9:59:59.000,9:59:59.000 So how are we going to beat[br]this novel coronavirus? 9:59:59.000,9:59:59.000 By using our best tools: 9:59:59.000,9:59:59.000 our science and our technology. 9:59:59.000,9:59:59.000 In my lab, we're using[br]the tools of artificial intelligence 9:59:59.000,9:59:59.000 and synthetic biology 9:59:59.000,9:59:59.000 to speed up the fight[br]against this pandemic. 9:59:59.000,9:59:59.000 Our work was originally designed 9:59:59.000,9:59:59.000 to tackle the antibiotic[br]resistance crisis. 9:59:59.000,9:59:59.000 Our project seeks to harness[br]the power of machine learning 9:59:59.000,9:59:59.000 to replenish our antibiotic arsenal 9:59:59.000,9:59:59.000 and avoid a globally devastating[br]post-antibiotic era. 9:59:59.000,9:59:59.000 Importantly, the same technology[br]can be used to search 9:59:59.000,9:59:59.000 for antiviral compounds 9:59:59.000,9:59:59.000 that could help us fight[br]the current pandemic. 9:59:59.000,9:59:59.000 Machine learning is turning[br]the traditional model of drug discovery 9:59:59.000,9:59:59.000 on its head. 9:59:59.000,9:59:59.000 With this approach, 9:59:59.000,9:59:59.000 instead of painstakingly testing[br]thousands of existing molecules 9:59:59.000,9:59:59.000 one by one in a lab[br]for their effectiveness, 9:59:59.000,9:59:59.000 we can train a computer 9:59:59.000,9:59:59.000 to explore the exponentially larger space 9:59:59.000,9:59:59.000 of essentially all possible molecules[br]that could be synthesized, 9:59:59.000,9:59:59.000 and thus instead of looking[br]for a needle in a haystack, 9:59:59.000,9:59:59.000 we can use the giant magnet[br]of computing power 9:59:59.000,9:59:59.000 to find many needles[br]in multiple haystacks simultaneously. 9:59:59.000,9:59:59.000 We've already had some early success. 9:59:59.000,9:59:59.000 Recently, we used machine learning 9:59:59.000,9:59:59.000 to discover new antibiotics[br]that can help us fight off 9:59:59.000,9:59:59.000 the bacterial infections that can occur[br]alongside SARS-CoV-2 infections. 9:59:59.000,9:59:59.000 Two months ago, TED's Audacious Project 9:59:59.000,9:59:59.000 approved funding for us[br]to massively scale up our work 9:59:59.000,9:59:59.000 with the goal of discovering[br]seven new classes of antibiotics 9:59:59.000,9:59:59.000 against seven of the world's[br]deadly bacterial pathogens 9:59:59.000,9:59:59.000 over the next seven years. 9:59:59.000,9:59:59.000 For context, 9:59:59.000,9:59:59.000 the number of new class of antibiotics 9:59:59.000,9:59:59.000 that have been discovered[br]over the last three decades is zero. 9:59:59.000,9:59:59.000 While the quest for new antibiotics[br]is for our medium-term future, 9:59:59.000,9:59:59.000 the novel coronavirus[br]poses an immediate deadly threat, 9:59:59.000,9:59:59.000 and I'm excited to share that we think[br]we can use the same technology 9:59:59.000,9:59:59.000 to search for therapeutics[br]to fight this virus. 9:59:59.000,9:59:59.000 So how are we going to do it? 9:59:59.000,9:59:59.000 Well, we're creating[br]a compound training library, 9:59:59.000,9:59:59.000 and with collaborators[br]applying these molecules 9:59:59.000,9:59:59.000 to SARS-CoV-2-infected cells 9:59:59.000,9:59:59.000 to see which of them exhibit[br]effective activity. 9:59:59.000,9:59:59.000 These data will be use to train[br]a machine learning model 9:59:59.000,9:59:59.000 that will be applied to a [?][br]library of over a billion molecules 9:59:59.000,9:59:59.000 to search for potential[br]novel antiviral compounds. 9:59:59.000,9:59:59.000 We will synthesize and test[br]the top predictions 9:59:59.000,9:59:59.000 and advance the most promising[br]candidates into the clinic. 9:59:59.000,9:59:59.000 Sound too good to be true? 9:59:59.000,9:59:59.000 Well, it shouldn't. 9:59:59.000,9:59:59.000 The Antibiotics AI Project is founded[br]on our proof of concept research 9:59:59.000,9:59:59.000 that led to the discovery[br]of a novel broad spectrum antibiotic 9:59:59.000,9:59:59.000 called Halocin. 9:59:59.000,9:59:59.000 Halocin has potent antibacterial activity 9:59:59.000,9:59:59.000 against almost all antibiotic-resistant[br]bacterial pathogens, 9:59:59.000,9:59:59.000 including untreatable[br]pan-resistant infections. 9:59:59.000,9:59:59.000 Importantly, in contrast[br]to current antibiotics, 9:59:59.000,9:59:59.000 the frequency at which bacteria[br]develop resistance against Halocin 9:59:59.000,9:59:59.000 is remarkably low. 9:59:59.000,9:59:59.000 We tested the ability of bacteria[br]to evolve resistance against Halocin 9:59:59.000,9:59:59.000 as well as Cipro in the lab. 9:59:59.000,9:59:59.000 In the case of Cipro, 9:59:59.000,9:59:59.000 after just one day, we saw resistance. 9:59:59.000,9:59:59.000 In the case of Halocin, 9:59:59.000,9:59:59.000 after one day we didn't[br]see any resistance. 9:59:59.000,9:59:59.000 Amazingly, after even 30 days, 9:59:59.000,9:59:59.000 we didn't see any[br]resistance against Halocin. 9:59:59.000,9:59:59.000 In this pilot project, we first tested[br]roughly 2,500 compounds against E. coli. 9:59:59.000,9:59:59.000 This training set included[br]known antibiotics, 9:59:59.000,9:59:59.000 such as Cipro and penicillin, 9:59:59.000,9:59:59.000 as well as many drugs[br]that are not antibiotics. 9:59:59.000,9:59:59.000 These data we used to train a model 9:59:59.000,9:59:59.000 to learn molecular features[br]associated with antibacterial activity. 9:59:59.000,9:59:59.000 We then applied this model[br]to a drug repurposing library 9:59:59.000,9:59:59.000 consisting of several thousand molecules, 9:59:59.000,9:59:59.000 and asked the model to identify molecules 9:59:59.000,9:59:59.000 that are predicted[br]to have antibacterial properties 9:59:59.000,9:59:59.000 but don't look like existing antibiotics. 9:59:59.000,9:59:59.000 Interestingly, only one molecule[br]in that library fit these criteria, 9:59:59.000,9:59:59.000 and that molecule[br]turned out to be Halocin. 9:59:59.000,9:59:59.000 Given that Halocin does not look[br]like any existing antibiotic, 9:59:59.000,9:59:59.000 it would have been impossible for a human,[br]including an antibiotic expert, 9:59:59.000,9:59:59.000 to identify Halocin in this manner. 9:59:59.000,9:59:59.000 Imagine now what we could do[br]with this technology 9:59:59.000,9:59:59.000 against SARS-CoV-2. 9:59:59.000,9:59:59.000 And that's not all. 9:59:59.000,9:59:59.000 We're also using the tools[br]of synthetic biology, 9:59:59.000,9:59:59.000 tinkering with DNA and other cellular machinery, to serve human purposes like combating COVID-19 [??] we are working to develop a protective mask that can also serve as a rapid diagnostic test. How does that work? Well, we recently showed that you can take the cellular machinery out of a living cell and freeze-dry it along with RNA sensors onto paper in order to create low-cost diagnostics for Ebola and Zika. The sensors are activated when they're rehydrated by a patient sample that could consist of blood or saliva, for example. It turns out this technology is not limited to paper and can be applied to other materials, including cloth. For the COVID-19 pandemic, we're designing RNA sensors to detect the virus and freeze-drying these along with the needed cellular machinery into the fabric of a face mask, where the simple act of breathing, along with the water vapor that comes with it, can activate the test. Now, if the patient is infected with SARS-CoV-2, the mask will produce a fluorescent signal that can be detected by a simple, inexpensive handheld device. In one or two hours, a patient could those be diagnosed safely, remotely and accurately. We're also using synthetic biology to design a candidate vaccine for COVID-19. We are repurposing the BCG vaccine, which has been used against TB for almost a century. It's a live attenuated vaccine, and we're engineering it to express SARS-CoV-2 antigens, which should trigger the production of protective antibodies by the immune system. Importantly, BCG is massively scalable and has a safety profile that's among the best of any reported vaccine. With the tools of synthetic biology and artificial intelligence, we can win the fight against this novel coronavirus. This work is in its very early stages, but the promise is real. Science and technology can give us an important advantage in the battle of human wits versus the genes of superbugs, a battle we can win. Thank you.