. 00:00:14.848 --> 00:00:17.163 Over the next few days, his head was swollen 00:00:17.163 --> 00:00:18.884 with abscesses, 00:00:18.884 --> 00:00:21.167 and in fact his eye was so infected 00:00:21.167 --> 00:00:23.070 that they had to take it out, 00:00:23.070 --> 00:00:26.050 and by February of 1941, 00:00:26.050 --> 00:00:28.487 this poor man was on the verge of dying. 00:00:28.487 --> 00:00:31.685 He was at Radcliffe Infirmary in Oxford, 00:00:31.685 --> 00:00:33.991 and fortunately for him, 00:00:33.991 --> 00:00:35.041 a small team of doctors 00:00:35.041 --> 00:00:36.930 led by a Dr. Howard Florey 00:00:36.930 --> 00:00:38.997 had managed to synthesize 00:00:38.997 --> 00:00:41.820 a very small amount of penicillin, 00:00:41.820 --> 00:00:43.901 a drug that had been discovered 00:00:43.901 --> 00:00:46.223 12 years before by Alexander Fleming 00:00:46.223 --> 00:00:49.930 but had never actually been used to treat a human, 00:00:49.930 --> 00:00:52.340 and indeed no one even knew if the drug would work, 00:00:52.340 --> 00:00:55.980 if it was full of impurities that would kill the patient, 00:00:55.980 --> 00:00:57.894 but Florey and his team figured 00:00:57.894 --> 00:00:59.616 if they had to use it, they might as well use it 00:00:59.616 --> 00:01:02.181 on someone who was going to die anyway. NOTE Paragraph 00:01:02.181 --> 00:01:05.836 So they gave Albert Alexander, 00:01:05.836 --> 00:01:08.715 this Oxford policeman, the drug, 00:01:08.715 --> 00:01:11.132 and within 24 hours, 00:01:11.132 --> 00:01:13.394 he started getting better. 00:01:13.394 --> 00:01:17.370 His fever went down, his appetite came back. 00:01:17.370 --> 00:01:19.683 Second day, he was doing much better. 00:01:19.683 --> 00:01:21.921 They were starting to run out of penicillin, 00:01:21.921 --> 00:01:23.983 so what they would do was run with his urine 00:01:23.983 --> 00:01:26.833 across the road to re-synthesize the penicillin from his urine 00:01:26.833 --> 00:01:28.768 and give it back to him, 00:01:28.768 --> 00:01:30.016 and that worked. 00:01:30.016 --> 00:01:32.496 Day four, well on the way to recovery. 00:01:32.496 --> 00:01:34.134 This was a miracle. 00:01:34.134 --> 00:01:38.370 Day five, they ran out of penicillin, 00:01:38.370 --> 00:01:40.637 and the poor man died. NOTE Paragraph 00:01:40.637 --> 00:01:43.350 So that story didn't end that well, 00:01:43.350 --> 00:01:47.700 but fortunately for millions of other people, 00:01:47.700 --> 00:01:50.706 like this child who was treated again in the early 1940s, 00:01:50.706 --> 00:01:53.740 who was again dying of a sepsis, 00:01:53.740 --> 00:01:56.890 and within just six days, you can see, 00:01:56.890 --> 00:02:00.243 recovered thanks to this wonder drug, penicillin. 00:02:00.243 --> 00:02:02.201 Millions have lived, 00:02:02.201 --> 00:02:05.785 and global health has been transformed. 00:02:05.785 --> 00:02:08.578 Now, antibiotics have been used 00:02:08.578 --> 00:02:11.705 for patients like this, 00:02:11.705 --> 00:02:13.842 but they've also been used rather frivolously 00:02:13.842 --> 00:02:15.586 in some instances, 00:02:15.586 --> 00:02:17.949 for treating someone with just a cold or the flu, 00:02:17.949 --> 00:02:20.423 which they might not have responded to an antibiotic, 00:02:20.423 --> 00:02:24.161 and they've also been used in large quantities 00:02:24.161 --> 00:02:27.803 sub-therapeutically, which means in small concentrations, 00:02:27.803 --> 00:02:30.986 to make chicken and hogs grow faster. 00:02:30.986 --> 00:02:34.552 Just to save a few pennies on the price of meat, 00:02:34.552 --> 00:02:37.252 we've spent a lot of antibiotics on animals, 00:02:37.252 --> 00:02:39.614 not for treatment, not for sick animals, 00:02:39.614 --> 00:02:42.730 but primarily for growth promotion. NOTE Paragraph 00:02:42.730 --> 00:02:45.587 Now, what did that lead us to? 00:02:45.587 --> 00:02:48.298 Basically, the massive use of antibiotics 00:02:48.298 --> 00:02:49.783 around the world 00:02:49.783 --> 00:02:53.587 has imposed such large selection pressure on bacteria 00:02:53.587 --> 00:02:56.240 that resistance is now a problem, 00:02:56.240 --> 00:02:58.010 because we've now selected for just 00:02:58.010 --> 00:02:59.985 the resistant bacteria. NOTE Paragraph 00:02:59.985 --> 00:03:02.825 And I'm sure you've all read about this in the newspapers, 00:03:02.825 --> 00:03:04.629 you've seen this in every magazine 00:03:04.629 --> 00:03:06.528 that you come across, 00:03:06.528 --> 00:03:08.328 but I really want you to appreciate 00:03:08.328 --> 00:03:10.499 the significance of this problem. 00:03:10.499 --> 00:03:11.950 This is serious. 00:03:11.950 --> 00:03:16.766 The next slide I'm about to show you is of carbapenem resistance in acinetobacter. 00:03:16.766 --> 00:03:19.154 Acinetobacter is a nasty hospital bug, 00:03:19.154 --> 00:03:20.487 and carbapenem is pretty much 00:03:20.487 --> 00:03:22.265 the strongest class of antibiotics 00:03:22.265 --> 00:03:24.721 that we can throw at this bug. 00:03:24.721 --> 00:03:27.990 And you can see in 1999 00:03:27.990 --> 00:03:30.185 this is the pattern of resistance, 00:03:30.185 --> 00:03:33.218 mostly under about 10 percent across the United States. 00:03:33.218 --> 00:03:37.215 Now watch what happens when we play the video. NOTE Paragraph 00:03:46.461 --> 00:03:48.516 So I don't know where you live, 00:03:48.516 --> 00:03:51.418 but wherever it is, it certainly is a lot worse now 00:03:51.418 --> 00:03:53.915 than it was in 1999, 00:03:53.915 --> 00:03:57.886 and that is the problem of antibiotic resistance. 00:03:57.886 --> 00:03:59.573 It's a global issue 00:03:59.573 --> 00:04:02.001 affecting both rich and poor countries, 00:04:02.001 --> 00:04:04.242 and at the heart of it, you might say, well, 00:04:04.242 --> 00:04:06.170 isn't this really just a medical issue? 00:04:06.170 --> 00:04:08.731 If we taught doctors how not to use antibiotics as much, 00:04:08.731 --> 00:04:11.676 if we taught patients how not to demand antibiotics, 00:04:11.676 --> 00:04:13.131 perhaps this really wouldn't be an issue, 00:04:13.131 --> 00:04:15.120 and maybe the pharmaceutical companies 00:04:15.120 --> 00:04:16.875 should be working harder to develop 00:04:16.875 --> 00:04:18.511 more antibiotics. 00:04:18.511 --> 00:04:21.890 Now, it turns out that there's something fundamental about antibiotics 00:04:21.890 --> 00:04:23.673 which makes it different from other drugs, 00:04:23.673 --> 00:04:25.694 which is that if I misuse antibiotics 00:04:25.694 --> 00:04:27.431 or I use antibiotics, 00:04:27.431 --> 00:04:31.291 not only am I affected but others are affected as well, 00:04:31.291 --> 00:04:33.629 in the same way as if I choose to drive to work 00:04:33.629 --> 00:04:36.268 or take a plane to go somewhere, 00:04:36.268 --> 00:04:38.242 that the costs I impose on others 00:04:38.242 --> 00:04:40.682 through global climate change go everywhere, 00:04:40.682 --> 00:04:43.455 and I don't necessarily take these costs into consideration. 00:04:43.455 --> 00:04:46.334 This is what economists might call a problem of the commons, 00:04:46.334 --> 00:04:48.314 and the problem of the commons is exactly 00:04:48.314 --> 00:04:50.739 what we face in the case of antibiotics as well: 00:04:50.739 --> 00:04:52.889 that we don't consider — 00:04:52.889 --> 00:04:55.891 and we, including individuals, patients, 00:04:55.891 --> 00:04:59.050 hospitals, entire health systems — 00:04:59.050 --> 00:05:01.198 do not consider the costs that they impose on others 00:05:01.198 --> 00:05:03.554 by the way antibiotics are actually used. NOTE Paragraph 00:05:03.554 --> 00:05:05.959 Now, that's a problem that's similar 00:05:05.959 --> 00:05:07.941 to another area that we all know about, 00:05:07.941 --> 00:05:09.870 which is of fuel use and energy, 00:05:09.870 --> 00:05:11.369 and of course energy use 00:05:11.369 --> 00:05:14.451 both depletes energy as well as 00:05:14.451 --> 00:05:17.713 leads to local pollution and climate change. 00:05:17.713 --> 00:05:19.523 And typically, in the case of energy, 00:05:19.523 --> 00:05:21.831 there are two ways in which you can deal with the problem. 00:05:21.831 --> 00:05:25.576 One is, we can make better use of the oil that we have, 00:05:25.576 --> 00:05:27.691 and that's analogous to making better use 00:05:27.691 --> 00:05:29.239 of existing antibiotics, 00:05:29.239 --> 00:05:30.930 and we can do this in a number of ways 00:05:30.930 --> 00:05:33.160 that we'll talk about in a second, 00:05:33.160 --> 00:05:36.847 but the other option is the "drill, baby, drill" option, 00:05:36.847 --> 00:05:41.038 which in the case of antibiotics is to go find new antibiotics. NOTE Paragraph 00:05:41.050 --> 00:05:43.100 Now, these are not separate. 00:05:43.100 --> 00:05:46.522 They're related, because if we invest heavily 00:05:46.522 --> 00:05:48.806 in new oil wells, 00:05:48.806 --> 00:05:51.760 we reduce the incentives for conservation of oil 00:05:51.760 --> 00:05:54.286 in the same way that's going to happen for antibiotics. 00:05:54.286 --> 00:05:56.454 The reverse is also going to happen, which is that 00:05:56.454 --> 00:05:58.792 if we use our antibiotics appropriately, 00:05:58.792 --> 00:06:01.573 we don't necessarily have to make the investments 00:06:01.573 --> 00:06:03.750 in new drug development. NOTE Paragraph 00:06:03.750 --> 00:06:06.466 And if you thought that these two were entirely, 00:06:06.466 --> 00:06:08.288 fully balanced between these two options, 00:06:08.288 --> 00:06:10.471 you might consider the fact that 00:06:10.471 --> 00:06:12.743 this is really a game that we're playing. 00:06:12.743 --> 00:06:15.184 The game is really one of coevolution, 00:06:15.184 --> 00:06:18.116 and coevolution is, in this particular picture, 00:06:18.116 --> 00:06:20.472 between cheetahs and gazelles. 00:06:20.472 --> 00:06:22.090 Cheetahs have evolved to run faster, 00:06:22.090 --> 00:06:23.667 because if they didn't run faster, 00:06:23.667 --> 00:06:25.613 they wouldn't get any lunch. 00:06:25.613 --> 00:06:28.300 Gazelles have evolved to run faster because 00:06:28.300 --> 00:06:31.509 if they don't run faster, they would be lunch. 00:06:31.509 --> 00:06:34.395 Now, this is the game we're playing against the bacteria, 00:06:34.395 --> 00:06:36.452 except we're not the cheetahs, 00:06:36.452 --> 00:06:37.929 we're the gazelles, 00:06:37.929 --> 00:06:40.716 and the bacteria would, 00:06:40.716 --> 00:06:42.549 just in the course of this little talk, 00:06:42.549 --> 00:06:43.975 would have had kids and grandkids 00:06:43.975 --> 00:06:46.360 and figured out how to be resistant 00:06:46.360 --> 00:06:48.834 just by selection and trial and error, 00:06:48.834 --> 00:06:50.746 trying it over and over again. 00:06:50.746 --> 00:06:54.518 Whereas how do we stay ahead of the bacteria? 00:06:54.518 --> 00:06:56.572 We have drug discovery processes, 00:06:56.572 --> 00:06:58.202 screening molecules, 00:06:58.202 --> 00:06:59.930 we have clinical trials, 00:06:59.930 --> 00:07:02.078 and then, when we think we have a drug, 00:07:02.078 --> 00:07:05.823 then we have the FDA regulatory process. 00:07:05.823 --> 00:07:08.001 And once we go through all of that, 00:07:08.001 --> 00:07:10.266 then we try to stay one step ahead 00:07:10.266 --> 00:07:12.562 of the bacteria. NOTE Paragraph 00:07:12.562 --> 00:07:15.339 Now, this is clearly not a game that can be sustained, 00:07:15.339 --> 00:07:16.476 or one that we can win 00:07:16.476 --> 00:07:18.313 by simply innovating to stay ahead. 00:07:18.313 --> 00:07:21.618 We've got to slow the pace of coevolution down, 00:07:21.618 --> 00:07:25.300 and there are ideas that we can borrow from energy 00:07:25.300 --> 00:07:27.070 that are helpful in thinking about 00:07:27.070 --> 00:07:28.607 how we might want to do this in the case 00:07:28.607 --> 00:07:30.153 of antibiotics as well. 00:07:30.153 --> 00:07:32.393 Now, if you think about how we deal with 00:07:32.393 --> 00:07:33.816 energy pricing, for instance, 00:07:33.816 --> 00:07:35.665 we consider emissions taxes, 00:07:35.665 --> 00:07:38.249 which means we're imposing the costs of pollution 00:07:38.249 --> 00:07:41.080 on people who actually use that energy. 00:07:41.080 --> 00:07:44.060 We might consider doing that for antibiotics as well, 00:07:44.060 --> 00:07:46.771 and perhaps that would make sure that antibiotics 00:07:46.771 --> 00:07:49.172 actually get used appropriately. 00:07:49.172 --> 00:07:51.200 There are clean energy subsidies, 00:07:51.200 --> 00:07:54.255 which are to switch to fuels which don't pollute as much 00:07:54.255 --> 00:07:57.100 or perhaps don't need fossil fuels. 00:07:57.100 --> 00:07:59.960 Now, the analogy here is, perhaps we need 00:07:59.960 --> 00:08:02.220 to move away from using antibiotics, 00:08:02.220 --> 00:08:05.936 and if you think about it, what are good substitutes for antibiotics? 00:08:05.936 --> 00:08:08.100 Well, turns out that anything that reduces 00:08:08.100 --> 00:08:10.343 the need for the antibiotic would really work, 00:08:10.343 --> 00:08:13.485 so that could include improving hospital infection control 00:08:13.485 --> 00:08:16.380 or vaccinating people, 00:08:16.380 --> 00:08:18.677 particularly against the seasonal influenza. 00:08:18.677 --> 00:08:21.208 And the seasonal flu is probably 00:08:21.208 --> 00:08:24.212 the biggest driver of antibiotic use, 00:08:24.212 --> 00:08:27.131 both in this country as well as in many other countries, 00:08:27.131 --> 00:08:29.151 and that could really help. 00:08:29.151 --> 00:08:33.254 A third option might include something like tradeable permits. 00:08:33.254 --> 00:08:37.500 And these seem like faraway scenarios, 00:08:37.500 --> 00:08:39.927 but if you consider the fact that we might not 00:08:39.927 --> 00:08:43.310 have antibiotics for many people who have infections, 00:08:43.310 --> 00:08:45.547 we might consider the fact that we might 00:08:45.547 --> 00:08:47.858 want to allocate who actually gets to use 00:08:47.858 --> 00:08:50.572 some of these antibiotics over others, 00:08:50.572 --> 00:08:53.898 and some of these might have to be on the basis of clinical need, 00:08:53.898 --> 00:08:55.833 but also on the basis of pricing. 00:08:55.833 --> 00:08:57.743 And certainly consumer education works. 00:08:57.743 --> 00:09:00.344 Very often, people overuse antibiotics 00:09:00.344 --> 00:09:02.621 or prescribe too much without necessarily 00:09:02.621 --> 00:09:04.227 knowing that they do so, 00:09:04.227 --> 00:09:05.658 and feedback mechanisms 00:09:05.658 --> 00:09:07.560 have been found to be useful, 00:09:07.560 --> 00:09:09.489 both on energy — 00:09:09.489 --> 00:09:11.029 When you tell someone that they're using 00:09:11.029 --> 00:09:12.946 a lot of energy during peak hour, 00:09:12.946 --> 00:09:14.416 they tend to cut back, 00:09:14.416 --> 00:09:16.183 and the same sort of example has been performed 00:09:16.183 --> 00:09:17.993 even in the case of antibiotics. 00:09:17.993 --> 00:09:19.974 A hospital in St. Louis basically would put up 00:09:19.974 --> 00:09:24.166 on a chart the names of surgeons 00:09:24.166 --> 00:09:26.385 in the ordering of how much antibiotics they'd used 00:09:26.385 --> 00:09:28.329 in the previous month, 00:09:28.329 --> 00:09:30.671 and this was purely an informational feedback, 00:09:30.671 --> 00:09:31.854 there was no shaming, 00:09:31.854 --> 00:09:33.989 but essentially that provided some information back 00:09:33.989 --> 00:09:35.943 to surgeons that maybe they could rethink 00:09:35.943 --> 00:09:38.172 how they were using antibiotics. NOTE Paragraph 00:09:38.172 --> 00:09:40.186 Now, there's a lot that can be done 00:09:40.186 --> 00:09:42.335 on the supply side as well. 00:09:42.335 --> 00:09:44.112 If you look at the price of penicillin, 00:09:44.112 --> 00:09:45.763 the cost per day is about 10 cents. 00:09:45.763 --> 00:09:47.521 It's a fairly cheap drug. 00:09:47.521 --> 00:09:49.658 If you take drugs that have been introduced since then — 00:09:49.658 --> 00:09:52.302 linezolid or daptomycin — 00:09:52.302 --> 00:09:54.180 those are significantly more expensive, 00:09:54.180 --> 00:09:59.631 so to a world that has been used to paying 10 cents a day for antibiotics, 00:09:59.633 --> 00:10:02.163 the idea of paying 180 dollars per day 00:10:02.163 --> 00:10:03.730 seems like a lot. 00:10:03.730 --> 00:10:05.717 But what is that really telling us? 00:10:05.717 --> 00:10:07.682 That price is telling us 00:10:07.682 --> 00:10:09.580 that we should no longer 00:10:09.580 --> 00:10:13.697 take cheap, effective antibiotics as a given 00:10:13.697 --> 00:10:15.464 into the foreseeable future, 00:10:15.464 --> 00:10:17.994 and that price is a signal to us 00:10:17.994 --> 00:10:19.603 that perhaps we need to be paying 00:10:19.603 --> 00:10:22.156 much more attention to conservation. 00:10:22.156 --> 00:10:24.860 That price is also a signal 00:10:24.860 --> 00:10:27.735 that maybe we need to start looking at other technologies, 00:10:27.735 --> 00:10:30.387 in the same way that gasoline prices are a signal 00:10:30.387 --> 00:10:32.977 and an impetus, to, say, 00:10:32.977 --> 00:10:34.845 the development of electric cars. 00:10:34.845 --> 00:10:36.622 Prices are important signals 00:10:36.622 --> 00:10:38.208 and we need to pay attention, 00:10:38.208 --> 00:10:40.660 but we also need to consider the fact that 00:10:40.660 --> 00:10:44.912 although these high prices seem unusual for antibiotics, 00:10:44.912 --> 00:10:47.151 they're nothing compared to the price per day 00:10:47.151 --> 00:10:48.535 of some cancer drugs, 00:10:48.535 --> 00:10:51.905 which might save a patient's life only for a few months or perhaps a year, 00:10:51.905 --> 00:10:53.675 whereas antibiotics would potentially 00:10:53.675 --> 00:10:55.501 save a patient's life forever. 00:10:55.501 --> 00:10:56.820 So this is going to involve 00:10:56.820 --> 00:10:58.782 a whole new paradigm shift, 00:10:58.782 --> 00:11:00.638 and it's also a scary shift because 00:11:00.638 --> 00:11:02.967 in many parts of this country, 00:11:02.967 --> 00:11:04.711 in many parts of the world, 00:11:04.711 --> 00:11:06.780 the idea of paying 200 dollars 00:11:06.780 --> 00:11:09.671 for a day of antibiotic treatment 00:11:09.671 --> 00:11:12.213 is simply unimaginable. 00:11:12.213 --> 00:11:13.947 So we need to think about that. NOTE Paragraph 00:11:13.947 --> 00:11:15.760 Now, there are backstop options, 00:11:15.760 --> 00:11:18.436 which is other alternative technologies 00:11:18.436 --> 00:11:19.630 that people are working on. 00:11:19.630 --> 00:11:22.282 It includes bacteriophages, probiotics, 00:11:22.282 --> 00:11:26.330 quorum sensing, synbiotics. NOTE Paragraph 00:11:26.330 --> 00:11:29.369 Now, all of these are useful avenues to pursue, 00:11:29.369 --> 00:11:31.979 and they will become even more lucrative 00:11:31.979 --> 00:11:35.060 when the price of new antibiotics starts going higher, 00:11:35.060 --> 00:11:37.957 and we've seen that the market does actually respond, 00:11:37.957 --> 00:11:39.965 and the government is now considering 00:11:39.965 --> 00:11:43.732 ways of subsidizing new antibiotics and development. 00:11:43.732 --> 00:11:45.455 But there are challenges here. 00:11:45.455 --> 00:11:47.030 We don't want to just throw money at a problem. 00:11:47.030 --> 00:11:48.549 What we want to be able to do 00:11:48.549 --> 00:11:50.828 is invest in new antibiotics 00:11:50.828 --> 00:11:53.804 in ways that actually encourage 00:11:53.804 --> 00:11:56.824 appropriate use and sales of those antibiotics, 00:11:56.824 --> 00:11:59.287 and that really is the challenge here. NOTE Paragraph 00:11:59.287 --> 00:12:01.616 Now, going back to these technologies, 00:12:01.616 --> 00:12:03.979 you all remember the line from that famous 00:12:03.979 --> 00:12:06.205 dinosaur film, "Nature will find a way." 00:12:06.205 --> 00:12:09.524 So it's not as if these are permanent solutions. 00:12:09.524 --> 00:12:13.610 We really have to remember that, whatever the technology might be, 00:12:13.610 --> 00:12:16.486 that nature will find some way to work around it. NOTE Paragraph 00:12:16.486 --> 00:12:18.557 You might think, well, this is just a problem 00:12:18.557 --> 00:12:21.301 just with antibiotics and with bacteria, 00:12:21.301 --> 00:12:23.247 but it turns out that we have the exact same 00:12:23.247 --> 00:12:25.981 identical problem in many other fields as well, 00:12:25.981 --> 00:12:28.933 with multidrug-resistant tuberculosis, 00:12:28.933 --> 00:12:32.495 which is a serious problem in India and South Africa. 00:12:32.495 --> 00:12:34.282 Thousands of patients are dying because 00:12:34.282 --> 00:12:36.116 the second-line drugs are so expensive, 00:12:36.116 --> 00:12:38.343 and in some instances, even those don't work 00:12:38.343 --> 00:12:40.413 and you have XDR TB. 00:12:40.413 --> 00:12:42.224 Viruses are becoming resistant. 00:12:42.224 --> 00:12:45.390 Agricultural pests. Malaria parasites. 00:12:45.390 --> 00:12:47.173 Right now, much of the world depends on 00:12:47.173 --> 00:12:50.870 one drug, artemisinin drugs, 00:12:50.870 --> 00:12:52.826 essentially to treat malaria. 00:12:52.826 --> 00:12:55.413 Resistance to artemisinin has already emerged, 00:12:55.413 --> 00:12:57.767 and if this were to become widespread, 00:12:57.767 --> 00:12:59.115 that puts at risk 00:12:59.115 --> 00:13:02.006 the single drug that we have to treat malaria around the world 00:13:02.006 --> 00:13:05.220 in a way that's currently safe and efficacious. 00:13:05.220 --> 00:13:07.018 Mosquitos develop resistance. 00:13:07.018 --> 00:13:09.255 If you have kids, you probably know about head lice, 00:13:09.255 --> 00:13:10.968 and if you're from New York City, 00:13:10.968 --> 00:13:13.701 I understand that the specialty there is bedbugs. 00:13:13.701 --> 00:13:15.956 So those are also resistant. 00:13:15.956 --> 00:13:18.835 And we have to bring an example from across the pond. 00:13:18.835 --> 00:13:21.190 Turns out that rats are also resistant to poisons. NOTE Paragraph 00:13:21.190 --> 00:13:23.891 Now, what's common to all of these things is 00:13:23.891 --> 00:13:26.597 the idea that we've had these technologies 00:13:26.597 --> 00:13:31.218 to control nature only for the last 70, 80 or 100 years 00:13:31.218 --> 00:13:34.246 and essentially in a blink, 00:13:34.246 --> 00:13:36.797 we have squandered our ability to control, 00:13:36.797 --> 00:13:39.288 because we have not recognized 00:13:39.288 --> 00:13:42.100 that natural selection and evolution was going to find 00:13:42.100 --> 00:13:43.274 a way to get back, 00:13:43.274 --> 00:13:45.323 and we need to completely rethink 00:13:45.323 --> 00:13:47.666 how we're going to use 00:13:47.666 --> 00:13:50.760 measures to control biological organisms, 00:13:50.760 --> 00:13:54.224 and rethink how we incentivize 00:13:54.224 --> 00:13:56.450 the development, introduction, 00:13:56.450 --> 00:13:59.118 in the case of antibiotics prescription, 00:13:59.118 --> 00:14:02.890 and use of these valuable resources. 00:14:02.890 --> 00:14:05.270 And we really now need to start thinking about them 00:14:05.270 --> 00:14:07.228 as natural resources. 00:14:07.228 --> 00:14:09.466 And so we stand at a crossroads. 00:14:09.466 --> 00:14:12.625 An option is to go through that rethinking 00:14:12.625 --> 00:14:14.438 and carefully consider incentives 00:14:14.438 --> 00:14:16.992 to change how we do business. 00:14:16.992 --> 00:14:19.253 The alternative is 00:14:19.253 --> 00:14:22.336 a world in which even a blade of grass 00:14:22.336 --> 00:14:24.765 is a potentially lethal weapon. NOTE Paragraph 00:14:24.765 --> 00:14:26.565 Thank you. NOTE Paragraph 00:14:26.565 --> 00:14:29.300 (Applause)