Hemdeep: Welcome to Big Ideas in Microscale, the podcast where we explore groundbreaking research happening at the microscale where micro innovations makes a big impact. We’re excited to showcase the incredible work being done by our users from around the world who are pushing the boundaries of microfluidics, lab on a chip, organ on a chip, and beyond. Through these conversations, we hope to learn from their experiences, uncover their insight, and bring their big ideas to wider audience. So whether in a lab, on the go, or just curious about the future of microtechnology, join us as we dive into big ideas at Microscale.

Hemdeep: Welcome back to Big Ideas at Microscale. I’m Hemdeep, your host and co-founder of Creative CADworks, CADworks3D, and Resinworks3D.

Robin: I’m Robin, co-host and technical writer on the marketing team. Over the last two episodes, we’ve been in conversation with Chen Li, a PhD student from McGill University’s Cellular Microenvironment Design Lab, following his work in bioengineering and organoid research. In part one, we explored Chen’s early research into hydrostatic pressure and epithelial cell differentiation. And we also got a behind the scenes look at the quirks of his academic lab life. including his knack for suspiciously breaking equipment.

Hemdeep: Then in part two, we took a deeper dive into how his team used custom hydrogel-based pressure sensors to build and test more realistic 3D models of tissues.

Robin: If you missed those episodes, we definitely recommend going back and giving them a listen first as they set the stage for today’s conversation in a big way. In this final part, we shift focus from experimentation to innovation. Chen shares how they repurposed a microfluidic model originally intended for placenta research to enable better access to organoids and allow for realistic pressure gradients.

Hemdeep: We’ll also get into how 3D printing has revolutionized their prototyping process and how Chen’s entrepreneurial spirit led them to co-found LabGiant, a platform designed to help labs share equipment, designs, and expertise, much like open source software communities. This episode is more than just organized. It’s about building the future of research, democratizing lab access, and rethinking how collaboration gets done.

Robin: For the full experience, check out the visual aids linked in the show notes. Whenever you hear this sound, that means there’s a visual to follow along with and a timestamp to match the episode. So, let’s get back into big ideas at Microscale.

Hemdeep: So there is, think, ⁓ a fairly famous paper discussing the controlling pressure differentials in 3D organoids written by Nikolov. How did that paper ⁓ inspire the project and the device that you’re creating right now?

Chen: Yeah. So that paper is really, I think when we saw it was, we were able to get access to the lumen side of organoid and the outside of the organoid. Before that organoid would just be a comp of cells and which have a lumen and it’s just enclosed and it’s not accessible. Like when you think about a real organ, real organ are always accessible to the lumen. That’s how they have to function. So with that kind of model, in which you can have access to both sides. Then I think that would allow us to do a lot of studies that would be more accurate and relevant to the real world. I first started working out for another PhD student that already graduated. His idea was to make placenta models within those device. Unfortunately, we never got it to work well before he graduated because it’s actually very hard to laser. shape a pattern inside a Hydro gel. It took us a while to kind of get something to close, but not enough for that patient to use it for a person in the model. But then we saw like, oh, like we could use it for my project because now we have access to both sides. Then it will be very easy to regulate, try to find a way to induce a pressure that would have an effect on one side or the other. Because before that, if you just put organoid under pressure, it will kind of just equalize on both sides. We wouldn’t have like a gradient of pressure across the membrane and that’s what we really need for my project.

Robin: So for the Placenta project, that was just your regular clump of cells. Is that right? And then now you have your unique shape that you kind of developed.

Chen: for placenta project was we didn’t get the anywhere except for putting some cells inside the whatever the shape that we carved. we didn’t really grow anything like an organoid. But right now the plan is like to see if you could replicate that paper, which is actually a lot harder than we thought to do. We thought it was, which is always like that when you try to replicate a paper and then see if you can find a way to induce that pressure. somehow very easy with a liquid column, for example, on one side or the other.

Robin: So I’d advise then that you’re trying to replicate. Are you fabricating in the exact same way or do you have your own methodology for that?

Chen: Yeah, actually that’s where the 3D printing comes in ⁓ handy, right? Like before to get anything to fabricate something of that resolution, especially there’s some micro pillars involved that holds the hydrogel, the collagen together. For those kind of features, you really need SU-8 to create the mode to get anything at that resolution. That’s why actually we decided to buy the Prophiletics 3D printer. It’s because it was so that we can make a very high resolution PDMS device. That’s the approach that we pivoted to to make those device from now on, which I’m super glad because those SU-8 mode that we had, only two of them worked out of six. The productivity was very low, right? Like every time I could only get two device to work out the six mode that I have. And if there’s something you want to iterate, you can do it that easily on SU-8. Use the studio printing, crank out another mode. if you have a feature that you want to test, it’s very easy to iterate.

Robin: specific device, like what was the time difference between the SU-8 mold versus like the 3D printed mold?

Chen: I was fortunate enough to not having to make those S8 modes. It was from the PhD student that graduated. But I know that he spent a long time with a lot of alignment process. He had to build his own device to align the mask. It’s a huge pain.

Hemdeep: Did you find when you started using 3D printing that you can now deploy different strategies of orientating certain model features or exploring other features in the Zed or anything like that on your side?

Chen: Yeah, actually, for example, some device, not for a PDMS device, because PDMS, I think we have just a high limit before it becomes too hard to peel off and make. But some existing, just like a one-piece device, then yeah, definitely. can all think that before you have to add, let’s say, for my liquid column, you have to of piece something else, like a tube or something to it. And now I can just print it directly in that direction. But in terms of a microfluidic device, we’re still limited by the mold that we’re making. If it gets too tall, then the PMS piece doesn’t come out as well.

Robin: So for the columns, you said you also 3D printed that?

Chen: No, that’s actually for another device, one of the side projects that the RPIs are making us do. And we use a lot of 3D printing for that device. It’s basically we’re trying to integrate a membrane on which we can culture the device. So maybe I could use it for my project. I don’t know, maybe. We’re trying to integrate a membrane inside a microfluidic device that’s directly printed using 3D printer. Yeah, for that to induce the flow, we’re thinking to just use a liquid column. And it’s super useful that we can just print it directly. instead of having to add another liquid column.

Robin: Is there a reason why you chose to 3D print it? It’s just like out of convenience?

Chen: Yeah, I don’t think there’s other ways to make that device at this point. So it’s convenient. Our hope is to eventually put a 3D printed device in all the biology lab so that every time we make something new, we can just send them the file and the protocol, and they could just get the device, print it out themselves. So we try to make it as easy as possible to make, like no surprise. party and the component and things like that. So ideally it would be a one piece. They just click print and they can get the device that we developed for them to use.

Robin: Essentials Syncs, we’ve talked to a couple of other researchers, and they all have that same vision where you can share devices amongst each other. Because now it’s digital file, right? And as long as you have a 3D printer that is able to print that out, it’s very now easy to share that knowledge and build that community around it.

Hemdeep: Have you noticed, is there any sort of limitations that you still find with 3D printing that you wish could be areas of improvement? I know that there’s ⁓ always a need for new materials. That I think has become one of the biggest things people are always asking about. But what is it that you would like to see improvements in 3D printing?

Chen: The biggest one is definitely the need for new material. Like for our field would be have those resin that’s biocompatible. That would be very useful. Yeah. There’s a lot of, you know, think progress on that recently. I’ve seen paper getting out about those clear biocompatible resin that the lab make themselves that still seems to achieve like a high enough resolution to be useful. That’s for sure. Like the biggest one. Now that I’m thinking about it, I could see improvement maybe for like resin specifically. That’s what we’re trying to figure out as we’re making this membrane embedded device is there’s no easy way to stop and go. Like an FDM 3D printer is so easy to just stop and add or thing and keep going. But I think it’s still very hard to do on resin. I don’t know how that would be solved. But I think that’s something that’s missing compared to the flexibility of the end FDM 3D printers.

Hemdeep: That’s true.

Robin: As you kind of progress through your line of research, is there a bigger picture once you have these in vitro models done? Is there like ⁓ a sort of disease that you’re looking to kind of diagnose using like the differentiator markers or anything like that?

Chen: Like I’m a engineering background, right? I really enjoy making those device for whatever needs is out there. But I personally wouldn’t have like a bigger goal of looking at a specific disease that’s like way outside of my expertise. Yeah. I enjoy like making the device. Like, you know, when my PI tells me like, I can make a device to make this, like to test this. like, ⁓ cool. You know, I’ll try to make that happen. But when it gets too vile, that’s the thing. I don’t even have the confidence to be able to look into things like that. But a bigger picture on my side would be trying to fully characterize the effect of the hydrostatic pressure and then see if we popularize that to some kind of a new. trans wall product or something else that we develop. So that is the norm for anyone who’s trying to do those air liquid interface differentiation so that they first know about the effect of a hydrocyte pressure and second, they can also have an easy product to use to help them induce that hydrocytic pressure.

Hemdeep: I also understand that you’ve co-founded a new lab called LabGiant. Why don’t you tell us a bit about that venture of yours?

Chen: OK, so it’s not a lab. It’s an online platform. So I can go more into it. Yeah, for sure. So basically, when I started my master’s, I noticed a lot of things that was not as efficient as I would like it to be. And you know what they say, right? Like for engineer, when something doesn’t work exactly how they want, they’re trying to find a way to fix it. That’s basically, essentially, what I did. Once, I think I had to characterize a sample, and I just didn’t know how. I eventually we managed to do something, but then after a while I saw like an equipment that exactly I thought I could use in another lab. Like they weren’t even using, it’s just collecting dust. No, just like, okay, that makes no sense. Like we should know about things like this to make it more efficient for everyone. That’s when I realized that a lot of labs in academia, it’s like works in silo, right? We don’t really know the other labs equipment expertise. know, a lot of professor end up buying duplicated equipment. That’s a lot of money wasted too. So that’s why we’ve made this marketplace that’s designed for research labs where they can share all kinds of resource, whatever expertise, even digital files. They can just put it on there and it’d be super easy for other users to look at what’s around them. And even for some of the more niche tools, let’s say the HydroSight device I made, another lab might be willing to try it out. but they don’t know how to make it. I also put that on the marketplace where they could just get it from us. I’ll ship it to them for a small price. And I think that’ll be much more efficient way of collaborating than Arcturne way, is usually is that you have to read a publication. You like that publication. then like I did, I tried to recreate that publication. And I find it doesn’t work because it just lacks the detail in the methodology to fully replicate it. A more efficient way would just be directly collaborate through the work, right? Through the product, right? If one lab is really good at making it, then just sell it to other labs. And then we can just grab the work and keep going. thought that was very similar to, if you guys are familiar, why software engineering has been able to progress so quick is because they have this system on GitHub where they can just grab the code and just keep going with the code. They don’t even necessarily understand what was going on with that code. That’s why software engineering has been able to…
progress so quick, right? It’s like very efficient system at building on each other’s work. And that’s what we’re trying to build with Labgiants.

Hemdeep: I’m actually on the site right now while we’re chatting. How do you find time for this? I’m looking at this. I’m just going, this is a well laid out site. It is extremely intuitive. can see why labs, any lab would want to be on a platform like this.

Chen: Oh, thank you, thank you, it’s really great to hear this.

Hemdeep: And you’re right in terms of collaboration, it is extremely valuable, especially in the research field. There is a lot of duplication that happens. I’ve always found that if you can figure out a way of getting someone someplace faster, you’ll always find a marketplace for it. this certainly I just am just taking a quick look and I’m wow. And do you guys have access to the next next gen AI? That sounds like something that that we need to explore further. Are you going to be creating a large language model for ⁓ microfluidics or is it worth

Chen: Yeah, no, that’s the goal. So basically, as we were having all those database of equipment resource, what we realized is that even me, as an Atherios PhD student, I love those equipment. As your idea of what they do, especially when they have a very technical name, like no one knows what the thermal ICP 2000, like I don’t know what that does. But then, would know. AI would know exactly what that does. So we implement AI so that they can recommend you the equipment resource that can know like a… just depending on your needs. So basically, you really have to tell our AI about what’s your problem, what you’re trying to solve. And our AI will be able to guide you, just, you might want to use this equipment, or use that resource, or look at this expertise from that lab, and guide you around to help you find those things easier for you. We showed that to a law professor. They also felt like it was a game changer in how we would do research. Because as the large language model gets better, you’ll give everyone out there a baseline of how to do research, of how to think of a solution to a problem. That’s our goal for LabGiant.

Hemdeep: This is fantastic. I can get lost in this rabbit hole of tools and technology.

Chen: Yeah, no, that’s why we have an export page, rather a home page where you can just like, if have something new publication, something new tool that they build that they want to share, you can just scroll the export page and just say, well, maybe I like this. I want to try this and just click the link and get one from them. I think that’s our vision for LabJet.

Robin: And are you looking to get labs all over the world on board for this or is it like regional?

Chen: We’re starting with McGill, know, still refining a platform. It’s our beachhead of the market. But no, I think it absolutely makes sense to expand, build this network of a research lab around the world so that we can all collaborate, right? Like see what’s out there too. Amazing. You know, about the first question, how do I find time for this? the real answer, it sounds a bit bad, is just like not really caring about work-life balance at this point. Just like now, it’s just, yeah, they, they time PhD weekend. I work on this with my co-founders, you know, who are, who are software engineers. And then they’ve been, they know that without them, I wouldn’t be able to make this happen. Of course. Yeah. It’s just a lot of, sacrifice on time, right? Yeah. I think that’s the advantage. Like I was, I have to do this in my twenties because if not, I don’t think I have time to do this in my four.

Hemdeep: To be young again, ⁓ No, no. This has been a very informative conversation, Chen. We got a very good sense of exactly what you do at the lab, and then you’ve introduced us to this offshoot of your work life, ⁓ where you sacrifice everything for the rest of us at labgiant.ca. And we will put the links to ⁓ this ⁓ labgiant. Thank you. Any final closing remarks, Robin?

Robin: Thank you for joining us, first of all. It’s been a real pleasure talking to you and kind of getting to know your work and what it is you do, all the devices that you’ve created. I don’t know if you’ve broken your own devices or if that’s just other labs ones.

Chen: Thank you for having me.

Robin: If there’s any other links or anything else you want to share, just please do and we’ll love to do that for you.

Chen: You guys also follow us on LinkedIn, you know, like me or LabGiant. We also have a LabGiant account there. Of course.

Hemdeep: What do do for fun? And how long in a typical week would you spend? Split your time between lab work. Obviously you have to present and start developing your PhD work and everything. And then you have lab giant. Do you breathe? Do you eat at all? Do you sleep? Are those optional?

Chen: Yeah, I try. I’ve been on the Make Your Varsity Bamenton team for a while now. This was actually my last year to be on the team. I think it was time for me to retire from Bamenton. And I’m looking into some other activity I could do, not just to stay in shape. But yeah, I would say that’s the main fun I’m having outside of ⁓ all the work.

Hemdeep: All right, then that’s great. Again, thank you very much for doing this, taking some time out to chat with us. And I think when this lab giant starts picking up a large language model, we should have you come back on because I think large AI is going to be extremely important for new development.

Chen: Yeah, no, we, we, we’re thinking of training it like not only on database, but also everyone’s like expertise publication and things like that. So I think that would really help everyone to just have an easy way to find the things around them for research.

Hemdeep: Well, we’ll see you around. Take care of yourself.

Chen: Thank you. All right. Have a good day. Bye. Bye.

Robin: And with that, we’ve reached the end of our series with Chen here on Big Ideas at Microscale. Don’t forget to check out the episode notes linked in the show description for all the supporting material and resources we mentioned here today.

Hemdeep: Over the past three episodes, we’ve explored Chen’s journey from engineering fundamentals to cutting edge bioengineering, where he’s helping reshape how we model and understand complex tissue systems. We followed his work on hydrostatic pressure and epithelial cell differentiation, saw how innovative pressure sensors and 3D organoid cultures are changing the game, and finally, we dove into the tools that make it all possible, from microfluidic devices to 3D printed labware.

Robin: Chen’s work reminds us that research isn’t just about solving problems. It’s about asking better questions, building better tools, and reimagining how we collaborate. A huge thanks to Chen for sharing his story, his insights, and his vision for the future. Next time on Big Ideas at Microscale, we’ll be talking to Andrew Wallman, Anne Tong, and John Shanley from the Sparks Group of Avdee, where we look into the role of 3D printing in drug discovery. Until then, thank you for tuning in and as always, stay curious, keep exploring and never stop asking the big questions that are shaping this world. Whether you’re in the lab or on the go or just curious about the future of technology, join us as we continue to dive into big ideas at MicroScale.