Gene therapy is an experimental technique that uses a person’s genes to treat or prevent a disease. 

While it’s still in its formative stages, in the future, gene therapies might take the place of invasive surgeries or drugs. James Dahlman works at the intersection of nanotechnology and genetics, and discusses his work with experimentation, research design, and gene therapy applications.

Dahlman is an Assistant Professor in School of Biomedical Engineering at Georgia Tech and Emory University. Dahlman leads the ​The Dahlman Lab for Precision Therapies at Georgia Tech.

Album art, illustration

Steve W. McLaughlin

College of Engineering
Dean, College of Engineering
Southern Company Chair
Professor, Electrical and Computer Engineering
Steve McLaughlin, headshot

James Dahlman

School of Chemical & Biomolecular Engineering
Assistant Professor
James Dahlman, headshot


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Steve McLaughlin: You’re listening to “The Uncommon Engineer.” I’m your host, Steve McLaughlin, dean of the college.
Announcer: We’re just absolutely pleased as punch to have you with us. Please say a few words.

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Steve McLaughlin: Hi everyone, and welcome to “The Uncommon Engineer” podcast. I’m Steve McLaughlin, Dean of the Georgia Tech College of Engineering. Our podcast is all about how Georgia Tech Engineers make a difference in our world and in our daily lives. In this episode, we’ll be talking about gene therapy. It’s an experimental technique that uses a person’s genes to treat or prevent a disease. While it’s still in its formative stages, in the future gene therapies might take the place of invasive surgeries or drugs.

Our guest today is Dr. James Dahlman. He’s a professor in the School of Biomedical Engineering at Georgia Tech and Emory. James’ work is at the intersection of nanotechnology and genetics, specifically gene therapy. Welcome to the program, James.

James Dahlman: Thank you very much for having me. Pleasure to be here.

Steve McLaughlin: So, you know, we’re hearing lots in the news about so called immunotherapies where novel techniques of using your own immune system to attack disease, CAR-T, and maybe even CRISPR. Can you say a little bit about that and why this is such an exciting area?

James Dahlman: Yes. So I can say as somebody who works in gene therapies, it’s a very exciting time to be in this field right now. The potential for gene therapies is tremendous because they treat disease by going after the root source which is the genetics itself. I think that gene therapies can be sub-divided in to three buckets: In one bucket the goal is to produce a lot of the gene; in this case the disease would be caused by not making enough. The second bucket is designed to turn off genes; in this case the disease would be caused by producing too much. And then the third bucket, you’re actually going in and editing the genome itself; this is the newest form of genetic therapy but it still has some promise. 

There are many other examples. Some of the work that we perform in my laboratory is designed, again, to solve a very simple problem. If you want a genetic therapy to work, you need to get it to the right cell type. If you have cystic fibrosis and you want to change gene expression in the lung in order to treat the disease, you want that drug to go to the lung. You don’t want it to go everywhere else. Once again, the simple problem of getting the drug to the right place at its core is an engineering problem.

Steve McLaughlin: One of the things you talked about was turning off or silencing a gene. Before you talk about the specific therapies, can you give us a little bit of primer on what that really means?

James Dahlman: The easiest way to explain this is to go back to sort of biology 101, and that is DNA makes RNA which makes protein. So the DNA is like the blueprints—it’s what makes you, you. And the DNA’s job, or one of its jobs, is to produce protein which really does the work. So DNA will encode for a certain protein. If the DNA gets a mutation in it, it will encode for the wrong protein and that protein can cause disease. In the case of shutting off a gene, what we’re really doing is shutting off the protein production. And we can do this at two different levels: The first level is shutting off the RNA production, and the second level is by changing the DNA itself. The most advanced clinical trial so far work at the RNA level; they aren’t quite there yet with the DNA stuff.

Steve McLaughlin: Can you say a little bit about your own work and the kinds of things that are going on in your lab regarding silencing or turning off genes and what’s the application?

James Dahlman: It’s a really exciting time to be a scientist in gene therapy right now. My lab focuses on one simple problem: How do we get the drug to go to the right place? This problem lies at the interface of chemistry, of what we call nanotechnology, and biology because we are packaging drugs inside nanoparticles, which are just very small particles, in order to get them to go to the right tissue, and to protect them from being degraded and attacked by your body. So my lab focuses on developing nanoparticles that target genetic drugs to the right tissue. A nanoparticle is simply a small particle. I’m about 6 feet tall, and I am 1.8 billion nanometers tall. The systems that we create are about 50 nanometers in diameter. They’re little spheres. We package the genetic drugs, whether it’s DNA, or RNA, inside these little spheres, and the nanoparticles act as, almost, mail carriers that take them to the right cell type—the disease cell type—and help them avoid healthy tissues. This reduces side effects and it improves drug efficacy.

Steve McLaughlin: So I’m kind of imagining these nanoparticles, you know, with the therapies or drugs inside of them, and somehow they get in to your body, and they’re going throughout the body. How do they know where the right place to go is, and then once they find the right place to go, how do they then deliver the therapies to the tissue or the cells?

James Dahlman: It’s another great question and, again, it lies right at the interface of chemistry and biology and engineering. When you take an aspirin, the aspirin doesn’t have flippers or heat seeking technology that goes right to your headache; it kind of goes everywhere. When you take a genetic drug, if you didn’t target it in any way it would do the same thing. So the way I would think about this is you can divide the process in to two steps: The first step is getting to the right tissue. So just imagine that you’re a nanoparticle, you know, you’re minding your own business but suddenly you get injected into this blood stream. The blood stream is chock full of proteins and lipids and all sorts of stuff here. Your blood isn’t just water; it’s like a soup that’s full of all these biomolecules. So you may interact with some of the biomolecules, but you’re passing by the heart, you’re passing by the lung, you’re passing by the pancreas, the liver—all these organs. And every organ is going to look a little different to you. If we designed the nanoparticle the right way—let’s say for cystic fibrosis where you want to target the lung—we designed it in a way that the lung looks better to you than the liver, or the lung looks better to you than the kidney. And so you end up in the lung more so. That’s the first step: getting to the first place. 

Once you get there, there’s a second, very exciting and interesting step, which is getting into the cell itself. So although the biology and the biological processes that govern this are still somewhat unclear, we do know a few things which is that cells gobble things up actively. Just like us, cells need nutrients, and they get nutrients from their environment, from their neighborhood, if you will, and from the bloodstream. So cells gobble stuff up very actively. Ideally, your nanoparticle is designed in such a way with such a chemistry that makes it tasty to cells so they end up gobbling it up. This allows the drug to get into the cell where it can do its job. So again, I would sort of divide it in to two parts: First, getting to the right tissue and then, second, getting into the cell once it’s at the tissue.

Steve McLaughlin: So the delivery of the nanoparticles to the cells, that really sounds like an engineering problem. Can you say more about the drug delivery, because it’s so specifically targeted, what your students are doing with that?

James Dahlman: My students are developing what we call “DNA barcoding technologies.” And the easy way to think about this is we’ve developed technologies that allow us to perform a few thousand experiments all at once. The technology behind it is pretty fun. Think about it this way: We can make a giant library of nanoparticles. nanoparticle 1 might be small. nanoparticle 2 might be large. Nanoparticle 3 might have a positive charge on it. Nanoparticle 4 might have a negative charge on it. We can make thousands of different nanoparticles with different chemical structures. We don’t know which ones are going to work. So how can we test thousands? Well, the way we do it is we use DNA as a molecular tag. So nanoparticle 1 gets DNA barcode 1. All that means is nanoparticle 1 carries—instead of carrying a drug to turn off a gene, it just carries a little tag that’s a DNA sequence that we know. Nanoparticle 2 carries a different DNA tag: just a different sequence, again, that we know. And you can do this you know many times in a day. My students have made up to 250 Nanoparticles each with its own molecular tag within a day.

You can then mix all the particles together and administer them in a single experiment. You then isolate the DNA, and you can use deep sequencing—again, this technique that you spit in a tube and send it to or to 23andMe. We use that same machine that—the DNA sequencing machine—to analyze how all of those DNA sequences behaved at once. So if you do 250 different nanoparticles and 250 sequences, and you run your experiment and you take out the cells, and it turns out that barcode number 17 shows up in those cells more so than the other barcodes, that means that nanoparticle number 17 might do a good job. So this allows us to perform hundreds and thousands of experiments simultaneously. And actually using this process, we’ve been able to identify nanoparticles that do target new tissues and new cell types. So it’s pretty efficient. I think we can accelerate the development of drugs this way.

Steve McLaughlin: So let me get this right. This is incredible. So I think the way that people have done experiments for hundreds of years is they try one thing at a time; they try one therapy at a time and you then test that therapy. You’re saying, now you can do that same thing: Instead of testing one therapy at a time, you can test hundreds or thousands of therapies at a time. And I guess your goal is, in this case, it’s about the delivery of the nanoparticle into the cell, and all then you need to do, is read out and then examine the cell and see which of the nanoparticles got through. Do I have that right?

James Dahlman: Yes, that is exactly right. And I can tell you that it is a very exciting time to be in the lab right now because I thought up this technology a few years ago. It took a while to engineer it so that it was robust, but it is now working. And in a typical experiment now, one of my students will test about 250 nanoparticles, and we’ll analyze the delivery to, let’s say, 30 cell types. So 250 times 30 is what—whatever that is—7500 experiments performed at once.

The data sets that we’re generating now are so big and so much bigger than anything I’ve reported in my career, that we actually had to develop a bioinformatics pipeline to analyze the data sets because there was no pipeline to my field to analyze it. It’s pretty fun because what you can find is that let’s say nanoparticle 17 does well in lung cells, but really doesn’t do well in heart cells. Well, that’s great because you can have specific delivery to the lung, and so we can measure delivery to our target tissues as well as all of our, what we call “side effect tissues” or “off-target tissues,” in a single experiment. So we can do years of work basically in three days. And I think this is a real step-function change in the ability to do these experiments.

We are interested in commercializing this in order to get products to patients more quickly. The ultimate goal is to accelerate the development of genetic therapies, and I think this platform really does stand a chance to do that. We know that we’ve received a lot of interest from the field so far from companies that are already in the clinic, in fact, and they view this technology as very promising, and a way to accelerate how quickly genetic therapies actually make it into clinical trials and actually make it into patients. So we’re really excited about all of these opportunities.

Steve McLaughlin: So the idea of barcoding, you know, nanoparticles to get to tissues for addressing diseases is absolutely fascinating. How close is this to actually being used, say, in humans or how applicable is it to humans? And looking in your crystal ball, when do you see those kinds of things having an effect on patients?

James Dahlman: So I do think our work has implications for human disease. I’ll give you an example that’s pretty exciting right now: We have initiated a collaboration at the National Cancer Institute outside D.C., and this collaboration is with a surgeon. This surgeon does this very cool thing: He operates on patients that have liver cancer. He would do it anyway; it’s part of the normal procedure. And after he does the surgery to remove the tumor, he actually made a machine that keeps the tumors alive for about a week. And, as you can imagine, these things are very rare samples and they needed to be treated with respect. So one of the advantages of our system is we can essentially perform a few hundred experiments using one patient tumor instead of performing one experiment with a patient tumor. And although we haven’t started these experiments with him yet, I am hopeful that we’ll be able to start experiments like this where we’re screening directly in patient samples maybe within the next two years. That would be great. I think the key point here is that when you’re dealing with patient samples, and so I think it actually is an advantage of our system that we can test hundreds of things per sample instead of one thing per sample.

Steve McLaughlin: So you talked about the three different approaches to gene therapy, one of which was gene editing. I’ve heard about this technology called CRISPR—about what CRISPR is and the kind of work that’s going on in your lab?

James Dahlman: CRISPR is, arguably, the most exciting biotechnology discovery certainly of the 21st century, so far. Put succinctly, CRISPR allows us to edit the genome very easily. Even five years ago, if you wanted to take DNA and change the DNA sequence, you could do it using things called zinc fingers and talons, but it was going to take a lot of money, and it was going to take a lot of time. CRISPR does the same thing as zinc fingers and talons—it edits DNA, it changes DNA sequences, but it’s really, really easy to use. And so now, for the very first time, scientists can do something as simple as edit 10 different genes, 100 different genes, and see which gene causes a tumor to grow. You can accelerate these scientific studies. Therapeutically, CRISPR can be used to edit cells so that they target tumors more effectively. And in the future, CRISPR may be used to edit the genome inside human patients as well in order to turn off a gene that’s causing disease.

So from our lab’s perspective, we do a lot of work on CRISPR. CRISPR’s not going to work unless you get it into the right cell, and so from our perspective, we’re just trying to get it into that right cell. I will say, from a scientific perspective, CRISPR is one of the most, if not the most, exciting technological development I have ever been exposed to. It is changing how things are done.

Steve McLaughlin: I’d like to change directions just a little bit and hear you talk about your own path, maybe even from junior high or before, how you made your way to Georgia Tech and how you made your way to wanting to study this area and become a biomedical engineer.

James Dahlman: When I went to MIT and Harvard Medical School for my graduate work, I was in what’s called the HSC program. I started drifting more towards biology and medicine. So at MIT, I did my Ph.D. work in materials science, but you’re also forced to take two years of medical school at Harvard with the medical school students. And so I remember one very interesting day as a first-year graduate student walking out of a pathology exam at the medical school and then walking right in to a quantum mechanics exam after taking the bus—so it really does stretch your brain a little bit. As I got in to the medical school classes, it became clear that biology was just so elegant and it really is a beautiful science. It also became clear that engineering was going to play a huge role in the future of biology, and that’s definitely been the case. I came to this point by just following my natural love for science. I’ve never done science that’s boring to me, and I only do science I find interesting, and this has been a huge advantage.

Steve McLaughlin: Professor Dahlman, I have one last question for you: What makes you an Uncommon Engineer?

James Dahlman: I think the thing that is most uncommon about me as an engineer is the fact that I’m willing to, and excited by, the idea of merging completely different fields together. My lab right now is at the interface of genomics, chemical engineering, and nanotechnology. And as far as I know, we’re the only lab that’s sitting here. I think it’s a lot of fun to really be out there on the cutting edge trying to marry new fields together. I think that’s what really sets us apart.

Steve McLaughlin: Fantastic! Thanks very much, James. We really, really appreciate you being here.

James Dahlman: Thank you very much for having me. It was a real pleasure.

Steve McLaughlin: Be sure to tune in next month when we talk to Professor Brendan Saltaformaggio about cybersecurity.

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Audio & Captions

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[interposed voices of Steve McLaughlin] ...sounds incredibly sounds have abilities that span...I'm really geeking out here.
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Steve McLaughlin: I'm really curious about why an engineer? We think of these therapies as being the domain of doctors and hospitals and patients. I'm an electrical engineer. You know, I work on cell phones and computer chips. And we think of engineers as bridge builders and things like that. Can you say a little bit about why engineering is so important to some of these new and novel therapies

James Dahlman: A lot of the most important problems, or hurdles I should say, that are facing gene therapies are actually engineering hurdles. To give one easy-to-understand example, we have a professor at Georgia Tech named Krish Roy who's developing what we call CAR-T therapies. These are therapies that use T cells to treat disease. So you take your own T cells out of your bloodstream, you change their genetics inside a dish, and you put him back in and train them to go after a tumor or something like this. They've actually been pretty promising, but there's one simple problem with them: It's hard to make a lot of them. And so you can run these small clinical trials right now, but if you want to scale up and treat thousands of patients, people, even the biggest companies in the world don't know how to make enough T cell therapies to treat thousands of people. That is, at its most core, an engineering problem, and that's what Professor Roy is doing.

Steve McLaughlin: I know that you have students in your lab, both undergraduate and graduate students. Can you say a little bit more about what your students do and the kind of interests and impact that they're having?

James Dahlman: Gladly. I will talk about my students all day. The first thing I will say is that we are very lucky here at Georgia Tech to have really excellent students at the undergraduate level and the graduate level. A special shout out to Cory Sago, Collina, and Melissa. Our students are excellent, and they do perform a lot of different types of experiments. So if you're a student in my lab, you learn a lot of different techniques. This includes designing the nanoparticles, which is a chemistry-based technique. You know, you may want to make a nanoparticle that is 50 nanometers, and then you want to make a nanoparticle that's 100 nanometers—that involves different chemistry.

Once you make the nanoparticle, you need to package the drug inside of it. This involves what we call “microfluidics” which is another engineering technique. You then want to administer the drugs to cells to see if they work. And that involves some biomedical engineering as well. And then on the back end, we actually do this analysis called “deep sequencing.” It's the same thing that you do when you send your, you know, when you spit in a tube and send it to or 23andMe. And that involves a bunch of molecular biology. And so our biomedical engineers here at Georgia Tech learn chemistry, chemical engineering, biology, biomedical engineering, and molecular biology all at once in the lab.

Steve McLaughlin: So you now have developed a technology that allows you to effectively test many thousands of potential therapies all at one time. So not only does that seem to be an incredible breakthrough in terms of drug delivery, but it also sounds like it has huge implications for all kinds of therapies, and maybe even starting a new business or or a new company that tries to commercialize it. Can you say a little bit about—you know, it spans so many dimensions, can you say a little bit more about the things that have you most excited?

James Dahlman: We're very excited right now. The way I kind of divide the work up is in one bucket we have this simple question which is let's find drug delivery vehicles, let’s find nanoparticles for non-liver tissues—that's the real clinical need right now. And we do this pretty simply; we test thousands of things and we try to learn from the experiments. You know, we'll do Experiment 1 with particles 1 through 250, and then we'll use bioinformatics to learn from those data, then use those data to inform the design of particles 251 to 500. And we just kind of iteratively improve the delivery and try to find things that target new tissues.

The second bucket is also interesting; it’s more scientific. The second bucket is, right now, we don't really understand why nanoparticles work or why they don't. And we don't understand the factors that affect whether a particle works or not. So we can perform really interesting biological studies to understand which genes actually alter how well the nanoparticle works itself.

Steve McLaughlin: So you have a nanoparticle that has inside of it, you know, a drug that you want to deliver to a cell, and now you've attached kind of a barcode to it. So first of all, what a fantastic engineering problem. But the engineer in me might say, “Well, what about if by putting that barcode on the nanoparticle, does that change or affect how effective that that nanoparticle can be?” What's the interaction between the barcode? Could that somehow inhibit or prevent the therapy from being there?

James Dahlman: I think in some cases the answer will be “Yes.” So if you asked, “Does this DNA barcode affect how well a nanoparticle will deliver aspirin?” The answer is probably “Yes” because aspirin is a very small molecule that is not charged. However, if you said, “Does this barcode affect the delivery of an RNA therapy?” The answer is almost definitely “No” because the barcode in the RNA look exactly the same. And so it really depends on the type of drug that you're trying to deliver. It will be interesting to try and design barcoding systems for small molecules like aspirin. I do think it is possible but, you know, it could take another two years of work before we get anything that's robust.

Steve McLaughlin: So it sounds like your experiments generate a huge amount of data, and you need to have the ability—you know, if you're going to run, I assume in the future you're going to have the ability to run not just hundreds or thousands, but even many more, that will result in incredibly rapid advances and development of new drugs and therapies. But you're going to be generating tons and tons of data. So it sounds like you need to know a little bit of computer science and a little bit of mathematics and your students are kind of learn all trades. So is that kind of where all this is headed?

James Dahlman: So that speaks to the interdisciplinary aspect of my team. So my team has—my students have backgrounds in biology, biomedical engineering, chemical engineering, chemistry. And we also have two bioinformatics students from the Georgia Tech master’s bioinformatics program here whose sole job is to develop the mathematical framework and the bioinformatics pipeline on the back end for that exact reason. So, one thing I'll say is, if you're a student out here listening and you're thinking, “Oh man, I don't know if I have what it takes to become a biomedical engineer. You know, I studied math as an undergraduate.” You can become a biomedical engineer. It's a very collaborative discipline and it's a discipline that needs people with different skill sets. And so some of the best biomedical engineers in my lab have no formal training in biomedical engineering.

I grew up in Dayton, Ohio, which is in southern Ohio near Kentucky. I was not born, but raised, in Ohio, and I stayed in Ohio all the way through my undergraduate where I got that at Wright State University, which is the local university. I studied biomedical engineering, but at that time I was actually doing materials science research at the Wright-Patterson Air Force Base, so I was basically an Air Force contractor for four years as an undergraduate. And this was really traditional material science; we were working on what are called “bulk metallic glasses” with the express purpose of making a corrosion-resistant material that was lightweight enough to be shot up into space. It's pretty far afield of what we're doing now.

Well, after I graduated from with my Ph.D.—I’d done my Ph.D. in a lab that focuses primarily on chemical engineering, so I had chemical engineering skill set. What interested me at that time wasn't chemical engineering. What interested me at that time was genomics. And so I jumped ship and joined a genomics lab that was called the Broad Institute, which is a dual organization set up between Harvard and MIT. And you can think of it as the human genome building, basically. it's where some of the world's best genomics scientists reside. I loved that work at the Broad, and I learned a lot about molecular biology and all these genomic skill sets. And I just had this gut feeling that I could I could use these genomic skill sets somehow to improve chemical engineering. And lo and behold, that's actually exactly what happened. All of the barcoding stuff that we've been talking about today that my lab does, all of that was learned at the Broad Institute.

My lab lives at the interface of chemical engineering and molecular biology and genomics. And that's because I think, luckily, I followed my gut and just did what I liked. And that happened to be chemical engineering in genomics. I've been very lucky to have excellent mentors. I did my Ph.D. with a guy named Robert Langer who's just a storied biological engineer, and I did my postdoc with Feng Zhang who is a young, rising superstar in the field of gene editing. I am not Robert Langer; I'm not Feng Zhang. However, I do my best to pass on their mentoring styles to my students because I really sincerely appreciate what they did for me.

One of the best parts about being in Georgia Tech is the quality of our students. I love mentoring these students. It's probably the best part of my day is interacting with my students in the lab—it is the best part of my day. The other parts of my day are spent grant writing, so I guess, you know, it definitely is the best part of my day.

Steve McLaughlin: I remember from high school biology, you know, the double helix of DNA, and you're saying CRISPR has the ability to go in, kind of identify parts of that DNA strand and literally edit it out to change it.

James Dahlman: So every cell in your body has three billion base pairs in it. Let's say the gene that's causing trouble is located at base pair 1003. How on earth are you going to find base pair 1003 from a string that’s three billion base pairs long? Well, CRISPR does that. You can go in, find base pair 1003, and perturb base pair 1003 very specifically. You may ask how on earth did this happen, and I will tell you that CRISPR evolved as a bacterial defense mechanism. So think about it this way: Bacteria and viruses have been battling it out since life began and there are viruses that infects bacteria; they're called bacteriophages—just another name for a virus that gobbles up bacteria. The virus attacks the bacteria, and the way it works is it injects its DNA into the bacteria, and this makes more virus. What CRISPR is a bacterial defense system to remember what viral DNA is—so to remember that it got attacked by this virus, and then to delete the viral DNA when it gets attacked again. All we did was we took that DNA recognition and DNA deleting system, and we repurposed it for human cells, and this is what CRISPR is. That's basically a bacterial defense system that we've hijacked and used to edit DNA now.

We use CRISPR in two ways in my lab. The first is we develop CRISPR-based drugs to go after cystic fibrosis or to go after a hemophilia or, you know, whatever. There are a lot of genetic diseases that would benefit from CRISPR therapies. And the second way that we use CRISPR is we use it to study biology. You know, it is now far easier than it's ever been to knock out this gene or knock out that gene and see what happens. So if I want to figure out if gene A or gene B is affecting how well my nanoparticle works, because I want to understand how my nanoparticle works, I can just CRISPR gene A and I can CRISPR gene B, and I can see if the nanoparticle works. So CRISPR, in addition to being therapeutic, potentially, is already accelerating the rate that we can make scientific discoveries in the biological space.

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