New Matter: Inside the Minds of SLAS Scientists
The official Society for Laboratory Automation and Screening (SLAS) podcast explores advances in automation, cellular imaging, big data and what's coming in the spaces between traditional scientific disciplines. Guests often include members of SLAS along with innovators, leading experts and other members of the global scientific community to highlight technology and even career stories. Episodes are released every week and subscribe to New Matter - available on all podcast players.
New Matter: Inside the Minds of SLAS Scientists
The Pixel System from CytoTronics | New Product Award Winner with Shalaka Chitale
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This episode highlights SLAS2024 New Product Award Winner Cytotronics.
Director of Biology at CytoTronics, Shalaka Chitale, Ph.D., joins us to provide an in-depth look into the award-winning product the Pixel System.
Chitale shares insights into the development and functionalities of the Pixel system, a revolutionary technology that combines cutting-edge electrical imaging with microplate-based assays. This system is set to transform cell analysis, enabling high-throughput, label-free monitoring and manipulating cells at a single-cell level and offering unprecedented insights into cell morphology, function and behavior.
Learn more about the Pixel System by visiting:
cytotronics.com/products
Full transcript available here
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Hannah Rosen: 00:00:04 Hello everyone and welcome to New Matter, the SLAS podcast where we interview Life Science luminaries. I'm your host Hannah Rosen, and today we are joined by Shalaka Chitale, Director of Biology at Cytotronics. Cytotronics won the SLAS2024 New Product Award for their Pixel system. So welcome to the podcast Shalaka.
Shalaka Chitale: 00:00:23 Thank you. I'm happy to be here.
Hannah Rosen: 00:00:24 Oh, we're happy to have you. So, to start us off, can you just kind of give us a little bit of your professional background and your areas of expertise?
Shalaka Chitale: 00:00:32 I have always been interested in biology. I got my PhD in molecular genetics and then during my postdoc I was actually working in phenotypic screenings in oncology. And it was, even though it was in academia, it was a very um, drug discovery focused lab. And actually, while I was at that lab, and this was a year before Cytotronics even got funded to exist, I connected with Jeff and Dwayne, the co-founders, and they found me through my LinkedIn 'cause they were looking for people with expertise in phenotypic screening and high content imaging, and those were all things I was doing. And they kind of told me about the technology and they were trying to get feedback about how to make it usable in the lab for scientists at higher throughputs, et cetera. And I thought the technology was really cool. So, a year later when they got funding, Dwayne reached back out and asked if I wanted to be a part of Cytotronics. And that's kind of how I ended up here and it's been a great journey. So, I think I was the second employee hired and now we are up to about 16 people. So, we're still a small team but much bigger than we were, and we've really had time to develop the technology and really be a part of it. It's cutting-edge science and we are continuing to do that and we're really excited to have people use our product this year.
Hannah Rosen: 00:01:46 Yeah, wow, that must have been really exciting to get in there, like, kind of really at the ground floor and get to see the company grow and I'm sure it'll just continue to grow from here. So that's really awesome.
Shalaka Chitale: 00:01:56 Absolutely. Yeah, it's been great.
Hannah Rosen: 00:01:58 So tell me, how do you guys feel about Cytotronics winning the SLAS New Product Award?
Shalaka Chitale: 00:02:03 It felt really good. So, SLAS was actually, uh, when we launched the Pixel officially. So, we were kind of excited to get other people to see it and we knew we were up for the award, but I think it only really sunk in when all the judges came by. 'cause they came by in like, groups and it was pretty intense. I, I think I talked to most of them, and we were like, going through it and we were on a timer. We had to talk about the product. So, it was like, getting used to talking about it to people as well. But I think mostly it was really exciting. You know, when you have a cool idea and there's this technology and you're like, I think this is so cool, but what do other people think about it? And you kind of need that external validation 'cause at the end you want other people to use it and it, it really felt like that. I think winning the award was a really strong validation of our approach and the technology in general. The whole team was really excited about it.
Hannah Rosen: 00:02:54 Yeah, well I mean that's amazing. That's really speaks well for your product, that it's kind of kind of the first time that you're really out there officially presenting it and to win an award through the whole process. It's a real kind of trial by fire. But yeah, like you said, it's real validation that this is a great product. So, you said that this was kind of the first time that you guys were really promoting the Pixel, talking about it with customers. So, you know, like, I'm guessing since this is kinda your first time promoting the product, that this was your first time at an SLAS conferences as vendors and, you know, what was your overall experience? What was the reception like uh, to the product?
Shalaka Chitale: 00:03:31 Personally, I was amazed at the scale of SLAS. I think I knew it was big, but I wasn't expecting it to be that big. So, Dwayne from our commercial team actually went to SLAS in San Diego last year, but we weren't presenting. He was kind of scoping out. Right.
Hannah Rosen: 00:03:45 <laugh> Doing some recon.
Shalaka Chitale: 00:03:49 Exactly. <laugh>. So, this year I think it just, it was very productive for us as a company. I think we just talked to a lot of people from academia, industry, pharma, biotech. There's just a wide range of people and it led to a lot of productive contacts, and I guess at the heart of the technology we wanted to be high throughput and automatable. So, to be on the same floor with all these robotics technologies, it kind of like, puts you in the same space. So, it was really cool. The first time I walked onto the exhibition floor, I was very taken aback at how big it was. I've never actually been to the Boston Convention Center before <laugh>.
Hannah Rosen: 00:04:25 It's big, it's a big convention center. Yeah, it takes you like 10 minutes to get from one side to the other.
Shalaka Chitale: 00:04:32 I was exhausted at the end of three days <laugh>, I was like, I’m done.
Hannah Rosen: 00:04:35 Yeah, so gets your, gets your workout in, that's for sure. So, um, you've mentioned, you know, that this was your, your company's first time really kind of showcasing this product, the Pixel. Can you briefly describe for us, you know, what exactly is the pixel? What does it do?
Shalaka Chitale: 00:04:54 So, the Pixel is taking our electrical imaging technology, uh, and that the technology is based in microplates. So, we kind of have a 96 and a 384 well microplate and the way we've structured it is that most of the recording and measuring technology’s all on the plate. So, we think of the plate kind of as the instrument and then the Pixel has the plates which are of two sizes. And then we have readers of two sizes as well. So, you can either get a single plate reader that's really easy to use, plug and play, you kind of put it in your own incubator or if you want slightly higher throughput you can get a reader that's a eight plate and it's a benchtop incubator. So, it has its own integrated temperature climate control essentially. And then to go with the plates and the readers, we have the software package, which is an important component and we've kind of gone with a web-based approach. So, the entire software is a web app, so you can control your experiment and monitor it remote, which as an experimental biologist who's very rarely been able to work remote, that's huge.
Hannah Rosen: 00:05:54 <laugh>. Yeah.
Shalaka Chitale: 00:05:55 On the weekend you can just monitor your experiment as it's running, you don't need to go into the lab. And then of course we have the data part, 'cause the data we are generating is really complex. So, we also have a data analysis part of the software which lets you visualize the data, plot it in different ways, export it for analysis elsewhere, things like that. So those are kind of the three components of our Pixel system.
Hannah Rosen: 00:06:17 That's so awesome that you have that remote monitoring capabilities because I feel like, you know, as we start talking more and more about, you know, these concepts around the lab of the future and what do we want and especially after the pandemic, this idea of remote monitoring and, and you know, being able to not have to come in at three in the morning or you know, on the weekend. So that's, I'm sure a lot of people would be really excited about that feature. <laugh>.
Shalaka Chitale: 00:06:42 Yeah, it's great. Although the, the downside is you can even put it on your phone, I haven't put it on my phone, but our CEO has, his wife has a rule for him that he's not allowed to check any experiment after 8:00 PM <laugh> because it's like, if things are going wrong you're like, oh no, you're worrying about it at home.
Hannah Rosen: 00:06:59 <laugh> That's a very good point, you have to set some real solid boundaries for yourself when you can take your work home like that <laugh>. Yeah. Or your wife will set them for you it sounds like <laugh>. So, I'm wondering, you know, you you, you mentioned that you have these two different sizes of the microwell plates and then you also have these two different readers. Can you use both sizes of the plates with both readers or does one kind of go with the other?
Shalaka Chitale: 00:07:24 No, you can use both plates with either of the readers. So, it's really a matter of like, what you want to do and I think that's kind of the flexibility that you can change what you wanna do halfway through and that's fine, everything is gonna be compatible. So, I think the thought process is that people will start with a single plate reader, and you can develop your assay, you can develop in 96, you can miniaturize it further as you want, but then once you're done with that it's really easy to scale up. So, it's just a matter of doing the same thing in multiple plates that you can run at the same time. So, you don't have to kind of redevelop the assay to be compatible with the high throughput but it's already compatible with the high throughput.
Hannah Rosen: 00:07:59 That's fantastic. So, we've already talked about a couple of these innovative aspects of the Pixel. Can you go into a little more detail about what it is about this product that really does make it new and innovative on the market?
Shalaka Chitale: 00:08:11 The main point I think that really brings it home is the fact that we are basically combining multiple biological instruments into one. So, we use electrodes to monitor the cells. The spatial resolution of our electrodes means that we are monitoring it at a single cell level, which already puts us kind of, you know, in the whole single cell arena. But then at the same time we can, not just measure, so we use impedance measurements to measure morphology and function of cells. We can layer that with electrophysiological measurements to measure function and cardiac and neuron cells or electrogenic cells in general. But then we can add metabolic measurements on top of that as well. In addition to measurements, we can also actually manipulate the cells, so you can selectively kill cells or even use it to generate little holes and use it for delivery. So, we are really just combining maybe five systems into one and it's scalable. Like I said, it's really easy to go from a single plate assay to a multi-plate assay. And we're really building the system to seamlessly integrate into your existing automation so that you know, everything that you know about your assay will still hold, but it's more like instead of running five different assays, you just ran one and you can do it much more easily.
Hannah Rosen: 00:09:20 Yeah, that's fantastic. I mean all those capabilities you just outlined, that's, that's a lot <laugh> but is doing a lot of different things.
Shalaka Chitale: 00:09:27 It is a lot, and you can kind of pick one or the other or pick all at the same time and like, I think that's really, you know, what makes it really flexible and makes it applicable across a wide range of areas.
Hannah Rosen: 00:09:38 Definitely. So, you said that this system uses electrical imaging. Could you maybe just describe a little bit about, you know, what is electrical imaging, how does that compare to other live cell mapping methods and what are the advantages of using this new system?
Shalaka Chitale: 00:09:54 Absolutely. So, myself, I'm from an optical imaging background and I think it's easy to put it in terms that are similar to optical imaging, which makes it easy for people to understand. But essentially in optical imaging you're using light to look at different things about the cells. In our case we are using electrical fields. So, because cells have lipid membranes, they're gonna distort electrical fields in various ways. So, for our morphological and functional features, we're actually using electrical fields to generate information like cell viability, cell barrier, blackness, attachment, motility. So, because we can do our measurements over time, we can also extract time dependent manner information and we can combine modalities. So, some of these things you can also do with optical imaging, right? But in our method, it's completely label free. So compared to optical imaging where you would have to add maybe a fluorescent label, you can do bright field imaging, but it's not a lot of information usually.
Shalaka Chitale: 00:10:48 But we have a lot more information label free. Our methods are completely non-destructive. And I think the biggest point is that you can scale up without any compromise. So, in optical imaging time is always a limiting factor. So, the more time you take per plate, the less time you have to do the number of plates. And then you know, you can't take five hours to image a single plate because then your cells have changed while you're imaging the same plate. But in our case, each scan is taking, so, either under a minute or like, depending on if it's some EFs measurements, maybe two minutes. And no matter how many plates you add, everything's happening in parallel. So, it's not, you don't have to compromise, you don't have to say, okay, if I have more plates, I take fewer measurements or something like that. So, I think it really gives you that live cell advantage without any of the compromise that you need to do in optical imaging. And then of course you're generating unique information. So, a lot of the functional measurements we do, you can't see through optical imaging and then measuring electrogenic cells for example. I mean you can kind of do it some methods but you, you can't make them in parallel the way we do.
Hannah Rosen: 00:11:53 Yeah, I mean that's, that's really cool especially with the, you know, the nerve cells and the heart cells and, and sort of, you know, this electrical imaging, it doesn't interfere with the electrical capabilities of the cells at all?
Shalaka Chitale: 00:12:03 No, not at all. So, the voltages we use are very low. So, they don't interfere with any cells, not just electrogenic cells. On the other hand we can up that so we can use this electrodes to stimulate cells if we want to. Um, so you can actually selectively stimulate a neuron then and then see what's happening to its function or you can measure it non-invasively and see what it's doing by itself.
Hannah Rosen: 00:12:24 Wow, that's pretty amazing that you can have that, such refined control over it. Are there any like, caveats to using this system? You know, are there any cells that it doesn't particularly work with or any, you know, drawbacks?
Shalaka Chitale: 00:12:39 One of the caveats, and I always say this, is that if you're looking for something super specific subcellular, so for example, I think one of the things people look at is like mitochondrial function and you have really good dice for mitochondria, you can use them. It's unlikely that you'll pick those things up with our system just because our resolution is at a cellular level, not quite subcellular. If it's causing a bigger change in morphology you might pick it up but then the better method to study it might just be using your existing methods. So far we haven't had any caveats in terms of which cells you can use on it. You can pretty much use any cells on it, but of course you have to use our micro plates and our micro plates are glass, not plastic, which a lot of people use. So sometimes you need to modify assays or like, modify the ways you plate cells for them to be compatible. But like I said, so far we've done 30 plus types of cells including primary neurons, primary cells, IPCs, and we've been able to make them all work. You know, sometimes if we get a protocol from someone that's for plastic, maybe we have to tweak it a little for glass, but in the end it works.
Hannah Rosen: 00:13:45 So it sounds like, you know, in terms of the resolution that you're getting with this electrical imaging is more on the cellular and, as you said the, not the subcellular. So maybe not like, a replacement for techniques like cell painting for example, but for maybe more like whole cell imaging?
Shalaka Chitale: 00:14:01 Yeah, kind of. We actually did a comparative study with cell painting specifically for profiling. So going in, my expectation was that they're just two very different techniques, you know, so the types of data you see are different. So, the types of differences you can resolve are also gonna just be unique and that's essentially what we found when we did a comparative study. So, there's a whole overlapping set of compounds that we could identify, and cell painting could identify. And then there were some effects that you could see only through electrical imaging and then some that you could see only through cell painting. So, they, they're very complimentary approaches. I would suggest you use them both and that's generating the most amount of data. But of course, sometimes the one is better than the other for your particular question.
Hannah Rosen: 00:14:41 Yeah, that's very interesting. Mm-Hmm <affirmative>. So, speaking of that, you know, are there any types of research that the Pixel is really ideal for?
Shalaka Chitale: 00:14:50 So we've seen a lot of pull for applications in with neurons and cardiac cells specifically because the existing methods can only measure function and they can't look at cell structure and function at the same time, which we can do. But in general really any process where cells are gradually changing over time in phenotype and that, there's a lot of those I guess, but for example, anything in toxicity, you know, where the cell behavior is changing or in IPSC differentiation or, you know, where you create disease models where you're expecting your cells to go from one phenotype to another. All those are really great to be starting on this platform. And I think, you know, the time dimension that we are adding, it just lets you see things that you've never seen before. Like, I'm regularly surprised by the data we see and I'm just like, this is amazing. I've looked at it with optical imaging, but I've never really looked at it with so much detail.
Shalaka Chitale: 00:15:36 The other case I guess is like, anywhere where you have very precious samples. So, I think for primary cells or patient samples where, you know, you have very limited sample and you want to extract as much information as you can from one experiment, in that case I think, you know, this is the way to go because you can, it's, since it's non-destructive, you can also just extract as much information as you want and then use those cells for something else after. So, I think it's like a great first step for applications like those.
Hannah Rosen: 00:16:11 Wow, that's amazing. And it sounds like you're generating, you know, so much data through this system and I was wondering, I don't remember if you mentioned this earlier with the software that you are providing, is there any sort of like data analysis or data management that goes along with that?
Shalaka Chitale: 00:16:26 Yeah, so the data actually gets uploaded from your Pixel system straight up to the cloud. And so, we have some buffers so that if you lose internet connection you're gonna be okay <laugh>. But essentially the data gets uploaded to the cloud and then the raw processing happens there. And then we have a whole interactive web app where you can extract your data and that's kind of where our data science team comes into play where we are really figuring out what is the easiest way to let biologists, so people like me, look at your data so you know quickly whether what's happening in your experiment, you know, so you kind of wanna boil it down to the most important features and like, how can you look at them in a video? And we found that actually videos are the best way to look at things 'cause your eye picks up changes really easily.
Shalaka Chitale: 00:17:10 But then you can also generate traditional plots to do any type of analysis. What we are building out is to be able to do a high dimensional analysis of your data. So, for people who have access to data scientists, which is not everybody, we make available our notebooks. So, we might not have a fancy UI attached, but the, you can actually build your own analysis pipelines in Python to analyze the data and that again happens through the web interface so that you know the data's already curated but then you can analyze it as you want. So, we really want people to have options when it comes to data analysis.
Hannah Rosen: 00:17:43 Yeah and that's nice 'cause that gives people the flexibility 'cause people may have like, a system that they're accustomed to using that they, they really like and it's nice that they're not gonna be forced to transition or learn something new.
Shalaka Chitale: 00:17:54 Yeah, exactly. Yep. We kinda wanna make it accessible to every level of user. So, someone who's in the lab and who wants to just say, Hey, are my cells alive? But then also like, you know, a data scientist who's asking maybe more complicated things of the data.
Hannah Rosen: 00:18:09 Yeah. So, what inspired you guys to create the Pixel?
Shalaka Chitale: 00:18:12 That's a great question. So, I actually asked Jeff this question before I came in here 'cause I was like, from a technology side, what inspired you? And he actually worked on this um, during his postdoc and this entire technology kind of existed in a single chip format and they were at Harvard and talking to people from the Broad and they really wanted to do it in a high throughput and so they put it in a 96 well format and I think that's where it started. And then we've just kind of built off of that. You know, the more, sort of, experiments we run, the more we discover we can do with the system, and we have a really strong internal biology team, so we are really thinking from a user perspective. So that's kind of where, you know, this low throughput and the high throughput options, they all come into play from things we are thinking from a user perspective because we really want everyone to have access for it, and for it to be easy to run. I think that's definitely my top priority 'cause I've worked with instruments in the past that have been really easy to use and then some that have been really hard and it just changes. Like you, you know, even if it's the best technology ever, you're not gonna use it if it's just too hard to get started. So, we wanna make it really easy in the Pixel system specifically. We've designed that system with that in mind.
Hannah Rosen: 00:19:25 Yeah, that's fantastic 'cause yeah, definitely. You know, adoption is a huge thing and yeah, I've said this before, you can have the best technology in the world but if you can't get anyone to use it, what good is it <laugh>?
Shalaka Chitale: 00:19:37 Exactly. Mm-Hmm <affirmative>.
Hannah Rosen: 00:19:38 That's great. Well, I mean it sounds like you guys have already accomplished so much with this technology. So, looking towards the future, you know, what are you guys looking forward to accomplishing over the next year with the Pixel?
Shalaka Chitale: 00:19:49 So at SLAS we actually launched the single plate reader of the Pixel and then later this year we're gonna launch the eight plate version. But this year we are calling it the year of the beta. So, we really want, we are signing up beta users, so we kind of have a limited number of systems that we're offering and we want people to just get their hands on it and start playing with it. And everyone has a completely different application in mind. So that's really gonna like, generate a lot of data. We want to be very hands on in helping people get started on it, especially with the data analysis part. And we really want to learn from our beta users to refine the product. So like, you know, for the next year, I think that's really what we are focusing on and, you know, just refining the product based on user feedback, refining the software and getting it to a place where early next year we are planning to launch the fully automated version of the eight plate reader. So that'll be compatible with robotic arms, and you can just put it right next to all your other instruments and then just forget about it. And so that's taking, developing it from a eight plate manual to an eight plate automated is also gonna take some effort. But that's kind of where we are heading to early next year.
Hannah Rosen: 00:20:58 Wow, that's fantastic. Mm-Hmm. <affirmative>, can you tell us a little bit more about this beta program and how, if people are interested in participating, is there a way for people to get involved?
Shalaka Chitale: 00:21:07 Of course. So, I mean, contact us <laugh> through our website, through our contact form. But what we're doing is really talking to people who are interested, talking about the technology in detail and then the beta program is kind of like a try it and buy it. So, we are actually offering people a set amount of time to play with it and then decide if they like it. If they don't, they can ship it back to us. We are hoping that they choose to keep it of course <laugh>, I think they will and it's across a wide range of functions. So like I said, we just, from a manufacturing perspective, we are taking limited beta users, but we're still very, very open to collaborations and I would encourage anyone who's interested to visit us virtually, but also we're located in Boston and we love having people over to really show them the technology, you know, in person. 'cause it, it looks really cool. <laugh>.
Hannah Rosen: 00:21:55 <laugh>. That's awesome. Mm-Hmm <affirmative>. So as researchers are out there, you know, listening to this and they're interested in, in this technology and maybe giving the Pixel a try, is there anything that they would need to know about, you know, adapting their assays or their cells or sample preparation? Anything that they would need to know going into it before they really get started using the Pixel for their research?
Shalaka Chitale: 00:22:18 I think any assay that someone is currently running in a microplate format is essentially compatible with the Pixel. And I would say that any protocol you're using to seed your cells, grow your cells, any coatings, chances are that's all going to be compatible. But you're gonna generate data, well just more data and it's often very unexpected. And that's happened to us in a lot of assays, which we've regularly run in other methods or even over the past year we've been doing some pilots with pharma partners, and again they've wanted us to run assays that they're running in-house, but then we run it on this technology and just because we have this added resolution and different types of information, we just come up with unique insights and I think it's really easy, like I said, to get started, it's plug and play. So, I would encourage anyone to try it and you might be surprised by what you see and it, you know, more importantly, like, you can change the types of questions you're asking because you have different data. Like, if you had no way to measure it, you wouldn't ask those questions, but now you do. So, get creative I guess.
Hannah Rosen: 00:23:19 Yeah, I love that. It's funny, it's like, get prepared because you're gonna get more data than maybe you wanted and you gotta be ready to to use that data. That's so funny. Uh, well Shalaka, thank you so much for joining us today. It's been really exciting to learn more about you and Cytotronics and the Pixel and uh, we were just so excited to have had you at SLAS2024 and have you be one of our New Product Award winners. It's really, the Pixel is a fantastic product and we really can't wait to see you guys at future SLAS events and see where this technology goes.
Shalaka Chitale: 00:23:55 Thank you so much. Yeah, we're excited as well. We'll definitely be at SLAS next year. Yeah, can't wait.
