Chris Love: The United States no longer has an invention problem. We're, we're, we're the best in the world at invention today, but what we have is an industrialization problem. We don't understand how to bring some of these ideas quickly into the marketplace to test them out and to advance the underlying technologies that are a part of that.

Narrator: You're listening to Augmented Ops, where manufacturing meets innovation We highlight the transformative ideas and technologies shaping the front lines of operations, helping you stay ahead of the curve in the rapidly evolving world of industrial tech 

Elisabeth Reynolds: Great to be here back on Augmented Ops. My name is Liz Reynolds.

I'm a professor of the practice at MIT, uh, and also an advisor to Tulip, and I'm here with my colleague from MIT, Chris Love, from the Department of Chemical Engineering, and we are here to discuss our new book, Priority Technologies: Ensuring US Security and Shared Prosperity. And part of the reason of being o- on this, I think, is not just that we are excited about our new book, it's also because one of the major themes across all of the six chapters in this book is manufacturing and how we're gonna advance manufacturing in the US.

And so the book, just to give people a, a sense of it, is six chapters. I edited the book, and the forward is written by our colleague, Simon Johnson, who is not only a professor at the Sloan School of Management, but also the winner of the Nobel Prize in Economics in 2024. It is a book that covers six areas that we think are important for the country, both from a national security and economic security point of view.

We can discuss that in more detail, but before we do, maybe Chris, you wanna introduce yourself. 

Chris Love: Sure. Thanks, Liz. It's a real, real pleasure to be here today. I'm faculty member in chemical engineering and work in the Koch Institute for Integrative Cancer Research, where we focus on biotechnologies. Uh, but my passion really lies in thinking about manufacturing.

I'm one of the faculty co-directors for the new MIT Initiative for New Manufacturing, which I'm sure we can talk a little bit more about, too. 

Elisabeth Reynolds: Excellent. So let me just set the stage on this book. The idea here was to provide not, you know, all priority technologies for the country, but a view on a number of them.

And of course, the view on priority technologies, historically, we've talked about national security, you know, in a defense context. I think now, particularly post-pandemic, we think of national security as being both defense and kind of economic security. So if we take the case of semiconductors, right?

Really important for our defense industrial base, but what we saw in the pandemic was lack of access to semiconductors, you know, cut our auto industry off at the knees and led to basically a, a third of inflation in 2021. So that link between national security, economic security, I think, um, more, uh, pronounced these days.

And what we look at in the book is, first, foundational technologies, critical minerals, semiconductors, frontier technologies, biomanufacturing, quantum, uh, and of course, you wrote the chapter on biomanufacturing. And then what I would call downstream technologies, so advanced manufacturing, the chapter I wrote, and drones as sort of an important case study.

And I think what comes across in my mind, if you read a- all of the chapters and sort of take it all in, is that w- Our innovation ecosystem that we've had and that was set up sort of post-World War II is necessary but maybe not sufficient for what it takes today to lead in new technologies. And the priority here or the, or the urgency of this agenda, I guess, is in part generated by what we've seen in terms of the rise of China.

And everybody's quoting this, uh, research that came out of Australia, but that 20 years ago, the US was leading in 60 out of 64 key technologies, and today we're actually behind China in something like 57 out of 64 of those technologies, so a real flip. And the question is, how do we regain or gain global leadership to be competitive in some of these areas?

And I think the book is trying to provide a pathway forward that's accessible and that speaks to both the in- innovation ecosystem and the industrial ecosystem. 

Chris Love: Yeah, Liz, I think that th- this idea that innovation is sufficient is one that we've kind of held as a society now for, you know, 20 or 30 years at least, as we've allowed, you know, production to go offshore.

And, you know, I think in doing so, what we've given up is aspects of that innovation and the value capture that comes from actually learning by doing and in production itself. As you know, MIT has been thinking about this problem for nearly 40 years, going back to Made in America, where, you know, studying how Japan was, at the time, competing with the United States, kind of recognizing that technology wasn't sufficient.

It's necessary, it's a key component, but that we also have to think about the broader ecosystem and the workforce and how we actually implement manufacturing as, as a system and not simply as a set of technologies. And your point that this book is really trying to outline not just one area, but several areas is also really important.

If our friend Simon was here, he would certainly say that investing in many technologies because you don't know which one is going to win is actually really important as we think about a strategy. And so underlying all of that, as you've mentioned, right, is manufacturing. We can't bring these technologies to market, uh, if we don't have production capabilities.

Elisabeth Reynolds: Yeah. I always liked the vision, I guess, that was put forward by Vannevar Bush, who of, of course, MIT president, but also was the head of the Office of Scientific Research and Development during World War II and sort of created the endless frontier vision in 1945. It's interesting to think 80 years ago what that vision was, and I think the vision was one in which we're not interested in so much a, a stock of technologies as a flow of innovation, right?

And that's where the US has been so strong. We've had both on the R&D side, on the startup side, on the venture side, all of that moving to create, you know, the most innovative economy certainly in the last, uh, whatever decades. 

Chris Love: The United States no longer has an invention problem. Right. We're, we're, we're the best in the world at invention today, but what we have is an industrialization problem.

Right. We don't understand how to bring some of these ideas quickly into the marketplace to test them out and to advance the underlying technologies that are a part of that. 

Elisabeth Reynolds: Yeah. 

Chris Love: And this is where learning by doing is so important. 

Elisabeth Reynolds: Right. This is a great segue, I guess, maybe into the biomanufacturing story.

Um, but one of the things that you find in the chapters on semiconductors and drones is that in both cases, you know, invent it here, make it there has played out. And we've seen now the country become, basically get caught short on the semiconductor side, and certainly the CHIPS Act and the bipartisan effort to try and build back our capabilities in semiconductors is, is well on its way and I think having some success.

And on the drone side, we've seen, you know, all of the innovation for drones came out of the US, Japan, some in Europe. 80% of drones are now manufactured in China, a problem certainly from a military point of view, and as we've seen with Skydio and export controls on the civilian side. So in both of those cases, we had a very efficient supply chain that did not serve us in moments of conflict or crisis.

We're pulling back, trying to figure out how do we rebuild that. And it seems to me like it's a little bit of a cautionary tale for the biomanufacturing story. 

Chris Love: Yeah, super interesting to look at these other cases in other sectors to kind of see what's played out. Those are very mature sectors, as you've described.

We could say biomanufacturing today is still in its adolescence in some ways. Like, this is a technology space where, and maybe just for some context, right, thinking about the bioeconomy, this is in the news a lot these days, uh, the idea that biology can produce almost any type of product is, you know, something that, you know, we all have experience with.

It, in many ways, biology's the original general purpose technology. Maybe today it's becoming a general production technology. We can make foods, materials, chemicals, raw materials for diagnostics, vaccines, biopharmaceuticals, all of these different kinds of components that are part of our regular supply chain are elements that biology can now produce.

But the key is not in engineering the biology to make those. We know how to do this in many ways today. It's in actually being able to bring those to scale through manufacturing practice. And this is where, you know, if we look at what's happened in semiconductors and some of these other technologies, we've allowed for that invention to occur, and then we've deliberately allowed the, the production to move elsewhere.

Originally, biotechnology was focused here in the United States. If we look back to Genentech and the original insulin production and some of the initial phases of biotechnology, companies like Genentech, Amgen, Sanofi grew up in this era where they were very much vertically integrated. They were controlling the ability to produce because no one knew how to produce these types of medicines.

But today, as we've allowed, you know, for this to, to move overseas, our supply chain in this industry has optimized across the entire globe. And as a result, right, we're in this kind of moment in time where we have to choose. You know, we can come up with the best ideas here in Kendall Square and, and, and the Boston area, but if we allow them to go overseas to be produced, we're losing that knowledge base about how to produce them.

And just simply with the rate at which we're now innovating ideas in biology, you know, lots of different kinds of medicines for rare diseases, new kinds of, uh, food and nutritional supplements, even pharmaceuticals, things that can be made by biology like antibiotics, you know, we don't have the ability to bring those innovations into the marketplace fast enough, uh, today reliant on, you know, what's a highly centralized model that starts to resemble some of these other sectors as you mentioned.

Elisabeth Reynolds: So particularly interesting, I think, given where we're sitting and what's going on in the country, what about advanced manufacturing technologies and how that's transforming the biomanufacturing? What's, what the opportunities are, I guess, in the US? 

Chris Love: One of the things that we forget is how manual much of manufacturing historically has been, and almost always you have to learn how to make before you can automate, and then you have to learn how to automate before you can really control it with software.

And for industries like advanced manufacturing, this is now going through that transition to where we're becoming much more software driven, much more automation, uh, embedded into how we produce things. In biology, this is still a highly manual process, is you take a large lab experiment and you come to my lab at MIT and see a small reactor Production's really not much different, it's just at a much bigger scale.

It's a bigger tank of fluid. And so there's a lot of manual touch points, a lot of, of movement around in the facilities. You know, I think one of the trends, and you and I have had the chance to kind of think about this over several different sectors over the past couple years together at MIT, is that software-driven, AI-enabled, and highly automated small micro factories are becoming a really interesting way to think about the future of manufacturing, where we can keep pace with the innovation that's occurring on the product side.

Elisabeth Reynolds: Right. And so this vision of distributed manufacturing, bringing manufacturing continuous improvement into the process, AI now hugely, um, impactful, right? 

Chris Love: These are all enabling technologies. I mean, bio- biology's hard. I think we can all- Mm-hmm ... admit that, like, we don't really understand it on many levels.

Uh, and as we think about, you know, what's it going to take to bring biotechnologies to be a, a fully mature and robust industry, uh, you know, across many different areas of the supply chain, we are gonna have to learn how to control that biology better, and I think this is an opportunity for AI. It's ubiquitous now, right?

We, we all are living with it and trying to understand how we're going to use it in our workflows. Using it to help unlock biology seems like an enormous opportunity, not just in helping to inform design of new medicines, as we're seeing in many places, or improve clinical trials, but actually in the manufacturing.

How do we use it to better understand processes? How do we, uh, understand how to provide better control around our facilities? And how do we know how to troubleshoot better? 'Cause I think one of the challenges in manufacturing we often forget about is that you actually have to deal with deviations.

There's things that you're gonna see in manufacturing that you've never seen before during a process just because of the number of times that you're iterating now. But AI provides a really interesting toolkit to ask, you know, how do we optimize that, that production process? 

Elisabeth Reynolds: Right. And I think one of the things that I've been getting as questions about the book is, "Well, where's the chapter on AI?"

And our approach to it was, of course, AI, you know, a critical technology, emerging general purpose technology, um, but it should be viewed as a tool, and it's a tool across all of these six areas that we discuss. The challenge is the adoption, right, and the deployment of that technology. And Simon and I have been, uh, working on something in which the title is called Winning the AI Race is Not Enough, because right now it feels like the whole discussion about technology in the US practically is around AI, you know, bigger, better, faster models and things like that.

But the, the real point here is how are we gonna deploy it? How are we gonna apply it, gain the, you know, productivity gains, also find ways to augment workers, make their work better and more productive, and also create more quality jobs? So I feel like the AI piece should be seen as sort of a layer across all of these chapters.

You know, how are we bringing it to bear? And the good news is I think that AI feels like that we're democratizing it. The quicker we can get it into the frontline workers' hands and deploying and, and working for us, the better. My feeling is we're now-- Like, there's been a tipping point. Now people are really looking at it that way.

Chris Love: Yeah, I think it's interesting thinking about the workforce integration with AI. I mean, this is something that, again, we, we've thought about and you led, you know, a substantial study on this about 10 years ago now. Yeah, when it was 

Elisabeth Reynolds: all about the robots. 

Chris Love: Right, work of the future when we were worried about are robots taking our jobs.

I mean, in some ways this is coming back around for us now to think about as well. But, you know, I think one of the findings that came out of those studies at MIT and Work for the Future was really that jobs don't necessarily go away when new industries hit. They just change shape. And as we see what AI can do, it can really supercharge and empower people to be able to make better decisions in complex situations, and that a core part of work in the future is going to be how do we make good decisions given what's around us?

So judgment and decision-making are gonna be really important in this new era of AI, and I think we're gonna see that play out in manufacturing for sure as we move towards software-driven, smaller facilities allowing us to learn faster. How do we learn faster? We learn by making and doing, and that's gonna be software-driven, and ultimately there will be an AI component to that.

So workers who can really bridge between fundamental knowledge in operations and some of the engineering skills to be able to use AI to help inform and make better decisions on the shop floor, much like what Tulip is helping enable here, really creates that opportunity to create new kinds of workers that we haven't had before.

Elisabeth Reynolds: Yeah. So I would say we've hit a couple of the themes that, uh, one finds across the book. So one is a manufacturing component to all of these technologies. The other is supply chain resilience and what does that look like? Obviously, in some cases, we want domestic production capabilities. Certainly, we're leaning in on critical minerals and that in the country right now.

Um, but it also is relying on allies and partners and building out global supply chains that are also more resilient. Workforce, another key topic that we find across the board. Basically a shortage of workers, both at the sort of technician level, but also at hi- in the higher ed, you know, engineers and post-graduate students as well, and that I think is another topic that we need to lean into, certainly as a country, and particularly at a time in which our immigration policies are, uh, you know, running counter in some ways to bringing the best talent to the country.

How, what are you seeing in terms of workforce needs and opportunities in the biomanufacturing space? 

Chris Love: Yeah, I think it's just one of these areas where as a country we're, we're, we, we have like 100 years' worth of work to do in like 10 years or something- ... to bring along, you know, the kinds of workers that we need to enable this new era of manufacturing in the United States.

You mentioned the jobs are changing in new ways, you know, and as we think about what that interface looks like, we need to adapt our educational systems to address that. And this is really all across the entire spectrum. We need to think about how do we educate students in K through 12 and in high school to be prepared to enter the workforce directly to participate.

We have, you know, half a million jobs, uh, in manufacturing that are unfilled right now, uh, and these are good jobs. They're not the old jobs that we kinda think of as manufacturing, but they're increasingly automation-oriented, uh, where there's an opportunity to really, uh, do new things, but we aren't educating folks to, to bridge that gap.

We have workers that are in the field that are having to get familiar with digital tools like the ones that we're, we're, we're seeing here at Tulip and that others are developing. Uh, how do we encourage them and find new roles for them in this, this space? You know, one interesting innovation on that front is some work that's being done at MIT to develop a role called the technologist.

And so the idea is to create something akin to a nurse practitioner, but for manufacturing. So in the healthcare sector, you have a nurse and you have a doctor. A nurse practitioner is this important role that's one of the fastest growing roles in the United States, uh, to fill this gap of between decision-making and kind of the overall maintenance of the patient, if you will.

Uh, as we think about what that looks like in manufacturing, someone who sits on the shop floor that has an understanding of why we're building processes, why manufacturing supply chains operate, but knows technically what is happening on the floor, is a really powerful person that can help, you know, bridge gaps between these two parts of the organization.

In many ways, MIT has been leading this type of, uh, hybrid role for many years. Uh, one of the original recommendations out of Made for America in 1989, if you go back and read back to then, was a similar kind of identification of an, a need for a role that bridges between, um, in that case, business practices and management of supply chains and the operations on the shop floor of the manufacturer.

Uh, and this led to the creation of the Leaders for, at the time, Manufacturing program, and now the Leaders for Global Operations at MIT, uh, that's really bridging between Sloan School management practices and an MBA and engineering skills within, uh, the School of Engineering. And, and I think these are examples of the kinds of roles that we need to think more about in that interface that educational systems have, you know, forgotten a little bit about, is how do we help bridge the communication gap between these different spaces?

Elisabeth Reynolds: Yeah, it's great that you're hearkening back to the Made in America effort. I always laugh because they say that the Made in America book was an MIT bestseller, which is hard to fathom. But it was. It was a wake-up call about, um, US productivity challenges in industries. And, and what's 

Chris Love: amazing about it is if you go back and read the first paragraph in the book- 

Elisabeth Reynolds: Yeah

Chris Love: right, you could've written it today, right? It's all about how we're losing ground, and that to live well, we have to produce well, and that w- you know, we're losing ground in this battle, and how do we think about, you know, reshaping things to be more productive here in the United States? 

Elisabeth Reynolds: Yeah, it's extraordinary.

And we should also mention on the whole Technologist Vision that MIT... That work has been, um, sponsored by the Department of War, and it's engaging with, at this point, I don't know, 10 to 20 community colleges, that that is the, you know, the idea of post-secondary education. And it's very much also taking a page from the German model, where the Germans have for a while created that pathway through their apprenticeship model of both on the shop floor skills that are learned, as well as kind of engineering principles.

So very exciting. You know, at its early stages now, but I agree that transformation has to happen, you know, at our educational institutions really. 

Chris Love: A- and really thinking about continuous learning. Mm. Like I, I think, you know, we, we optimized a system in a certain era where it made sense to kind of stage gate through particular educational elements, and with the four-year degree programs being the most important of that, you know, for most, for most p- people.

And access to that was remarkable and continues to be. But we're in a new era where information is now available in a lot of different forms, and really principled thinking with good judgment and decision-making is something that we have to kind of lean into as core skills, as we've talked about. And how do we think about bringing that type of education into kind of all sectors of society as we're, uh, enhancing, you know, what, what will be a new industrial base here?

Elisabeth Reynolds: Yeah. One of the other things that I think is important across, um, all the chapters, which perhaps, you know, feels like it's a bit under attack today in the country, is the importance of the R&D piece of this. You know, we've always had an engine that focused on the R&D, but what I found remarkable across the, the board was how much of the R&D that's, that provides the opportunity for leapfrogging is actually connected to our, the manufacturing processes, right?

So in quantum, it's scientific breakthroughs and it's engineering breakthroughs that are really important at this point in time. In mining, of course, we've got technologies that are involved in, uh, separating tailings, you know, materials science, but it's also in the production science as well, or in the, in the manufacturing sciences.

So it's sort of a very interesting view on the role and the importance of R&D at a time when NSF, NIH have been under attack by the federal government. I think Congress has been trying to, and has restored some of that, but we know at MIT we've been hit hard. I think the president just said 20% of the budget, uh, for next year, 500 plus students now won't be on campus that might have been.

This has got a serious impact, and I, I wonder if you, you know, from the biomanufacturing perspective, your vision of what's unlocked if we can, you know, invest in some of that, um, early stage R&D. 

Chris Love: Yeah, I, I think one of the things that we call for in the book is, is a focus on the science of biomanufacturing.

We've lost a little bit of this perspective of actually doing the science necessary to figure out how to make things. We, you know, celebrate the idea of innovating a new drug or a new medicine, but ultimately, you know, and my doctoral advisor used to say, "Ideas are cheap." It's only being able to bring that to the patient that matters, and the path to that is through manufacturing.

And, you know, we have manufacturing practices that work. There's an amazing number of medicines that have reached patients globally, uh, but there's many more patients that are underserved. You know, there's something like 9,000 rare diseases, uh, that don't have treatments, and this is, you know, a- an area where, as we get better in biology, you know, we talked about AI and unlocking new insights to medicine, we have to be able to make medicines more efficiently and more effectively.

And so the whole idea that we should innovate in production is something that has been, you know, really holding this field back in many ways. And sometimes it's because we talk about regulations and compliance, but the regulations are the regulations. It's, it's a playbook. How do we think about bringing new technologies to bear in this and demonstrating them?

And part of what we call for i- in the book, you know, as we, we went through and, and worked on this together, is really thinking about how do we, you know, get to these leapfrog demonstrations, right? Like, there are technologies that exist. We've been fortunate enough to work on some of these at MIT over the last 10 years, uh, through programs sponsored by the Department of Defense and the Gates Foundation and others to really think about small manufacturing systems that could deploy anywhere, I mean, practically in this room that we're sitting in, and make GMP material.

We've had these technologies for a long time. That's not sufficient. It's actually thinking about how do we innovate not just the research side, but also the demonstration component. And, you know, I think this is s- another element where we've kind of forgotten about this. We're very focused on the innovation, but we also have to actually bring these things to a point where there's enough demand on the market side to actually pull in private financing.

Elisabeth Reynolds: Right. Our colleague David Autor just put out a paper looking at the evolution of skills and occupations over time and how important one of the findings that they track, uh, over the decades of looking at how occupations and, and skills have been evolving is the really important role of the demand pull of federal dollars coming in to try and figure out how we create the internet or GPS or nuclear, whatever it is, and the ripple effect of what that has done for specializations and skills.

And so this question of what is the role for the government In trying to not just spearhead the R&D piece, but help pull these technologies through some of that early-stage demonstration. I think that's become, you know, something that we've understood is, is a weakness in the US capital market system, right?

We've seen a strong venture community come around to all the innovations, but if they're interested in exiting in eight years, uh, or less, what does that mean for some of our engineering, you know, quote, "hard tech" manufacturing-type technologies? And I think we've seen both, I think, on the private sector and the public sector, a lot of innovation going on, a lot of experimentation.

How can we bring more capital, certainly from the public sector, to de-risk technologies and crowd in private sector? Uh, Office of Strategic Capital now in, uh, the Department of Defense and then Ex-Im Bank and how that might play a role in, in also trying to provide low-cost capital and even equity to companies now.

Chris Love: Yeah, it seems like this is that challenge that entrepreneurs always face in kind of that, the second valley of death. We often talk about the valley of death, but it's like really that first stage is getting the idea out of the lab and into, you know, some demonstration that it actually works. That phase, at least in my experience as an entrepreneur, is relatively straightforward in many cases.

You can find venture capital that's excited about that, or you can, you know, find ways to bootstrap aspects of it. But bringing these technologies to scale, uh, and this is something that we're thinking a lot about within the Initiative for New Manufacturing at MIT, as you know. How do we think about this scaling question?

What is the right model for financing? What's the role of the government and the private sector? And ultimately for innovators, like, how do we actually bridge that gap together? As you mentioned, this is a place where we've historically had a challenge. You know, we're really good, again, at invention, but we're very poor at actually bringing things to commercial scale.

And what we've tended to do within our financial capital markets is to rely on folks that already have existing capacity somewhere for manufacturing, and oftentimes today that's overseas. But as we've talked about, that's losing the opportunity to capture some of the value that comes from innovating the actual manufacturing processes.

Elisabeth Reynolds: Yeah, I think the investor community has historically wanted asset light, uh, companies and, but I think that's shifting. I think people are understanding we're gonna have to pay something for resilience. That may be something that they'll have to see kind of in a, in a different type of manufacturing structure.

We also have to see what it means to get to the other side, you know, to that missing middle is what people are talking about a lot in the energy space. Do we need new tools, new insurance tools that would help, you know, with investors make that commitment? And I think we're also seeing in the venture space in trying to bridge this area an extension of people's vision for what they should be comfortable investing in, because it's gonna take longer for a lot of this.

And the upside right now, the demand certainly from the defense industrial base is huge right now in the US, but we're seeing that in defense, we're seeing it in critical minerals, we're seeing it in semiconductors, a whole host of areas where we are seeing a significant crowding in of the private sector.

Even in energy, I think we're seeing a lot. 

Chris Love: Well, I think in many ways, like this is how we identified the priority technologies that are in this book, right? Priority technology is one that has the potential, the kind of dual use components, that it's gonna be helpful to drive economic prosperity, but also addresses aspects of national security.

And as we think about, you know, what's required to do this, it's gonna take a partnership of private sector, government, and academia to, to really unlock many of these technologies. You mentioned quantum and, uh, biotechnology both as, or biomanufacturing as two examples of frontier technologies. Both of these have, you know, to see them be truly transformative, five, 10, maybe even 20-year horizons to actually having the kinds of impact that we're expecting from them, uh, on the broader society.

This is a long time in a venture capitalist's lifespan. Mm-hmm. You know, they, they, they tend to work in three to five-year cycles, and so what's the right bridge to think about Private sector funding, but long-term strategic capital that the United States can invest in. And I think this is where there's an opportunity to move beyond just technologies that are already being commercialized, like AI we talked a lot about, right?

There's a lot of momentum there. These are technologies, among others, that could use some additional crowding of financing from both sides, uh, to help facilitate kind of getting over that, that boundary or the, the activation barrier. 

Elisabeth Reynolds: Right. And I think what we're seeing right now is, um, one of the tools in the toolbox of the current administration is taking equity stakes in companies, which in many cases makes sense because of the unique circumstances, you know, of critical minerals where we may not have a lot of players and things like that.

In general, I'd like to see a broader approach in which we're trying to build sort of competitive industry and provide a number of different ways in which we incent private sector investment and maybe not sort of distort markets in, in, in many ways. But the fact is we're, you know, very focused on trying to build, uh, globally competitive companies and trying to find ways to bring more capital to bear in a system that has faltered, really.

And, and when we look at, for example, how China does this, which is enormous amounts of money, a lot of it wasteful, and yet they are scaling, you know, companies and bringing products to market and now dominating in many areas, and I think it's something that we need to observe as a country and figure out, okay, what parts of that make sense and what parts don't?

I know in the biotech space, you know, China's rise is, is been remarkable, and as we, you know, looked, uh, about 80% of biopharma companies operating in the US are reliant on Chinese production. You know, what do you think g- going forward that looks like for the US? 

Chris Love: Yeah, I, I think it's really remarkable how much they have, with speed and dedication, installed really over the last 20 years some of the, you know, s- really frankly, some of the best contract manufacturing on the planet for producing biopharmaceuticals.

And as you say, many biotech companies now are reliant on their services to be able to bring some of their ideas into the clinic. And so ultimately, this creates a technical challenge for us, both on the economic side, but also on the national security side and thinking about access to medicines, uh, in, in this kind of current moment.

How do we think about this? Well, if you look back historically, we take our, our friend Simon Johnson again and think about, you know, w- w- some of his lessons to us in thinking about history. If we look in the UK in the 1920s, penicillin was discovered, so the original discover of one of the first antibiotics was in the United Kingdom.

And it was in World War II where that antibiotic needed to be scaled up in order to be able to treat soldiers, uh, on, on the Allied front. And to do that, the technology that was required wasn't available in the United Kingdom. It was in the United States. We had deep tank fermentation through some of the companies like Lilly and others across the, and Pfizer across the country that were able to scale up this production of antibiotics to treat, to treat the soldiers.

Where is the capital of biotechnology today? It's like literally right around us as we sit here in the Boston area, uh, in Kendall Square. So the ability to produce at scale allowed us to learn how to do that, which ultimately led to some of the first recombinant products made. So insulin, you know, recombinant means with DNA, uh, and bacteria in the 1980s in Genentech, all of that learning was, uh, uh, because we had the ability to connect innovation with production.

If we look at what's happening today in China, we have much of the production ca- capabilities that we're reliant on now sitting there. Uh, they've trained in our best academic centers, and they are now creating discovery with, like, AI tools and other things. The barrier to discovery in medicines and other parts of biotechnology now is super low.

And so if it's super low to come up with an idea and ideas are cheap We have to be able to produce it. Where is that capability? And so we're seeing this play out presently as many assets now from China have been through, you know, many stages of clinical development. They have production capabilities, and many of the large global biopharm companies are investing heavily in assets that were developed, uh, in China.

This creates some interesting challenges for us as we think about, you know, s- m- supply chains and security of medicines. 

Elisabeth Reynolds: Right. But we are not going to match China on scope or scale. I mean, what, what we've heard from our colleague, Yasheng Huang, like they are competing with Africa on the low commodity product, and they're competing with us on semiconductors on the high-end value-added product.

And they're, you know, they're 10X the number of engineers, et cetera. We've got all those numbers. So, you know, it's really about being strategic about where we can compete and, and in what products and what areas, and it's going to be higher value-added work, no question about it, and it has to be in what I consider, you know, areas that we have real competitive advantage, niche, you know, leapfrog technology opportunities.

And so do you see that in biomanufacturing? What... You know, what areas do you think we, we should be focusing on? 

Chris Love: Yeah, I think that's exactly right. We can't build facilities faster and less expensively than you can in other parts of the world, and so we have to really play to our strengths of what we do well in the United States, which is innovation.

And so how do we think about that here when you have to innovate faster at the scale of the facility, not just the idea, but the actual production side? Uh, and, you know, some of the things that are happening now, right, again, trends because of software, AI, automation, all of these things are allowing us to really shrink the factory down.

We had an opportunity to develop some programs at MIT that have now spun out into a company called Sunflower Therapeutics that's advancing GMP production equipment for manufacturing biopharmaceuticals in a room that would look kinda like this. Uh, this is very far from what a typical plant looks like today, but the cost of building a facility of that type could be 10 to 100 times less expensive than the traditional facilities that we build in biopharmaceuticals.

Typically, these facilities cost anywhere from, you know, half a billion dollars to $2 billion. They take three to five years to advance and be ready for production. There's no way we can build fast enough on that timeline with enough facilities across the nation to really overcome the, the mismatch between how fast we're i- ideating new ideas in medicines or food, um, and other parts of the, the bioeconomy With that production capability.

But imagine, you know, much like inkjet printers, the ability to scale out. Scale out becomes a really important concept where we have unique capabilities, I think, that we can leverage on and build on, not just in biomanufacturing, but in many of our sectors, and we're already seeing this play out in aspects of automotive production and in, uh, assembly technologies.

We can't assemble iPhones in the United States. Well, actually, there's companies trying to do this through small microfactories that can compete very, very effectively. 

Elisabeth Reynolds: Yeah. So I think that this is why this moment is so exciting for all of us involved in manufacturing, one way or the other, is that, you know, to achieve some of the goals that we see out there, whether they're around national security, whether around, you know, taking advantage of a potentially, you know, $4 trillion bioeconomy growing, that this ability to scale production to both, you know, have the capabilities but also have the capacity, again, I don't think we have to be making everything here, but that is critical to our goals, whether it's across the critical minerals, the semiconductors, all of the things we've been talking about, and that is a story of robotics.

It's a story of automation. It's a story of AI. And you see this starting, I think, to ripple across... You know, we've been talking about this perhaps for a long time, but right now it's really about how fast can people adopt. That's the question. And so, for example, the Special Competitive Studies Project, SCSP, in Washington has started a national, uh, security commission on robotics and advanced manufacturing.

I sit on that commission. The Congress is considering some kind of national commission, um, to look at robotics and, and how we adopt more quickly. And people understand, like, without that pathway, particularly given the shortage of workers we have, we don't have a chance. So how do we do this? And I think that's the moment where you see this enthusiasm and o- sense of urgency.

Chris Love: A- and opportunity. Right. I think we should not forget that, like, the real opportunity of thinking about distributed production here, not just in biomanufacturing, but across sectors, is the ability to build ecosystems of prosperity across the country. By making the entry to production lower, we can bring ideas from anywhere into production.

And we see this in additive manufacturing today, where 3D printers are changing the way that people can get entry into the marketplace. What if we could do this in biomanufacturing or some of these other sectors where there's, uh, an opportunity to build smaller facilities that actually seed an entire new base within a region around universities or other centers?

You know, one example that I like to look at is in the bioeconomy especially, we already have an example. It's in craft brewing. There's something like 9,000 craft brewers now across the United States. It accounts for about 25% of beer volume sales in the United States. And while we'd like to make things that are, you know, maybe m- m- higher value add, like medicines and, and other kinds of nutritional supplements than just beer, it does have a really remarkable knock-on effect in the local economies.

Every job at the, at the facility generates at least four more jobs in the immediate surrounding areas and as much as eight in the surrounding region. It creates a restructuring of the supply chain. Farmers start to adapt their crops to provide the raw materials that go into the facility, and obviously you have the ability to respond flexibly to consumer demands in changing the types of beers or things that are being made.

Not everything is gonna have this exact feature to it, but as we think about what you could do in rare diseases or in other kinds of a- applications of biotechnology, what would it look like to build regional systems in Iowa and in Indiana and other parts of the country where there's an opportunity to really seed new ideas and new innovations, uh, in production because we've lowered the barrier to production itself?

Elisabeth Reynolds: Right, and I think that was in part why we put the, the term shared prosperity, uh, in the title of this book, was that innovation just for innovation's sake is not enough. Unless we see the benefits of innovation being shared broadly, we have pushback and, and understandably so. You know, the, the fear of the robot has been real.

If your, if your wages have not increased in real terms in, in 30 or 40 years, you're not sure that technology is working for you. And so how do we make sure that technology is working for everybody, uh, and that these innovations are actually playing out? And I think partly what's exciting about this moment is we've understood now in a way that we didn't in the past several decades that actually supply chain resilience and manufacturing are part and parcel of our innovation ecosystem, that it's the innovation ecosystem meets the industrial ecosystem, and both of those are important.

And when we kinda complete that picture, it actually has a lot of downstream positive spillovers for communities, for workers. The hope there, I think, is that we can create a better model for some of these jobs, you know, with a trajectory for middle income jobs and career paths. 

Chris Love: It's this convergence.

It's the convergence of the ideation economy with the production economy, and actually this is something that we've thought a lot about at MIT in the past as well. The, uh, production and the innovation economy study, the PIE study, really highlighted that this, this proximity is important because you learn by seeing what you left on the table when you're producing things.

If you can push the production a little bit better, you can change the design. You don't get that just from the first idea, "Oh, I want to make a new product." It's actually, "What is that product that I can manufacture at scale? I need to see it to learn it." And this is really where I think there's so much excitement right now is the potential of bringing these things together.

As you know, the Initiative for New Manufacturing at MIT has kicked off in the last year, and this is really what the focus of it is, is, you know, MIT has thought a lot about how these things should play out at a systems level, and, you know, the challenges we've talked about here is this component of bringing it out and diffusing that into the ecosystem.

And so we're super excited about using MIT and, and the Initiative for New Manufacturing as a catalyst to really transform, uh, production across the United States so that we can have better jobs, more productive, and more resilient systems for, uh, all sectors. 

Elisabeth Reynolds: Yeah. Our, our colleague Jesus del Alamo talks about the innovation really happening on the manufacturing floor for semiconductors, and that's been TSMC's strength.

Uh, and you know, it's played out in terms of packaging and all these areas. And so, you know, the US is playing catch-up on now manufacturing frontier chips in the US, which is a really exciting proposition. But we don't have the workforce that we need. We have to address sort of environmental challenges, et cetera.

But we have an opportunity to rebuild and create that, um, capability in the, in the US now, and people understand that as a, uh, both the national and economic security aspects of that. And I think so far so good, you know. I mean, there's bumps along the road, but we are seeing those investments now by multiple companies around the country.

Chris Love: Yeah, I think we're at this moment in time where we can make manufacturing cool again. Hmm. Right? We've sort of forgotten as a country that manufacturing is actually a great thing. People like to make things, and with, with new innovations and technologies, these are things that help you make better, and this is really what, you know, automation software, AI, robots, these ultimately allow us that co-working experience that it's, it's about making things, but doing it in a way that really is transformative, both for your family and for, for the larger ecosystem.

Elisabeth Reynolds: And ma- it's only, I think, through that new technology that we're gonna actually attract the next generation into this. They are, you know, they're born and bred on all of these technologies, and they want to be working with them. And so that may be the way that we can bring more of the young people into the, into manufacturing going forward.

Chris Love: Absolutely. 

Elisabeth Reynolds: Yeah. 

Chris Love: It's a fun time. 

Elisabeth Reynolds: Yeah, it is. Well, this has been great, Chris. I love talking with you. Anytime we get, we get... This is more time we've had together than, you know, in the last three months. So wonderful to engage, great to have Tulip hosting us, if you will, on this, and we, uh, are excited about our new book and, and hope people will, uh, will get a chance to read it.

Chris Love: Yeah. Thanks so much, Liz. It's a real pleasure to be here. And yes, it's great to spend time with you and, uh, great to be here at Tulip. 

Narrator: Thank you for listening to the Augmented Ops Podcast from Tulip Interfaces. We hope you found this week's episode informative and inspiring. You can find the show on LinkedIn and YouTube or at tulip.co/podcast.

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