MSU Research Foundation Podcast

Transforming Clinical Trials with Ripple Science

• MSU Research Foundation • Season 1 • Episode 10

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In this episode, we talk with Peter Falzon, president and CEO of Ripple Science, a clinical trials software company that spun out of the University of Michigan and now serves researchers around the world. Ripple’s platform helps academic institutions, healthcare providers, and industry sponsors recruit and retain participants in clinical studies, tackling one of the top reasons clinical trials fail.

Peter shares how he went from launching startups in Silicon Valley and Japan to becoming a mentor-in-residence back in Michigan, where he helped Ripple transition from a homegrown academic tool into a flexible, scalable platform. We discuss the challenges of participant engagement, why trials often struggle to meet recruitment goals, and how Ripple’s AI-powered tools help researchers do more with less. Peter also talks about building the company with support from Michigan’s university and venture capital ecosystems—and why now is a critical moment for clinical research innovation.

Host: David Washburn
Guests: Peter Falzon (President and CEO, Ripple Science)
Producers: Jenna McNamara and Doug Snitgen
Music: "Devil on Your Shoulder" by Will Harrison, licensed via Epidemic Sound

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David Washburn:

My conversation today is with Peter Falzon. Peter's the president and CEO of Ripple Science, a true Michigan company that has developed and markets a clinical trials management platform focused on recruiting and engaging participants for clinical trials. I hope you enjoy the conversation. Welcome to the MSU Research Foundation podcast. My conversation today is with Peter Falzon. Peter is president and CEO of Ripple Science, a company focused on delivering a software platform to help streamline clinical trials. Now, as a reminder, this is designed to be a fun and informative conversation and is not investment or legal advice. And you should also know, Ripple is a portfolio company of the MSU Research Foundation. Our venture subsidiary companies, Red Cedar Ventures and the Michigan Rise Pre-Seed Fund, have both invested in Ripple Science. Peter, thanks for being here.

Peter Falzon:

Thanks, nice to be with you.

David Washburn:

Peter, tell me about your background. Where are you from, where'd you grow up, where did you study and how did you arrive to become the president and CEO of Ripple?

Peter Falzon:

So I am a Michigan native. I grew up in and around the Detroit area, went to the University of Michigan undergraduate economics and Japanese studies major and then spent about 10 years living and working in Japan, first in the auto industry, for Toyota. I was in the finance department at their headquarters in Toyota City, Japan, working with the teams that were building factories overseas. So it brought me back and forth to Michigan, to Kentucky, to Ontario, where the company was making investments, and then along the way I connected with a Palo Alto, California-based technology company. I met someone there. They were making medical devices in California laser-based medical devices for eye surgery and had sort of a beachhead in Japan but really needed to make investments and expand their business in Japan. So that's how I ended up in the medical device businesses. They hired me to set up their Tokyo office. So it was my first startup. I think it was 28 years old and we went from me opening an office and starting to import products to a distributor to about 55 employees and five offices and about a $40 million business in four years Just a rocket ship. And that company was based in Silicon Valley. So I started to spend more time in Silicon Valley. We exited that company. It got sold to a larger medical device company and so then, after 10 years, I went with a group of engineers. We started another company that made lasers for dermatology. That company IPO'd in 2004. Lasers for dermatology that company IPO in 2004. Congratulations.

Peter Falzon:

I sat on boards and worked with startup companies and mostly in the laser diagnostics and medical device sector, and started spending more time back in Michigan.

Peter Falzon:

I bought a loft in Detroit, relocated back. And I bought a loft in Detroit, relocated back, did some work both at Wayne State and the University of Michigan, helping at the Venture Center as a mentor- in-r esidence and that's where, as a mentor- in-r esidence at the University of Michigan, I was working on the life science portfolio companies when they asked me to look at Ripple and that's where I first learned about the platform and after spending about six months working with the founder, Nestor Lopez-Duran, who at the time was a professor of psychology at the University of Michigan and developed Ripple to support his research, after working with him for about six months on his fundraising plan and go-to-market, he decided that this would be my next project. He had a limited period of time, a one-year sabbatical, to get the company off the ground. He did a great job ground, oh wow, did a great job. And then, when it was time for him to go back to the university, I took over and started raising funds in earnest and moving the company into faster paced commercial mode.

David Washburn:

Wow, yeah, it's you're. You're just a, a, a prototype of the classic entrepreneur- in- residence or mentor- in- residence who's had a very successful career, international career, spent time with early stage companies in the Valley, got to go through an IPO, make your way back to Michigan and probably not ready to, you know, check out completely, start sort of hanging around. Check out completely, start sort of um, hanging around universities to see what sort of smart people are working on Just uh. I love that. I just love that story uh of of, of doing all those things and bringing, bringing that experience to bear for um, an early stage technology coming out of a out of a university.

Peter Falzon:

I remember hearing about the homecoming. I think yeah, yeah, right, Dan Gilbert was sort of a big influence in, you know, Invest Detroit and the Community Foundation of Detroit and others were really in in working hard and that was a big event. And I was in Silicon Valley at the time and I remember hearing about that and reading about it and I thought, ok, I'm going to get on that bandwagon.

Peter Falzon:

And that's when I started spending more time in Detroit. So what they did, I think, was extraordinary, because it created a buzz, wow, and it made those of us realize that, you know, we may have gone to Silicon Valley or another place because of opportunity, but we have the ability to create opportunity as well as just jump on the bandwagon and benefit from it, like we did when we were younger.

David Washburn:

So you meet a faculty member who is um, did you say he he was starting, he was doing research and built a system just to manage the clinical trial he was working on? Is that how that sort of started?

Peter Falzon:

So Nestor is, like most founders, a very creative person, a polyglot. He just has the ability to do many different things right, and when he gets interested in something, he dives fairly deeply and learns a lot. He describes himself as a lifelong learner. So Nessar is a professor of psychology. He ended up becoming the chair of the department at the University of Michigan before retiring, and his area of research was children or adolescents with depression, and his lab that was conducting this research was NIH funding.

Peter Falzon:

So in addition to being a teacher, he was doing a lot of research on childhood and adolescent development be, recruiting and managing participants in studies were struggling to meet the recruitment targets that he committed to in his NIH grant and therefore his funding was in jeopardy. So he kind of doubled down and dug in to figure out how do they go about recruiting participants and what tools do they use. And what he came, what he determined was that, instead of using a set of patched together tools that were mostly available free, like Excel spreadsheets, SurveyMonkey, ACT, I think he was at one point trying to adapt Salesforce, which was not free for part of its CRM and communication capabilities yeah, participants he created a specification and wrote a grant proposal to build a platform that had the components of all these different tools that he was using.

Peter Falzon:

That got funded, and then they hired some programmers and then he built the first version of Ripple in order to support their recruitment, which is sort of a marketing campaign. Right, you got to get the word out, then you have to screen campaign. Right, you got to get the word out, then you have to screen, and then you have to enroll and manage and schedule participants through a series of protocol, visits and steps, and it all has to be highly secure. You're dealing with PHI, PII, so you have to be not only HIPAA compliant but you have to have and you're working inside of a university, so they're really high security privacy requirements that needed to be built into the tool.

David Washburn:

Huh, what a fascinating story. So I assume he disclosed this to the tech transfer office and then Ripple took a license.

Peter Falzon:

Did they file patents or did they just treat it as copyright? Derivatives thereof belonged to the university because it was developed with grant funding. Nestor was so successful with this platform that he became the poster child for effective patient recruitment and trial execution within the Department of Psychology at the University of Michigan. Part of the reason he ended up being the chair, I believe.

Peter Falzon:

He won't say that, but I think it's part of the reason and it's the largest department of psychology in the US.

Peter Falzon:

So he goes from worrying about his continuation of his grant funding because he wasn't meeting his goals to being the star clinical trial recruiter at this department. And so then other faculty at the university in psychology, and then over in the medical school, psychiatry, where there's a lot of joint research program going on started to adopt Ripple. So it started to spread within the university. It spread very early to Michigan State University because there were co-investigators at Michigan State who were working on some of the same grant-funded projects. So that's why we're also within the Michigan State orbit and have been almost from the beginning. And then folks at other universities wanted access to it and that had grants, grant funding from different sources. And so when Nestor approached the department chair about how to make this available to grant fund I think University of Connecticut team, University of Connecticut team was the first it was determined that the best way to make this available to researchers globally. We're now in 10 countries and there have been over 6,000 studies that have been oh wow.

Peter Falzon:

Ripple platform has been used to recruit and manage participants, but it all started with that first visit to the tech transfer office and the decision that they needed to spin up a company in order to make this available commercially worldwide. And that's around the time that I was asked to spend some time with Nestor and work on his business plan and go-to-market plan.

David Washburn:

You know, when I think about clinical trials, especially with a therapeutic or a device, there's obviously science that may or may not work, and a clinical trial could fail just because of science. But if you throw science sort of out of the equation, is it possible for clinical trials to fail because they're poorly managed? And is that really the sort of thing that you all have produced here?

Peter Falzon:

Yeah, the numbers are fascinating, right? So $78 billion spent a year on early stage drug development, the majority of that being for clinical trials. 92% of clinical trials fail. The number one reason that cited when a clinical trial is closed and without meeting its endpoints in clinicaltrials. gov is insufficient recruitment. Number one. Number two insufficient retention loss of patients to follow up. Therefore, they're not able to gather all the data that they need. And then the quality quality the data goes down, can't meet their endpoints or can't they don't have the data power to meet their endpoints because of loss of patients. So those are the number one and number two reasons that clinical trials cited when clinical trials are closed without meeting their endpoints at on clinicaltrials. gov. So it's a well-recognized and huge problem.

David Washburn:

Interesting and clearly that was what Nestor was sort of struggling with when he embarked on this project to try to improve the recruitment and engagement.

Peter Falzon:

He knew that this was a big, big problem, that this was a big big problem If he could crack the code to provide something that made that part of the clinical trial process better, and by better, I would say primarily it's more predictable, right Recruitment. I like to describe it sometimes as it's the last mile of wire in a phone and the old phone systems when there were wires right.

Peter Falzon:

So it's like from the pole to the house, from that clinical research team in the clinic to the participant at their home right, and that happens in a very decentralized way, differently in almost every clinic right? If you're sitting in a University of Michigan clinic and your patients are all within five miles of your hospital, you communicate with them one way and you schedule them and interact with them and keep them engaged in the trial using certain methods and techniques. If you're in the UP and your patient population is spread 200 miles in each direction, then it's a completely different challenge to find and manage patients in the clinical trial. So the beauty of Ripple, what Nestor figured out, is that recruitment and management of patients in clinical research happens differently and therefore you can't it doesn't work to create a software platform that's rigid. It has to be really user configurable so that your process to find, enroll schedule, remind folks about where they are in the process. The tool can adapt, can be adapted to your workflow.

Peter Falzon:

You don't have to adapt your workflow to the tool and that's where Ripple stands out from almost every other tool available to these folks, if you think about Salesforce for example, you know it's sales CRM and you set it up for a workflow and then, if you have sales people all over the country, they have to manage their pipeline based on those different steps that the sales manager at a central location has set up. So there's one workflow. That's right, and with Ripple, every single site with everything can configure their own workflow and then the data all rolls up into a common configuration for reporting.

David Washburn:

I can't imagine how tricky it is, because you have to be innovative and you have a flexible system, yet you have to follow HIPAA and FDA and SOC 2 and God knows what else. Uh, you know to that that. You know all the above, yet you want to have a flexible system and you've got AI on the scene. I assume that's getting baked into the platform now. So how do you manage that balancing act?

Peter Falzon:

So I think you hit on something really, really interesting, which is: research is protocol driven. Yeah, protocol. The last thing you want in a protocol is a protocol variation or deviation I'm sorry, protocols. The deviations are bad. So you've got a very rigid process where out at this, but out at the site, we're trying to provide everyone with ultimate flexibility that conforms to that protocol. So that's where the platform has to be where. That's where the platform has to be solid and protocol driven, yet flexible at the margins, so that work can actually take place the way it needs to take place.

Peter Falzon:

We, in terms of AI, if you go all the way back to the early days of Ripple, at the time we weren't calling it AI. Way back to the early days of Ripple, at the time we weren't calling it AI, we were calling it machine learning, and we were one of the early companies to build an algorithm to predict dropout early, and there's a white paper that we wrote at the time that continues to be downloaded and referenced quite a bit. But basically what we did is we learned. At the time there were about 1,700 studies that had been completed on the Ripple platform at research locations at about 60 different locations around the world. Today we're at 500 different academic medical centers and institutions and locations in 10 countries.

Peter Falzon:

But at the time there was enough data for us to build a machine learning algorithm that could identify certain activity, words or statuses in Ripple that signaled or correlated with dropout sometime down the road. And what we learned is that the average participant that did drop out of a trial that didn't finish dropped out at touchpoint number 11, right? So, and that's there's the recruiting back and forth and pre-screening consent enrollment. So, and that's there's the recruiting back and forth and prescreening consent enrollment. So there's probably 10, 8 or 9 different touch points early on and then after enrollment there's probably another 20 or 30. But the average dropped out at touch point number 11, which is pretty early in the trial, but still after enrollment, trial, but still after enrollment. And we were able to predict those folks at touchpoint number four with about 94% accuracy.

Peter Falzon:

Oh wow, and it was. It turned out to be not one thing, but it might be. It takes three phone calls to connect with them during the pre-screening process. Or they phone calls to connect with them during the pre-screening process, or they rescheduled the second or third appointment, or they didn't respond to a reminder. Or in the coordinator notes there may have been four or five words that continued to pop up at a frequency higher than we normally see. So we use large language model processing and other predictive analytics to create what today is, you know, an AI feature, which is to predict dropout early.

David Washburn:

You were before AI mania even kicked in.

Peter Falzon:

Not because we wanted to exclude those patients from trials though. Yeah, it's so that the research team could put extra resources on keeping them in the trial, and that's what we learned. If we know who the folks are who are likely to drop out or more likely to drop out, we'll put 50% more resources on that. 10% we can afford to do that we can't afford to do that with everybody.

David Washburn:

Yeah, that makes sense. Well, you, you made a reference earlier to some of your customers, uh, academic medical centers and probably some universities and probably some pharma companies. Um, there's a lot going on in the sort of federal landscape with research funding and so I'm curious kind of what risks that potentially brings to the company. And you know what are you hearing from your customers in academia.

Peter Falzon:

Yeah there, let's just say these are challenging times. I think that comes with the territory in any industry there. I don't, I don't, I haven't worked in an industry yet where it's just clear sailing all the time related to uncertainty, primarily uncertainty in funding and how those especially NIH funding, and how that's going to shake out in both development, because new drug development relies a lot on the academic research industry to do early stage work and then license out or spin out right. So it's affecting development and it's also affecting the clinical trials that are aimed at bringing those developments to market or validating them. To me, that presents an opportunity to leverage the platform to do more with less, because all of our customers are uncertain about funding right now.

Peter Falzon:

Understand how the platform automates routine tasks so that their staff can free up some time to focus on other things. Or in some cases, they don't have the budget to have a staff of 10. They only have the budget now to have, especially with overheads coming down, we're seeing staffs getting smaller. So streamlining workflows, automating tasks, automating the communication back and forth to participants so that it's less manual and you're really the humans on your staff only really need to jump on the phone if someone fails to confirm an appointment or doesn't, or has a question that needs a human to answer. Integrated data management so that they're spending less time pulling data from different systems in order to create reports.

Peter Falzon:

Right, if you've got a multicenter study going on, like we have, several between, where there are, we have an early child development study where the PI is a Michigan State PI but the co-PIs who are working with the parents and the children in this long-term longitudinal research study are working at Wayne State University, the University of Michigan, Michigan State, and all the satellite hospitals around the state, so it's literally happening at 30 locations in Michigan, with the Michigan State University PI principal investigator being the center, because they're on one platform and they all log into Ripple, reporting rolls up, even though they're doing things differently at each site. How many participants are in the funnel when the next visit is, how many of those visits were completed, how many of those visits were missed? All of that information is available on the platform, and so it allows them to work more efficiently rather than have to share spreadsheets or send a report. And so it allows them to work more efficiently rather than have to share spreadsheets or send a report and then someone at the Michigan State Center Coordinating Center Office having to merge all that into one report. So the platform can actually be a huge productivity tool to help people through these tough times.

David Washburn:

Well, tell me about the company in terms of, um, how many? How many people are in the company? How many are, in sort of, based in Michigan versus worldwide? Um, and then, maybe, um, you have a long list of Michigan based investors. And so you found, uh on, on your return back from Silicon Valley, that you could stand up this company in the ecosystem, and I wondered if you could comment on some of the stats on the company and then just how the ecosystem helped.

Peter Falzon:

Yeah, I mean, it's a Michigan company through and through. So not only was the technology developed in Michigan, we were on site in an office in Ann Arbor until COVID. We learned how to work remotely and we went remote during COVID, but the founder, who remains active and supportive of the company, still has his main residence in Michigan. I still have my residence in Michigan, although I do spend time in California as well. We are right now a team of about 13 people. The leadership and board remain primarily Michigan-based, although we're no longer in an office in Ann Arbor. During COVID, we all learned how to work remotely and, frankly, after COVID I couldn't get anybody to come back to the office, even though I was driving back and forth from Detroit. So we ad apted to that and as we're hiring customer success people and sales representatives and developers were we're also looking, you know, the market is, people want the flexibility to work from home and the tools are so good today that, um, I don't think we missed a beat.

Peter Falzon:

uh, and we're perhaps even more productive because we're not spending so much time in cars as a software company we can do that because we deliver everything over the internet and you know the CFO, the chief and the CFO, the CISO, myself, the board.

Peter Falzon:

We're all primarily based in Michigan and we have people mostly in the Midwest that augment the team in Michigan. In terms of funding, the funding has overwhelmingly come from the VC and Angel networks in Michigan. So Michigan State University Research Foundation, through two funds, and the University of Michigan, through three funds, are two of the largest investors in the company and for me that, coming from Silicon Valley, that was a surprise, because there isn't that level of university support out in California for early startups. Almost all the money comes from private funds, not from university funds. So it's been eye-opening and it's been great because the universities have been terrific partners.

Peter Falzon:

Now, granted, these aren't gifts, right, the university fund managers are tougher than some of the institutional VC fund managers in doing diligence because, they're often using endowment funds and these are pretty sophisticated offices that know what a good investment is, and so the bar is pretty high. And then, if you look at, Invest Detroit Ventures was one of the first right, uh, efforts to private, uh, what do I want to say? The private sectors, um, answer to diversifying the economy in Southeastern Michigan.

Peter Falzon:

So, that provided some funding. And then we do have some out of state venture capital um Rise of the Rest Fund from DC. Dan Gilbert is a big LP in that, so that's why they're pretty active in Michigan. Mercury out of.

David Washburn:

Texas. They have an office in Ann Arbor, that's right.

Peter Falzon:

Adrian Fortino at that office is in the center of so many things happening in the state of Michigan with early stage companies. He's very well connected. Early stage companies he's very well connected Um. So yeah, we have a good mix, but, um, I'd say um, being a university spin out and having the financial support of the universities is a really nice part of the story there. Yeah, good support.

David Washburn:

Yeah, um, well, I, I get excited about it because, you know, I, I for MSU and U of M. I think there are a handful of companies that we've, that we've together co-invested in, and uh, this is certainly probably the first, if I'm not mistaken and um, we, you know, I think we compete. We compete in a lot of ways, but we're also friends, uh, and and colleagues and supporters of one another for the greater good of the state of Michigan. So this is a great story where uh, MSU Research Foundation and um and and um, U of M

David Washburn:

um are both on the cap table of this exciting uh company. And and I appreciate your comments earlier I think, um, certainly in Silicon Valley, um, there, there's enough sort of capital flowing around there where the universities probably don't need to be in this game, whereas I think as soon as you leave the coasts you do tend to find, you know, we know every early stage university investor in the Big Ten. They all have funds SEC same. They all have funds SEC same. I think a lot of these schools, more in the sort of inside of the country, tend to get into this game because maybe there's not a ton of sort of just private capital sitting around from people who have launched companies and exited companies, so the angel investors are much more plentiful on the coasts than, I would say, in the Midwest. Well, what a great story, you know, a spin-out and growing the company here and continued success to Ripple Science.

David Washburn:

And our guest today has been with Peter Falzon. He's the president and CEO of Ripple Science. Peter, thanks for being here.

Peter Falzon:

Thank you so much. It's been a pleasure and I appreciate the continued support you.

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