In this episode of The Future Of, Gabby Everett, Director of Business Operations and Strategy at BioLabs Pegasus Park, and Claire Aldridge, Chief Strategy Officer at Form Bio, join host Jeff Dance to discuss the future of biotech. They unveil the advancements, challenges, and ethical considerations in the biotech industry. Discover the potential of the genomics and omics revolution, the impact of COVID-19 on biotech, and the transformative potential of biotechnology in shaping the future of healthcare.

Claire Aldridge – 00:00:01: We’ve been waiting for the genomics, you know, the value of the genomics revolution for 30 years, right, since I started graduate school in 1991. And we’re finally now actually getting the value out of the genomics revolution, and now it’s more of an omics revolution.

Jeff Dance – 00:00:18: Welcome to the Future Of, a podcast by Fresh Consulting, where we discuss and learn about the future of different industries, markets, and technology verticals. Together, we’ll chat with leaders and experts in the field and discuss how we can shape the future human experience. I’m your host, Jeff Dance. In this episode of The Future Of, we’re focused on the future of biotech. We’re joined by Gabby Everett, the Director of Business Operations and Strategy at BioLabs Pegasus Park in North Texas. And Claire Aldridge, Chief Strategy Officer at Form Bio. To explore the future together. We’re excited to have you. Gabby is an experienced scientist, innovator, and leader in the biotech industry with a passion for educating and empowering others. She also has a PhD in Biochemistry from Texas A&M. Claire is an accomplished biotech strategist and leader, passionate about moving science into the marketplace where it can truly change people’s lives. She also has a PhD in immunology and genetics from Duke. I’d love to hear a little bit more about your experience and kind of your journey in the biotech industry, but first off, thank you for being with us on the show.

Gabby Everett – 00:01:32: Thank you for having us.

Claire Aldridge – 00:01:34: Thanks for having us.

Jeff Dance – 00:01:35: Awesome. And these two are friends, so it’s awesome to bring you together and to kind of hear your different perspectives and insights. So thank you again. Claire, if we can start with you, tell us more about your journey in the biotech industry.

Claire Aldridge – 00:01:47: Yeah, so I trained as a scientist, got a PhD in immunology and genetics, but knew that I was not cut out to be a bench scientist. And so, you know, really kind of wondered what do you do with a PhD when you’re not going to kind of follow that traditional path? And this was about 30 years ago, where there wasn’t as much focus on biotech or, you know, different things like that. But I was fortunate to get involved in the commercialization aspect of science. How do we take the discovery that scientists make and turn them into products that can actually benefit people? So that’s been the space I’ve played in for the last over 25 years, 27 years now. How do we do that? And I like to do it in a variety of different ways. So I’ve been an investor and gotten to do it at, you know, kind of that very early stage of identifying those ideas and funding them and helping them get off the ground. I’ve done it in commercialization offices at academic medical centers, but I’ve also done it in startups. And that’s where I am now, where you’re actually trying to take those innovations and apply them to real world use-cases. So to me, that’s what’s exciting about science is the discovery piece is cool to learn something new about something. But I love that practical application of it. How do we use it to solve something that’s actually a problem in the marketplace, particularly in health care, where you can address disease progression or outcomes?

Jeff Dance – 00:03:05: Amazing. So you’ve been there some like almost from the very beginning. I mean, biotech is relatively new. That’s awesome. 

Claire Aldridge – 00:03:12: Absolutely.

Gabby Everett – 00:03:12: Yeah.

Claire Aldridge – 00:03:13: So it’s, you know, biotech as a whole industry. I think it kind of started a little bit in the 70s when we first started to figure out how to make insulin and things like that. But as far as like the explosion, that’s really been in the last 10 to 15 years of finally having enough knowledge about the molecular underpinnings of disease to be able to manipulate that and not just treat symptoms, which is kind of what we’ve done up to then.

Jeff Dance – 00:03:38: Amazing. Gabby, tell us more about your journey in biotech.

Gabby Everett – 00:03:41: Sure. So my PhD focus was on bacteriophage. So viruses that infect and kill bacteria. And in fact, we worked on the lysis mechanisms and the proteins that actually do the killing, which is awesome for me because I had a very personal vendetta against bacteria at the time. So it was really rewarding for me to be able to basically turn on a protein and take out an entire culture of bacteria in under two minutes. I could hear their little microscopic screams coming from the flask. So that was really rewarding. Got to do it.

Jeff Dance – 00:04:16: Your own war zone, micro war zone.

Gabby Everett – 00:04:20: I waged war against bacteria and they feared me. However, after grad school, I shifted just a little bit and joined a probiotics company. So there I actually had to keep the little buggers alive and make them happy. But it was interesting because there’s always been this constant arms race with bacteria against each other. A lot of them populate the same regions and the same dirt and the same niches. So there’s a lot of mechanisms that they use against each other. So some of the probiotics that we used actually had anti-salmonella, anti-E.Coli properties. So I was kind of still able to wage my war a little bit. But my goal with that company, it was product development, cradle to post commercialization support. Effectively, it was a startup. So I got to wear many hats. I had to do the formulations and test formulations and write patents. And we were very good at it. We got 10 patents granted while I was there. But honestly, my real passion is in scientific communication and empowerment. And that’s where BioLabs comes in. So we’re a biotech startup incubator in North Texas. And we have 24 companies with us right now that are doing everything from cancer therapeutics all the way up to wearable medical devices. And my job is to know what they do, know how they’re differentiated, know what their gaps are. Like maybe they need a contract manufacturing organization for a clinical trial batch. Maybe they need an FDA regulatory consultant. So really help them make those connections, fill in the gaps. And then finally, my role here is really to help build a vibrant, rocking biotech ecosystem in North Texas. And that’s how Claire and I met in those activities.

Jeff Dance – 00:06:07: Amazing.

Claire Aldridge – 00:06:07: I’ve been trying to build a vibrant, rocking biotech ecosystem in North Texas for a very long time. And really the last five years, we’ve gotten so much traction and enthusiasm, just really starting to get a lot of companies coming out of our universities and solving real problems and getting drugs approved that are changing lives.

Jeff Dance – 00:06:26: Sounds like you guys are in the hub of innovation and on the forefront of really leading the future. So excited to have you with us. Tell us, you guys are awesome, cool scientists that are working on the future. Tell us a little bit more about yourselves personally. What do you guys do for fun?

Gabby Everett – 00:06:40: This time of year, honestly, it’s football season for us. So that includes grilling, hanging out with the family, watching our own sporting our favorite teams. And other than that, yeah, just hanging out.

Claire Aldridge – 00:06:53: I went to Duke, so I’m less interested in the football portion of the year, and I get excited in the basketball portion of the year. But I think one of the things we’ve been able to build in North Texas is a real community around this space. One of the things I like to say is, biotech is a full-contact sport. So a lot of what we do too is how do we make those connections? How do we have those collisions so that we can keep moving these things forward? So one of the things that’s been really great is that, as we’ve been building this community, we have actually developed real friendships with each other. I spend a lot of time with people I know professionally, thinking about how do we get more investment dollars? How do we figure out how to manufacture these drugs? How do we do that in a fun way? How do we keep people engaged and get people excited about science? So lots of things for fun, like read, exercise. I have a 16-year-old daughter. That’s a lot of fun, surprisingly. I did not expect it to be fun. But I do think that what we’re trying to build in North Texas, there are hubs around biotech, Boston, San Francisco, San Diego, the Raleigh-Durham area. We’re trying to build something new here, so it is really important that it’s a cohesive, collaborative, and still fun. So where they are at my labs, one of the cool things that’s part of that entire campus is a brewery, called Community Brewery. I like to joke that beer was the first biotech because it’s a product of yeast. A lot of the early drugs made in biotech were made in yeast. So just having that environment where you run into the people you need to run into, while you’re socializing as well as doing your work, is what has to happen in order to accelerate what we’re trying to build.

Jeff Dance – 00:08:40: Nice. A lot of type 2 fun. Well, if I was a biotech startup, I would be seeking you guys as board members or your investment dollars. I would love to work with you already. You guys seem really fun. I did note that, Clara, you are Forbes’ 10 women leading the synthetic biology revolution. So it’s cool to see that recognition.

Claire Aldridge – 00:08:58: It’s not the revolution I thought I would be recognized for.

Jeff Dance – 00:09:01: Cool recognition. And Gabby noted that you are future 50 in the Dallas, Fort Worth area for leading disruptors for innovation impacts. It’s nice to see that recognition. Now that we have some of the formalities out of the way, let’s dive into the future. I want to start with a little bit more of the present. Some of the things that have happened recently, and then transition to the future along with some of the opportunities and challenges that will be ahead. Tell us a little bit more about the main sub-sectors for biotech. I know, Claire, you mentioned you’ve been there since the beginning. Really, a lot of the growth has happened, sounds like in the last 30 years, roughly now it’s being what, hundreds of billions of dollars industry. What are the main sub-sectors in biotech and what are some of the ones that are bigger and growing faster right now?

Claire Aldridge – 00:09:48: I think COVID taught us a lot about where we needed to put our dollars in order to make sure that we are generating things that are really useful across a broad population. And I think that when you look at where biotech is going, I mentioned earlier, we have been working on what I like to call the genomics revolution or even the omics revolution for a long time. So understanding what your DNA is telling you, what your RNA is telling you, and what your protein is telling you and how those three work together to be health or disease. And so now we’ve got enough tools, whether it’s CAR T-cell therapy or gene therapy or monoclonal antibodies, we now have things that are disease modifying that actually change the course of the disease. Don’t just treat the symptoms. So the areas that I see a lot of growth in are how do we start to improve kind of the ability, get additional insights into using those tools to do more broad therapeutic development. Right now, those tools are often used in cancer or autoimmune disease or progressive neurodegenerative disease, diseases that are really, really have a horrible impact, horrible outcomes. But how do we start to use them in heart disease and diabetes where we’ve got some things that are okay, but we’re not doing disease modifying yet? And then the other big area that I’m particularly excited about and why I joined Form, I actually tried to retire. I’m very bad at being retired. But I joined Form because what we were seeing a lot of is computational tools being used in biotech. Again, with all of this omics data, we have just gigabytes, terabytes, I don’t even know the size of the bytes of data that we have that we don’t know how to analyze. We don’t know how to get the insights out of it. And so, you know, being able to work with sophisticated software developers to say, how would you analyze this data, get insights out of this data? And I feel like it’s a little bit more of a wholesome use case than like scraping Facebook to figure out a new way to do a targeted ad. So let’s use these tools that we’ve developed and apply them to some of these huge data lakes that we’ve got and understand more specifically kind of, I think of it as a signature of disease and how we could impact that.

Gabby Everett – 00:12:11: And to piggyback on that with all of this omics data that we have right now and the new tools that we have in AI and machine learning are allowing the personalized medicine revolution, you know, and precision medicine. You know, nowadays your doctor can take your tumor and send it off to be analyzed and compared, you know, not just analyze the tumor for your own specific case, but take that case, compare it to the literature, compare it to clinical trials, and be able to, you know, use that information to actually predict better outcomes and predict exactly what therapy is going to use or it’s going to work and what combination therapy is going to work. So adding all of that together, the science, how we do the science, how we analyze the data, how we use that data now to predict better outcomes is like revolutionizing medicine.

Claire Aldridge – 00:13:10: You have maybe even had or somebody you know gone to the doctor and needed a blood pressure medicine or an antidepressant or something for attention deficit disorder. And they will actually do genetic testing now and say, this is the med that is most likely to work for you. And so, you know, being able to take that even more broadly and thinking about everything is precision medicine now. It is no longer just, you know, this is what works for 80% of the patients. We’ll see if it works for you. Now let’s really figure out what’s going to work for you.

Jeff Dance – 00:13:42: So truly like understanding you and then understanding based on data after understanding you like what is going to work and then getting that medicine. How widespread is that happening now? Like is that where, you know, is this touching, you know, 3% of what we’re doing? Is it like 30%? You guys are at the forefront. So, but are we in that trajectory right now where you’re going to see things really start to move or how far have we moved already? Because when I go to the doctor, they’re not doing any DNA testing yet.

Claire Aldridge – 00:14:12: You know, it really depends, I think, on the specialty. You know, you’re going to get that much more commonly in oncology, for example. It also is like where you’re getting your care. If you’re at an academic medical center, you’re much more likely to get it. I think that, you know, when we talk about the future, what I think is a place where we need to put resources is how do we make that scalable? How do we make that something that is available in rural communities, you know, communities that are not served by a tertiary academic medical center like a Johns Hopkins or a Duke or a UT Southwestern here in Dallas? And that’s going to be a technology solution too, right? We need to figure out how to get the tools out into the communities. And you know, when you think about that from a public health perspective, imagine the impact you could have on bringing that kind of precision to the bulk of your patient population, right? Most people aren’t in urban centers seeing patients, seeing doctors at a tertiary academic medical center.

Jeff Dance – 00:15:11: Interesting. One of the things you mentioned, Claire, I’d love to hear from both of you guys on this, was that, you know, the pandemic, we saw some rapid advancements sort of during the pandemic. Tell us more about some of the things that changed and the things that we learned in the last few years from the pandemic.

Claire Aldridge – 00:15:26: We can’t discount the work that happened before the pandemic that allowed some of this, but that sequence for the coronavirus was published in January, and we had approved vaccines using a brand new modality, mRNA-based vaccine by December. So that is an unheard of speed to get something through that entire process. So that was something that we learned was that a lot of the time constraints are not maybe really necessary, and we need to think about our entire process to look at new drugs, new treatments, new diagnostics, whatever it is, and try to be a little more aggressive because people need these, right? People are progressing in their disease as clinical trials are going through. I think the other thing that we learned is that talking about precision medicine, we learned a lot because we had this horrible experiment that happened, which was a lot of people genetically diverse people got the same virus at the same time. So we were able to do population-based studies that we’d never been able to do before and actually look at the genetics of people who progressed or people who got long COVID or people who there’s been studies recently about people who were exposed and never really showed anything. And so it’s a horrible experiment that happened, but we’re trying to get good out of it to again in Form how do we make decisions and how do we figure out where we apply our next research dollars. You know, you think about those patients that have a genetic predisposition to not even show many symptoms of COVID. Well, let’s explore that and understand that and can we use that to design a next therapeutic? So to me, those are the two really big things that happened is we learned that sometimes the slowness of this process is artificial and we have a way operation warp speed. We’ve just recently announced the FDA has operation warp speed for rare diseases. So again, let’s be aggressive about moving these things forward, keeping patient safety at the forefront, and then, you know, let’s continue to mine this horrible experiment that happened for guidance for precision medicine going forward.

Gabby Everett – 00:17:40: Yeah. And I think another thing that came out of COVID honestly was really a lot of awareness about biotech and what biotech is and why it’s so important. You know, those pandemic years was such a massive boom for biotech, not just technology, but also investment in the technology, right? Like investment was off the charts three years ago.

Jeff Dance – 00:18:02: It’s had the world’s attention.

Gabby Everett – 00:18:03: Yeah, exactly. And, you know, and it’s started to wane since then. But like I said, that awareness, I think, was a huge takeaway from it.

Claire Aldridge – 00:18:12: I do like to joke as an immunologist, it was my time to shine.

Jeff Dance – 00:18:15: I love it. It’s interesting to hear this word like a great, it was a big experiment and there’s kind of hard sides of that. But, you know, to think about all the data that we captured through that and the ability to not have the mRNA vaccine sort of like save a bunch of humanity, but then to have all that data and all that investment, all the innovation sort of paved the way for helping solve so many other things, that’s promising, I think, to hear.

Claire Aldridge – 00:18:41: A draw a negative that came out of it though is I think we learned that we have a lot of work to do on scientific communication. Scientists can sometimes have a little bit of a perspective, believe me, I’m a scientist. I’m not going to explain all this to you and it’s like, yeah, but I read on Facebook, right? And I think what we as a community learn that we need to get better at is communicating science and figuring out how to communicate science broadly that has kind of a trustworthiness behind it. I think there was a lot of misinformation and loss of trust in some of our leading groups that normally had the public’s trust. And so that was a real shame and again, an area where we could improve and we need to see that as an opportunity to learn and get better.

Jeff Dance – 00:19:30: As a whole, you know, things were changing so much through the pandemic and what we thought was changing. I think that was sort of like people were, it was just all up in the air. But then I think in that uncertainty, without more communication as a whole, people fill those voids with the information that they have from different perspectives, right?

Claire Aldridge – 00:19:49: Well, I think, just to kind of go on that a little bit more too, like the recognition that as scientists, we know that we drew this conclusion with the best data we had today. And in two weeks, we might have better data and we’ll draw a different conclusion. We didn’t communicate that well. The reason things are changing, wear a mask, don’t wear a mask, is because we learned something.

Jeff Dance – 00:20:09: We were one of the companies Fresh developing a unique ventilator that could scale into places like Africa. Because we thought that was the solution early on, right? And then we kept evolving. So it was a crazy time. You know, biotech has its share of ethical concerns. How do you guys, what is your perspective on how we balance sort of innovation where you guys are at the forefront kind of with ethics? And then was there anything we learned also from the pandemic there?

Claire Aldridge – 00:20:34: My feeling on ethics is really transparency is key. There are going to be ethical considerations. We’ve seen it with the CRISPR being able, we have tools now to edit embryos. There’s lots of places where there are ethical concerns. And to me, sunlight is the best thing about that. And so making sure that we are very open about what we’re doing as scientists, what we think the tools can be used for, and making sure we’re keeping the right guardrails up.

Gabby Everett – 00:21:08: You know, I think anytime you do something new, you’re going to ruffle some feathers. But that being said, the new things that we do and the new technologies that are being developed, all of that is for the good of society. You know, most of us are out here trying to make the world a better place. And I think, you know, it’s that intention that’s important.

Jeff Dance – 00:21:25: Let’s transition to the future more. As we look to the future 10 to 20 years from now, what sort of advancements do you guys anticipate? I mean, you started off talking about true precision medicine. Do we think we’ll see that at a global scale for everyone 10 to 20 years from now? What other things will we revolutionize? Any predictions?

Gabby Everett – 00:21:45: We talked about this previously with that whole personalized precision medicine thing being the future of healthcare. It means tailoring therapies to a person’s specific genetic biomarker profile with AI and ML were able to analyze not only specific profile to see what needs to be done, but also analyze these huge data sets, the literature, other patient profiles, those outcomes, trial data, figure out what works and what doesn’t. And Claire definitely hit the nail on the head as far as we’re starting to treat the disease now and get to the heart of the disease rather than just treating the symptoms. We’re actually finding cures.

Claire Aldridge – 00:22:28: And I think if I’m going to be a futurist and really talk about the magical make-believe world that I hope happens, one, I think every doctor will have a sequencer in their clinic. When you go for your yearly physical, there will be DNA analysis. And there have already been some studies doing it on newborns. So it will be something that you have your entire life, that you have this pattern of your particular makeup. And so when I think about where I hope we get, and I think we have the ability to get, it’s more about being able to use machine learning and AI, like Gabby was talking about, and start to understand the transition to disease so that we can start looking at these molecular signatures before there are physical signatures and maybe start to intervene even before actual cellular damage happens. So that’s the magical world that I’m looking forward to.

Jeff Dance – 00:23:21: So every doctor has a way to kind of understand you even before symptoms arrive.

Claire Aldridge – 00:23:28: Right, because there’ll be a signature, right? Things happen at the molecular level before you see it.

Jeff Dance – 00:23:33: That’s deep. You know, as we think about like disease and organs going to tissues, going to cells, then going to data. Is it the advancement of the compute and our understanding of that, that enables something to then surface back to a recommendation? Is that sort of like, how are these advancements coming together? What are the pieces that are coming together that get us to that future?

Claire Aldridge – 00:23:57: The compute power is huge.

Gabby Everett – 00:23:59: Very true. And taking that computing power and looking holistically at everything. I think that one of the things that we’re starting to realize now is how interconnected everything is. I talked previously about biomarkers. I came from a probiotics background, learning about gut health and how that impacts inflammation and how inflammation can trigger other disease states and how these disease states slough off these different nucleic acids and proteins and molecules. And you can detect those proteins and molecules and be able to correlate that back to the severity of the disease state and use these different AI machine learning computational tools that we have right now to analyze those biomarkers to get to those precision medicine treatments to get to those better outcomes. So it’s really cool to see the convergence of all the technologies and really all the fields kind of come together right now.

Claire Aldridge – 00:25:01: Yeah, I think, you got to think about that. Scientists have always gone really deep in their area of expertise and inquiry and exploration. And now that we’ve got this depth, we’re starting to say, how do they connect across? And how does what’s happening in the kidney affect what’s happening in the liver and the lung? And how does that manifest? And what can we tell is happening with a patient based on looking at these things holistically and less kind of individually.

Jeff Dance – 00:25:32: We are our own ecosystem, our own organism, and we have our own signatures and everything’s interconnected essentially. So our history has been treating a thing, but the future is understanding how all that’s connected.

Claire Aldridge – 00:25:46: When you think about you, we would go to a cardiologist and the cardiologist might not ask you at all about what’s happening with your kidneys. If you’re having cardiovascular problems and your blood pressure’s not quite right, your kidneys are going to be impacted as well. And so looking at these things more holistically so that we can intervene, yeah.

Jeff Dance – 00:26:05: Is that happening at the drug level as well? Like thinking about, is it happening where we’re thinking about? Because we all hear stories of people that are in like 17 medications or something like that, especially when they get older. Is that happening at that level as well where they’re thinking about how drugs are interacting?

Claire Aldridge – 00:26:21: So I think when we think about that, there certainly is thoughts on how do we minimize those interactions. But as we start to understand really the molecular basis of that disease and we can affect that, then hopefully those other organ involvements would be reduced because we’ve gotten to the foundation of the disease. Because a lot of times you’re taking those 17 meds because it’s 17 different symptoms that are being treated.

Jeff Dance – 00:26:47: So you’re throwing darts essentially at all those different things, hoping that some work together. And not understanding how they all kind of affect you or maybe affect your gut or something like that. Technology, you mentioned cloud compute is making a big change and you cited ML and AI. ML is sort of being a basis for really artificial intelligence or really sometimes we say AI, but it’s really like big algorithms that are centered around that data. I’m curious, are you seeing anything with generative AI or do you anticipate generative AI sort of playing a role where we’re putting neural nets over these large data sets and we’re generating things as a result?

Gabby Everett – 00:27:28: I think that is a Claire question.

Claire Aldridge – 00:27:33: So we’re seeing it already in protein design, right? So they’re now using generative AI to come up with proteins that have never been imagined and are not currently in nature. And they’re using generative AI to say, “make me a new enzyme that does this.” And so they’re definitely using it in that space. In our company, we’re using it on DNA sequences. How can we come up with a new DNA sequence that will make the same protein, but be more manufacturable so that we can make these drugs cheaper and safer? So those are the places that it’s being applied right now. What I think we have to be very careful of in this space is sometimes it’s great to use generative AI to come up with an image, like a new logo, or some sunny picture of Kanye West plus a mushroom, right? Like just whatever it is. But to use it for something that has implications for health or some other part of that, that’s an area where there’s a real ethical consideration for us because a lot of those data sets that these things are trained on are very biased. And so we have to be super careful about that. We know that we’ve seen things in the past where when we’ve used these kind of tools, we get something out that doesn’t work for anybody that’s not of Caucasian descent. And so we need to be, first place we need to spend some time and energy is making sure that we bring diversity into those data sets so that when we start to do this kind of work, bias from the get-go, yeah.

Jeff Dance – 00:29:11: So inclusive data sets, knowing that we’re building algorithms and new drugs off of those data sets. Are we at a place now where we are testing potential drugs and simulating how they might affect people just in the data and kind of compute space? Are we doing simulations where we don’t require a living organism? I know experimentation is everything when it comes to biotech, but are we at a place where at Fresh we do simulations in the robotic environment in 3D environments that are artificial that we’ve mapped to the real world, but we don’t always run the robots around even though we have them? So is that happening in biotech as well?

Gabby Everett – 00:29:51: It definitely is and it’s really exciting, right? So previously, if you have a drug, if you have a cancer therapeutic, you want to know what cancer you’re going to target with it, right? So the only way really you would know that would be to do multiple expensive experiments on several different cell lines and maybe move to several different animal models and just kind of, you know, almost a shotgun approach to what particular cancer are we going to target. Well, nowadays, you can take your molecule and you can throw them into these predictive algorithms that will assess, again, literature, past clinical trial data, what those outcomes were to help you better predict what cancer you should go after.

Jeff Dance – 00:30:38: Interesting.

Claire Aldridge – 00:30:39: And can even model potentially which protein or which pathway that drug would impact.

Jeff Dance – 00:30:45: And that’s all in compute space. Awesome.

Claire Aldridge – 00:30:48: And it takes up a lot of compute space. And that’s been an advance that has allowed this, right? They’re very, very hungry.

Jeff Dance – 00:30:55: Cloud computing, probably industry specific clouds for this. What other advancements in technology do you guys see playing a role in the future? So compute power’s been big. Obviously, the advancements in AI is not new, but there’s been a lot of advancements recently in putting large algorithms over that compute power. There’s large data sets that are mentioned in the grand experiment with COVID and all the data we got from that. I know data is just continuing to come together. What else do you guys see playing a role from a technology perspective, or are those some of the big ones?

Claire Aldridge – 00:31:28: You know, the one that I think that we haven’t really touched on, we’ve touched on it a little bit, but it’s something called real-world evidence. When you think about how you take a drug to your clinical trials, oftentimes the gold standard is a placebo-controlled double-blinded trial, where people don’t know if they’re getting the drug or not, so that you can minimize placebo effect, you can see what actually happened. For many diseases, that’s starting to become a little bit unethical, because using that drug, for example, requires delivering the drug to your spinal cord. Is it ethical for a medically fragile patient to receive a sham injection like that, or a sham shunt put in their brain for something that is disease modifying? So we’re starting to aggregate data from enormous bodies. The electronic medical record has really facilitated this. How do we pull all of that data out and start to understand what is the real-world evidence the trajectory of this disease, how fast will it progress, what are the biomarkers we should look at, what are the labs we should look at, what are the imaging things we should look at, so that we can then not have those placebo-controlled trials? Because like I said, we’re starting to get into ethical conversations about how do you really, this is not just taking a pill, these are now really invasive therapies, and so is that the right thing to do? So, I think real-world evidence, we’re going to hear a lot more about that and how we can use that, because you can also meet half as many patients in your trial if you don’t need half of them to be getting a sham treatment. So that’s going to accelerate, you know, again, how do we do these things faster?

Jeff Dance – 00:33:03: That’s awesome. Are you seeing advancements where this data is coming together? And I’m wondering if there seems like for the last 20, 30 years, we’ve been talking about the digital medical records, but we have all these isolated instances where it’s truly not coming together. And I’m wondering if, you know, I know the government’s talking about it, trying to put some more regulation in place, but are you seeing that at that level great progress in bringing these data sets together and having a larger data set to run off of?

Claire Aldridge – 00:33:32: I think we’re seeing it more outside of the US. In the US, our healthcare system is not really too fragmented and there’s too many negative repercussions around your own personal health data that people are nervous about. And so Israel, for example, they have a database of almost every person in the entire country. And so that’s a place where Israel is doing remarkable work on being able to mine that data for important things.

Jeff Dance – 00:34:00: We might have to borrow data from the rest of the world in order to apply some of the innovation that’s happening kind of here in the US. Gabby, you’re at the center of seeing a lot of startups. What are some of the exciting things that you’re seeing in biotech?

Gabby Everett – 00:34:13: Oh man, there’s far too many to really count. We’ve talked about this personalized medicine thing, really cell and gene therapy is a huge boom right now. Again, being able to cure the disease and as opposed to just treating it. We’re also seeing advancements in immunocollegy. So being able to train your body on how to attack those traitorous cancer cells. Just so many advancements right now.

Jeff Dance – 00:34:43: Claire, for you from the startup scene, what are some of the things you’re seeing that you think could be really promising for the future?

Claire Aldridge – 00:34:49: It used to be that if you had a new target, you could design a small molecule and you could get investment dollars for that and you could kind of almost certainly get a nice ROI for your investors. What we are starting to see from that investment perspective is a little more depth in understanding how this is really working and how do you kind of figure out what is the right patient population to go after. Again, in the past, we have thought about diseases as one big bucket, but now we know, again, going back to precision medicine, that the same disease presenting in 15 different people with 15 different genetic backgrounds is actually 15 different diseases. And so how do we know which of those 15 is most likely to benefit from your therapy? So what we want to see from an investment perspective is we want to see that you have an understanding of that, you have a strategy around that to really be able to understand what’s the right patient population to go after to see a clinical benefit. So from that investment perspective, we really want to know what are your biomarkers that you’re going after? Do you have that full understanding of your disease, the mechanism of it, and what the genetic underpinnings are for the rest of the genome, besides just that disease genome?

Gabby Everett – 00:36:06: Right, and as those technologies start to advance and as our computing technologies start to advance, it’s also making us think a little bit more deeply about clinical trial recruiting as well. You know, so using all of these technologies to better predict outcomes. Like Claire said, you’ve got, you know, 15 different patients with the same disease, you’ve got 15 different diseases. Well, how can we, you know, use these different predictive models to help predict clinical trial results? And well, if you get a negative, why is that? And trying to get information from that as well.

Jeff Dance – 00:36:39: We’ve talked briefly about some of the startup scene. I know we’re focused a lot on healthcare, which is one of the most exciting aspects of biotech as we change humanity, improve humanity. You guys are at the forefront of that. What are some of the bigger companies in the future that you think will, I know there’s like the current players, but what other kind of big companies you see changing the future and really leading the future? It happens often at both ends. And sometimes the small guys disrupt the big guys, but the big guys also have massive resources and sometimes can deploy a cool billion or something like that to a problem and use that capital. Any thoughts on big companies that we’re going to continue to see make big strides in the future?

Claire Aldridge – 00:37:21: And I was going to say, one of the ways biotech works is that those big companies eat the little companies, right? They acquire them, and that’s a lot of their innovation engine. So in my opinion to look at, yeah, is to look like Pfizer right now because of all the coronavirus stuff. They’re sitting on a pile of money, right? They’ve made so much money. And so they’re probably going to go out and acquire whatever they see as the next cool new thing. And so that’s how I see those little companies rarely become the big companies because it’s so capital intensive in this space. So you have to take it to a certain point and then you really need a big company like a Pfizer to commercialize, right? Moderna is an example of a little company that became a big company, but they became a big company because they were at the right place at the right time. They’d been working on mRNA vaccines for cancer for a decade. And so they were able to make one for COVID fast. And so that really accelerated them. But that’s not the usual fact.

Gabby Everett – 00:38:26: That’s exactly where I was going to go is the trend that we’re seeing right now is that large pharma companies, they’re starting to divest in their own R&D departments and they’re looking to the smaller biotechs for their next big therapeutics. Like Claire mentioned, there’s so many advancements happening all in parallel right now that a company trying to keep up with everything, it’s basically impossible, right? So they’re going out, they’re seeing the new trends, they’re gobbling up the small guys. And it’s these small biotech startups that are having the biggest impact in healthcare right now because of that.

Jeff Dance – 00:39:00: So it’s all part of a healthy ecosystem essentially.

Claire Aldridge – 00:39:04: And just to kind of like what we talked a lot about healthcare, but the other places where all of these molecular advances like ag tech, veterinary medicine, synthetic leathers, you know, all of these different places are using a lot of the same technologies and doing it in a much more sustainable manner. So I think healthcare is the place we love, but there’s huge, huge potential in these other areas as well.

Jeff Dance – 00:39:28: And they’re interconnected, of course, you know, advancements in one kind of impact another nice. You know, in the startup ecosystem that you guys are involved in, is it like 80% that are in the healthcare focus?

Gabby Everett – 00:39:39: In looking here in North Texas, things are healthcare focused. You know, we’re here at BioLabs at least. There’s a lot of diversity here in our North Texas space. We’ve got 24 companies and if I had to break them out into different industries and modalities, we would have 15 different categories. So it’s very broad, very diverse here.

Claire Aldridge – 00:40:00: But also in Gabby’s BioLabs, that’s where the lab that is working to de-extinct the woolly mammoth, the dodo, the thylacine is. So that is something that is completely a little off the normal path, but doing amazing work that is advancing science and really looking to make an impact in climate change.

Jeff Dance – 00:40:22: I think we haven’t quite touched on these other industries and verticals, but it sounds like it, you know, the potential is huge in kind of every direction.

Gabby Everett – 00:40:30: Yeah, definitely.

Jeff Dance – 00:40:32: What’s the, you know, as we think to the future, I just have a few more questions. Like, can you envision anything crazy? Like any sort of, like you mentioned, I mean, it’s crazy to think that we can go to a doctor and have like have our own. Genome sequence and get like some truly precision, and every doctor would have something, but I envision it, you know, I believe it, because sometimes technology leaps, and even in places like Africa, you’ll see like, oh, they didn’t have a whole bunch of things, but a new technology comes out and it just leaps forward, you know, all of a sudden everyone has cell phones, even though they don’t have a home computer or something like that, right?

Claire Aldridge – 00:41:06: Well, I think in some of these developing nations, right, they never put in phone lines because cell phones leapfrogged landlines.

Jeff Dance – 00:41:14: Any other kind of crazy prediction as we think about the future?

Gabby Everett – 00:41:17: I think we’re going to see a lot of growth in healthcare. The fact that we can automate and do drug discovery at a high throughput scale that’s never been done before. We’re starting to look at repurposing drugs that have already been approved by the FDA. What other indications can those drugs be used for? Because of the scale that we’re able to do science at now, I think we’re going to see a huge boom.

Claire Aldridge – 00:41:43: And I think from a public health perspective, being able to start to look again, going back to data, precision medicine, we’re going to be able to change the way healthcare is delivered in our communities through data.

Jeff Dance – 00:41:57: Any other thoughts on ethics? Technology tends to have a life of its own. Sometimes it runs so fast that humans don’t quite catch up. And then we kind of, we realize some consequences thereafter. As we think about designing the future with intent and trying to keep people at the center of that, any other thoughts on standards or ethics or things we need to be watching out for? You’d mentioned before minority populations and making sure our data sets are inclusive. Do any other kind of key focus areas come to mind as we think about the ethics and the impact to humanity?

Claire Aldridge – 00:42:32: Big one and you know it’s a little bit in the news this week with the Medicare saying they’re going to negotiate pricing for these 10 drugs and Mark Cuban’s Cosmos Pharmacy. I think the kind of drugs we can develop now are very expensive to make and so you know but they’re disease modifying so in the long run they’re cheaper. But you don’t get to amortize it over the life of the patient. So I think we need to have some really honest and tough conversations about access to care. And how do we make sure that we are not creating a system where this care that can benefit broad groups of our population is being gate-kept for only certain parts of the community.

Jeff Dance – 00:43:16: We kind of saw some of it in the pandemic, right? We saw, in the great experiment, saw examples of that where, you know, entire countries just didn’t have access to these life-saving vaccines.

Claire Aldridge – 00:43:26: You know, again, that’s a real ethical concern, even within the US, right? We have things that we know are disease-modifying, CAR T-cells, great example. If you’re in rural Iowa, you’re not going to be able to access a CAR T-cell therapy.

Jeff Dance – 00:43:41: Gabby, for you, what’s been one of the most rewarding experiences being in this awesome space?

Gabby Everett – 00:43:46: I have to point to the biotech boom in North Texas. It’s really bizarre to think about. Like Claire mentioned, the past five years have been just really game-changing for this region. The fact that this Biolabs location has been here for about 18 months, and we’ve already hit year six occupancy metrics, and that just goes to show what the appetite is for biotech in North Texas, the ability to feed it, the ability to support it, the venture report, the growth that we’re seeing. That’s been one of the most rewarding things. And again, talking about the different diversity, you know, we’ve got neurodegenerative companies and we’ve got de-extinction companies and med device companies. There’s a little bit of everything here.

Jeff Dance – 00:44:35: It sounds like a fun place I need to visit.

Claire Aldridge – 00:44:38: And you should come visit, we would love to host you. Don’t come until it cools down though, October, hopefully.

Jeff Dance – 00:44:43: Claire, for you, you know, what’s a place as we see the future unfold, you know, what’s a good resource or leader that you look to for kind of insights? You know, you’re already an influential leader in the space, but you know, for those that are kind of newer to the space, where do we kind of keep up with the latest advancements?

Claire Aldridge – 00:45:01: So we have a number of trade publications, Endpoint, Stat News, Fierce Biotech. Those are kind of things. And really, we had a lovely, lovely, lovely biotech community on Twitter. We still kind of do, but we’re a very… It’s a full-contact sport. We’re an incredibly collaborative industry because we have to work together. This is hard. It is not easy to develop new drugs, and most of them fail. So I think both Twitter and LinkedIn are really great places to stay up to date. You get to know kind of the latest things. There are, especially on Twitter, there are people who are live tweeting what’s happening at a public FDA hearing, as well as what’s happening at a scientific conference. So you can absorb that information almost in real time that’s happening in multiple different locations. So those are kind of the places where I personally keep up to date. There are leaders in the race that… People like George Church and Bob Langer, both of them are in Harvard and MIT respectively, who started a lot of companies in Dallas. We have Eric Olson, who started a ton of companies. So those are the kind of people you like to talk to about, I’ve got this idea. What do you think about? Is this really something that a company could be built around? And sometimes the answer is yes, and sometimes the answer is no. But I think it’s just a matter of consuming information and thinking about it, and you’re letting it roll around in your head for a little while.

Jeff Dance – 00:46:27: I loved your earlier thoughts about the speed of the process. This is a space where it seems like the process is always gatekeeping some innovation for, oh, it’s out here, but you got to wait five years or 10 years. And so this notion of the speed of innovation around the process itself, and then the confluence of the technology and the data coming together where you can simulate something and then get somewhere quickly because capital’s at ready, looking to snap you up and deploy it. It seems like we’re at a perfect storm to rapidly innovate. Just to wrap up, any other thoughts about the future that you’d like to share with the audience? Does anything else come to mind?

Claire Aldridge – 00:47:08: Kind of one of my little talking points is we’ve been waiting for the genomics, you know, the value of the genomics revolution for 30 years, right, since I started graduate school in 1991. And we’re finally now actually getting the value out of the genomics revolution, and now it’s more of an omics revolution. You know, that’s what I would love everybody to take away from this, is that the future of medicine is going to be different than what the past was. It’s going to be less about going to a doctor and getting a pill, and more about understanding how the disease is working, or what is your predisposition to a disease, and what do you need to do today so that you never develop it.

Jeff Dance – 00:47:50: I think of the future is you. It’s like truly understanding you. In the Future Of, that’s exciting to think about that much personalization. Well, thank you both for your insights and wisdom as biotech leaders and influencers that are shaping the future and watching the future unfold. It’s fun to hear how everything’s coming together and to think about how that’s going to benefit each of us individually. So it’s our pleasure to have you on the show today.

Gabby Everett – 00:48:19: It was great to be here.

Claire Aldridge – 00:48:21: It was wonderful to be a guest here.

Jeff Dance – 00:48:23: Thank you. The Future Of Podcasts is brought to you by Fresh Consulting. To find out more about how we pair design and technology together to shape the future, visit us at freshconsulting.com. Make sure to search for The Future Of in Apple Podcast, Spotify, Google Podcast, or anywhere else podcasts are found. Make sure to click subscribe so you don’t miss any of our future episodes. And on behalf of our team here at Fresh, thank you for listening.