Artificial Intelligence has futurists understandably excited about its potential to transform decades-old industries. If they want a real-world glimpse at how this is unfolding in practice, ask Philip Poulidis.
Poulidis is CEO at ODAIA, a five-year-old startup spun out of the University of Toronto, whose AI-powered commercial insights platform helps pharmaceutical companies reduce sick patients’ time to therapy, enhancing their chances for recovery.
“All of our experiences are captured in data,” Poulidis said. “And our collective experiences could be leveraged to determine that I went through a certain therapeutic path and had the exact same test results and symptoms as someone else who’s going down a different therapeutic path. Why is that? Which one is more efficient? Which one is better? Maybe the doctor or those treating physicians are not even aware of a new therapy or new techniques.”
ODAIA’s platform, called Maptual, eliminates that guesswork. Armed with accurate insights, pharmaceutical sales teams better understand the journey of healthcare prescribers and their patients, putting them in a position to get their therapeutics to the patients who need them. The upshot: reduced patients’ time to therapy and better patient outcomes — all the result of facilitating meaningful interactions with healthcare providers through human-centric software powered by AI.
For Poulidis, the son of Greek immigrant parents who came to Canada, it’s the culminating achievement in a career where he’s left his mark as an inventor, a business executive, and an entrepreneur.
Q: I’d like to start by asking about something that I found charming. You’ve recounted how your folks never gave you a book without first inscribing a personal message on the inside cover. What a great way to connect with a child.
My parents never just gave us a store-bought card or a book without personalizing it. For them, it was all about trying to teach us lessons and impart the learnings and experiences that they had in their lives. I really valued that.
Q: Can you talk about their backgrounds?
My father was born in a seaside village in Greece, and my mother was born in a mountain village; both were about an hour’s drive from Greece’s second-largest city, Thessaloniki, where they both went to school. My father studied engineering while my mother went to nursing school. After graduation, he joined the Merchant Marines as an engineer and traveled the world at a young age. I think it taught him never to be afraid to venture off and explore and do something different. That’s something that he taught his children at a very young age: if we’re interested in something, tear it apart, explore it, learn about it. You never know what you’ll learn and how you’ll come out of that.
Q: Did that color your worldview growing up?
It really did. It was this fearless attitude. If there’s something you’re curious about, dive in and explore it. Even if you end up being disappointed or getting hurt or failing, it doesn’t matter. It’s a learning experience.
Q: How did your family make its way to Canada?
My father wanted to continue his academic studies, so he applied to the aerospace engineering program at the University of Toronto. He got accepted and married my mom shortly after she graduated from nursing school. They moved to Toronto, but within a year, my mom became pregnant with me. That really changed things for my parents.
My dad had to work to support the family, knowing that I was going to be born in a few months. So, he dropped out of the aerospace program and went looking for a full-time job as an engineer. That’s what he wound up doing, working at various companies over the years. He’s still doing that at the age of 81 as a chief engineer at one of the largest hospitals in Canada — Sunnybrook Hospital.
Q: How did that example rub off on you?
One was my mother’s entrepreneurial spirit. After my first sister was born, it was very difficult for her to be a nurse and work night shifts, so she quit nursing and focused on raising us. After we got into our teen years and could take care of ourselves a bit more, my mom wanted to do something. So, she bought into a franchise. It was a specialty coffee store, and she learned the business from the ground up. She ended up owning three coffee shops. And I remember working at every single one of them as a teenager — even through university. She taught me quite a few things, including how to learn to be comfortable with “pivots.”
Q: What would that mean in day-to-day practice?
If certain things are not working out, it’s okay to try something new. I know a lot of these concepts are so familiar to the tech startup world, but I learned these from her when I was 14 or 15 years old. She would constantly experiment even if it meant failure. I remember one example. She was frustrated with the quality of her baked goods suppliers. She tried a few but eventually said, you know what? I’m going to do it myself. So, she vertically integrated and bought a bakery and used that to supply her coffee shops. It ended up being successful, though not without its challenges.
Also, my father, who was very technical, introduced both me and my two sisters to math at a very young age. He tutored us and as a result, I remember going into classes and would always be two or three grades ahead of everybody else in math.
Q: Before ODAIA, you worked at several tech companies during your career. How did you start out?
My first job in the mid-1990s was at an ISP called Interlog Internet Services in Toronto. I had signed up to be a customer, but when they shipped me the floppy disc with Netscape and the dial-up software, it failed during the modem configuration. I was able to get it working but thought I should let them know because the instructions that they had were wrong. I called up the support line, and the founder of the company answered the phone. After telling him the configuration and the instruction manual were wrong, we ended up talking for over an hour. Eventually, he invited me to meet for lunch. One thing led to another, and I ended up joining the team — running sales, marketing, and customer support.
Q: How much did you know about that before coming on board?
Nothing. Again, it was that fearless approach to trying new things that my parents taught me. I just dove in and got hooked on the whole entrepreneurial thing.
Q: Looking at how your career subsequently unfolded, you were involved in a few startups and ended up working for several larger companies. Was that by design?
I’d say it was more serendipitous. It wasn’t as if I was chasing these jobs. Come to think of it, I don’t think I’ve ever formally applied for a job in my life and shared a resume. My path just happened naturally. I ended up going to all these other companies through connections that I had and through people that I had met. But I did learn a lot along the way.
Q: A key event in your journey came when you were put in touch with Julia Hu, the founder of Lark. My understanding is that they were looking to make a pivot, and you had a background in SaaS. How did that work out?
Lightspeed Venture Partners, which was an early investor in Lark, made the introduction. When I went in there, I quickly realized that Lark’s true value was in the coaching software that they had. At the time, they had a device you would wear to coach your sleep. The hardware was just a means to an end. The value was really the fact that they could train a system to be a digital coach and take patients or customers through a journey of improving in certain areas. They chose sleep — but it could have been anything.
Q: Something that wouldn’t necessarily have to rely on hardware?
Sleep requires hardware because you need to know how a person is sleeping, their motions, their heart rate, and whether they’re waking up — all that stuff. But what if you chose a different path? What if you looked for other therapeutic areas? As I said, the real value was in the coaching. So, what about finding other areas where, for example, we could coach people how to avoid becoming diabetic? It’s all about lifestyle change. Lifestyle change can be influenced by a change in behavior, so if you’re coached through it, this can have a big impact.
Q: Was that the first time that you got interested in digital health?
Yeah, absolutely. I truly fell in love with the ability to use technology to influence health outcomes. Something big changed inside of me, and I really wanted to go down that path with my next startup.
Q: ODAIA was spun out of the University of Toronto when Helen Kontozopoulos, your co-founder and chief tech evangelist, reached out to you. How did that come about?
They were working on taking very large disparate data sets and invented a way of timestamping activities across different databases. They were stringing them together to map to a single entity journey, and then layering AI on top to predict how to change the trajectory to a better outcome. When I saw that, I thought it was going to be a significant game changer.
Q: Did you have a clear idea at the time how that could be integrated into a solution?
At first, Helen and I didn’t know where or how to apply it in a way that we could turn into a real business. That’s when we started to talk to different pharmaceutical companies, asking about the biggest challenges in their product life cycles: from drug discovery to clinical trials, to getting approval to launching in the market, to treating patients. We wanted to learn where there was a lot of manual effort that could be easily replaced by technology.
AI was being used in drug discovery. It was being used in helping to improve clinical trial patient selection. But it really wasn’t being leveraged in go-to-market. Pharma companies were still very inefficient in terms of hiring salespeople, putting them out into the field, and having them go and sell to physicians. We started looking at the numbers, and it really blew us away that in the US alone, $20 billion gets spent on marketing and sales to doctors by pharmaceutical companies. It’s ridiculous.
Q: And you were vetting this idea from the perspective of a veteran business exec who knew how to run operations and apply technology to help make operations more efficient.
I was brought in because I had helped build companies. I knew when to hire the right people with the right expertise and how to build a highly scalable platform.
Q: There’s a lot of excitement around AI’s potential, but ODAIA is already offering a great example of how this technology can change an industry.
It really can. We hear examples from our customers all the time, and I love hearing them. The average time between a patient having symptoms to the time they get treatment can be many, many years. If you shrink that down by leveraging data and AI, imagine the health outcomes you can improve for patients.
Q: Pharma has been open to adopting new technologies like AI and ML when it comes to things like drug discovery. But it’s been relatively slow to deploy those same tools on the commercial side of the business after therapeutics are ready to be marketed. Why is there a disconnect?
It took me a while to figure this out. Many companies offer solutions for enabling commercial teams in pharma to be more efficient, but these solutions are more consulting-based. They do inject some data science techniques and some AI, but it’s all done in a bespoke manner. That’s the key difference. They go into a pharma company and treat it like a consulting project. What happens is that they take three or four months to build these projects up and eventually deploy them. But when they eventually deploy them, the insights and suggested actions are outdated. They send that to the sales team and say, “Okay, here are the physicians that you need to go after.” That time lag is huge because it involves a lot of manual effort. I know one company that employs hundreds of data scientists in India to literally crunch through these data sets to come up with target lists — just because it’s cheaper.
Q: How did ODAIA approach that challenge?
We completely automated everything. Within Maptual, a brand manager can go in and use a dropdown list with a no-code method to easily create a brand objective. For example, we had a customer who wanted to identify patient populations and their prescribers where they could replace oral therapy with an antipsychotic [treatment] with a long-acting injectable. Their existing route of administration required patients to take pills daily. But sometimes, patients would forget to take their pills and would go into remission. And then the longer that goes on, the harder it becomes for them to remember to take their medications. It’s very dangerous for the patients. Whereas an injectable would last a whole month or longer. They were looking for these patient populations as well as for the physicians who had a high propensity for prescribing an injectable over an oral.
You can program our algorithm with a few clicks. Literally, a few hours later, the sales team has its plan of action. As new data comes in instantaneously — because lab data, claims data, prescription transaction data, etc., all keep coming in — our algorithm can process all of that in near real-time and react in near real-time.
Q: Did the pandemic make the industry more amenable to the idea of digital engagement tools? Salespeople obviously couldn’t rely on in-person meetings anymore.
Very much. I also think it became clear to pharmaceutical companies that it wasn’t so much the volume of reps that they needed to have market coverage. It was more about giving them effective tools. If you had the right tools for the right rep, you could help that rep perform the same as five reps who are not using proper tools and educate physicians on new therapies more efficiently. I think that shift happened as well. Ensuring that reps are not only picking the right physicians but are also using data to inform the best way to connect with them.
Q: Was it a challenge to get enough historical data to train the algorithm so you could calibrate the interactions with the doctor to their individual person?
No, not at all. The data is there. The beautiful thing about the life sciences industry is that there’s a ton of historical data that goes back many, many, many years.
Q: And this is where technology helps automate the process?
Our algorithms can train very quickly in any therapeutic area and understand patient journeys. They can understand what precursor drugs patients were typically put on after a certain diagnosis and by which doctors. They understand the prescribing behavior and what the outcome was for those patients. There’s a lot of data out there that could be leveraged.
Q: What’s the average time of symptoms to treatment of a patient?
Multiple years, depending on the condition or disease. Let’s use my wife as an example. She’s got Celiac disease, but she didn’t know that for close to 15 years. Every time she ate food, she would get violently ill. She wanted to find out what was causing the reaction. It got misdiagnosed first as acid reflux and then as IBS. Eventually, a doctor decided to check for Celiac. But as a result of eating gluten for decades, it had caused a lot of damage to her intestinal walls. Thankfully, she was able to correct it — slowly. This is what I mean when I say that from the time you experience symptoms to the time you get the right treatment, it may take years, sometimes decades. We want to shrink that gap using AI and data.
Q: You have a ton of business experience, probably a lot more than other startup execs. As you look back, was there anything specific that prepared you to be a CEO? Or did you acquire those skills by doing?
It’s more the latter. Earlier in my career, I had invented a compression and encryption algorithm for video streaming. But there is no compression algorithm for experience. You have to get burned. You have to have success. You have to be able to live through different experiences as an entrepreneur to prepare for the next one. I’m not ashamed to say that even though I’ve got as much experience as I do under my belt, I still don’t know everything.
Q: What do you think technologists need to do to master the challenge of leading teams and managing operations? That’s a different language from what they normally use.
It is. One thing that I learned early on was to surround myself with people who can fill those gaps or blind spots. I know myself and I know my strengths and weaknesses, and I know the people that I need to have around me to be successful.
Q: In retrospect, what was the biggest challenge you had to overcome as a leader of a startup?
There were countless challenges, starting with being at the point where we nearly ran out of money. One of the biggest challenges was learning to align myself with people who shared the same values and had the same goals and aspirations as me. Because if there’s conflict there, it will manifest itself in pretty much every aspect of your entrepreneurial experience. I learned early on that it’s not just making sure that I align myself with investors who I can trust and with whom I have shared values and goals. It’s also with people within the company — co-founders, people on the senior leadership teams, and every employee that we hire. It is so important to pay attention to that.
Q: Any short list of recommendations for younger tech entrepreneurs on how to prepare for what they’ll face?
Don’t be afraid to bring in people who are smarter than you in areas where you’re not strong. A stubborn CEO is a failed CEO. You have to enjoy being wrong and owning that, as well. When I mentor young CEOs, I tell them it’s very easy for someone to step into the CEO role and then try to wear that hat in every aspect of their role. But the true role of a CEO is not to lead through management; it’s to lead through enablement and removing barriers for everybody that you’ve brought in to do their job.
Q: Almost as if you’re the orchestra leader or chief coach, if you will.
Exactly. I know that a lot of young CEOs tend to compare themselves to others or compare their companies to others, constantly looking for external validation. It’s like following the Twitter feed of other CEOs religiously. “What did they do? Let me do the same thing.” No, you can’t do that. You can’t always compare yourself to others because every situation is unique, and every person is unique. That’s a trap. You can’t live by that.
Q: One thing I must ask: You have a pair of lucky socks you make sure to wear when you present to investors. Do you pass along the same advice to the entrepreneurs you mentor?
You read that, didn’t you? It’s funny because that article was about something else, and I talked a lot about all these other topics, and that’s the one thing they wrote. Too funny.
Q: What’s your favorite book?
The Blind Watchmaker by Richard Dawkins.
Q: Favorite movie?
Q: I saw that you reposted a tweet by another entrepreneur, Sahil Bloom, who wrote that having regret is a lot more painful than failure. Is that how you approach your work?
Absolutely. Going back to what I said before in terms of learning to enjoy being wrong, you must know that if you fail, it’s a learning experience. You’ll regret not trying. Regret is a lot worse than failure itself because at least you know that you tried and learned from it. It’s like [Teddy Roosevelt’s] “man in the arena” saying.
Q: Who’s had the most influence on your professional career?
My parents. I owe them a lot. My wife, because without her support, I wouldn’t have been able to go down multiple entrepreneurial journeys — it’s not easy without a strong support network, both personal and professional.