1 00:00:00,160 --> 00:00:04,160 Speaker 1: This is Bloomberg Business Week with Carol Masser and Bloomberg 2 00:00:04,240 --> 00:00:08,000 Speaker 1: Quick Takes Tim Stinovic from Bloomberg Radio. But last year 3 00:00:08,080 --> 00:00:09,800 Speaker 1: McKinsey came out with a report and they noted that 4 00:00:09,800 --> 00:00:12,799 Speaker 1: the bio economy could have a directing economic impact of 5 00:00:12,880 --> 00:00:15,480 Speaker 1: up to four trillion dollars a year over the next 6 00:00:15,480 --> 00:00:18,680 Speaker 1: ten to twenty years. One company working in that world 7 00:00:18,880 --> 00:00:24,439 Speaker 1: is in Scripta, Shri Kazaraja Cook. Let me try it again, Shrekazaraju. 8 00:00:25,000 --> 00:00:27,680 Speaker 1: He is president and CEO of the digital genome engineering 9 00:00:27,680 --> 00:00:30,680 Speaker 1: company that we just mentioned in Scripta and he joins 10 00:00:30,760 --> 00:00:33,080 Speaker 1: us on the phone in San Francisco Street. Forgive me 11 00:00:33,840 --> 00:00:37,040 Speaker 1: from the mispronunciation. It's what I can't even read my 12 00:00:37,080 --> 00:00:39,400 Speaker 1: own notes or fonetics. Um, but it is good to 13 00:00:39,400 --> 00:00:41,800 Speaker 1: have you here. And I have to say that my producer, 14 00:00:42,080 --> 00:00:44,639 Speaker 1: you bet, my producer and I were talking earlier that 15 00:00:44,760 --> 00:00:47,120 Speaker 1: this was just something that we love to talk about. 16 00:00:47,440 --> 00:00:49,840 Speaker 1: Tell us, first of all, um, how are you doing 17 00:00:50,000 --> 00:00:53,280 Speaker 1: what the past year has been like? Yeah? Well, first 18 00:00:53,320 --> 00:00:55,240 Speaker 1: of all, Carol, thanks for having me on. I'm a 19 00:00:55,320 --> 00:00:57,640 Speaker 1: big fan of Bloomberg Radio. I listened to it every morning, 20 00:00:57,640 --> 00:00:59,600 Speaker 1: so I did want to say that before he started, 21 00:01:00,080 --> 00:01:02,480 Speaker 1: UM in the morning, you didn't say the afternoon. Now 22 00:01:02,520 --> 00:01:06,520 Speaker 1: I'm a little worried. Now I'm just kidding a yeah, 23 00:01:06,760 --> 00:01:09,560 Speaker 1: I wish I could listen all day. UM. Well, the 24 00:01:09,680 --> 00:01:14,039 Speaker 1: last year has been phenomenal on many fronts. UM. Obviously, 25 00:01:14,120 --> 00:01:17,240 Speaker 1: the the opportunity we're going up against has gotten a 26 00:01:17,280 --> 00:01:20,920 Speaker 1: lot more visibility, and we'll talk about what that means 27 00:01:20,920 --> 00:01:23,039 Speaker 1: in the bioeconomy, but it is going to be something 28 00:01:23,080 --> 00:01:25,959 Speaker 1: that I think people start hearing much more about in 29 00:01:26,040 --> 00:01:29,200 Speaker 1: the additional dimension that it adds to the potential of 30 00:01:29,200 --> 00:01:33,679 Speaker 1: our economy and to society at large. UM. The pandemic 31 00:01:33,760 --> 00:01:35,880 Speaker 1: has obviously made it tough for for us, as it 32 00:01:35,920 --> 00:01:39,360 Speaker 1: has for many other companies who are innovating UM. But 33 00:01:39,520 --> 00:01:43,320 Speaker 1: we have very dedicated employees who have been in the 34 00:01:43,400 --> 00:01:48,080 Speaker 1: lab diligently working. We've had our commercial teams diligently preparing 35 00:01:48,160 --> 00:01:51,560 Speaker 1: to to launch our our first commercial product, the Onyx platform, 36 00:01:51,640 --> 00:01:54,080 Speaker 1: which we announced just a few weeks ago that we 37 00:01:54,080 --> 00:01:57,440 Speaker 1: we shipped our our first commercial unit. So UM, we 38 00:01:57,560 --> 00:02:00,400 Speaker 1: are trying to make progress despite the pandemic. We'll tell 39 00:02:00,480 --> 00:02:05,880 Speaker 1: us exactly what the bioeconomy is. Yeah, So, so it 40 00:02:06,040 --> 00:02:08,880 Speaker 1: is UH, as I said, it's to me, it's a 41 00:02:09,080 --> 00:02:12,680 Speaker 1: it's an additional dimension to the economy and new referenced 42 00:02:13,160 --> 00:02:19,520 Speaker 1: at the outset McKenzie statistic. Another statistic from McKenzie last 43 00:02:19,600 --> 00:02:24,960 Speaker 1: year was that in principle, approximately of the physical inputs 44 00:02:24,960 --> 00:02:28,720 Speaker 1: to the economy could be biologically produced. And when you 45 00:02:28,880 --> 00:02:31,120 Speaker 1: sort of take a step back and think about that, 46 00:02:31,120 --> 00:02:34,600 Speaker 1: that explains the magnitude of what we talked about with 47 00:02:34,639 --> 00:02:37,840 Speaker 1: the bioeconomy. Biology has played an important role in the 48 00:02:37,919 --> 00:02:41,639 Speaker 1: last decade on discovery and life sciences and even in 49 00:02:41,960 --> 00:02:46,200 Speaker 1: the production of therapeutics. However, bioeconomy is larger than that. 50 00:02:46,400 --> 00:02:50,280 Speaker 1: It affects many more industries beyond just healthcare, and it 51 00:02:50,320 --> 00:02:54,799 Speaker 1: has much more far reaching impact into products that all 52 00:02:54,840 --> 00:02:57,680 Speaker 1: of us touch every day. And and there's a couple 53 00:02:57,720 --> 00:03:01,079 Speaker 1: of themes that are sort of catalyzing this movement UM 54 00:03:01,120 --> 00:03:03,640 Speaker 1: and some of them are very familiar to us. That 55 00:03:03,800 --> 00:03:10,760 Speaker 1: the movement to sustainability UM, the movement to to climate change, 56 00:03:10,800 --> 00:03:14,120 Speaker 1: to adapt to climate change, and the basic movement around 57 00:03:14,160 --> 00:03:17,720 Speaker 1: just greater performance and efficiency of our of our products 58 00:03:17,720 --> 00:03:22,120 Speaker 1: and businesses. So there are so many confluent catalysts that 59 00:03:22,160 --> 00:03:26,040 Speaker 1: are really accelerating this movement in the bio autonomy. So 60 00:03:26,080 --> 00:03:28,480 Speaker 1: I feel like we're speaking tree and kind of broad 61 00:03:28,720 --> 00:03:31,040 Speaker 1: strokes here. So tell me, like drill it down, like 62 00:03:31,680 --> 00:03:35,440 Speaker 1: does this include things such as growing food and labs, 63 00:03:35,520 --> 00:03:38,120 Speaker 1: growing organs and labs? Like is tell us kind of 64 00:03:38,120 --> 00:03:41,160 Speaker 1: when we get down to a granular, granular level, like 65 00:03:41,280 --> 00:03:45,280 Speaker 1: what exactly this means? So, so the most common things 66 00:03:45,320 --> 00:03:47,400 Speaker 1: that you might read about if you were to Google 67 00:03:47,520 --> 00:03:52,320 Speaker 1: Google it would be UM in agriculture, crops or plants 68 00:03:52,360 --> 00:03:57,400 Speaker 1: that are disease resistant UM that are they're characterized traits 69 00:03:57,480 --> 00:04:01,280 Speaker 1: that allow them UM to to to grow and prosper 70 00:04:01,440 --> 00:04:04,240 Speaker 1: more efficiently. So agriculture is a place where you might 71 00:04:04,320 --> 00:04:06,680 Speaker 1: hear and see this a lot. And as our global 72 00:04:06,720 --> 00:04:10,000 Speaker 1: population grows, as we're trying to get more efficiency out 73 00:04:10,000 --> 00:04:14,160 Speaker 1: of the land and water um in in plants UM. 74 00:04:14,200 --> 00:04:16,600 Speaker 1: This is one area that a lot of companies are 75 00:04:16,600 --> 00:04:21,479 Speaker 1: looking for to see UM innovation and benefit cosmetics. You 76 00:04:21,560 --> 00:04:25,200 Speaker 1: find that that also are starting to talk about using 77 00:04:25,839 --> 00:04:32,160 Speaker 1: UH gene engineering to to manufacture more sustainable UM cosmetic products. 78 00:04:32,800 --> 00:04:34,360 Speaker 1: We also see it if you kind of move back, 79 00:04:34,560 --> 00:04:35,960 Speaker 1: you know, and I said it is beyond healthcare, but 80 00:04:35,960 --> 00:04:38,280 Speaker 1: if you kind of move back to healthcare, even in biologics. 81 00:04:38,400 --> 00:04:40,880 Speaker 1: You know, just today I was talking to a researcher 82 00:04:40,960 --> 00:04:44,520 Speaker 1: in Europe who was very keen in his study of 83 00:04:44,960 --> 00:04:49,920 Speaker 1: antibiotics antibiodetics. Antibiotics haven't really been advanced in the last 84 00:04:49,920 --> 00:04:53,520 Speaker 1: two decades, and many of the organisms in the body 85 00:04:53,560 --> 00:04:57,400 Speaker 1: have have shown resistance to antibiotics. So researchers are studying 86 00:04:57,839 --> 00:05:01,559 Speaker 1: what causes that and can we identify and isolate those 87 00:05:01,600 --> 00:05:03,840 Speaker 1: parts of the genes that contribute to that so that 88 00:05:03,880 --> 00:05:07,280 Speaker 1: we can design more effective antibiotics in the future. So, really, 89 00:05:07,320 --> 00:05:09,599 Speaker 1: as you can tell just such a wide range of 90 00:05:10,080 --> 00:05:13,000 Speaker 1: potential application, I want to get right back to our guest. 91 00:05:13,000 --> 00:05:16,320 Speaker 1: Shree Kasaraju is with us. He's president and CEO of 92 00:05:16,360 --> 00:05:19,680 Speaker 1: the digital genome engineering company is called it SCRIPTA and 93 00:05:19,720 --> 00:05:22,040 Speaker 1: Tree still with us on the phone in San Francisco. 94 00:05:22,320 --> 00:05:24,600 Speaker 1: So Shri, tell us about kind of where your company 95 00:05:24,600 --> 00:05:28,680 Speaker 1: fits into this world of the bioeconomy, what you are 96 00:05:28,720 --> 00:05:33,280 Speaker 1: specifically doing, who you're working with, sure, Carol, So the 97 00:05:33,600 --> 00:05:37,040 Speaker 1: mission for in script is to enable researchers to realize 98 00:05:37,080 --> 00:05:40,640 Speaker 1: the full potential of the bioeconomy, and specifically what that 99 00:05:40,720 --> 00:05:44,560 Speaker 1: means is in our in our first product that we're launching. 100 00:05:45,200 --> 00:05:48,640 Speaker 1: It represents the first digital genome engineering platform in the 101 00:05:48,680 --> 00:05:51,240 Speaker 1: world that can sit on a bench in a lab. 102 00:05:51,839 --> 00:05:57,440 Speaker 1: This initial platform is for microbial so yes Nikoli organisms 103 00:05:57,520 --> 00:05:59,799 Speaker 1: And just to kind of put this in the context, 104 00:06:00,120 --> 00:06:04,040 Speaker 1: can it do a typical experiment, a gene editing experiment 105 00:06:04,120 --> 00:06:06,240 Speaker 1: that a lab may have done with a couple of 106 00:06:06,279 --> 00:06:08,960 Speaker 1: PhDs over the course of many months up to a 107 00:06:09,040 --> 00:06:11,599 Speaker 1: year now can be done in a matter of weeks 108 00:06:11,680 --> 00:06:15,719 Speaker 1: or months and it's an incredible savings of time. But 109 00:06:15,839 --> 00:06:19,760 Speaker 1: more importantly, the scale um of of edits that this 110 00:06:19,960 --> 00:06:22,599 Speaker 1: can produce in a single run can get up to 111 00:06:22,760 --> 00:06:26,719 Speaker 1: ten thousand single edits and parallel, So there's incredible power 112 00:06:26,800 --> 00:06:29,839 Speaker 1: in the scale of this platform UM, and it's really 113 00:06:29,880 --> 00:06:32,680 Speaker 1: opening the minds of many researchers that we speak to 114 00:06:32,760 --> 00:06:35,279 Speaker 1: about what kind of work and research they could do 115 00:06:35,360 --> 00:06:38,719 Speaker 1: with it UM. So that's that's the Onyx platform, and 116 00:06:38,800 --> 00:06:41,800 Speaker 1: behind it UM we're in development on several other very 117 00:06:41,839 --> 00:06:44,440 Speaker 1: exciting platforms as well. Can you talk to us at 118 00:06:44,480 --> 00:06:46,760 Speaker 1: all about some of the partners or the some of 119 00:06:46,760 --> 00:06:48,520 Speaker 1: the areas that you're working in specifically, I know you 120 00:06:48,560 --> 00:06:51,560 Speaker 1: talked about kind of applications of this UM so I'm 121 00:06:51,560 --> 00:06:54,400 Speaker 1: assuming a lot of it is either agg or healthcare. 122 00:06:54,400 --> 00:06:58,680 Speaker 1: I mean, where is it. Well, we're just getting started commercially, 123 00:06:58,680 --> 00:07:01,400 Speaker 1: so we announced our first commercial shipment to gene mill 124 00:07:01,880 --> 00:07:05,119 Speaker 1: UH in the UK in Liverpool. UM. There are two 125 00:07:05,200 --> 00:07:08,680 Speaker 1: main categories of folks that that we're talking to right 126 00:07:08,720 --> 00:07:12,200 Speaker 1: now about about the platform. One is your your core 127 00:07:12,240 --> 00:07:17,000 Speaker 1: academic research centers and to our our bio industrial companies 128 00:07:17,000 --> 00:07:20,240 Speaker 1: and the range of industries that that represents your your right. 129 00:07:20,320 --> 00:07:22,720 Speaker 1: You know, it's a it's a very wide range, UM. 130 00:07:22,800 --> 00:07:26,480 Speaker 1: And but many of these folks are already utilizing Crisper 131 00:07:26,840 --> 00:07:29,800 Speaker 1: in some way, meaning they're doing some form of gene 132 00:07:29,920 --> 00:07:33,240 Speaker 1: editing UM in house already UM. And they're looking to 133 00:07:33,520 --> 00:07:37,440 Speaker 1: to really make those experiments more efficient, but also explore 134 00:07:38,000 --> 00:07:40,240 Speaker 1: what more can they do with a more powerful system 135 00:07:40,240 --> 00:07:44,000 Speaker 1: and platform. So, Okay, forgive me because I'm thinking we've 136 00:07:44,000 --> 00:07:45,560 Speaker 1: got a lot of listeners and we have a really 137 00:07:45,560 --> 00:07:49,240 Speaker 1: smart audience. UM. And I'm gonna unt this is not 138 00:07:49,320 --> 00:07:52,320 Speaker 1: my world, but it definitely interests interests me in terms 139 00:07:52,320 --> 00:07:55,000 Speaker 1: of gene editing and kind of where this is all going. So, 140 00:07:55,040 --> 00:07:57,200 Speaker 1: if you were sitting down with someone to explain kind 141 00:07:57,200 --> 00:08:00,520 Speaker 1: of the potential because it sounds like we're on the 142 00:08:00,560 --> 00:08:03,160 Speaker 1: cusp Uh, there's a lot out there already, but there's 143 00:08:03,160 --> 00:08:04,800 Speaker 1: so much more that could be done when it comes 144 00:08:04,840 --> 00:08:08,640 Speaker 1: to the bioeconomy or uh, the genomic engineering that you 145 00:08:08,640 --> 00:08:11,720 Speaker 1: guys are involved in. UM, how would you explain it 146 00:08:11,800 --> 00:08:13,960 Speaker 1: kind of to a lay person in terms of how 147 00:08:14,000 --> 00:08:16,920 Speaker 1: it might impact us in the years to come? Also 148 00:08:17,040 --> 00:08:20,280 Speaker 1: as an investor kind of who will be the players 149 00:08:20,320 --> 00:08:22,080 Speaker 1: involved in it? Because I am curious about kind of 150 00:08:22,120 --> 00:08:25,640 Speaker 1: your own future. Yeah, sure, yeah, that's a great question. 151 00:08:25,680 --> 00:08:29,160 Speaker 1: So to put this into context, if we think about genomics, 152 00:08:29,400 --> 00:08:32,720 Speaker 1: and even with COVID, we've heard about some of these 153 00:08:32,840 --> 00:08:36,280 Speaker 1: terms of the technologies that are being used. PCR and 154 00:08:36,360 --> 00:08:39,880 Speaker 1: next gen sequencing are amongst some of the biggest step 155 00:08:39,920 --> 00:08:42,520 Speaker 1: function changes in our history as it relates to genomics, 156 00:08:42,559 --> 00:08:46,160 Speaker 1: and those are all around reading genes and that's provided 157 00:08:46,240 --> 00:08:49,640 Speaker 1: us incredible information. We've utilized it in a variety of 158 00:08:49,679 --> 00:08:54,439 Speaker 1: ways for research, even trying to develop UM diagnostics or 159 00:08:54,559 --> 00:08:57,320 Speaker 1: or even things to fight things like the US the 160 00:08:57,400 --> 00:09:02,600 Speaker 1: COVID nineteen virus. What what what Cristper has done is 161 00:09:02,640 --> 00:09:07,480 Speaker 1: provided a step function change against those prior historical advancements 162 00:09:07,559 --> 00:09:12,640 Speaker 1: Now with Crisper, we can edit genes. We can write 163 00:09:12,760 --> 00:09:16,600 Speaker 1: genes instead of reading them, and that the opportunity around 164 00:09:16,640 --> 00:09:19,920 Speaker 1: that is massive. When you when we speak to researchers, 165 00:09:20,080 --> 00:09:23,280 Speaker 1: they're trying to create as much they call it variation. 166 00:09:23,400 --> 00:09:25,960 Speaker 1: That means as much things to study around, something to 167 00:09:26,120 --> 00:09:29,880 Speaker 1: learn as possible. But it's not just about research and information. 168 00:09:29,920 --> 00:09:33,960 Speaker 1: Now with with gene editing, we can also create new products. 169 00:09:34,280 --> 00:09:37,280 Speaker 1: And that's the biggest change with this advancement of what 170 00:09:37,840 --> 00:09:40,079 Speaker 1: we in script as well as others are going to 171 00:09:40,160 --> 00:09:43,080 Speaker 1: be doing, as we're not only going to be understanding information, 172 00:09:43,160 --> 00:09:46,080 Speaker 1: but we're going to be creating products um with this 173 00:09:46,160 --> 00:09:49,920 Speaker 1: technology as well. And that is where the breath of 174 00:09:49,960 --> 00:09:54,760 Speaker 1: the opportunity is just so incredibly massive that that we're 175 00:09:54,800 --> 00:09:57,280 Speaker 1: all quite excited about it. Well, So tell us about 176 00:09:57,320 --> 00:10:01,240 Speaker 1: this billion dollar Series E finance round. I think it 177 00:10:01,280 --> 00:10:04,679 Speaker 1: was led by Fidelity. There's also funds and accounts from 178 00:10:04,720 --> 00:10:06,600 Speaker 1: t ro Price that are involved in it. Tell us 179 00:10:06,600 --> 00:10:08,880 Speaker 1: about that and and that kind of that money. What 180 00:10:08,920 --> 00:10:12,480 Speaker 1: will you guys plan to do with it? This this 181 00:10:12,600 --> 00:10:15,280 Speaker 1: is a just an incredible market I know, you know 182 00:10:15,400 --> 00:10:18,920 Speaker 1: all the listeners know that from watching the market environment 183 00:10:18,960 --> 00:10:22,760 Speaker 1: we're in and seeing the premium for for innovation and 184 00:10:22,800 --> 00:10:27,800 Speaker 1: growth companies UM, and specifically in in the life sciences. 185 00:10:27,840 --> 00:10:30,000 Speaker 1: You know, this whole area of gene editing also has 186 00:10:30,040 --> 00:10:33,840 Speaker 1: been extremely robust and a lot of capital going against 187 00:10:33,880 --> 00:10:36,560 Speaker 1: it because there's a lot to do. UM. We we 188 00:10:36,640 --> 00:10:40,160 Speaker 1: looked at this round as as an opportunistic financing UM. 189 00:10:40,240 --> 00:10:42,520 Speaker 1: We were well capitalized. UM. There are a lot of 190 00:10:42,520 --> 00:10:45,880 Speaker 1: alternatives for companies to raise money to go public. UM. 191 00:10:45,960 --> 00:10:47,920 Speaker 1: We think we got the best of both worlds. We 192 00:10:48,040 --> 00:10:52,000 Speaker 1: got really world class long term investors, and we also 193 00:10:52,160 --> 00:10:55,720 Speaker 1: retain the ability to to grow our business privately, you know, 194 00:10:55,760 --> 00:11:00,160 Speaker 1: which affords tremendous flexibility UM and the opportunity to to 195 00:11:00,320 --> 00:11:02,400 Speaker 1: explore new areas. And so the hundred and fifty million 196 00:11:02,440 --> 00:11:05,280 Speaker 1: dollars you know, I use the word opportunistic, it's really 197 00:11:05,320 --> 00:11:09,040 Speaker 1: around going after additional areas that where we can bring 198 00:11:09,040 --> 00:11:12,319 Speaker 1: our technology UM to more and more researchers. So those 199 00:11:12,320 --> 00:11:15,160 Speaker 1: are these are things down the road beyond what we're 200 00:11:15,280 --> 00:11:19,000 Speaker 1: already developing with either Onyx or our Mammalian platform. What 201 00:11:19,200 --> 00:11:21,480 Speaker 1: is the growth of the company do you I mean, 202 00:11:21,480 --> 00:11:25,680 Speaker 1: I know you're early in what are your expectations going forward, 203 00:11:27,320 --> 00:11:31,800 Speaker 1: this is such as we've established such a large market. 204 00:11:32,080 --> 00:11:36,640 Speaker 1: The the focus for for us is exactly that, having focus, 205 00:11:36,720 --> 00:11:41,240 Speaker 1: picking certain areas and customers and really showing success of 206 00:11:41,280 --> 00:11:44,600 Speaker 1: our platform. So it might be contra to what someone 207 00:11:44,679 --> 00:11:47,720 Speaker 1: might think about, you know, really growing going fast and 208 00:11:47,760 --> 00:11:52,280 Speaker 1: growing fast for us that the long term future gets 209 00:11:52,320 --> 00:11:56,440 Speaker 1: solidified and much stronger if we can be successful showing 210 00:11:56,480 --> 00:12:00,480 Speaker 1: customers applications where they can use this technology, gene where 211 00:12:00,480 --> 00:12:03,840 Speaker 1: they can do things they haven't done before. So when 212 00:12:03,880 --> 00:12:05,960 Speaker 1: we look at this, and when I think our investors 213 00:12:06,000 --> 00:12:07,840 Speaker 1: who got involved in the series, he looked at this, 214 00:12:08,320 --> 00:12:15,600 Speaker 1: it wasn't about driving um platform revenues or sales, you know, 215 00:12:15,679 --> 00:12:18,600 Speaker 1: this was about how do we secure our place as 216 00:12:18,679 --> 00:12:23,320 Speaker 1: a long term impact you know that can drive a 217 00:12:23,360 --> 00:12:26,960 Speaker 1: new paradigm change, not just for the technology but for 218 00:12:27,040 --> 00:12:29,800 Speaker 1: us as an organization. You know, they they've encouraged us 219 00:12:29,800 --> 00:12:32,600 Speaker 1: to be aggressive and invest um and to take our 220 00:12:32,640 --> 00:12:35,760 Speaker 1: time making good decisions. You know that that aren't necessarily 221 00:12:35,760 --> 00:12:39,200 Speaker 1: short term oriented, but can drive greater long term stability 222 00:12:39,240 --> 00:12:41,360 Speaker 1: and success. We think this is going to be a 223 00:12:42,200 --> 00:12:46,400 Speaker 1: new large market and so being early, being smart about 224 00:12:46,440 --> 00:12:49,360 Speaker 1: how we build a company for the future are our paramount. Well, 225 00:12:49,400 --> 00:12:51,040 Speaker 1: we look forward to hearing more and I hope you'll 226 00:12:51,080 --> 00:12:53,200 Speaker 1: come back and by then, hopefully I will have your 227 00:12:53,320 --> 00:12:57,840 Speaker 1: name down Pat Tree uh Kosaraju. He is the President 228 00:12:57,920 --> 00:13:01,319 Speaker 1: CEO of the Digital Genome Engineering cow Bunny in Scripta 229 00:13:01,400 --> 00:13:04,000 Speaker 1: and we appreciate his time. Shares it Dell by the 230 00:13:04,000 --> 00:13:05,840 Speaker 1: way up about eight point four percent, and the after 231 00:13:05,920 --> 00:13:08,400 Speaker 1: hours saying it's going to spin on em Ware software 232 00:13:08,480 --> 00:13:11,640 Speaker 1: unit by the fourth quarter. Have a good and safe evening, everybody. 233 00:13:11,800 --> 00:13:12,839 Speaker 1: This is Bloomberg