We ask MIT’s Vander Heiden to delineate science from engineering—and NCI from ARPA-H

“The lines are much more blurred in terms of what’s an engineering problem and what’s a basic science problem.”

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Matthew Vander Heiden, MD, PhD

Matthew Vander Heiden, MD, PhD

Director, Koch Institute for Integrative Cancer Research, associate professor of biology, member of the MIT Center for Precision Cancer Medicine, Ludwig Center for Molecular Oncology, and Broad Institute of Harvard and MIT

I can tell you, seeing patients is not entirely an algorithm. We can want it to be algorithms, we can build algorithms in to help quality of care, but people are people and every case is individual and there’s some art to that. 

The boundary between basic science and engineering has been the subject of animated discussions in cancer research for quite some time. Where does science end and engineering begin? Is that boundary porous? How does it shift over time?

Today, these questions have gained urgency as the Biden Administration  stands poised to spend an additional $6.5 billion by creating Advanced Research Projects Agency-Health within NIH. This amount is roughly equivalent to the NCI budget. (The Cancer Letter, April 9, 2021).

The boundary between science and engineering may coincide with the boundary between ARPA-H and NCI, insiders say. What kinds of institutions will it engage as ARPA-H contractors? Will contracts be awarded to academic institutions or to industry?

To get a sense of where these discussions may take cancer physicians and scientists, we spoke with Matthew Vander Heiden, an oncologist and cancer researcher who recently became director of the MIT Koch Institute for Integrative Cancer Research (The Cancer Letter, April 2, 2021). 

“There’s always been great basic biological cancer research at MIT, and there was increasingly fabulous [cancer-related] engineering at MIT—and the idea was to try to bring those two things together and say, ‘What if we took applied scientists and basic scientists and co-housed them, would we approach things differently?’ And I think that is a model that has been phenomenally successful,” said Vander Heiden, who on April 1 succeeded Tyler Jacks, who served as director for more than 19 years, first for the MIT Center for Cancer Research and then for its successor, the Koch Institute.

“That said, some problems are clearly scientific,” said Vander Heiden.

Jacks, Vander Heiden’s predecessor, is now president of Break Through Cancer, a $250 million privately-funded research initiative, and is the David H. Koch Professor of Biology at MIT (The Cancer Letter, Feb. 25, 2021). 

Another MIT colleague, Eric S. Lander, has been nominated to the position of Science Advisor to President Joe Biden. The position has been elevated to a Cabinet-level post.

Last week, NCI Director Ned Sharpless suggested possible areas of collaboration between NCI and ARPA-H (The Cancer Letter, April 16, 2021).  

Vander Heiden spoke with Matthew Bin Han Ong, associate editor of The Cancer Letter, and Paul Goldberg, editor and publisher of The Cancer Letter.

Paul Goldberg: Well, Matt, congratulations, first of all. This job does not come up very often.

Matthew Vander Heiden: It’s quite an honor, and I feel very privileged to have been offered this position, so it’s really nice to have this opportunity.

Matthew Ong: You’ve been at MIT Koch for 11 years. What sets your cancer center apart from others? What will you do that hasn’t been done? What areas of research are you most excited about pursuing for the cancer center?

MVH: I have been at the Koch Institute for the better part of my career, and I think I chose to come here because it always has been a place that’s a little bit different. I think it’s really the visionary leadership of the people who came before me that really tried to create a new model for how to have a cancer center that I think made a lot of sense from the perspective of being in a place like MIT.

We’ve always had phenomenal basic cancer research at MIT, really going back decades, to the earliest days of cancer research and Tyler [Jacks]’s and Susan Hockfield’s vision to say, well, there’s always been great basic biological cancer research at MIT, and there was increasingly fabulous [cancer-related] engineering at MIT—and the idea was to try to bring those two things together and say, “What if we took applied scientists and basic scientists and co-housed them, would we approach things differently?” 

And I think that is a model that has been phenomenally successful. Others do this too now, but it’s one that I still value and I think does make us a little special.

We have this perspective. I can tell you, having come from an MD basic science background. 

I did clinical training in oncology, and then, I also always viewed myself as very much a basic scientist, but I’d always lived in the biomedical research world—how do physicians and basic biological discovery scientists approach problems?

One of the coolest things I learned coming to MIT is that there are all these amazing engineers that really approached problems in very different ways, and it was so cool when people would show up at my office and say, “Hey, I built this device. What can I do with it?” And I was like, “Wow, that’s a very different way of thinking about things.”

I really noticed that engineers approach things from a problem-solving standpoint. It’s like, “Oh, this is the problem we need to solve. How do we break it down? What are the practical solutions that we can do to get there?” 

And those have been really great solutions to things like drug development, and drug delivery, and some of those types of things historically.

Tyler’s great experiment of co-housing us has been so wildly successful that I can tell you, from the trainees that work in the building, they don’t even think of themselves as scientists or engineers anymore. 

They joined programs and they have degrees and deans they have to talk to, but the lines are much more blurred in terms of what’s an engineering problem and what’s a basic science problem and how can you go back and forth between those two things?

I think it’s not just the structure that sets us apart as a cancer center, but I think that it really does work that way, that there really are people who think about, “Oh, wouldn’t it be cool to do this?” 

And people in my lab would then go ask people in the engineering lab, “Oh, wouldn’t it be cool to do this?” Or, from the reverse side, I’m sure it’s also true: “We built this cool thing, I wonder if it’s applicable to the problems that this lab is trying to solve?”

I think a lot of that back-and-forth has led to some really exciting new directions and opportunities and I’m excited to foster that and hopefully lead us to address the next round of challenging questions. 

There are new technologies being developed, new engineering solutions, and so, we want to make sure that we incorporate those—to the extent that they make sense to go after cancer—into what our center does, while at the same time we also have to remember what got us here.

That means we also need to continue to do excellent basic science. 

There are lots of engineering problems in cancer, but there’s some problems in cancer that are not engineering problems, and that means we also have to be able to address those.

PG: We’ll return to that, that’s a fascinating question. That’s probably the most relevant question in cancer research right now. But your research area of focus is cancer metabolism. Will you continue to run your lab, and what’s next in your work?

MVH: Yes, absolutely. I’m going to continue to run my lab. I’m still really excited about the work my lab is doing and I hope we can continue to make a big difference.

Part of why I’m excited about my lab is, I think, because as we’ve learned more about metabolism, there are some things that I think are now questions that have become more engineering problems and those are easy to ask. But I also think there’s a lot of basic things that we just don’t understand, and if we understood those better, we’d get a better handle on things too. And I’m more than happy to talk as much as you want about my own research.

I don’t know how much you want me to take off my Koch director hat and put on my lab director hat? I’m happy to do that and tell you what we’re most excited about there.

PG: Yes. If there’s a way to do that, that would be great.

MVH: One of the biggest questions in metabolism really has to do about what dictates why different cancers do metabolism differently, because in the end, that’s the key to really taking advantage of it or not.

One of the most common questions that I get is that, will we ever be able to target metabolism? Because all cells do metabolism, and will there ever be therapeutic windows, and all of those types of questions. It’s just so complicated. 

But I actually think maybe going after metabolism is one of the most successful things we’ve really done, and that’s because we have all kinds of chemotherapies that attack metabolism.

I always like to point out to people that we give chemotherapy to people, because it works. It’s our best therapy in a lot of cases, and we cure people, especially as adjuvant therapy with some of these old drugs, and the questions around what’s the drug like 5-FU target—well, it targets an enzyme thymidylate synthase.

Why are some cancers dependent on thymidylate synthase more than others? That’s really the therapeutic window question. I think if you view it that way, I think there’s a lot of excitement there.

I repeatedly tell my lab that if we could figure out which patients are going to respond to 5-FU or not, we’d help a lot more people than developing many of the new drugs that have been developed recently, because a lot of people get 5-FU, and we know it helps some, and we know other people don’t respond to it and we don’t really have a good understanding of that.

So, what I’m excited about is really this notion that, what seems to drive the metabolic phenotype and therefore the metabolic dependencies of different cancers—which goes to questions like, where are some of our existing chemotherapies going to work, versus how you might develop new drugs—has to do not just with the genetics of the tumor itself, but it’s how the genetics of the tumor interacts with where the tumor came from and what environment that cancer is in.

I think what a lot of the emerging data is telling us is that, when a cancer arises, it takes the existing metabolic program of its tissues and it alters it in a way that takes on the mutational character that helps lead it to become a cancer. What that means is that every single cancer is pulling together its own metabolic program to allow it to do what cancer needs to do, which creates an opportunity. I think in the end, this is where therapeutic window comes from. 

A liver cancer doesn’t use the same proliferative metabolic program as a lung cancer, because it takes the liver program and now allows it to proliferate, or takes the lung program and now allows it to proliferate.

And I think it’s those shifts that are really underlying why ultimately what leads to why some cancers are more or less dependent on other things, and I’m particularly excited about some insight that I think each tissue has its own metabolic environment that is largely a property of the tissue and not defined by the cancer itself.

I think it’s ultimately those constraints that may be speaking to things like metastasis and response in different sites, and so, I think there’s a lot of really cool, basic understanding questions that we can derive from that that in the end might be the key to answering what I think is the biggest question in the cancer metabolism field, at least from a translational standpoint.

And that is, well, here’s a great target, but how do I know which patient is best to receive this drug? Because that’s been the hardest thing for cancer metabolism to solve, and it is what has led it to every pharmaceutical company having a bunch of metabolism programs 10 years ago, and now not all of them do. Part of it is because they don’t know how to pick patients. Then, that’s on us.

That’s going to, what’s an engineering problem and what’s a science problem? I think the unknown, it’s not an engineering problem—knowing how to pick which patients are going to respond to a particular drug, at least with respect to metabolism. I think that is all the stuff I spoke to that my lab is interested in, I think is really understanding basic how do cells interact with their environment and what defines the environment.

There are engineering problems in how you answer those questions, but it’s still an unknown question. In answering those questions, I think will open up new possibilities.

On the other hand, if I want to deliver a drug to a specific location, or if I want to make a drug against a specific target, it’s well known how to do that, and it’s just a matter of engaging the right people who are good at it and solving the problems to overcome.

I had an interesting experience once, 10 years ago. I used to say, “Oh, metabolism’s great because we all know how to make drugs against these things. It’s much easier than other things or enzymes, so we know how to screen those things.” And the drug hunters pushed back and said, “Some of these targets are actually really hard,” and, of course, they’re absolutely right.

They are really hard, those are problems that the solution may be hard or the solution may require more work; some things are easier than others, but in the end, we know how to make drugs, that is something we know how to do. We know how to deliver drugs, and maybe we could do it better.

There are a lot of engineering problems that need to be solved, but the question of who gets those drugs, that’s not always in it, sometimes it is an engineering problem, but I would argue for metabolism, it’s not. And so, it’s a great example of where having basic science approaches with engineering people solves both sides of the problem.

And it’s an example of how I’ve really valued and benefited from being in the MIT cancer center, because I want to solve the basic questions required to make the next conceptual leap and open up a whole new area of things that are solvable to help patients in the short term.

But then there are some things there that could be solved in the short term and let’s work with the engineers to solve those problems, because they both make a big difference for patients.

MO: You’ve talked about this and probably answered this question many times now—speaking of translational science and engineering problems, everyone’s talking about what’s going to happen with ARPA-H, and Biden’s proposal for the DARPA-like agency. So, the question that perhaps we should ask is, “If we’re going to take that approach, are we at a point where cancer becomes an engineering problem?”

MVH: Look, part of the excitement amount around ARPA-H is, we’ve developed all these vaccines in the last year—no one thought that was possible, and we were able to do it. Maybe if we apply the same type of thinking to cancer, we can do the same thing.

I absolutely love that thinking, and I think there are probably things that we can do better there. But I would also point out, what allowed us to do the vaccines is, had we not had decades before thinking about: Could we deliver things by mRNA? Is that possible? How does one do that?

There are a lot of pieces that went into allowing, like, “Oh, now we have this new understanding of maybe how we can deliver mRNA. Maybe we could use that for a vaccine,” and then it became an engineering problem to try it and, lo and behold, it worked.

I think the interesting thing that will come from this and as being now director of a basic center—there are other basic centers out there—is, I think there’s also value in making sure we continue to support the basic efforts, so that the non-engineering problems also can move forward.

Progress in the new discovery space, also requires, of course, capital and more of that and more resources, and commitment there also helps make sure that the thing that is not the engineering problem today becomes the engineering problem of five years from now, so that we can solve that.

I really like to think a lot about the history of cancer and where have we done well, and things like that, because it’s easy for people to say, “Oh, we still haven’t cured cancer.” Well, I can tell you, as a medical oncologist, you are much better off being diagnosed with cancer in 2021 than you were in 2011 or 2001 or 1991, or, God forbid, 100 years ago, we didn’t even do anything about it.

So, where are our successes? Yes, we don’t cure all cancer, but we’re much better at managing cancers even that we don’t cure, and we’re much better at curing a lot of cancers that we couldn’t cure before, and progress has come from a lot of places. Progress has come from, not just new drugs, it’s also come from better supportive care and it’s come from solving some of the things to make people get the right drugs, and how do we combine the right drugs.

Those advances [that] were not sexy in the “here’s my new target” [sense] have arguably done as much to make the outlook of, look, no one wants a cancer diagnosis today, but it does allow more hope to be injected into those conversations.

Twenty years I’ve been practicing medicine, the conversations I can have with people with a new diagnosis of cancer have changed. We talk about different things today than we talked about before. 

There’re many more options, many more things from the future—immunotherapies that weren’t even on the table back then. Targeted therapy was just starting to come into the excitement of like, “Alright, let’s make these new targeted kinase inhibitors to go after the signaling enzymes.” That was just on the horizon.

Now, do we do it well for everybody? No, absolutely not. But the people who benefit from it benefit tremendously.

PG: When Kennedy made his moonshot speech, moonshot was already a series of engineering problems. We’re now talking about maybe some portion of the Cancer Program, 50 years after the National Cancer Act becoming maybe an engineering problem. Well, big chunks of it are, and increasingly they are…so, we’re almost at the point where Kennedy was, during the moonshot speech with respect to the space program.

MVH: Yes. I think that’s a great analogy, but I think it’s also not a perfect analogy, and I think getting this right is important. And I’ll only say that, because we have to be realistic with the expectations of the public.

It’s great to promise we’re going to cure all cancers in 10 years, but if that’s not a realistic goal, and I guess I would come back and say that, there are some things in cancer that are engineering problems, that weren’t engineering problems in 1971 when the National Cancer Act was signed.

So, now, 50 years later, there are things that have become engineering problems because of all the effort that was put in in the last 50 years. Now, the pace of scientific discovery is accelerating and that’s what I was saying, there’s a tremendous opportunity to capture the engineering problems. We are in a lot of ways at a juncture for many things, where if we put the right pieces together, now we can accomplish something new.

But on the flip side, there are some things we have to be realistic about and realize that there are some things we fundamentally don’t have an engineering solution for, and that’s why we always got to make sure we keep an eye on that and move forward. And I think it’s important to message that to the world, so that the world has the right understanding of what’s going to get us to the ultimate goal, which is no cancer suffering.

PG: Well, MIT is a part of the Break Through Cancer foundation, so how does your work connect with that, and how does it connect to ARPA-H?

MVH: The Break Through Cancer thing is an incredibly exciting opportunity, and I can tell you that we at the Koch Institute are absolutely thrilled to be included in that. I think this is the largest-ever gift in single organization to attack cancer.

And it’s very much aimed at let’s findfinding new creative ways to make sure we accelerate the solving of those engineering problems, the translation of what we know today, so that the new ideas we have really end up in the clinic.

My role, obviously as the leader of the Koch Institute, is being involved in that. Now, I also agreed with our previous leader, Tyler Jacks, who’s leading that initiative. Tyler asked me, was I on board being involved in this? And that was a very easy, yes.

As a center, he also asked if personally I would be involved in this in a way, because the way that Break Through Cancer is structured is, each of the five institutions that are participating, they’re going after a select number of diseases, and within those diseases, they’ve identified individuals at each institution who can work with each other to build the collaborative projects, look for the solutions and coordinate, brainstorming within their institution.

So, I’ve been involved in many parts of it, but I’ve been leading the pancreatic cancer effort for MIT just because that’s been an area of interest for my laboratory and connections I’ve had with people at other institutions anyway. I’m involved ion a personal put-my-lab-hat-on [way], but also, from an institutional standpoint, obviously I really think this is a tremendous opportunity and it’s another way to get the resources that are necessary to try to fix some of these problems.

I am not personally aware of direct collaboration between ARPA-H and the efforts at Break Through Cancer. Might some of those things exist? They very well could, but I’m not really sure that it’s something I can comment on with any insider knowledge.

MO: I think if ARPA-H fully gets funded, it’s going to be kind of like Biden’s second Moonshot, so to speak, even though it’s not exactly the same thing. I’m going to ask a completely hypothetical question where, say you were the director of ARPA-H, what would you do with those funds that is different from, say, what the Moonshot has accomplished?

MVH: Well, I think this is where some of the organizations like Break Through Cancer and Stand Up to Cancer create a roadmap for what can be successful, and I think the excitement of something that comes from the federal level like that is a degree of support that is very difficult to accomplish from any philanthropic source.

And that is how can we lower barriers to taking our best ideas and making sure we test those ideas in the clinic, and, absolutely, I know that’s part of what the Moonshot is, but that I’m sure will be part of ARPA-H. I think it should be part of ARPA-H, because look, those are the things that are there.

I think if I was part of ARPA-H, because I think this is relatively small dollars, relative to what I just discussed, is I would make sure that some of those dollars also go to make sure that we’re building the pipeline for the future, so that the engineering problems of tomorrow are defined today. Let’s solve the engineering problems of today, but also let’s make sure that we don’t sacrifice, not overcoming the challenges that aren’t yet there.

I think there’re very specific new opportunities today that didn’t exist before. One of the most common things that’s talked about a lot that has been on my mind a lot at MIT is that, there’s been tremendous advances in computer science and machine learning, and lots of things in the news about wearable devices and how should Google and whatnot be involved in health care.

Those are big questions out there, but the bottom line is that, more and more data is being collected. I’ll leave it to other people to make sure that this is done ethically and in a way that is right for society. That’s not an area that I feel like I can comment on, but the reality is, we’re collecting that data ethically or unethically. And I think there’s an opportunity out there to make sure that we apply that in the right way to solve problems.

As a physician, I will comment on something that is not often discussed here, and that is that there’s a push-pull here, there’s something called clinical judgment and a bunch of clinicians are talking about, “Oh, if we just collect a bunch of data, now we’ll know what to do.”

I see patients. I can tell you, seeing patients is not entirely an algorithm. We can want it to be algorithms, we can build algorithms in to help quality of care, but people are people and every case is individual and there’s some art to that, and not all people problems are as simple as, “Oh, let’s collect more data, and now, we’ll know what to do.”

But that doesn’t mean we can’t collect more data and answer questions that, before, we couldn’t ask, and now I’ll just make an analogy to my own research.

I talked about this at the recent AACR meeting, but seriously, one of the most common questions I get—I get an email like this roughly once a week—someone’s diagnosed with cancer and they want to know what they should eat. We as a medical community, do not have a very good answer to that question. That is not an easy question. I think there’s certainly basic lab approaches to doing those and my lab is doing them, but in the end, from a population science perspective, we need to think about how do we collect data differently.

Well, tons of data coming in, if we collect enough data on diet and we leverage the right data coming in now, well, maybe there’s a way where we could actually generate real hypotheses and real new ways of thinking about that problem that could be tested in the lab, but ultimately could help build us to answering those questions.

And there’s a million other questions out there like that, that apply to all the lifestyle questions that I’m sure are on your minds, like what does your family member call you up and ask you? If they’re non-science people, they call you up and ask me, “Oh, I read this article, is drinking this drink good for me or bad for me?”

The answer is not so simple. And I think taking the next step in personalized medicine, there’s a tremendous opportunity to do that with all the data that’s being collected. But I think it also means that we need to fight the temptation to fall into…because when you get into things like that, people have opinions and those opinions aren’t always based on purely scientific things, to say it diplomatically.

I know I like to use the analogy of, when I was younger, pasta was health food, and now pasta is the evilest thing in the world, because it’s high carb. People felt as strongly in the 1980s that low fat was good for you as they feel today that low sugar is good for you. And the bottom line is it’s not so simple as one or the other, and there’s lots of data out there to argue that it’s not so simple—but, now, we have the opportunity, with all the data coming in, maybe we can start to answer some of those harder questions, find the more nuanced answers to them.

But that means we’re going to have to have the right people. It’s what MIT, what we did before, we need to make sure that people who can do the data collection and the computer science are thinking in the same way.

How do you apply that to the right questions? And how do we answer those questions in a way that we generate hypotheses that the basic scientists can act on to understand better? And the engineers can act on to give people real advice and real solutions that can be translated to the world.

So, that’s just an example of the types of things that I think we are poised to do today that, honestly, it was science fiction when I took my job at the Koch 10 years ago, but it’s not science fiction anymore. It’s a stretch, but that doesn’t mean, if we don’t have stretch goals, we’re not going to have the new engineering problems of the future.

PG: I’m just asking you this question because you’re an informed observer or informed participant in all of this. So you’re not speaking for anyone other than yourself, how would you split up the scientific agenda of NCI and ARPA-H?

MVH: That’s a really hard question to address, because there’s lots of variables that go into that, even speaking for myself that I don’t have all the information to really know this. Obviously, NCI has a huge job and there’s lots of stuff that has to be done, from patient education to running clinical trials, to the R01 investigator pool.

People like to look at the R01—and no one talks about this anymore—but the R01 is the same as it’s been. The size of the R01 when I was a graduate student is exactly the same as it is today, and I can tell you that things are not cheaper today than they were when I was a graduate student.

So, I think all of those things are important, and I think NIH and NCI have to have a mission that has to be about both basic discovery as well as translation and education, and all of those other things. I think the interesting thing is, does ARPA-H take on some of that role that then allows the NCI to focus more on other roles, or do you duplicate those roles in ARPA-H as in a way to infuse new things into different places?

Maybe the right answer is you use ARPA-H to solve a certain problem, and then that frees up money in NCI to solve other problems. But no one asked me to be NCI director or head of ARPA-H, so the good news is I don’t have to make those decisions, but I think those are going to be the types of things that one has to think about, because I think there’s value in all of it.

And if you spend more dollars on one thing and you take dollars away from another thing, well, someone’s really happy, but someone’s really sad. And not just about the individual careers, but I think the missions of all the different things that NCI funds are important—education for patients is important, outcomes research is important, epidemiology research is important, clinical trials are important, basic discovery is important, all those things are important.

And having more money injected into the system, if it’s coming through a different mechanism, I think that’s the way one has to have a big picture. And, I would hope, speaking as myself, that whoever is running NCI and whoever is running ARPA-H are talking to each other and working together and not running parallel agendas.

PG: You’re talking about an immediate doubling and then expansion of methodologies, or maybe even, or expansion of imprint—overnight.

MVH: Yes. Look, there’s some lessons we can learn from this. In the Clinton era, they doubled the NCI budget and a lot of stuff happened quickly that ended up causing problems 10 years down the road. And so that’s great, and we got to expect some of that may happen again.

But nonetheless, it’s hard to go from zero to 60. There’s going to have to be some ramp up, but this is where good leadership is important, and that’s why I really think, I hope that there is discussion amongst all of the people who fund the different aspects of this to make sure that there is a strategic plan going forward, and things grow in the right way, such that all the new stuff does get built and used properly—and you don’t reach what unfortunately was a fiscal cliff that happened around the time I was, a little bit before when I was hired at MIT where suddenly all these independent, soft money places appeared and then disappeared, because they were not sustainable when the NCI budget contracted or didn’t grow. I guess it’s more, didn’t grow than contract.

MO: I’d like to draw on your experience working with industry and also, MIT’s experience with contracting with industry. The DARPA model as we understand it relies heavily on contracts with industry. What do you know about the advantages or disadvantages of this approach? Is that what ARPA-H might do? What’s going to happen with that?

MVH: As far as I know, none of this has been decided or announced, so if you notice something different, please tell me. But I think some degree of contracting with industry is not only likely, I think, it’s actually the right thing to do. And that is, industry is great at solving certain problems.

I’ve been involved in startup companies and I’ve been involved in advising mature companies, and even those groups are good at different things. What is industry good at? Industry is much better at making a bunch of molecules and screening through those, people do this in academia, but industry is much, much better at this because this is not something that is always amenable to graduate students and post-docs and fellows doing them.

It’s writing the same assay a thousand times to find the right drug and figure out your DMPK is not something that is always the right thing for academia to do, so, industry does that much better. I also think that there are certain things, especially when it’s, let’s have a professional staff that’s very good at one thing, solve one problem, really comes into play. My best hybrid experience in this has really been the NCI RAS Initiative, which you probably have covered and know something about.

I’ve been on the advisory panel for the working group for that, now for a while, and I’ve really seen something develop where it’s like, “Well, if we’re ever going to target RAS, there’s a certain number of things that we have to be able to solve, to think differently about that.” And I think they have been phenomenally successful in solving problems in structural biology, and things that have been catalytic for the basic science community.

And they’ve done some things that have helped with targeting of RAS, but they’ve then partnered with industry partners to really enact what are the specific molecules and ways that one will try to act on their things, because that now becomes a bigger operation and to build the expertise within NCI Frederick is not the most cost-effective [approach]. It’s much better to leverage the infrastructure that already exists for drug discovery out in either startup or mature pharma companies, because they clearly have an interest in doing this, and the goals are aligned.

I could see ARPA-H operating in a similar way—here’s big problems that need to be solved. Academia does these best—let’s look for that. Contracts to specific government-type labs, which are almost a hybrid between industry and academia, or if it’s all the way to a for-profit industry. Or you’re going to do other things well, and then, in the end actually, how do you build drugs and develop them, and bring them to patients? That’s going to be best done in industry. From the translational standpoint, you’re going to have biotech and pharma partners that help do that.

The ability of NCI to contract with industry is obviously much more complicated in the way that it’s structured, whereas ARPA-H could be structured in a way that it does that better, because, certainly, DARPA contracts with industry in a way that’s very different than other parts of government.

PG: Oh, it’s fascinating. It’s very different definitions of industry, because defense has its contractors, health has different contractors, I’m just wondering to what extent this is going to go to institutions such as yours, to do maybe more of the turn-the-crank engineering research?

MVH: I’m certainly open to those types of things. The Koch Institute as one of the basic centers is in a unique position that we need to decide for ourselves, how much do we want to be involved in turn-the-crank type problems like that.

And I think it comes down to, you look in the end, we are MIT, and we have an academic mission, and so, there has to be academic people in ways that that academic mission aligns with the turning the crank. Otherwise, I’ll do what others at MIT do: I’ll start a company and that’ll turn the crank.

I think now we get into the nitty gritty detail of what it is. I think there are, to the extent that there’s a new technology being developed, a hard engineering problem being solved that can involve some turning the crank, like we’ve done some of this within the Koch Institute around some of cancer vaccine thinking, maybe some of the single-cell technologies about how one analyzes single-cell technology, some of those things now are getting easier and easier, but at the time when it was hard to do, there was a lot of that going on and we built infrastructure and stuff to be able to do those things within our center.

And I could certainly see projects like that happening if they were the right match through an ARPA-H like thing. But if it’s truly a turning-the-crank thing, now you’re probably much better off outside of an academic institution, just because, we do have to live up to our academic mission.

PG: But these are fascinating questions that I think everybody is now asking themselves and struggling with. And it’s wonderful to watch this, and to cover it. Is there anything we’ve missed?

MVH: We’re at a tremendous time in science and I’m really excited to see what can be done next. I feel very privileged to be part of an institution that I think has such amazing, talented people viewing these problems in different ways, and as you bring up, it’s going to be interesting to see how all of these hard problems are solved.

I’m excited to have my team with me to help try to solve some of them, because hard problems require great people that are smart and committed. I’m really lucky to be at a place where I feel like we have that in spades. That’ll be a lot of fun to see what we can do, and hopefully we can help contribute to thoughtful solutions to some of these, and make some of the right decisions that in the end, we’ll be able to look back on this and say, “Wow, that was a really amazing thing that happened, and look at all the great stuff that happened because of it.”

PG: Thank you so much.

Matthew Bin Han Ong
Associate Editor
Paul Goldberg
Editor & Publisher
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NCI has selected Exact Sciences Corp.’s testing laboratory in Phoenix, AZ to participate in the ComboMATCH clinical trials, an NCI-funded precision medicine initiative. As a ComboMATCH-designated lab, Exact Sciences will use its new OncoExTra test to analyze tumor tissue and paired normal blood samples from patient participants and uncover the specific abnormalities in a patient’s tumor that may be most effective to treat. 
Matthew Bin Han Ong
Associate Editor
Paul Goldberg
Editor & Publisher