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So my name is Charlie Moffet.
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I'm from HighRes as the intro had and I'm going to give you just a quick intro on what HighRes Bio is all about.
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Is there anybody maybe just show of hands that works in an automated lab or has worked in an automated lab, aspires to work in an automated lab?
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OK, I got my work cut out for me.
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So I'll give you a quick intro on what our company's about and then more importantly the direction that we are moving towards in creating the lab of the future, lab of tomorrow.
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So just a little background on us, we are committed to accelerating the laboratory work environment in terms of progress consistency, data management that everybody sees and is dealing with on a regular basis.
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And with that creating consistent workflows through the various devices that they are operating in a lab environment.
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And so we do this both from a hardware and software perspective.
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So a little more background, we could base HighRes on three pillars of how we operate. This being innovation, accessibility and then reliability.
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So touching on the first one innovation, we are company has been around for 20 years.
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We've seen, like to think anyway, we've seen and tried and done everything and for the most part, we integrate other people's devices and technology that are out there.
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We don't like to reinvent the wheel.
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However, there are always instances where we find gaps and people need to fill that gap somehow.
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And if there's not something out there already, then we'll try to do something on our own.
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So we do have a few of our own devices, but we try to also be as agnostic as possible and integrate other stuff that's out there, especially if it's the customer's preference already.
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For accessibility, this is creating a system that is available to anybody.
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So whether it's a little academic lab or a 10 site global pharmaceutical company, we like to think we have something for everybody.
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So relatively cheap and inexpensive, easy to operate devices and then enormously complex devices as well, and everything in between.
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And then reliability, as I mentioned, we've been around for over 2 decades.
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Actually this month marks 21 years and some of the key products that we have been on patent now for the better part of 18-19 years.
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And if anybody wants to know, we're based in Massachusetts, just north of Boston in Beverly.
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So looking at the lab of today, or for that matter the lab of yesterday, what we typically see or experience from others is a very disjointed, fragmented, siloed environment.
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I often times use academics as a classic example for this because that's often times how they operate.
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Everybody has individual budgets.
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They develop their own skillsets within a lab, irrespective of what the people right next door are doing, which could be totally complimentary or maybe even the same, but they'll still spend lots of money buying equipment, learning how to do something in that lab without ever talking to their neighbours.
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Obviously very inefficient, especially on a global scale.
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You could spend lots of time and money to do the same thing over and over again inefficiently.
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And then as you might imagine, execution on that, you're going to have lots of different inconsistencies in the pathways because this group's going that way, this group's going that way, this group's going that way.
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And as you might imagine, when you get to the analysis stage now you have three very different results all put together, especially when you're trying to find that blockbuster drug for your company.
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You got a mess and at some point you're going to have to go back and do all that work over again because the data points don't align.
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Everybody relate to that much?
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I see one person nodding.
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That's good.
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So the approach that we're trying to take is bringing all of that together.
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And so part of that is forcing people to actually talk to each other, but it's also implementing hardware and software programmes such that the data and the workflows start at the same point, integrate at the same point.
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Whether it's LIMs, lab notebooks, analytical software, and then the data on your server or cloud or whatever ends up at the same point and is and can be parsed the same way and everything.
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So if we just pull the three points that we had from the lab of yesterday and look to the lab of tomorrow, now you have systems that are designed to do specific tasks.
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You could have in theory, a person that is proficient at using that.
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And now everybody in the company can go to Bob.
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Bob's going to run it correctly the same way and everybody's going to get the same data.
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Execution on that's going to be a lot easier and a lot cheaper because you already know what you have as a starting point and what the finish point should be.
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So it's almost plug and play.
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Execution should go from several months to maybe hours or days.
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And then the final point is analysis.
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So like I said, all that data has been either stored, parsed, metadata, pieced together the same way.
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So and is located in the same spot.
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So it's easy to find, it's easy to pull apart, you can get stuff as you need it as opposed to having to run to different departments, different databases, whatever, asking for access.
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So how do we do this?
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So just from a software perspective, we do have Cellario Scheduler, and this runs our local platforms, which I'll touch on in a minute.
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But we've also implemented CellarioOS.
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This is a cloud based orchestration layer of software.
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It's probably three years on the market now.
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We had a few beta customers that have been using it, big pharma, big biotech and but it's been a bona fide product for the last couple of years.
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And with this, now you're able from a single dashboard view everything that's going on from one lab to one or one location, 1 country, whatever the case might be, see the assays that are going on, the inventory that you're working with, the data that you're working with.
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And that software is going to be tied into your LIMs, your electric notebooks, your analytical software.
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And one of the cool things really what I'll say, one of our customers kind of forced our hand down this or forced us down this path is the original intent for OS was to integrate our work cell systems.
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So for companies, I don't know, you could pick Johnson and Johnson, let's say they might have 30 systems globally of ours.
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They would be able to tie them all together through the software.
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OK, that's great.
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We had a customer, they have a handful of our systems 8 and they thought, you know what, we don't need the software to control that.
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We know how to control your system because it's organised already.
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We need to control and track all of the offline systems, all the standalone devices.
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There's no tracking whatsoever as to when Bob went there, how many plates you ran, which barcodes maybe you could get that eventually and then when it was all finished and where that data went.
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So we have implemented another portion add on let's say to CellarioOS where you're not only able to do actual workcells, you could do other companies workcells for anybody that might have some of our competitors products.
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And then certainly any standalone devices can all be intercalated and run under the same environment.
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So again, you could sit on a dashboard and you can see exactly what's going on in Spain, San Diego, Saint Louis, whatever you want.
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So that's on the software side.
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If we look at hardware, which I don't want to skip over too much, we generally start with a work cell that looks something like this.
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So often times a robot in the middle, it could be on a rail, it could just be on a pedestal on its own.
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For the most part, we implement Brooks robots.
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They actually have a table upstairs.
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I argue we're one of their biggest customers.
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And then with that, we have Cellario Scheduler that is tying together for your assay and specific to the workflow that you have all of the other devices, and our applications team primarily will help you determine which of those devices and sometimes how many of those devices need to be around it.
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So you know, you might have a reader or something that's an hour long read.
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Well, if you want to do 100 plates a day, that one reader is going to be bogged down.
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So you're probably going to need 4 of them.
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We'll be able to simulate all of that in Cellario and put together a works out that's going to get you where you are now to where you want to be.
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So we did our own incubator.
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We have our own liquid handler, other third party devices, whatever it takes.
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We're not opposed to using other people's equipment as well if somebody wanted to put a Hamilton liquid handler on there, for instance.
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So we try to be as agnostic as possible.
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And so I'll give you a quick use case, Apologies, I didn't have the animations on the version I was practising on.
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So we had a customer come to us wanting to do a high throughput purification platform.
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So they had really just a list of processes that they needed to fulfil without a lot of the devices that would work in an in an automated environment.
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And there just happened to be lots of things that aren't automation friendly.
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And so we teased out all of the information we needed to put something together.
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And in this instance, their biggest issue was that a lot of the steps are very long.
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And so if they wanted to achieve X number of plates a day, they wouldn't be able to do that in an 8 hour day because they have some steps that are an hour and a half long.
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So you really needed to go into that second, third shift ideally over the weekend as well.
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So what we call 24/7 or unattended runtimes.
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And that was the challenge, right?
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So we do our research on our end and then ultimately we'll put together a design with a series of devices that will work for them and as I mentioned before, with our Cellario Scheduler software, be able to simulate exactly what they can expect on that platform as they start to run it with all of the, let's say, perspective times.
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What's cool about that is as the device, once it actually exists, not just a 3D model, you can get real time data on how long that incubation step really is and then start to plug that into your simulation.
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So it's learning as you do future simulations based on real time, real life experience.
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So in this case, they were ultimately able to get 24/7 operation on a platform that did vial tearing to an initial QC step, purification, solvent evaporation, a quick way, solubilization, a final QC and then aliquot.
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And they were pretty excited about that.
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I think that system's been up and running for about a year, maybe year and a half now.
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So, and that's the end of my slides.
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So I'll let Jay finish this.
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So in most automation suites there is, as Charlie mentioned, one of the steps is typically there's an evaporation step.
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Typically it's at the end of the process, the workflow or the process.
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It does traditionally take a fairly good amount of time to do the actual evaporation.
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So often times our Genevacs and or other evaporators would be put into an automation suite as just a final step and usually a manual step.
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But in the last couple years, Genevac has collaborated with HighRes and also other automators to offer the new Genevac Easy 2 Bionic.
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What you see here on the right the system was designed to be automation as well as sample friendly.
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I can handle most common solvents that most of our customers will use.
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It can even handle HCL.
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You can do high boiling point solvents as well as fast lyophilize aqueous samples.
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So it is designed, it does the things that all our traditional systems do in med chem labs and in purification labs and things like that, does it quite well.
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But this system was designed specifically to be a little bit more automation friendly.
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The unit can be operated in remote, it can be operated in manual mode, which offers you consistency for your product as well as repeatability.
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So you're going to get the same result every single time you use our systems in the concentration or the dry down step.
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Really that's it.
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It's Genevac is the world leader in evaporators.
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We've been making them for over 35 years.
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We only make evaporators.
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So all our R&D goes into making better evaporators.
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We're sample friendly.
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You're not going to, when you use a Genevac system, you're not going to overheat your sample.
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You're not just not going to be any cross contamination because we have built in methods that prevent bumping and cross contamination and now we've incorporated that into these automation suites as well.
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So we are here at the show up in booth 51.
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If you have any interest in seeing an easy two, we have one on the bench.
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We'd love to show you the benefits of it.
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And if you have any questions, this is our local sales team for each region.
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And again we are here up in booth 51.
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So if you have any questions, please let us know.