Okay. Could you start by saying your name and your affiliation, sir?
I'm Derek Cook and a consultant in infectious disease and clinical microbiology in the John Ratcliffe Hospital,
and then also a professor of microbiology in the Buffalo Department of Medicine.
Thanks very much. And just very briefly, can you give me some kind of account of how you got to be where you are now?
But the first step in the journey perhaps was growing up in rural South Africa and
very rural South Africa and then made my way to medical school in Johannesburg.
And then from there went through the London School of Tropical Medicine and Hygiene in London and then
did my specialist training in the United States and then came to Oxford for the city four years.
And what made you pick? Microbiology, as I said.
Well, it is more. Not microbiology so much as medicine.
I trained as a physician transmits infectious disease.
Dr. And I've done a lot of general medicine and infectious disease work, but also trained in pathology,
sort of became qualified as what one would call a jobbing microbe ologist.
But preceding that, I've done a lot of research in the United States on microbial behaviour and that was.
Sort of. A natural a starting point to do what we refer to as clinical microbiology.
And the differentiation between them at many levels is not great to enough.
Two other differences quite substantial living across the practise of medicine but infectious disease,
but also having an understanding of the scientific basis of the microbes that cause disease.
So summarising it, I mean, the question I've written down is I'm asking everybody this.
If you had to define a single big question that gets you out of bed in the morning, what would it be?
But I could rephrase that. I'm not sure if it's the same question or not as what appeals to you about bugs.
That's sort of an interesting question because it's it's really solving problems that gets me out of bed in
the morning rather than and tax bucks represents one end of a spectrum of troublesome problems that you can,
can, can. Entertain yourself with a little and excite yourself with other levels and the diseases that cause a
fascinating in the way that they interact with their hosts and affect hosts at an individual level,
at a population level.
So it's really probably the interface between medicine and biology and all of that through fields that's appealing and interesting.
I like caring for patients. I like solving problems in the lab.
I like writing papers. I'm lucky to do a lot of those.
So let's move on to the pandemic. Can you remember how you first heard that there was a pandemic in the offing?
Well, I mean, it was just in the media and it was a. A.
A reference to it in the media, which was enormously similar to the first source outbreak.
It is completely reminiscent of that giant January or was out before it was December.
It was December 2019 and 19 December who had and I don't know whether 12 or 14 years before that.
The settlers outbreak that started in the southern provinces of China and then became prevalent in Hong Kong and didn't become a pandemic.
Well, this one did. But they're very similar at the beginning.
Yeah. And did you how did you sort of slow realisation that this was something that was likely to affect us?
Or did you initially think, Oh, that's interesting, there's another cell is happening in the forest and not expect it to?
I didn't have very strong expectations one way or another.
I mean, so as the first epidemic petered out, the Zika.
If it was huge in the media.
But for editing that was in Brazil, it's well, it was one of the particular first.
So I was in Brazil for it preceded it, I think it was evident before.
So I grew up with Zika in Africa. So big deal and.
And then there were similar limited outbreaks of of of other viral illnesses, such as sort of curvy in in the Middle East.
And there's obviously a particular outbreak in South Korea.
So you wouldn't was aware of this. It was only really.
January, February. Did you realise that there were going to be problems in an office of the W.H.O. in.
Like January. And it was just becoming apparent that Italy, the north of Italy, was having a particular problem.
And then it pretty rapidly became clear that this was going to spread around the world.
I was of first. I feel particularly alarmed about it because it was going to do from pretty even temper tantrums.
I looked at it with equanimity rather than a huge mess.
Mm hmm. But did you think this is going to change the way I work or what I work on?
No, it isn't going to change the way that that plan would work at that stage.
But it soon became clear that it was going to be a need for a huge effort and a massive response.
That's what we've vaguely anticipated, what would be involved in that?
But in other parts of what used to be called Zulu land in South Africa, what about other cholera outbreak outbreaks?
I've directed a major part of the Public Health England where we were thinking about these sorts of things.
I'm not taken with a long speech. I'm not trying to alarm the children.
I mean. But. Yes, yes, yes. I was matter of fact about it. If if it grew into something that was huge, one would deal with it and become involved.
So just this is just sort of by the way, that's always been the case. It wasn't just because this was about you.
Yeah. Yeah. So just to my background, to what we can talk about later.
Can you just outline briefly the natural history of the the epidemic as it's evolved from from December 2019 till till now,
in terms of where different variants appeared around the world and how they've affected case numbers.
So yeah, there's some aspects of it that were pretty predictable in the sense that if you have a pandemic, it's just around the world.
You knew that it would go away. So that was very clear.
It occurred ways that because of the immunity arising and then very people don't really know why waves happen.
Flu does. This is the biology behind this sort of not that clear.
I mean, the 1918 flu epidemic were.
Please. It's interesting. Must be a bit of you being a part of the way people behave.
But this season. A lot of variables.
So that was all going to be expected in my mind.
What wasn't really prepared for is how the properties of the virus would change.
And they have changed to list some characteristics. It is, in retrospect, easy to understand so that it would be completely intuitive.
But you didn't expect it was going to happen.
And those that those changes had to do with how to adapt it to the human which wasn't expected or other animals, as it did to me.
But it would become hugely more transmissible.
And then a lot of the hysteria increase of pathogens of the species is that it could be more
variant at the beginning and over time adapt to the host and become a lot less virulent.
Not clear that's happened yet, but one of the reasons for that immune escape is very well recognised.
So that wasn't really a surprise. The stick changes and transmission was a bit of a surprise.
This is with the emergence of new variants. It's only son.
So you mean the same variant can increase its transmissibility?
Well, what you're hitting on is something that got to do is lazy terminology.
Variances in some settings are very, very specific terms.
You get a single alteration in the genetic makeup.
But in terms of the way one has used it for the pandemic is.
Actually a specific word for it would be a lineage.
It's quite often has a number of mutations in it. And then in respect of transmissibility, it's.
It's a causative mutation that occurs, occurs and that can be on lots of different individuals.
And therefore variant is a funny way of describing it.
You might be aware of that, but it's it's confusing to to a lot of people.
And the more that the virus combines with itself or with it, you get kids get convergent evolution.
That's where the same mutation occurs and very different. Settings are linked.
Settings of the virus because of selection, you rapidly realised that the business was down to a few specific mutations and that's been surprising.
The extent to which the transmissibility of the virus has been changed by some specific mutations or might be a combination of mutations, may vary.
Researchers, not myself,
but researchers are very interested in how that might be additive with synergistic effects between combinations of annotations,
but it's certainly mostly down to single mutations, resulting in these quite profound changes in the behaviour of virus.
And some of them are thought to go hand in hand with altering it to the ability of the virus to escape immune protection of the host.
Which was expected. I mean, that is quite common.
So one thing I should have asked you earlier is I've I've got a question here.
What methods do you use to explore the question?
And I know you've been involved in a project, you know, if it's a project, an umbrella thing called modernising medical microbiology.
So can you just explain for the uninitiated what that involves?
So that that collection of people that have come together in this modernising medical microbiology arose from a large quantity.
We succeeded in getting. And it's it's it's grown organically.
Independent research is working very closely together.
And that's something a number of years ago.
In 2008. Yes. Yes.
That's about the. And. The ambition there was to.
Make use of new technology. So we're going to bear on.
Science in general, but in particular on microbial science and human infectious disease science.
And you could look at them holistically rather than as discrete parts of it.
And the technologies that are driving that.
Digital computational. Technology is quite obviously and very closely linked to that to the.
Tools enable you to recover the genetic code and in its entirety.
And the synthesis of those two made you able to assemble.
The code that's generated in little bits to form the whole chromosome with the genetic structure and then to mine that reflation again.
This. It's highly dependent on really advanced computational processes.
It's really fancy software, very high performance computers.
And then if you have that layer of information, how can you link it?
You know, if you're doing medical science to people and to do things like tracking infection in hospitals.
Yes. You know, understanding all manner of things, what the risk factors that account for people developing disease.
You could do all of the same things with human genetic code and it was more microbial in.
But there's quite a strong piece that's got to do with human genomics,
but a huge part that's got to do with large datasets about humans and health care systems.
What do people with a certain infection get? Severe illness and some very deadly illness, and how does that distribute across populations?
And to do those very large.
Analysis across large numbers of people and the microbes that they've got.
You could argue address by having confidence computing again.
I mean, it's very robust information. You're going to speak to Sarah Walker.
She's become absolutely key in that sort of work.
And and that was really the background thinking about modernising medical microbiology schemas.
How can you take these new technologies and as a result of studies, generate new information,
identify better ways of doing things that include better diagnostics?
And, you know, how can you identify ways of of of.
Recognising the best ways of preventing the spread of infection or even recognising when you have spread of infection, you can have interventions.
I think we have had a marvellous time, you know, again, holistically looking at the subject.
Can you give me some examples of some of the kinds of infections that you were interested in before COVID came along?
Well, a couple that have been highly illuminating if you take a disease caused by Clostridium difficile.
We had a. Amongst us.
We got a sense of humour, decency.
There was a great political imperative, almost interest, in ascribing the presence of these jobs as the disease to dirty hospitals.
I don't know if you can remember it in the press a lot.
We were sort of. Kind of unimpressed with reset and set about very deliberately to investigate the organism with that
particular question in mind and did a huge amount of work very carefully and in a systematic way,
collecting cases with the germ and with information about them and the germs themselves,
and were able to recover the genetic code by sequencing the microorganisms and then did combined epidemiological and microbial investigations.
The. The outcome of which was that the evidence for the hospital being dirty and the source of the infection was by mute.
And it was much more of a matter of these organisms increasing into the hospital environment, probably through other people.
And so people could carry them around and be perfectly well.
I mean definitely, yeah.
It's like 98, 99% of the germs life is in people who don't even know they've got it, never had a problem with it, but maybe even 99.5%.
Particularly children. Write another story. And that was sort of entertaining not to be opposed.
The idea of keeping the hospitals, but the idea that the germ represented a market for a dirty hospital per se.
It was a marker for a lot more than that huge amount.
Not all of it. Entirely teasing, and then we were able to demonstrate pretty convincingly.
Better than pretty convincingly that the whole so-called epidemic had to do with the way
that germ had become resistant to an antibiotic called ciprofloxacin quinolone antibiotics.
And what you had is the linkage of Clostridium difficile that acquired this causative gene that made it resistant to quinolones.
And then it's very rapidly. True selection.
But black sites could be two reasons why.
This is the selection going on in the background. And once Quinolone usage went down some 50% in the community amongst general practitioners.
These lineages reduced in number and disappeared and the epidemic disappeared with it.
So it had nothing to do with the hospitals and had everything to do with the use of these quinolone antibiotics.
So that was sort of entertaining and a counter to various political slogans.
We enjoyed that some loved and that you could never have discovered that without extremely sophisticated computing and DNA sequencing and systematic,
careful accumulation of information about the patients,
which we got from linking clinical records systems in the hospital and getting all
the the necessary information governance arrangements organised by the hospitals,
a huge effort. All those permissions to do it in a very diligent and safe way in terms of I think we've done some of the work with TB.
With TB. It's got lots of dimensions to it,
but one of the most pleasing is that we can take the genetic code and mine the genetic code and find signatures of resistance in the genetic code.
Get closer to mutations. There's a theme here and they they can be one amongst 4 million, 400,000 other nucleotides.
And that one change turns the organism from susceptible to resistant.
If you can very reliably identify those changes and determine purely genomically whether the organism is going to be resistant to.
Activity, licence, drug or not, and make decisions about whether to use it without doing the tedious job and the big faff of growing
its growing in the presence of the drug and figuring out if it grows from what started when we just
completed a huge global project across 27 countries around the world doing this in scale and then just
publishing a large number of patent papers that enable one to make those deterministic predictions from.
Computationally analysing the virtual codes and singling out which drugs that particular
strain would be resistant to and whether they are susceptible to those drugs.
And you can make that differentiation with a very high degree of accuracy.
And it's transmogrified how you practise.
You know. Tbe Manager management.
And it was very heavily used.
In assisting the W.H.O. created a catalogue, as they call it,
which is just a repository of the information about each one of those changes in the
genetic code so that people could develop tests for this various configurations and.
We really did most of the work towards creating this W.H.O. dust catalogue.
You think it could be a lot better when you're publishing all the papers too, to understand and target you would do that.
So again, that is the computation.
Huge, systematically collected samples around the world, brought together and analysed.
And it's not just medicine scientists of all different sorts as people from all around the world that want to effectively work together.
We had fantastic success working with China, India, the United States, and then many countries in Africa, Asia.
South America. So just to drag you back to Kobe, you had this tremendous set of tools for interrogating pathogens, infectious disease pathogens.
What point did you decide that you were going to turn some of that power on this new, new infection and help us do it with different drugs?
Well, how did it just what how did it happen? Well, as Sara and I said, you know, this is going to be a ridiculous feeding frenzy.
But to do research, we'll just work to support the general effort.
Right. And then about. February.
March. John Bell contacted me.
He said, you know, in government we've got a huge problem because we can't find people to.
Do what would be considered banal, menial, almost menial jobs.
Trying to stand up huge scale testing in the country.
And we don't even know whether any of the techniques involved in testing just how you swap or troops you carry stuff in,
how you process through through PCR machines, whether any of them meet the standards means we can roll this out in the country.
And then they were starting to market a whole lot of kids to see whether you picking your finger had antibodies to to the virus indicating
that you you had some element of immunity and there were all manner of people trying to sell government's complete rubbish and said,
we know this. Can you do stuff to help us set it all up?
We will we will assist in the effort.
So we set up a programme of work between here and at Porton Down and our new people from Porton Down.
So to Public Health, England, that started screen swaps,
just standard swaps to make sure that they were safe to use and it would not affect the testing values.
And we did talk about 500 swaps, but just the actual swap, just to stick with the bits of cotton wool to make sure it works.
Right. My goodness, we didn't get hundreds because we think they're going to be manufactured.
That would be flown into the country that were all the supply problems and you didn't know if you were buying rubbish or things that were.
So we set this up on a massive scale so they could buy with the understanding or knowledge that
these standards that you would say of safe to use and would not alter the performance of tests.
That's what it was, but no mindless sort of work.
We set up systems to do it on a huge scale and then we did the same to Immunity and I managed to call up friends around the
country because people had been infected with and then we had these banks of Sierra that we could then test and rollout tests.
We developed a huge allies of test here, just expanding the likes of test.
So it's a particular way that you measure antibodies.
So this was invented many years ago.
So antibody target, something which you can say is an antigen.
If you mobilise antigen somewhere, you can bring the antibody solution close to the localised antigen, targeted binds to the target.
And then you have ways of detecting the presence of the antibody on the antigen target because it binds very tightly.
If you wash stuff away, you're left with the antibodies and you can get signals for its presence and you can put this into a whole range of settings.
And we did this through Clayton and I think you place it through a pretty to trace you've seen them but how does that
differ from the commercial antibody tests of which I've done one because of the UK Biobank them to finger prick ones.
It's a different way of presenting the antigen and operating the test.
They're all the same biochemical reaction behind it, but different representations of it.
So we've got the national testing for the COVID 19 epidemiological survey is run by the Office of National Statistics.
I can take you ensure that we run through 5000 to 6000 samples today just around the corner here
and test them on machines for the presence of antibodies to different parts of the virus spike
apart from the protein part and the beginning of the journey to doing that started with being
able to do the testing to demonstrate these various kinds of people have made we're ready,
almost uniformly hopeless. And on the side we started to make one that would perform to hugely improve support you with performance drugs.
And now we've got that now fully established as a test with all the regulatory approvals that run 150,000 tests a month, and it's absolutely not that.
So we're telling you because that's had to be used in a lab setting.
Can that. Yes. Yes, yes, yes, yes.
If you get 6000 samples coming to the hospital for this is more than the entire pathology service in this hospital runs a day.
Right. So you've got this. I'll show it to you. It's stuck.
My gosh. How did that happen?
And so and that work was going on very closely to Jordan, working with the government, trying to stamp things up and end it.
But at some point in this process, when it was quite early on, wasn't it?
It was early March when the government suddenly said, we're going to have to stop testing.
So we were doing the PCR testing. That was accuracy.
It's actually that's quite interesting. That was the huge. Sort of realisation that Public Health England wasn't able to deliver the services that
would enable testing and many of the the the components of the national response.
In fact, I think the organisation went through a minor collapse.
That's how we got involved. They couldn't process these samples within their management structure because we put them down,
because we use the people that we set up a system for doing it with very able people.
But the formal structures that they had, the response malfunctioned early on.
And one of the aspects of that was working with the NHS.
They weren't able to run our tests and that really was a huge interest in setting up these lighthouse labs and mega labs.
The decision was highly controversial.
It wasn't a very straightforward thing and there was a lot of rancour around it, like a local hospital was very upset about it, hugely upset about it.
But to do it on scale, you had to deliver the reagents and the tools to do it, swabs and all the rest.
And you had to stand up to the labs themselves, which we didn't really get directly involved in,
although we put a huge effort into making sure that the workflows functioned very well,
the tabulate tested those and put them on to the right footing.
So and I got to know some of those people very well.
As well as setting up things in the hospital because we have a responsibility and a job to do that locally.
So this wasn't really research. No, but it was a COVID response.
So just so it counts case. And so all those wonderful things we were doing and then we have lots of people around.
They were enthusiastic. We came to work every day. We worked, you know, a minimum of ten, 12, 14 hours every day, non-stop, all three weekends.
And you say it wasn't research, but there were papers published. I mean, I've seen the paper in which you published this.
How, how rubbish the commercial antibody test.
We published more stuff this year. So we, we drew together all the young researchers we have all the old ones as well,
everybody and we both teams, we've worked unbelievably and unrelentingly through this whole process.
And then gradually as we and then Sara got recruited to go and run or in this study as the chief investigator.
In fact, she sits next to her. So she she lives and breathes.
And then we started to build very substantial research,
focussed around along the lines of we spoke about getting back to the genomic kind of research.
We are working on that very intensively as a consequence of a charitable philanthropic donation from Article ten years worth of their cloud resources.
Unlimited to support. Genome sequence data assembly variant coding mutations emit another analysis storage around the world.
So this is this builds on your scalable pathogen pipeline platform.
And this is not all that's about that. Well, that was a very lovely little innovation that was made.
Out of tbe work we did.
We took the first very poorly designed, very poorly coded software for taking the sequences of TB, assembling them and identifying other.
Samples of TB the group very closely related and we could.
Quantify that relationship so that we know that that been recently acquired from the person.
For one of two people who had it, if you reduced it down to two, was a cluster that would require that somehow from each other.
And that became this unit one known for identifying outbreaks of TB and is known nationally and how you trace those people.
Test and trace and then how you could predict resistance and all of that work.
We were able to say just from the gene. Code analysis that you've got to suspect that one can use any one of the drugs safe.
You know, you've got a resistant one. Think about that a bit more, which we can do.
And that's a national service. We developed that it became very clear to us that we had to.
Change the paradigm and that actually we wouldn't be able to establish with
computational resources locally and many data centres or computer clusters,
we'd have to put the software to the cloud because it became very clear that we couldn't design and create software that reached industry standards.
So we started working very hard on trying to understand what you could do better and hoped that we
would eventually have a partner with some tech organisations that would aid and assist in doing this,
as you would say properly. And that has happened as a result of the pandemic.
And it was recognised that the code that we had written that would provide a
platform for running the tools could be run in any one of the big global clouds.
And that was called this piece. I don't know what it is, but it's a scalable pathogen pipeline platform.
And that was it. That's what the West is. You know, it's in the name but yet did.
And that was recognised as a as a. That's quite an innovative development.
The sad thing is that as innovative as it was,
it's not scalable because there's so many other attributes that go into designing something like that and coding it that make it scalable,
but which you mean you can put it on these cloud technologies and you can run in parallel, not just ten,
not just 100, but thousands and tens of thousands of these jobs simultaneously and bring them together.
So that requires coding and platform, that enables that.
And although this intended to do it, it didn't do it very efficiently.
It's interesting to see that of the experienced Oracle.
Now that we are learning that you're going to have to redesign a lot of that.
You have to refactor it. And you have to. Restructure a great deal.
And so we had the insights before the pandemic.
The pandemic came along. We can now do the thing that we think to do much better, massively, massively that we would have otherwise done.
So what? What are the questions that you can answer using that that particular technology in relation to the pandemic or in relation to this virus?
I don't think it's this is incremental. This is a massive step change in terms of what you can answer.
What it is a step change in is accessibility to it.
All right. Induction of cost. And it turns it into an everyday commodity for that and anywhere in the world.
Yes, it becomes agnostic. You don't have to have expert people to take.
It's taking. You know, it's taking A to Z out of London and put it into Jeeps.
That's what this is doing. So it's taking what a lot of people loved.
It's having something you can have a hold and feel and look at and understand the concern.
I could be rude about it and turn it into something.
But this is digital, this intuitive. Ooh. That's touching point.
So you've got people in Africa, Philippines, everywhere collecting samples and being able to extract it, to extract the DNA, presumably.
Yeah. There's a lot of yeah, a lot of hard stuff to do.
But once they've got a genome sequenced, the challenge was to take the genome sequence, as it implied, already assemble it.
And then once you've assembled mining for the relevant pieces, after you've got the complete assembly in place.
And then having done that,
that you can analyse it and then tested to demonstrate that it's performing in the way that you want to perform against some standard.
And we can do that now so that somebody's got this type of secrets or that type of
sequence or this kind of method of preparing it and upload the information to the cloud.
And it comes back with the answers. And that hasn't been possible without having an expert locally to do all of that stuff,
work on the command line computer and even write a bit of code to make it work.
This is. At Europe's. You want to go somewhere?
That's how you go. That I've got this DNA sequence.
What is it? Search thoughts. So the Oracle people are doing that work with with you, with group that we're providing.
It's a partnership, actually. There's a whole lot of things that they do unbelievably better than we can never do software as well as they can.
Although we are establishing a vehicle to address that.
They donate T to Oxford to provide the tools that enables you to do those same
decent analysis that they will provide the infrastructure on there in the cloud to
process it and the software that enables you to configure those tools and make
them scale so that you can go from a few at once to tens of thousands at once.
And so if you want to run a million of these sequences on the tools that are available most places in the world now to get the answers,
it might take you a month to run them.
The ambition is to have it so you could run them in a day. I don't think they will.
But less than a month away, much less than a.
To me, that's sort of voodoo stuff because it means highly, highly, highly skilled people,
of which there are not many that bring that together to make it perform in that sort of way.
And so that's that's the difference. I don't I don't even get you more massive insights.
You get more rapid turnaround. That would be incremental.
Yeah. Yeah. So, I mean, another project of yours, which was, I guess, again, to do with speeding things up is the land pool.
So did that come about? This was well, we work with Oxford Nanopore Company because they were quite very sweet and because.
They've been sort of local originally a local tech start up and it's really brilliant.
But they are annoying because they're so brilliant they can do all of this stuff.
But they've they've been being quite reasonably, not that attentive to detail things.
And of course, you tend to the new detail. They're getting much better at that, becoming a really professional outfit.
And and they have got to take the group.
Is more than likely to become the winning ticket at the moment to be it.
So let's just go back to the beginning again. We have to bear in mind listeners who might not know the background to this.
What what does that technology do? These are the technologies that take the nucleic acids or the DNA,
RNA of an organism and then mix and process that material to generate an output, which is the sequence, which is the genetic code.
And there are lots of ways of doing it at different levels with different machines.
You can do it on each one of those different sheets. That's it.
So in a very different way. And out of it would come the genetic code.
So it's like if you like listening to music, you could have a radio produce, you could have a tape recorder doing it, you could have a turntable disc.
And they've all got to have their own way of getting music.
And it's a sort of range of devices that sequence that are quite different, that give you a sequence.
And they they constrained by various limitations, each one of them,
that they could slow to make it difficult to run or expensive to run exactly the same audio equipment, in a way.
And Illumina is the most successful one.
So what you might say is that they were like the Sony Walkman dominated the world and other little might come along and leapfrog over them,
which is Apple. Well, in a funny way.
Oxford, Nanopore is a bit like Apple versus Sony Walkman, which still dominates the world at the moment.
I think that it's quite possible that that Apple will leapfrog because they've got some really huge advantages in terms of the speed,
the terms of the cost takes to do it in this sense that it it's it's tiny, tiny miniaturised.
It's small, it's fast, it's cheap. And what has been your role in the collaboration?
Oh, we just worked with them a great deal and published a lot of work on that, of course.
So when they came at that point, they said, look, we would be interested.
Were it's a really neat technology.
So you're testing it again to stop doing it. The government was invested in it and withdrew the investment and no idea why.
It's a story yet to be told possibly. So it was a very, very, very smart way of doing testing that would be no better than a PCR.
It would be faster than doing PCR, but just and it would integrate into into computer infrastructure,
probably better than PCR is actually, funnily enough, a waste of the sequencing technology.
So in some ways, as elegant as that solution was.
The more elegant things that nanopore can can do by but gathering sequence in a more complete and comprehensive
way to serve your lessons with lost San Francisco so is so the the land pool was great we did it very well.
We worked with Sheffield doing it and got regulatory approval, but it would never roll it out.
Are you still using it in your lap? No. You wouldn't do that by using the machine.
The machine sequencing machines are still dead. We still use them.
Yeah, we have just about for the UK Health Security Agency in our routine laboratory research.
We help you with the routine that set up SARS-CoV-2 sequencing.
So we setting it up to get trained in a standard way in the routine lab and that will process through this article.
Related. Cloud peace. And that's an experiment to establish.
Nanopore sequencing cloud results to.
Hopefully a pretty straightforward, seamless way.
So it comes off the sequence that goes through the cloud in about 15, 20 minutes.
Currently, it takes about 4 to 5 hours to run this stuff through.
And this is all got to do with having the compute and being able to parallel the witness data that you're running through that well,
it probably will do it good. Start with smaller scale stuff that's here.
It's likely that the Office of National Statistics samples that have the virus in it will get all sequenced,
and we will probably do that at the moment studying Northumbria, and they do it very well.
Um, but there'll be, you know, ongoing discussions where the Northumbria do focus on other stuff and whether we should do these research related ones.
Yeah, I'm, I think we're pretty neutral for what needs to be done from.
For Battlefield.