The Additive Advantage Podcast
In today’s volatile markets, organizations face a brutal balancing act: the relentless pressure to innovate faster while maintaining operational excellence. Additive manufacturing (AM) was supposed to be the game-changer. But for many companies, it’s become a slow burn of money, time, and credibility.
We’ve seen it up close: $4 million spent, 18 months passed, a dozen engineers assigned—and still no outcomes. Pilots stall. Production doesn’t scale. ROI never makes it to the P&L. If you’re a GM or SVP who championed AM and now find yourself watching money burn while results slip away—you’re not alone.
The truth? Most companies treat additive as a technical side project, handed to engineering and isolated from the business, with the expectation it will somehow deliver like magic. But innovation without execution is just expense.
That’s where the Additive Advantage Model comes in—and this podcast brings it to life.
Hosted by Shon Anderson and Dani Mason, with a combined 20 years of additive manufacturing experience, The Additive Advantage Podcast brings you real conversations with industry leaders who have been in the trenches of transformation. These aren’t fluffy tech chats—they’re straight-talk interviews about what it really takes to make additive deliver.
The Additive Advantage Podcast
EP 18: Fall in Love with the Problem, Not the Solution
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What separates groundbreaking innovation from ideas that never leave the lab?
Dr. Scott Wood, Founder and CTO of CellField Technologies and Director of Biotechnology Innovation and Training at the University of New England, joins us to discuss the journey from academic research to real-world commercialization.
Scott shares how a research question about cell mechanics evolved into a company focused on improving how new therapies are developed, tackling one of healthcare’s biggest challenges: why so many promising treatments fail before reaching patients.
The conversation explores the difference between solving an interesting scientific problem and addressing a real customer pain point, why customer discovery is critical to commercialization, and the importance of getting out of the building to understand how people actually work.
Scott also shares how additive manufacturing has helped his team accelerate the rate of learning, giving researchers and students the ability to test, fail, iterate, and improve quickly. The discussion draws parallels between biotechnology and manufacturing—from designing technology that is fit for purpose to understanding that new tools don’t have to replace existing ones to create meaningful value.
Whether you’re developing new products, leading R&D, commercializing research, or implementing additive manufacturing, the takeaway is simple: fall in love with the problem, not the solution.
#AdditiveManufacturing #Innovation #Biotechnology #CustomerDiscovery #Commercialization #Research #Engineering #AdvancedManufacturing
About the Show
The Additive Advantage Podcast explores what it really takes to turn additive manufacturing into a scalable, performance-driven business capability. Hosted by Dani Mason and Shon Anderson, the show features real conversations with leaders accountable for outcomes — not hype.
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About the Hosts
Hosted by Dani Mason and Shon Anderson, industry leaders with deep experience in technology and additive manufacturing.
Ninety-five percent of all drugs that are proven safe and effective in a lab setting or an animal setting before they go into a human fail when they get into a human. And for osteoarthritis, which is the disease that I'm focused on specifically, that failure rate is a hundred percent. Nothing has ever been proven safe and effective at treating arthritis in a human. All we can really do is treat the pain or replace the tissue. That's really the problem that we're going after right now.
SPEAKER_02Welcome to the Additive Advantage Podcast. I'm Sean Anderson, joined by my co-host Danny Mason. This is where additive manufacturing meets accountability, and where we talk about turning pilot projects into production and ideas into outcomes. Let's jump in.
SPEAKER_00Today's guest is someone who sits at a fascinating intersection of science, engineering, entrepreneurship, and commercialization. Scott Wood is the founder and CTO of Cell Field Technologies and serves as the director of biotechnology innovation and training at the University of New England. His work is focused on one of healthcare's biggest challenges, creating more predictive models for diseases like osteoarthritis, so researchers can develop therapies with a much greater chance of succeeding in humans. But what makes this conversation especially interesting isn't just the science. It's the journey from academic research to building a company, the lessons learned through customer discovery, and how additive manufacturing has become an enabling technology that allows ideas to be tested, refined, and ultimately translated into real world impact. Whether you're working in healthcare, manufacturing, engineering, or simply trying to commercialize a new idea, Scott shares lessons that extend far beyond his field. Well, I appreciate you joining us, Scott. I've been excited about this conversation for a while, especially as we were prepping for it. I think a great place to start is why don't you just introduce yourself?
SPEAKER_01Well, it's my pleasure to be here. Thank you for the invitation. My name is Scott Wood. I am a professor at the University of New England. I'm the director of biotechnology innovation and training. I'm also an associate professor of biomedical sciences. And I am the founder and chief technical officer of Cellfield Technologies.
SPEAKER_00Hey, that's quite a portfolio. I'm excited to dig into each one of those in turn. I want to start with Cellfield Technologies. I feel like a lot of startup companies begin with someone seeing a problem that everyone else has just accepted as status quo. What problem did you believe needed to be solved? And why was it important enough to build a whole company around it? Yeah.
SPEAKER_01Well, problem I started out trying to solve is not the one I ultimately ended up building the company around, but in my academic research, so I'm I'm a mechanical engineer by training before becoming a biomedical engineer and then for my PhD work. And then I did my postdoc in a cell signaling lab. And when I got my first faculty job, I wanted to bring all of that together and study how the cells in the cartilage of our joints convert mechanical inputs into bio or into biological outputs. That's a process called mechanotransduction in cell biology. Kind of the business as usual way of culturing cells, the way that it's been done for the better part of a century now, is to put the cells in a glass or plastic, you know, flat dish. And, you know, as someone who's interested in understanding how these cells interpret mechanical inputs, the very first one we're giving them is that, right? We're putting them on a very stiff, we call it a substrate, a surface. Um, you know, that in the case of plastic is a hundred thousand times stiffer than the environment of the body that they're in. Um, in the case of glass, it it's literally one million times stiffer. And so, you know, we can do all we want to look at the cell signaling pathways that are happening when we probe specific molecular receptors. But if they're in that just ridiculously unrealistic mechanical environment, it's going to change the things that we're looking at. And so we could get the most beautiful data publishable, reproducible in the world, but it's never going to translate in an actual human if that's the system we're doing it in. And so initially start out trying to solve that problem by making a technology that would be more realistic for the cells mechanically, but still allow us to investigate the very transient and delicate cell signaling pathways, you know, that we're interested in studying.
SPEAKER_00Absolutely. And I think what would be great is to help folks understand, okay, this was, I'm going to use the word initial research problem we were solving, but where you are today, there's a massive problem. And I'll I won't steal your thunder, but a massive problem in how we think about diseases and treatments and qualification therein. Can you talk a little bit about maybe that the macro problem that you're looking to solve in addition to the one you just shared?
SPEAKER_01Absolutely. So the one that that initial one led us to is the fact that 95% of all drugs that are proven safe and effective in a lab setting or an animal setting before they go into a human fail when they get into a human. And for osteoarthritis, which is the disease that I'm focused on specifically, that failure rate is 100%. Nothing has ever been proven safe and effective at treating arthritis in a human. All we can really do is treat the pain or replace the tissue. That's really the problem that we're going after right now.
SPEAKER_00And, you know, what what do you think are the consequences of not solving both of these problems? I mean, clearly this is not a new disease. It's been around for a long time, and everyone has just kind of accepted here's what we do. But I think you have uncovered something really interesting when you shared, you know, the cure may be sitting somewhere. Why don't we have it? What are the difficulties when you think about it from the pharmaceutical company side in trying to address this problem? Yeah.
SPEAKER_01So there have been many attempts over time by the pharmaceutical companies to come up with drugs that could, you know, prevent or reverse the disease. The challenge, well, there are four main challenges. Number one is that the cell signaling pathways that lead to osteoarthritis are incredibly complex. And there are multiple avenues that you can get to that same endpoint. We all we call them all osteoarthritis, but they aren't necessarily being caused by the same things. And you can have more than one of those pathways at a time. So it's just an incredibly complex disease, even to understand in the first place. Another problem, and this is the one that that we felt like we were most able to solve with the technology that we're developing, is that for most of human history, there there has not been a commercially available technology that would allow pharmaceutical scientists to model the multi-tissue nature of a human joint in a laboratory setting. So in order, they they typically would have to look at just one cell type at a time, or or maybe a couple of them, uh, but not the really complex nature of a human joint that has bone and cartilage and a joint capsule and tendons and ligaments, and in the case of knees, meniscus, fat, right? There's there's all sorts of tissue that's present in those, and and those cells are all talking to each other in our in your body right now. And the usual way of doing things just didn't or does not allow for that level of back and forth cellular communication that happens in a real human body. So that's that's that's really what we are focusing on solving commercially. The other problems are that small animal models, especially, animal models generally, but especially small animal models, are are just fundamentally structured differently than human joints are. There's a lot we can learn from those systems. There's a lot we have learned from those systems. They they are very valuable, and I don't want to denigrate that importance that they have, you know, of all of the work that's been done in those systems, but at the end of the day, they are not human systems, right? And then the the fourth major hurdle is that in a lot of diseases, we we try to understand the difference between the healthy state and the disease state by looking at clinical samples. What do people who have this disease have different inside of them that the people who didn't get it do, right? Because it's such a complicated disease, and also because we don't typically have the ability to detect it until very late in the disease development process, because it's it's not painful until it's really, really, really bad. And so there's just a really high degree of person-to-person variability when we look at the cells that we get, you know, usually from a joint replacement surgery. So all of that together is what has led to the ultimate failure of all the attempts that have come in the past. And each one of those failed attempts was at the expense of decades of research and billions of dollars for those pharmaceutical companies. And so, yeah, in in some of our customer discovery work, we talked to a retired scientist from one of the big pharma companies who said that that company probably has the cure for arthritis sitting on a shelf somewhere. They just don't know what it is, and they're too afraid to try anything because of how expensive and painful it is when they fail.
SPEAKER_00Yeah.
SPEAKER_01But our technology, we hope, will will start to minimize that risk and open those doors again to further exploration.
SPEAKER_00Yeah, that it's so powerful, Scott. You know, when you think about your kind of your customer discovery journey where it's, okay, I struggle with this problem in my research. Maybe other researchers would benefit from it too. Oh my gosh, there's actually a huge epidemic out there that we have no way of addressing with high failure rates in terms of getting the late stage approval. And on the back end, it's buttressed by these companies to your point that have spent decades and billions to no avail. So there's no incentive to keep trying in such a high-risk environment. I mean, would you have any advice on those realms to people that are in this research to commercialization process? Because you yourself, the problem you set out to solve, you said it's not the one actually that my company is based around today. What did that look like? How did you do that customer discovery? How did you get that clarity of what problem you were trying to solve and the value you could bring so that you can be in a position where you're trying to go pitch it to these various agencies?
SPEAKER_01Yeah. Well, so you you you kind of hinted at that along the way, we did an NSF iCorps customer discovery project. And, you know, that that effort is really focused on finding product market fit for technologies that that grow out of NSF-funded research, which our technology did. And I think the kind of light bulb moment for me was understanding the difference between a scientific problem and a customer pain point, right? Where, you know, a problem is interesting to solve and and maybe even very useful to solve. But until something becomes a pain point for someone, they're probably not going to spend their own money to solve it.
SPEAKER_00If I could capture that and email blast that to every person I've ever met, I would. You know, I a lot of the audience on here, they're technical. And that's not a bad thing. But I I think they're more closely aligned, even if they're in the quote unquote private sector versus academia. That's how they think, right? This is an interesting technical problem. Could I solve it? Instead of this is an interesting technical problem, should I solve it? Is there a pain point? What would the benefit be? So I think that's a great applicable question that all of our audience that is listening should apply to their own problem. The other thing I think is really interesting, Scott, and some of this is just you and your background, but I also think it's the way your brain works. You know, your your work is spanning engineering and biology and material science and all of these different disciplines that I think a lot of times can be siloed within a company or within a research setting. Talk a little bit about how should people think about disciplines coming together to create something that wouldn't be possible, just going deep within a singular field.
SPEAKER_01Yeah. That's a big question to answer universally. So I'll start by just kind of taking my viewpoint on my particular pathway here. And I'm gonna start by by framing this in the context that UNE has just a world-class college of osteopathic medicine. And that's where my faculty appointment sits. And for those who aren't familiar with osteopathic medicine, the thing that really differentiates osteopathic medicine from what I'll call medicine as usual and business as usual medicine, right, is a series of kind of core principles that essentially boil down to viewing the body as a holistic organism, right? That's that's dynamic. You know, the function of the body is irreversibly tied to the structure of the body. You change one, you change the other. Um things are interconnected, communicating with each other, um, and and that the body can really start to heal itself if you put it in the right context, right? And so I didn't actually start out doing this on purpose, although my grandfather was an osteopathic doctor, and so I think maybe it was just ingrained in me from childhood without knowing it. But I've I've really integrated a lot of those principles into how we've designed our system. And so trying to take that, you know, when you have a big complex thing that you're trying to do, you know, in our case it's it's model human biology, but it could be, you know, any massive challenge, AI, there's a million off, you know, ways you could frame this here. But trying to silo a big project into one discipline is really, really hard. You need to in take that holistic approach and integrate all the different parts. And, you know, I think that's really what what we've tried or what I've tried to do in developing our technologies to bring, um, you know, starting with that fundamental structure-function relationship. Um, and you know, how do we manufacture that? How do we engineer the mechanical properties that we need? What biological questions do we then have the ability to answer that we wouldn't have had otherwise? You know, with the um I'm gonna bring in microfluidics, and that now allows more dynamic responses and and communication between separate, you know, physical systems that that we have the cells in them in our in our platform. So that's I hope that that answers it in a in a co cohesive way there for you. But yeah, that's how I think that's absolutely does.
SPEAKER_00And you know, we we have a lot of guests on this show and they have different flavors of the disciplines that they work in, but this idea of systems thinking and helicoptering up high enough, it's like, what problem am I trying to solve? And then what are the components therein and how are they interrelated in service of this goal? It's super critical. And I think it is very easy to start down here. You're like, it's easier for me to to understand what are these individual components. It's much harder to start here and say, I need to think the equivalent of upstream and downstream of whatever my process is so that I can make sure that I'm getting a real output. So it's it's very salient, even beyond, you know, this realm and functional medicine to a lot of the folks that listen to the show that are in manufacturing of various natures. It's very much the same principle. Uh, what do you think if I if we spend a little time maybe on the uh additive manufacturing portion? It's where our audience is passionate about. How do you think about either additive um 3D printing specifically, but also this idea of advanced manufacturing fitting into a technology stack for cell field? You know, is it do you think of it like a manufacturing tool? Do you think of it as a way to enable experiments or capabilities that weren't possible? How should people be thinking about 3D printing in this type of context?
SPEAKER_01Well, I think, you know, pretty much every manufacturing technique that we're integrating in our technology, I would classify as advanced manufacturing. A lot of them are, you know, they're they they derive from traditional manufacturing techniques, but but you can't just go buy off-the-shelf parts for them, right? Because they're all very finely tuned, and we are trying to integrate the you know, the material science with the biology and you know, integrating plastics with peptides and and all of these things, you know, to put cells on them and and make them behave in certain ways. So, you know, and uh I think the the thing to think about with 3D printing specifically, you know, for us has been the ability to cheaply and quickly try things out. And and a lot of the actually, you know, all of the 3D printed components of our system were designed by undergraduate students. And, you know, doing that with traditional manufacturing, which which you know um may have been an option, although with all the microfluidic parts, it it gets tricky. It would have been very, very expensive to have the learning processes that came through that development for those students and for myself too. As we did that, uh, you know, the 3D printing really gave us the ability to dream big and think about what we can do here, what do we really need? And and in, you know, how do we build something that that we can try and fail and learn and iterate and try again and get it a little bit better as we go.
SPEAKER_00Mm-hmm. Yeah.
SPEAKER_01And to do that very quickly.
SPEAKER_00I love that. That idea of, you know, how can it speed up my rate of learning? And I love that idea. We try to touch on people, business, and technology in this podcast and that idea of not only can it speed up the rate of learning that helps my company and my research move forward, but it also helps all those individuals that are interning, that are in their own student journey figure out how I can have a tool that speeds up me as a professional while I'm speeding up the business. Do you think I so I talk to obviously a lot of people in added manufacturing, but I spend a fair amount of time talking to people that are in the biology realm by nature of bioinks and bioprinting and some of the stuff in that, in that area? Do you think that I'll call it the additive manufacturing piece is maybe still underutilized in what is more biomedical research? And if so, how how do you start to bridge that gap that you have done as a person? Because it's mechanical and you understand biological, but a lot of times those are two different departments or two different colleagues. How do you think about that?
SPEAKER_01Yeah, I I do think that there's still room for growth. I I think it's been around long enough that that there's maybe a bit of an attitude of, okay, this has reached maturity, you know, but I think there's still a lot more that could be done. A lot of the bioinks, you know, again, kind of coming back to this osteopathic principle is really just a fundamental biological, physical, even principle of you know, structure, function, reciprocity. With the biowinks, if you treat it as just a goop, right, then it's only going to take you so far. But when you can start to think about it as a structure-giving material, um, you know, something that doesn't just have mechanical properties or, you know, chemical properties, but but something where you're actually able to print structure at a scale that matters for cell biology. Um, you know, I think that that if we ever hit that point where that becomes easy and affordable to do, that will really start to open up a lot of new questions that we can ask and problems that we can solve.
SPEAKER_00That was actually a perfect segue because kind of my my last question, just in this additive manufacturing topic, was that like as the technology continues to evolve, better materials, higher resolution, you know, getting into some bioinks, what possibilities are you most excited about for cell field to be able to utilize and then maybe the broader field?
SPEAKER_01I really I like the level of control that we have over the geometry that that not all of the techniques that that we've used are able to provide us. For instance, with we've used electro spinning for some of our scaffolds. And that's great. It's you know, there's a lot you can do with electrospinning, it's a really cool technique. I don't know, I went to a conference a couple of weeks ago and I I came across a company that does uh you know melt electro writing, which is a very similar technique. It doesn't get down to quite the same, you know, nanoscale that electrospinning can yet. I always tell my kids, you know, don't say you can't, say you can't yet. But the degree of control that you have over geometry there, right, is is just something that really wows me as an engineer to be able to say, okay, well, you know, I want to control, you know, the the exact I want something that's very reproducible where I can control exact spacing so that it's the same or or equally different every time, um, and not just kind of randomly within a predictable distribution. I think that that's really where I'm excited about additive manufacturing for cell field as as we continue to try new things.
SPEAKER_00Yeah, I think you hit on two really important points. It's, you know, can I have control over the geometry and the fidelity of my design, but is it also repeatable? I think a lot of times people get fired up about the former and they forget about the latter because they're in RD mode, not manufacturing mode. And we just are so used to saying additive manufacturing that we forget how critical the M is in that. Glad you brought that up. Um, because I think it's something, a point that gets lost a lot. As I kind of want to switch now and zoom out as we've been talking and help people understand what do you think the biggest misconception folks have about joint on the chip technologies versus where you are taking it in your own company?
SPEAKER_01I think that kind of depends on who you classify as folks.
SPEAKER_00Yeah, let's yeah, you take it anywhere. I mean, I'm thinking pharma, maybe, you know, as that someone who's invested a lot in this, maybe not with the results they're looking for. And maybe on the other one, uh, research. And if I can pick a third, your funding agencies, your investor vehicles. Like I think about those three stakeholders, and I wonder if how they think about this technology, what would you say is maybe a misconception they might have?
SPEAKER_01I don't know that the the funding agencies and regulatory folks, and I'm not aware of any misconceptions that they have. I think partly because they are the ones that are are setting the agenda, right? They're the ones that that really everyone is looking to for guidance on what what do these things need to do and be. Um and and I think the biggest misconception that I hear from them is that that these devices are gonna be wonder gadgets that can do everything all at once, right? And that, you know, they really need to be fit-for-purpose devices that are that are answering a particular question for a very specific context of use. And that, you know, I I think there's maybe a little bit of a misconception that, oh, hey, if somebody comes up with a good joint on a chip, then that's the only one that we need, right? Or whatever organ it is. Um, and that I don't think is ever going to be the case because each one is going to be built with certain engineering, you know, design constraints in mind uh to solve a particular problem, to answer a particular question. And as long as you know the the end users and the regulatory agencies and the funding agencies, you know, are are able to see and understand and make decisions based on the very specific context of use that this particular thing is meant to be for. Um, you know, that that there's room for a lot uh of growth and and really uh you know a whole industry can be built truly on on this idea of organ on a chip that doesn't need to just be a limited number of you know mega companies that that come out of this at the end of the day. I think there is also a bit of a misconception about organs on a chip generally, you know, and and and maybe trepidation in the scientific community, that you know, that that there is some concern that that funding agencies and regulatory agencies starting to promote the development and use of these technologies means that that we're trying to eliminate everything that came before. Um and that's really not the case. You know, the goal for these is to fill in critical gaps in the existing architecture of scientific product development and not necessarily to replace that architecture. Um you know, I I think that there will there will always be, again, you know, the context of use is key here. There will always be uses for traditional cell culture techniques. There will always be uses for bringing in animal models for understanding things at a at a truly organismal, you know, in a truly organismal framework, having a a a particular organ on a chip, or even when we get to the point of having, you know, entire bodies on chips, which hopefully, you know, that I think that's where the the industry would love to get someday. But even then, it's not going to be something that just replaces the entire scientific infrastructure that that we've spent the last 60, 70 years um, you know, building and making the the envy of the world.
SPEAKER_00There are so many parallels, Scott, when I think about 3D printing, this idea of fit for purpose, context specific. A lot of people look at a 3D printer and also think it's a magic wand that can do anything and everything you would ever want it to do. And this idea of, no, you know, it should be tuned to an application. That's how you get the desired results. It should be fit for purpose. You do need to be context aware. And on the flip side, what you're seeing in, I'll call it the research space, where it's, hey, we have this technology that's been around for 70 years. What do I do with this new one? Is it going to displace it? People said that about injection molding and additive, and that has not happened. They are tools in a toolbox. Injection molding's been around for a century. I promise you, we are not making our printers entirely with 3D printers. We are still using injection molding. And so I just love you sharing these principles because I think they're timeless and they can be cross-pollinated into this industry that we exist in for folks to see, yes, that is how the progression and advancement of technology and research go. It's not a wholesale replacement. And it also isn't a magic wand. And being able to find it practical use cases that, to your point, deliver value to real pain points, not just interesting technology or research problems is a big unlock. So I just I love that you shared all of that. No one paid you to do that. Um, so I just love it. And we'll have to, well, I think that's such a great takeaway for the audience too. What do you think when you think about maybe these pharma companies? Because to me, it it seems obvious, right? It's like, man, decades and billion dollars for a hope that I will be able to bring this next blockbuster to market. But oh, by the way, a hundred percent fail when you get to that, you know, final phasing. Maybe misconception is the wrong word, but how should pharma be thinking about the technology that you're trying to bring to market, maybe in a different way than they've been thinking about how they bring drugs to market historically?
SPEAKER_01That's a hard question to answer because A, I'm I'm not in pharma. And B, because um a lot of the people in pharma that I've talked to are are very excited about the development of these technologies. And they, you know, they they it it's really, you know, they're the ones that have been calling for these things uh from the very beginning. And so, you know, I I think maybe, you know, the the thing that's needed from them is is to just speak up even more loudly. And, you know, it it's well, okay, so along those lines, you know, when we were doing our customer discovery as a as an academic, um, and we were doing this during the pandemic too, which didn't help. Um I think we were the first iCorps, second iCorps cohort to use Zoom for our interviews. But you know, it it can be very difficult to make those connections person to person um and to learn who do I talk to, how do I talk to them. Um, I think if if the pharmaceutical scientists want more of these things to be getting developed, for them to find ways to communicate that more effectively to the engineers and scientists that are on that early stage development side of things, I think it would be very, very powerful. You know, and likewise, I think for people who are interested in developing commercializable technologies, I'm gonna get more more broad here and not just limit it to the organ on a chip space here. But um, you know, if if you're in the academic setting, get out of the building and go go find ways to to talk to people who are using products like the ones that that you're hoping to improve in the real world and find out, hey, what how do they choose what they do? How you know, what are the limitations of those choices and and the frameworks within which they have to make those choices and you know try to get a better understanding of that whole ecosystem. Um, and that that really is kind of what the iCorps is all about, and um, I think why it's so powerful.
SPEAKER_00I love that. I, you know, I obviously grew up in the sales and marketing realm and I work for a manufacturing company, and they use different words to describe get out of the building. It's like, let's go on a gimbal walk, which is where you just go to the work, timeless manufacturing principle. Like that's customer discovery, friends. Like that's going and seeing how people are using your products. And that advice is so good because we find in organizations a lot of times, and it's what you're describing, it may be slam dunk technology, slam dunk business case. And then you have this whole thing called change management. You have this whole thing called organizational management. And it's people. That's all it is, is people. How do I affect change through people? And so, to your point, being able to not just have a check here and a check there, but what is your problem? How are you using this technology? What would be a win for you? What does your boss care about? What does their boss care about? And there's no substitute for that. You won't get that reading another research paper or doing another RD project. You get that from actual human interaction. And I love that point, Scott, because I think that it can feel intimidating if you are on the technical side or you know, you think that's not my, that's not my swim lane. No, it's critical. And what it does is it helps you fall in love with the problem more than your solution. So I just you get three hallelujahs from me on that one because I I think it's great. I think it's great advice.
SPEAKER_01The Office of Management and Budget has recently put out a proposal that is currently in a public comment window that would vastly restrict the use of federal research funds for sending academic researchers to conferences. And that really is the best way, as an academic researcher, that we can get out of the building and interact with people in industry. You know, most of the pharmaceutical scientists that I have heard from in person and spoken with in person, I've done that at conferences. That's that is where those two worlds are most easily able to personally interact with each other. And so, you know, for any listeners who who are aware of that and haven't commented or or aren't aware of that, um, you know, please do look that up and and comment that that those connections are really critical for American innovation and commercialization.
SPEAKER_00Yeah, love it. And you you feel free, it's our podcast. So you can say you can say whatever you want. The only person that can take me off there is our producer up there. And so far she's left my mic on hot. So I love it. You know, as we're going through kind of the the last portions of our time, I want to ask just a couple more questions. And some are forward-looking for your company, and then some are about you. When you think five years from now, what would success look like for Cellfield, maybe for the the customers and patients you're trying to serve? You know, what impact, I guess, is the best question do you hope you've had in this space?
SPEAKER_01Well, uh, within a five-year time frame, I would say success for Cellfield would be to validate as many contexts of use for our device as we can. And and then not just to validate them, but you know, in this organona chip space, um, there there's kind of one additional step that is has recently been introduced by the FDA that that I think is very powerful, and that is qualification. Where you know these these devices are not necessarily FDA regulated. We don't have to get FDA approval to sell or market them. But the FDA ultimately would love to be able to use the data from these devices for interpreting preclinical results of you know candidate drugs. And in order for that to really happen, they they need to go through um, you know, kind of this qualification, regulatory qualification framework where the FDA can say, yes, you know, we we understand your device. It it answers the questions we need it to answer. Um, you know, this is the these are the questions that that we know that it can answer, um, you know, that context of use, and just really proving that out and proving that it's reliable and repeatable, and not just in one person, you know, not just in the hands of the people who developed it, but in anybody's hands. So I would say success for us would be getting to the endpoint of that process also. And that hopefully will then start to really open doors for pharmaceutical companies to be able to turn to us and say, oh, hey, we are developing a drug that fits your context of use. You know, we would love to use your device to generate data to to help us fine-tune our drug candidates to either pick the best one or eliminate ones that that are likely, you know, surprisingly likely to fail, um, or to fine-tune them to make them more likely to succeed.
SPEAKER_00Mm-hmm. Yeah, that that's that's incredible. And I think it will just fundamentally change, you know, kind of the the way therapies are developed and the speed to market. And you just think about, you know, another real classic manufacturing principle is that idea of value and waste and value is everything customers are willing to pay for, waste is everything else. And you're doing a lot of that, um, which I think is just it gets me excited. You know, I'm not in pharma, but I probably will be one of those patients based on the way that that that disease works. So it gets me fired up too. You know, I I just too want to know if you personally, Scott, I mean, you're simultaneously an academic researcher, you're an entrepreneur and and founder. Which of these roles has maybe challenged you the most? And what lessons have surprised you along the way?
SPEAKER_01I mean, they've all challenged me. I I've I I have grown a lot in each of those areas, and I still have room to grow in in all of those areas. It's hard to, it's how do you pick a favorite child?
SPEAKER_00Yeah, well, don't worry, we'll say you love them all equally.
SPEAKER_01Yeah. And I I truly I do.
SPEAKER_00Yeah. What do you think there's been any, you know, if it's maybe not a lesson that has surprised you, do you feel like maybe there's a belief you've changed your mind about? And it could be business, leadership, science, it could be any of those realms. Something that it's just like, as I've gone down this roll, I did a 180 here. Or, you know, I'm looking at this differently than maybe when I embarked.
SPEAKER_01I think probably the idea that you have to pick one thing and and be, you know, in academia, you have to be the best at your one little microcosm of the universe. And that's that's not untrue, but but I think it's not exclusive to everything else, right? You can you can be an academic researcher studying fundamental scientific questions and try to get your science out into the real world, you know, for other people to find value in. You don't have to rely on, well, I I do my part and then I send it on to someone else. And and you know, we'll let other people worry about how to make it actually useful. I I think it will be, but you know, I don't I'm not the one doing it. And then and I I think that's that's not the attitude you have to have to have. It is possible to to do both.
SPEAKER_00I love it. I think that's a perfect spot to end. Thank you so much for spending some time talking through this with us. And I'm I'm excited to get this out there and have people be able to engage with the incredible work you're doing. Yeah.
SPEAKER_02Thanks. Appreciate you having me on. It's been fun. Some great interaction and some real gold nuggets there.
SPEAKER_00Yes.
SPEAKER_02Where I want to start is, you know, Scott made this point that resonated with me about the difference between a scientific problem and an actual customer pain point.
SPEAKER_00Yes.
SPEAKER_02Why was that such a powerful moment, do you think?
SPEAKER_00I think it's this principle of so what? And he started out with a problem he was experiencing in terms of trying to be able to study these cells. But what was so refreshing is that he said, that's a very interesting technical problem. I wonder if there is any pain point that an actual customer would have. And as he went down there, it went from these cells are very challenging in their current environment to if you look at pharmaceuticals, he threw out stats that were mind-boggling to me. 95 to 97% of these trials fail in phase three and 100% for osteoarthritis, which means that disease is treatable, not curable. And when he said there might be cures sitting on a shelf somewhere, but if you've spent billions of dollars and decades studying it and it hasn't come to fruition, that's the real problem. And so it was a huge aha for him, and I think a good lesson for us all to make sure we're asking that so what every time a problem comes up, so that it's one we should be tackling, not just one we could be.
SPEAKER_02I couldn't agree more, and that applies to so many things beyond additive manufacturing. He also talked a lot about customer discovery. I love it when you hear a true scientist and researcher talking so much about the, you know, customer pain points, customer discovery. But how does that relate to the world we live in and what you see working with manufacturers every day?
SPEAKER_00Mm-hmm. Yeah, we talked a lot about how everyone has a different vocab word for the same thing. So customer discovery is what we call gimba if you grow up in manufacturing. And it's it's this idea of I need to get close to the people doing the work to understand the real problems that they have. That's what you're discovering. And then you're just working your way backwards into, in his case, you know, what would be the right technology solution to solve that. Same principle in additive. We spend a lot of time talking about do you understand the business metrics? What is a problem we're solving? What is the strategy of your company and how can additive fit into that? Same principle here. He's just applying it in this biological realm.
SPEAKER_02Another thing that he brought up that I'm going to ask you the question and then I'll see if if you have the same aha that I did. But he described additive manufacturing as something that not only can generate parts, but help them learn faster. What did you think about that?
SPEAKER_00I think it's spot on. Oftentimes you go into this thinking, can I speed up prototyping? Can I speed up production? And his emphasis on, no, can you speed up the rate of learning is so powerful. And he not only did it himself and in his research and as he's commercializing this product, but he used that, speed up the rate of learning as his workforce development tool. So he would deploy that with his undergraduate students to have them have the same feedback loop as well. And I think when you look through that lens of not only can I learn more about what I need to faster, but can I propagate this among others? That's back to curiosity as a skill. Applied learning can be one too. And I really love that approach he took.
SPEAKER_02Okay. Well, obviously you made the connection because I didn't even get to my follow-up. You were thinking about the same one brain, unfortunately 50% each, but uh the same comment from our podcast with Andre. And I even think about Patrick, Patrick Dobbs, whom we had on recently, and his, you know, talking about the benefits of failure and what you can learn from that. So a lot of parallels between what Scott Wood is doing with Cellfield and kind of additive manufacturing more broadly. Not that they are both in a petri dish and you know have unpredictable results, but what's what stood out to you about the relationship between the two?
SPEAKER_00So many, so many things. Uh I'll just list a few of them that really struck me. One is he said, you know, when I bring this research forward, there's this whole body of researchers in the field that think, is this going to completely replace the way things have already been done? I think about injection molding. And when additive came on the scene, there was the same fear, hype, excitement pending where you sit in that manufacturing ecosystem. And the answer is no, it's a tool in your toolbox. And so to see these folks go through that same thought process and evolution really struck me in the parallels. The other thing I love that Scott said is he goes, Do you know people think this is a magic box? And I said, I can't, I can't relate to that. Um but he goes, No, it's not a magic box. It has to be fit for purpose and context aware. And I love those phrasings because it very much is what we talk about in terms of fit for an application and aware of the system and environment and business metrics it exists in. And those things just hit me in terms of being the exact same trajectory. The last thing I would share is he talked a lot about optimizing the system. Now, the steps may be call different things, but that idea of this portion doesn't exist in a vacuum is very relevant when you're thinking about additive and all the conversations we have from the pre-process all the way through the post-process portions of this as a manufacturing technology.
SPEAKER_02For sure. You know, one of the other things that stood out to me is I think back to the conversation I had with uh Tom from Roanoke and this desire for repeatable, predictable outcomes in, you know, the scientific biotech research areas. And it's interesting to me how these researchers are turning more and more to additive. I know you talk with researchers from, you know, a wide array of fields. What are some other themes that you hear come out of those conversations as you're talking with scientists and researchers around the world?
SPEAKER_00Mm-hmm. Yeah, I think this speed up my rate of learning is becoming explosive. I'm getting more and more folks that are not only using it as a rapid prototyping tool, but they're using it to study novel materials or to help other grad students come up to speed faster. And the ability to implement that as a tool, a multi-purpose tool, is huge. I think the other thing is in this environment where they're trying to figure out how do I think about funding in the current constraints it may be under, where I used to have funding I could count on from certain places that are being supplanted. There's more defense funding and there's more thoughts on commercialization. So for a long time, I would talk to researchers and it'd be I have a three-year grant program. I hope this comes through and I want to study this novel thing. More and more my conversations with them are would you industry find this useful? Who in industry would find this useful? I have been part of more I-Core customer discovery interviews in the past 12 to 18 months than I would say in the past five to six years. And so I'm really seeing that spark in terms of the application being as important as pure foundational research.
SPEAKER_02I love that. And I mean, the obviously research is at the heart of what our academics do in our universities and other institutions, but translating that into value through application is so key. You know, I'm guessing a number of our listeners may think, well, I, you know, I don't really live in the world Scott lives in. I think based on some of the highlights you drew out today, they'll see a lot more parallels maybe than they thought. But if our listeners today were to take away one primary thing from this conversation, what do you hope it is?
SPEAKER_00Uh fall in love with the problem, not the solution. I think that that served him well at each stage of his company and his research career. And if I could sum up everything, why do customer discovery early and often? Why think about what problems should be solved? Why think holistically about technology as enabler? It all comes back to that. If you fall in love with the problem, you will come up with a multitude of solutions aimed at it.
SPEAKER_02Well, it's difficult to innovate when you've fallen in love with your solution. Yes, that just looks like driving a team toward one predestined um end. And I know in our experience, I won't ask you because I can't remember the exact number either, but how many times we've had to pivot or adjust along the way based on customer feedback and that that mindset of always being in customer discovery, or as we say, benign creations outlistening the competition is so vital to long-term success.
SPEAKER_00Agreed. Want to thank Scott again for joining us and sharing not only the incredible work happening at Cellfield, but also the mindset behind building technology that solves meaningful problems. One of these themes that stood out to us is that innovation isn't just solving interesting technical problems. It's understanding the people who experience those challenges and creating solutions that deliver real value. Whether you're developing the next medical breakthrough or the next manufacturing process, that principle remains the same.
SPEAKER_02Follow us on Apple or Spotify Podcasts and watch this episode on YouTube at the Additive Advantage Podcast. If you enjoyed it, please drop us a five star review on Apple or five stars on Spotify. Be sure to follow us on LinkedIn for updates on new episodes. Thanks a ton for listening. We'll see you next time.
