Speaker 1: Broadcasting live to New York, Bloomberg Erio to Washington, d C,
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Speaker 1: are listening to Bloomberg Markets. Carol Masterlock, Corey Johnson. We
Speaker 1: are live at the Museum of Science in Boston. Coming up,
Speaker 1: we're gonna talk a little bit about gathering lots of
Speaker 1: genomic data and how to put it to work. Yes,
Speaker 1: really fascinating data approach to uh the world of genomas.
Speaker 1: We're gonna take into that. But first us the very
Speaker 1: latest in business news inline's from Charlie Pellis. All right,
Speaker 1: thank you very much, Corey Johnson. Keep warm, guys. We
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Speaker 1: West Texas Intermediate Crude forty six oh two for a
Speaker 1: barrel of w t I crude down nine tenths of
Speaker 1: one percent. The Walt Disney Company reports after the closing
Speaker 1: bell the focus will be on ESPN as well as
Speaker 1: its theme park business, but Paul Sweeney Bloomberg Intelligence, Director
Speaker 1: of North American Research, as investors will also be keeping
Speaker 1: an eye on the film part of the Disney's business.
Speaker 1: Every single year they've seen to turn out three or
Speaker 1: four or five huge franchise tent pole pictures that are
Speaker 1: out of a billion dollars in global box office. So
Speaker 1: you know the acquisitions they made of Pixar and of
Speaker 1: Marvel and of Lucasfilms have really paid off for Bob
Speaker 1: Iger in the company. That business which historically has been
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Speaker 1: consistent growth story for them. And according to the earnings
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Speaker 1: is Bloomberg part the evolution of the business and the
Speaker 1: science of genomics is an amazing thing in Boston, certainly
Speaker 1: at the at the leading edge of that. John's right now,
Speaker 1: as Hans Modison, who is the CEO of a company
Speaker 1: called Wooshi Next Code, which is trying to create a
Speaker 1: sort of platform for using genomic data. What is the
Speaker 1: problem that you guys are trying to solve. So we're
Speaker 1: really trying to gather together in one place UM as
Speaker 1: much of the world's genomic data as possible and make
Speaker 1: it easily clearable by those who try to use it
Speaker 1: for better you know, diagnosis or to develop novel drugs.
Speaker 1: Is the is the collection or there? There are many
Speaker 1: large depositories of genomic data are handful, probably, uh, but
Speaker 1: I wonder if they're kept in very different data formats
Speaker 1: that makes it tough for them to sort of work together. Yeah.
Speaker 1: One of the key things you have to do is
Speaker 1: really to harmonize all of the public available data UM,
Speaker 1: make it in a form so that, know, you can
Speaker 1: cross compare it and so forth. So in many ways,
Speaker 1: what we try to do is similar to what Bloomberg
Speaker 1: did in the financial industry. So bring together and create
Speaker 1: a single data platform that allows you to access the data,
Speaker 1: queriod understand it and makes sense of it. Do people
Speaker 1: understand that that's kind of important to do to really
Speaker 1: kind of get the most out of all that UM
Speaker 1: gene data if you will. Oh yeah, because you have
Speaker 1: to have kind of a common platform, do you not, absolutely?
Speaker 1: I mean, if you want to use and make precision
Speaker 1: medicine reality, you have to come up with an industrial
Speaker 1: scale infrastructure that allows you to do this, you know,
Speaker 1: not for just a handful of people, but for millions
Speaker 1: of people. Um. So in order to do that, you
Speaker 1: have to have these large, robust, big data systems, which
Speaker 1: is what we're building. Well, how is the data different
Speaker 1: than other large piles of data, because certain there's a
Speaker 1: lot of data out there that's being manipulated by all
Speaker 1: sorts of organizations and businesses already. Yeah, so, I mean
Speaker 1: genomic data, of course, is very specific. Um each one
Speaker 1: of us carries around three point two billion bases of
Speaker 1: informay nation, which is encoded in our DNA. So the
Speaker 1: sequence I have a single person, the whole genome sequences
Speaker 1: about a hundred and twenty gigabytes, So it's awfully large.
Speaker 1: So you multiply that times you know, a million people,
Speaker 1: you get to some really really large numbers. Where are
Speaker 1: you in the process of building this platform. Well, we've
Speaker 1: actually been doing it for the you know, on and
Speaker 1: off for the past twenty years. So we started UM
Speaker 1: as a spin out from a company called Deco Genetics,
Speaker 1: which is where a lot of this technology was developed
Speaker 1: and UM that's right, and UM in the process was
Speaker 1: being used you know, to sort of organize, mine and
Speaker 1: manage arguably one of the biggest data repositories of you
Speaker 1: know what, make information in the world. So we do
Speaker 1: have a little bit of legacy and history of working
Speaker 1: with with big data like this, and and and and
Speaker 1: now we've been able to deploy it in various areas.
Speaker 1: We worked a lot with BC for instance. That's what
Speaker 1: I want to hear, how you de Yeah, So we
Speaker 1: worked with a number of both pharma companies and large
Speaker 1: hospitals in particular, so here in the Boston area, for example,
Speaker 1: we work a lot with the Boston Shield Dren's Hospital,
Speaker 1: UM helping them to diagnose children with rare disorders. UM.
Speaker 1: We also work with some pharmaceutical companies like a v
Speaker 1: Is is a partner of ours, doing large scale discovery
Speaker 1: in partnership with with another company in Ireland. UM. We
Speaker 1: also work with a number of precision medicine programs around
Speaker 1: the world. So we're assisting Geno England in the UK
Speaker 1: with our initiative. UM. We also work with the Guitaris
Speaker 1: and the Qutari Genio project and and so forth. So
Speaker 1: we're active around the world in many different instances. Where
Speaker 1: are the largest depositories of uh, if that's right, were
Speaker 1: the deposits of data generic data? And how were those?
Speaker 1: How is the data acquired? Well, I mean I think,
Speaker 1: for example, twenty three and me company that that part
Speaker 1: of the ANJIK is based a concept of the business is,
Speaker 1: let's create a great database that can be used anonymously
Speaker 1: just to do the specific drugs and so on. Right. Yeah,
Speaker 1: So obviously some of the some of large collections of
Speaker 1: of of DNA and some early molecular data are with
Speaker 1: some these consumer companies like twenty three and me and
Speaker 1: Ancestry dot com is another one, um color yeah, and
Speaker 1: then um uh and then the other big sources of
Speaker 1: course of these large national programs. So what do you anticipate,
Speaker 1: you know, like you said, there's so much data out there,
Speaker 1: but then being able to put it to work for
Speaker 1: either treatments, treatment modalities. Um, what do you see kind
Speaker 1: of using this data? What will it do? Yeah? So
Speaker 1: it's gonna basically allow you to come up with a
Speaker 1: much quicker and more accurate diagnosis of different diseases. Um,
Speaker 1: it's going to allow you to develop therapies that are
Speaker 1: effective for you, for you as a person. So it's
Speaker 1: kind of personalized medicine exactly. So it's going from one
Speaker 1: size fits all to to really being bespoken custom to
Speaker 1: the genomic makeup of each one of us and therefore
Speaker 1: much more effective and fewer side effects. Remember we talked
Speaker 1: with Bob right about UH when he was with Autism
Speaker 1: speaks about I think they were working with with at
Speaker 1: Google in terms of because each case of autism is different,
Speaker 1: and so you can create that are forms of treatment exactly. Yeah,
Speaker 1: it's all about trying to personalize the experience, you know,
Speaker 1: put the resources in and the technology to work so
Speaker 1: that it benefits the patient in the most effective mannering.
Speaker 1: Someday medicine will be just like all my suits included.
Speaker 1: That's my cost a little extra, really fascinating stuff. Hans Smartison,
Speaker 1: Uh for the CEO of Yeah, Honnest Smartson, I was
Speaker 1: so excited to rule my rs UH from Wushi next Go.
Speaker 1: Thank you very much for joining U out here in
Speaker 1: the cold. We appreciate it. Thank you for the look
Speaker 1: of world of national news headlines with Nathan Hagar, who
Speaker 1: was in the nation's capital for President Trump is putting
Speaker 1: off a decision Corey on whether to keep the US
Speaker 1: in the Paris Climate Accord. White House spokesman Sean Spicer
Speaker 1: had said the President would make up his mind before
Speaker 1: the G seven summit later this month, but now he
Speaker 1: says the President wants the opportunity to meet with his
Speaker 1: team to create the best strategy. This move could also
Speaker 1: allow President Trump to press world leaders for concessions. Now
Speaker 1: all the pres us that it waits. A new study
Speaker 1: from the u N's Climate Change Arms says global temperatures
Speaker 1: could top one and a half degree celsius above pre
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Speaker 1: first threshold under the Paris Deal. A co author of
Speaker 1: this study tells The Washington Post there is increased urgency
Speaker 1: to do something about minimizing global warming. The White House
Speaker 1: is defending President Trump's timetable for firing Michael Flynn as
Speaker 1: National Security Advisor, eighteen days after then Deputy Attorney General
Speaker 1: Sally Yates warned that Flynn may have been compromised by
Speaker 1: the Russians. I think he did have an honorable career.
Speaker 1: He served with distinction in uniform for over thirty years,
Speaker 1: and the President does not want to smear a good man.
Speaker 1: Spokesmen Sean Spicer says the President was informed right away
Speaker 1: when Yates aired her concerns. He calls Yates an opponent
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Speaker 1: would have taken a role in a Hillary Clinton administration.
Speaker 1: The Department of Homeland Securities thinking of expanding restrictions on
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