The Power Of AI In The World Of Biotech With Bradley Pryde
AI has been such a revolution in the biotech industry. Without AI, biotech wouldn't advance, and more people would be suffering. Learn the job of AI in biotech, specifically in the company OneThree Biotech. Join its co-founder, Bradley Pryde, as he sits down with host Chad Burmeister to tell us all about it. Learn how Bradley solves world health problems like cancer and what AI can do to lower its risk. Many people die of cancer every day, discover how AI is the first step to solving it.
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The Power Of AI In The World Of Biotech With Bradley Pryde
I've got Brad Pryde with me from New York City. He is the Cofounder of a company called OneThree Biotech. This is a company that's focused on leveraging AI to help solve very important problems such as cancer and then other things that are related, such as therapeutics. We're not going to talk too much about how AI is affecting the sales play at OneThree Biotech. We're going to go into how AI is helping in the biotech industry. It's going to be an illuminating conversation.
Brad, welcome to the show. Thanks for being here.
Thank you very much for having me, Chad. It's a pleasure to be here.
You're right across from Grand Central Station. Do you get to walk by there every day?
Yes, absolutely. It's very conveniently well-located.
I assume things are getting a little more vibrant there.
It's positive and negative. I'm going to be about a month away from not being able to get a sit on the subway, but I get to meet more people in the office, which was completely vacant over the summer, which is nice.
My son was telling me at a restaurant one time when it was 30%. He said, "Dad, why are you complaining? We got in with no problem. We've got a big wide open space." When we go skiing, he said the same thing. It's careful what you wish for sometimes. To help our audience get to know who you are and how you got to this place, when you're younger, 6, 7, 8, 9 years old, what was your passion? When you woke up in the morning, what did you like to do? Some people say sports. Other people say, "No, not at all."
Try to have a lasting impact on your community that goes beyond yourself.
I always liked a variety of different things. I was thinking about what did I consistently like. It was whatever it was I was doing. Typically, it's outside doing something exercise-related. I love sports. As long as it involves being able to see my friends, family, and other people who enjoy a conversation and learn through a discussion, that was always my passion. As I worked into different life experiences, that's what I was always drawn to at what affected people the most.
We came up with the term at an event I was at, communion, like, "Be in communion with others." This has caused us to remember that it's important and that a Zoom video in 2D isn't quite the same as a 3D meeting.
I can't wait to start going to actual live conferences as opposed to doing everything over Zoom, although that has been fun as well.
It actually has worked. I know a lot of people who are at Zoom. They've done quite well during these times, no doubt. Thinking about your liking and hanging out with other people, if you look at what you're doing now, how does that relate from then to now? Is there a common thread between those two things?
Yes. I'm more than happy to jump into my whole background in how I got here because I took a very untraditional pathway in order to get there, how I realized my core, and then thinking about how I started applying that to different experiences and ultimately where I came now. I think about the two parts of me growing up. I had my mom and dad. My dad was a CFO who was focused and quite introverted. Personality-wise, I didn't take after him at all. My mom was outgoing and then people on their side of the family typically were in sales and built their way up in their careers that way. I took after my dad and went into finance. It's not CFO-type finance. It's more on financial markets. I was enjoying that because you still have a certain degree of being able to interact with different people. That didn't feel quite right, but also the money is good, so it kept me there.
I moved in from buy-side finance into trading. It was also on trading that I had an unfortunate event happened where I lost a family member to cancer. Seeing how much of an effect that had on me made me realize how much I do care about people, made me personally want to do more purposeful, and mission-driven work within my life. Immediately, long story short, I ended up going into tech because I thought that if you established a certain type of technology, it's going to have a lasting impact on your economy and community beyond yourself. You have the ability to affect people to a greater extent. Originally, going to tech as a trade, I was seeking arbitrage. I don't think I was creating a lasting benefit for anyone else.
When in tech, I sold that business as the CEO. After the acquisition, I came back to New York. I was working as a strategy consultant, building out tech subdivisions for Fortune 500 companies, and working with the executive teams there. We had different implements of AI being applied to our different projects and companies are building out but I still had this hunger to get more involved in the fight against cancer generally because that was something that impacted me quite substantially. I don't have a scientific background, as you can tell from my experience. I started to network with other people and this was when I started feeling like I was heading in the right direction. It's not only was I setting off my path. I was also setting my path to help other people out as well.
I was meeting different people within the field. There are many different ways to get involved in a fight against a particular indication, one being cancer. It was when I realized what my current cofounders were doing that we could make a genuinely large impact based on the progress they've had from the scientific aspects so far, but then also how much it made sense to utilize and leverage the vast amount of data that had become prevalent in drug discovery and then apply it to the huge failure rate. In drug discovery, there was about a 96% failure rate. It was due to failures on the biological side, which we specialize in understanding. If you want to draw that conclusion, biology is people. That is where we fail.
Biology is extremely hard to predict. It's much harder than the weather. It has been around for a long time. In 2004, we sequenced the human genome, which helps. This is what our technology does. Ultimately, it makes predictions on toxicity where a lot of failures happen, cancer-specific subtype efficacies, and then understanding different mutations that patients may have that may make it more susceptible to certain therapeutics. A long story short, I navigated across a multitude of different experiences, but my undeniable draw is for that humanitarian benefit. I'm not going to lie. I'm a capitalist as well, but that humanitarian passion I had to follow. I would say for the first time that I'm feeling very aligned to my different goals there.
A lot of people, I don't think, ever get to that point where they recognize that focusing your career on your passion and making money at it can be one and the same. It's fun when you can get in that lane. I've talked to almost 100 people on this show. A common misconception by a regular employee who walks through the door every day is, "Is my job going to be impacted in a negative way?" It can be the elephant in the room. I have to believe your company doesn't exist if AI isn't available. Therefore, there are only net positive jobs. Is that a true statement? How many positive jobs have you created with AI?
Now, we're at a point where positive jobs for our company were above twenty. We're hiring people and growing. Technology is happening. There's no way to get around it. If there are dollars, the economy is heading in that direction. There's a chance that if you aren't constantly reinventing yourself, then it does affect your job. That is something that is inevitable when it's part of what we've always been part of as a society that the need to advance and solve problems that aren't currently being solved at the rate that can be solved by technology. If that replaces the current job that you're doing, I do feel like you need to improve your skillset and adapt around the technology. Everybody should have the ability to do so.
It would take a year for a human to go in, click around on LinkedIn, and figure out the data. It takes the computer eight minutes. Would you rather invest $60,000 for one year of labor or have it all done in eight minutes? I have to believe that the same thing in your business occurs. Years, decades, or centuries' worth of work collapsed down into minutes or hours. Is there an analogy you could use or something that you've seen from a time-saving perspective?
For us, when we're thinking about the sensitivities of whether or not my job is going to be taken over from AI, the stakes are so high. With a drug failure rate of 96% in oncology and people dying in 2020, 9.6 million, we would want to save time. We're thinking about the end goal of people who are passing away every single day. The efficiencies that we want to recognize in our journey to cure as many cancer subtypes as possible, we're going to take those because that's what we're focused on.
To give an example. There's a company that we came across who were in phase II trials. The company was called Oncoceutics. They were testing it against six different cancer types. The reason for that is they didn't know what their drug was hitting at that point in time. They were close to not getting a conclusive phase II trial, which would have set them back a multitude of different years. Also, there's a potential that their drug would have had to been shelved if they weren't able to get the supplementary funding to try it again, so we came in and made a prediction on what their drug was hitting, which was DRD2, a dopamine receptor.
Off the back of that, we made a prediction of what their ideal patient type should be based on that new finding. We looked at different predictions on biomarkers. It's a genetic mutation a patient may have. Also, we did genetic interactions and gene sexuality predictions to see what cancer types are being most efficacious against. Long story short, we found that it was efficacious against a rare methylated glioblastoma or rare brain cancer. We brought in the phase II trials focused on this based on our predictions because we give the quantitative AI predictions with the underlying qualitative supporting evidence for this. They were a huge success.
They've moved from phase II trials to phase III trials, which increases the value of their assets by substantial amounts. We're talking in nine digits, ultimately. They sold to Chimerix, which is $400 million in cash and other considerations. After being able to do that, it saved them in potential opportunity costs of very large amounts. It could have been an infinite amount of time this drug won't happen. To get to the point in time, it was over four years using traditional methods and they hadn't discovered what their drug was hitting. It was a three-month project, we were able to identify what their drug was hitting and then we took another three months to identify their patients. What they hadn't been able to accomplish in four years, we were able to accomplish them through to 3 to 6 months.
AI helps solve unsolvable problems. The value of artificial intelligence can't be understated.
That hits home because several people in my wife's family have the BRCA gene. They're predisposed to get cancer, specifically on brain cancer. My dad's dad died of that when he was in his early twenties. I never met that grandfather. You think of the financial returns that we talked about, taking four years and making it 90 to 180 days to solve a problem where they could have run out of money and stopped the project. How many phase 1 goes to 2 and goes to final approval? There's probably a significant drop-off. The value of artificial intelligence can't be understated.
We've been talking a lot about AI in biotech and how a company without AI could have taken another four years or abandon the project, for example. In 90 days, we were able to figure out using AI which type of cancer it applied to and then, in another 90 days, which are the viable patients who could be leveraging this drug. What a cool conversation. Where do you think the future is headed in AI? It seems like with Watson, I'm sure Google and Microsoft have something. Does it become platform-based? Is there a generic AI that can be plugged into multiple apps? Is it reinvented every time at different companies? Can you share a little bit more about your thoughts on that?
I think just because we're in this digital era where new information is becoming available across a wide variety of different spectrums of industries. I can speak specifically about our industry. What's going to happen is that first, people hear AI and it becomes a super huge buzzword. The adoption of AI and people trying new things goes high. What's going to happen is you'll see a dwindling down and different companies falling by the wayside. It's going to be the ones specifically that specialize in their niche that they're extremely good at doing. Within drug discovery alone, there are hundreds of different companies that do "AI in drug discovery." The point of the quotation being is there are multiple different types of AI and methodologies which people employ. It depends on what's going to be useful and who emerges from this big crowd with people within this specific industry.
What we do is specialize in understanding and applying AI to a multitude of different data types within drug discovery but there's a multitude of different use cases that can be applied within drug discovery across the board. There's natural language processing, so being able to read literature for different drug discovery purposes across different indications. There's AI just for the organizational sake of data. It's not making predictions but being able to read and analyze that and collect your data because people have a wealth of data they don't even know how to start and use with. There's AI for cell imaging where you're able to determine whether or not you see from an image that looks likely to have a tumor in it or not or a blood-brain barrier permeability.
There has been a fantastic Forbes article that was written in 2019 that shows the top 30 pharma companies in large part are adopting different activities, whether that's research and development, collaborations, or outsourced partnerships. The vast majority of them are outsourced. A lot of them from my personal interactions are trying to find out where it's useful because the pharmaceutical industry has been a laggard industry whereas the financial industry has adopted this quite quickly. There are a lot of institutions that are making profitable trades off of high-frequency trading and then other types of different longer-term trades with implementations of it. As we come out, long story short, people are going to become specialists in certain specific areas and those are the ones that are going to thrive. There's no doubt within different industries that have the ability to leverage data for a large amount of benefit will be adopted in some form.
The last question is around your specific role as COO and Cofounder. As the "COO" you're doing more than operations work with partner identification. What is your day in the life look like? What is your role and what are your goals?
It changes based on the priorities that we do have. A lot of the time, when we first got started, I was recruiting for the team, finding out the best computational biologists that we have there and machine learning scientists to help add to the team and understanding where we need to fill gaps based on different methodologies and information that people held in different specialties. We're trying to get cutting-edge people who may have gotten a PhD in a particular type of machine learning methodology that would be beneficial for this area of Biology. That was a hiring sprint that we ended up in the beginning and then it was ongoing. After that, what I would like to spend time on is trying to figure out how we best partner with the pharmaceutical industry and finding people who are within our niche for us to grow our scientific expertise and then help them build out theirs.
That in itself was a challenge to find out exactly what therapeutic area you're applying to what specific cancer types are on them. The next challenge, which has been relatively difficult and I'm sure you've experienced this yourself, is getting people to understand what AI is, unveiling the black box, and thinking about the best way to communicate that for their specific situations of saying, "Here is what we specialize in. Here are our case studies. Here is why they couldn't have done it without AI. This is what we believe we can bring to your specific situation." You have to get them interested enough within a one-hour call to say that there is a potential partnership to be formed here where we can develop our assets together. I would say that's the vast majority of the time and then all of the other non-sexy mundane stuff that everybody has to do.
There was a book I remember reading selling air and it was the Microsoft Story. Software is a combination of a bunch of zeros at ones and so being able to say what it does and how it does it. We worked with a company out of Miami called Epica.ai. They help you serve up like, "Would you like fries with that?" when you're checking out of your card on Amazon. It's hard to describe what that is until you look at a few case studies and say, "This was an 897% increase in sales." Sometimes, my team says, "I don't know, Chad. That one doesn't feel like real AI." I said, "I don't care if you call it AI, BI, CI, or DI. If it produces an 897% increase in sales, you can call it whatever you want." Getting to the case studies and helping people understand, "You mean that's the outcome I get by applying these two letters to the business problem that I'm trying to solve?"
Showing the outcomes is a good starting point to get people to listen, so you have the ability to have their attention to explain how it's working. It can be duplicatable, which is important.
Godspeed to you on solving the cure for cancer. It's interesting because AI, for the first time, finally we can start to think about, "How do we solve world hunger? How do we solve hiring disparities in managers making certain choices where an AI can tell you that?" There are so many possibilities that uplevel the human condition to be able to do things that we traditionally couldn't. Kudos to you. May the next generation have eradicated cancer based on the work that you guys are doing.
I would love to see that. Thank you so much, Chad.
I've been talking with Brad Pryde. He is the Cofounder and COO of OneThree Biotech. It's OneThree.bio. If you're in the biotech space or you know people in pharmaceuticals like my uncle and cousin, make the introduction. These guys are changing the world. Brad, thanks for coming on the show.
It was a pleasure, Chad. Thank you very much for having me.
About Bradley Pryde
Biotech COO & Co-Founder focused on Business Development
Brad brings a wealth of experience to OneThree which includes leading a tech start-up to acquisition as the CEO, building out tech-subdivisions from scratch for Fortune 500s as a Strategy Consultant, and much more.
While starting his career in finance in London Brad’s path changed course after his uncle was diagnosed with cancer, ultimately leading to him join OneThree Biotech.