Episode Transcript
[00:00:00] Speaker A: Foreign.
Welcome to the Bio Rossi Few and Far between podcast.
[00:00:08] Speaker B: I'm your new host, Melissa Alice.
[00:00:11] Speaker A: For the past six years, Mike F. Has served as both the leader of Bio Rossi and the steward of this podcast.
[00:00:18] Speaker B: And before he moves into his new
[00:00:19] Speaker A: role on the Board of Directors, I had a chance to sit down with him and ask him about his tenure on the podcast and his thoughts on some vital topics in the clinical trials industry.
[00:00:29] Speaker B: Chris o' Brien joins us today to
[00:00:31] Speaker A: zoom in on the origins of the Few and far between podcast, AI's rapid evolution in the industry and key takeaways from his role as CEO.
[00:00:40] Speaker B: We'll also introduce Chris to the other
[00:00:42] Speaker A: side of the lightning round, get his thoughts on CRO myths, patient centricity, and how long form media like podcasts is still important.
[00:00:52] Speaker B: I hope you enjoyed this episode and
[00:00:54] Speaker A: I look forward to being your host for the next stage of bioraassi and Few and Far Between.
Okay, let's start the podcast.
[00:01:03] Speaker C: Melissa Alice welcome to Few and Far Between.
[00:01:05] Speaker B: Thank you, Chris. I'm excited to be here.
[00:01:08] Speaker C: Congratulations on your promotion to president of biorassi.
[00:01:11] Speaker B: I'm thrilled with it and I'm excited that we're spending today with an official handover episode, today being your last day in the CEO chair and my first day in the president chair. We're going to hand over the Few and Far between podcast from your chair to mine, and I'm just delighted to have a chance to do that with you today.
[00:01:29] Speaker C: That's great. As am I. And I think you'll do a great job as host going forward.
[00:01:34] Speaker B: Well, you're going to test me on that right now because I'm going to interview you today.
[00:01:38] Speaker C: Fantastic.
[00:01:40] Speaker B: So let's talk about some reflections on this being your last day in the chair. What did you get wrong about this show in terms of where it would become?
[00:01:48] Speaker C: Yeah, I'm slightly spoiled for choice there, but I'll start with I really thought of this initially as a marketing vehicle, just as a tool that would help us to get the word out on biorasi.
And then what I didn't anticipate was that we would be able to evolve it into this communication channel that let us have conversations. Let me have conversations with such interesting people, CEOs of biotech companies and academics and writers and interesting thinkers who have all helped me to get better at what I do and really get deeper into the biotech ecosystem.
[00:02:29] Speaker B: And I witnessed in hearing and then watching the most recent episodes that we've had a lot of guests that really moved you. What's that single thread that connected those guests.
[00:02:39] Speaker C: Yeah, you know, there are. When we first started, again, I don't think we were programmatic about it. I certainly wasn't. But what has turned out to be true is that, unsurprisingly, in this world you get a lot of people who have made passion decisions about what they're pursuing. And so the thing that excites me the most is this ability to talk to these extraordinary biotech founders and some of the thinkers and writers that we've had on the podcast because they are making passion driven decisions about what they want to do with their lives. And that's not all that common in this world. It's, I think, highly motivating.
[00:03:19] Speaker B: Yeah, it definitely motivates me. I love to find out what someone's passion is and often it's not what their current pursuit is either. Yeah, let's switch the channel a bit to biotech innovation and in particular our funding environment, which certainly is capturing a lot of conversations as we're hopefully turning a corner. Where is biotech funding gone and what gets lost when capital gets scarce?
[00:03:43] Speaker C: Yeah, it's a really good question.
I think, you know, the headlines are pretty clear, pretty obvious that, you know, interest rates went up and, you know, the era of sort of free capital ended and the window on these special vehicles and SPACs kind of closed. And so we saw valuations correct downward really hard.
And that put the brakes on a whole bunch of things in the biotech industry. So I think we all agree on that. I think what's worrisome more than the cycle is what happens to the science that doesn't fit into a neat narrative. So the thing that worries me now is a concern about whether the US Government's going to continue to fund fundamental research.
This has been such an important part of the engine that is the biopharmaceutical world right now. This grant money and terrific science inside of universities, resulting in concepts that get spun out often into biotech companies, sometimes sold directly to big pharma. And then those biotech companies developing to the point where because they have access to the capital markets, they can actually get big enough to bring drugs to market, or they can decide that the business should be sold and should become part of a big pharma player. And that whole ecosystem, which I think versions of it exist elsewhere in the world, but it is nowhere as rich and as deep as it is in the United States, is at risk right now. And that's worrisome.
[00:05:17] Speaker B: It is. And yet there's still a Lot of hope about breakthroughs, about what's next. We live in this space of innovation and there's always this, this pursuit of the next breakthrough. Do you have a sense of what it is? And more importantly, is the CRO world ready for what that is?
[00:05:34] Speaker C: Yeah, well, listen, I think there are a number of claimants for the sort of the throne for what's going to be the most exciting medical breakthrough that we'll see or technical breakthrough that we'll see in the coming few years.
And there are people who are much more expert in that than I, who will opine on that. I do think that this intersection of multi omic data and AI driven target identification for potential future drugs, looking for signals inside of big data sets that humans just can't read manually. The era for that really feels like it's coming now. I think for a number of years we've been talking about this and we've had various people say that AI is general intelligence, artificial general intelligence is here or it's never coming or it's gonna cure cancer, or it's not gonna do anything. There've been all kinds of talk in all directions. It really feels like the technology continues to get better and if we can do a good job of feeding that technology with the right kind of data, that exciting breakthroughs are coming. So that's sort of, I guess, my answer to part one of that. And then is the CRO industry ready for that? I think yes and no.
I think that the CRO industries ability to take a protocol and turn that into proof of whether or not a drug is safe and whether it works that I have a lot of confidence in. And we have terrific organizations across the world and across the industry that are very good at doing all of those things. Some of them do it from soup to nuts like Bayarossi does. Some of them are specialists in one particular part of the, of the process. All of that, I think works really, really well.
How quickly CROs will be able to add AI expertise into their processes to make this go faster, that I think is still an open question. And one of the things that you and I have talked about is that particularly for publicly traded companies, it's a really strange dynamic right now set of incentives because if you're, if you're a public company and you invest in expensive AI initiatives, you're spending a lot of current earnings to try to, you know, become more efficient and make these things work. And then if they do, given that the billing model tends to be at the end of the day, hours plus you know that hours worked at some kind of markup, a cost plus model, you've kind of paid money to then charge less.
And that's a tough thing to get a public company CEO to get their head around.
So we'll see how quickly the big CROs are able to do this. Now I say that I think literally all of them have some kind of significant AI initiative in place. And people are hard at work trying to change the business model of clinical research to move it away from cost plus model and towards more outcomes based stuff. There are lots of reasons why sponsors should like that, but I think a lot of it is not fully figured out yet.
[00:08:40] Speaker B: I concur and I think too that we think about breakthroughs in terms of science and delivery of new assets. But I believe we're also on the precipice of a breakthrough about how drug development gets done.
And a big component of that is of course how we're leaning in on AI and data. So let's dig in a little further there. Cause I know this is a passion project of yours. In particular, you have a view of what AI can deliver in drug development. What's shifted over the past three years?
[00:09:05] Speaker C: So first of all, the models have gotten better, right?
That's an obvious thing to say if you spend time in this space. It's not necessarily obvious to everybody. So one of the things that I've seen is that I've heard from family members and folks that I know that don't like AI very much versions of, I tried it, it's not that good, made mistakes, blah blah, blah. And when you double click on that oftentimes that was six months ago and it was almost certainly with a free version of one of the models. And I think a way to think about this right now is that the free models are six months behind the paid models and the paid models are six months behind whatever the hell is happening inside of the, the, the companies that are building these frontier models. So you know what, the folks inside of, you know, Google and OpenAI and the other front running players, what those guys are seeing is some forward leap from where we are now. So when people inside of those companies say it's going to continue to get better, they're kind of cheating because they can see the better already. It's just not, it may not be finished and ready for release, but they're seeing that the progress is continuing. So that's one of the things I think that folks can get wrong. And my advice on that, my strong advice on that is pay 20 bucks and get a paid version of one of these services. I pay for several of them at this point because they're really, really useful tools. But even if you just pay for it for a month to get a little bit deeper into what AI can do now, it's pretty extraordinary. So that's an important thing that has changed, is that the models have gotten better and it feels like they're going to continue to get better. I don't really see that curve flattening in the near term.
The next piece is that we're getting better at knowing what to do with those models. So that's both about the ways in which those are used and the data on which we over which we exercise the model. So, you know, excellence in data and data that are really well organized is a critical part of getting the most out of these AI tools. So when people look at the things that we did a couple of years ago where folks were developing molecules and putting them forward and nothing has progressed very much, I think we have to then say all of those things are now different. The models are better, the data are cleaner, and we're smarter about the ways in which we humans are cleverer about how we use those models to try to drive results. So we just released, as we're recording this release today, a podcast with Zach Kohane and, and Zach said he think who is chair for bioinformatics at Harvard Medical School. He said he thinks this fall we will see some AI developed assets that make it through a phase two trial for the first time, start to move towards pivotal trials. So we're not quite there yet, but I think we're starting to see a lot of progress and I see that continuing.
I think it's very dangerous to assume that progress is peaked.
[00:12:11] Speaker B: Well, and certainly we'll reflect on this podcast a year from now and realize how little we even knew then.
It's messy. The real world data, the ability to have some mechanism to deliver on the AI promise. Where do you see that tension between the promise and the state of messy real world data getting resolved first?
[00:12:31] Speaker C: Yeah, well, first of all, I think it's incumbent on all of us to pay attention. So again, this is not something where you can say, I looked at it and I made a decision that it's gonna do X or it's gonna do Y. You kind of have to follow it and you have to play with the models, use them in your life. They're actually very, very useful in your work and in your, and in your, you know, if you're planning a vacation or trying to figure out some other weird project you're gonna do, I will tell you. I bought something. I bought a watch last year that came from Europe. I got a bill the other day from FedEx that said I owed several hundred dollars in tariff fees. And I thought, what the heck, that's not fair.
And so I asked Claude if it was fair and it said, not really. You can dispute it. And it gave me the contact email at the specific contact email for disputing a tariff at FedEx. It drafted the note for me and I submitted my thing and they waived the. They said we have reassigned this tariff to the appropriate party, which I assume is the company that sold me the watch. So pretty small example, but, like, there are tons of ways that you can do things like that and scaling up from there to much more dramatic projects as your fluency increases. So that's thing number one, I think, is to try to be open to and, and learning about the continuing development of the, of the tools. And then the challenge for all of us is to try to walk the razor's edge of neither. Neither blue blind credulity, where we just assume that curing cancer is a couple days away and there's going to be a brave new world or deep pessimism and just to try to go one step at a time. I think the other thing is, I remember when my mother was first diagnosed with cancer.
Her oncologist, she really wanted to know how the story was going to end. And her oncologist said, you got to focus on. You're like a car driving in the dark with your headlights on. Focus on what you can see in front of you. Don't worry about what's down the path. You can't know that yet. And that's kind of where we are with AI is focus hard on what's going to happen in the next six months or 12 months. Because beyond that, even the people who are living inside of these companies don't seem to have certainty about what things are going to look like.
[00:14:43] Speaker B: Sure, Yeah, I love that metaphor. And there isn't a need to light up the entire road, but having clarity on the road in front of you allows for an easier drive, at least. Yeah, I love that. Yeah, for sure.
So I want to reflect a bit on your podcast journey because one of the themes that has been pervasive is about leadership. And I love how you've had audience with so many people and been in the occasion to ask them about their leadership. So 68 interviews later what did this teach you about leadership?
[00:15:14] Speaker C: Yeah, that was not something that I expected to get out of the podcast experience, and I got a lot out of it.
I think, naively, I assumed that many of the CEOs that we've interviewed are technical founders or technical co founders. So they've got a deep science background that they bring to the table. And yet the best folks that we've talked to, I think, often talked about leading from a place of humility and curiosity and, and hiring people who are better than they are at whatever the discipline is that they're going to be focused on. So that's highly resonant for me and I think really encouraging, hopefully for all of us to realize you don't need to be the very best at everything. In fact, you can't be. That's not a realistic goal.
You should think about the things that matter most in your organization, try to get as good as you can at those things, and then hire well and, and enter into a dialogue with the people that you recruit into those kinds of roles. I think that is, I found that mildly relieving to reach that conclusion, having talked to a whole bunch of real superstar biotech CEOs.
[00:16:26] Speaker B: Indeed. So the baton is being passed from you to me, which is an exciting moment for both of us. What do you hope that I ignore from the playbook and what would you hate to see changed?
[00:16:40] Speaker C: What do I hope you would ignore? Well, I think that you'll have to find, so you can see my interests from the kinds of people that we've interviewed over the past couple of years, you may find that there's a slightly different set of targets that are exciting to you, and I hope you will follow your own curiosity on that, because I think the more authentically you, as the interviewer, are excited about the person that you're going to talk to, the better the output is. I think if it ever felt, which it has not for me, but if it ever feels like a task that you have to go through, I have to go talk to this person now.
I think you'd get a pretty boring conversation out the other side.
So that's the main thing to ignore. And then I think the thing I would hope you would keep is maybe this idea of targeting people who have something exciting to say about something they're passionate about.
And I think that's what makes few and far between interviews really great and super fun to do. And I will be a fan and listening to hear where you take it as we go forward.
[00:17:51] Speaker B: Oh, that's really Useful and good context too.
Let's reflect as well. What was the basis of starting this podcast? You did talk before about how you thought it might be a marketing tool, but what did it cost you?
[00:18:07] Speaker C: Yeah, mostly just. Just in air quotes time.
So, you know, we did not spend a lot of additional money on this. I would say our superb marketing team did an amazing job at editing these podcasts and marketing them. So it was not just my time, it was time from, from me and from the marketing team. And so for me it was, it was pretty prep time and then doing the actual podcasts themselves and then as I said, some hard work from our marketing and creative teams to put the images together and the music together and all those kinds of things and edit the episodes.
But I think it was a really good use of time.
We did not set out. I wish I could say that the strategy was this clear, Melissa, but I think when we are is best when we are honest about such things.
Where the POD has ended up is it turns out there aren't so many good long form opportunities for biotech CEOs to talk about what makes their company special.
And so we're now getting a lot of inbounds from PR firms who want to bring their CEOs on to have them talk. There are two things that are great about that. First, they usually are pretty good talkers because the PR firm doesn't put forward people that they think are going to be terrible and are going to hurt their, you know, hurt the prognosis for the company they're supposed to be helping. So they recommend good people and of course we are delighted to, you know, reach outside of our networks and contact those folks. So that's. That has turned out to be the lane that we're in. And of course since we run clinical trials, getting to know and build sometimes build a really doesn't always happen, but sometimes build a build a relationship with the folks who come on the podcast. I just had lunch the other day with a former podcast guest who was in Miami and being able to do that opens up the door for collaborating on clinical research projects and other kinds of things as we go forward. So it's been for me a way to connect into the CEOs and founders in the biotech world. And that's been well worth investment that we made.
[00:20:14] Speaker B: That's fantastic and a little bit of behind the curtain for our viewers and listeners. So here's a way to round out your reflection on the host of Few and Far Between. What would you tell Episode one, Chris as A message from Melissa at her episode one.
[00:20:32] Speaker C: That's a great question.
I would say this only works if you can do it from a place of both curiosity and authenticity.
So you want to bring people on who you are curious about and you want to be well enough prepared that you can ask good questions. You don't. Of course, we are not going to be experts in the science anywhere near to the degree that especially the scientific founders of these companies are.
But we need to know enough to be able to go to give them a platform and have a dialogue with them about all this stuff. So I would say that's. Number one is follow your curiosity and number two, prepare. You don't have to over prepare, but prepare for those conversations.
And I think that if you do those two things, you're going to do great. I guess the last thing is, funnily enough, most people do great in this context, but there are some people who freeze up when the camera starts and you realize, wow, this person is much more relaxed when we're not formally recording. And there you can use a trick if you can finish the podcast and keep. But we're still recording and you can ask them questions after the recording has technically ended and then ask them if it's okay to put those. To use those as clips and to use them. We've gotten some great content that way and sometimes we've just had people say amazing things after the podcast ended, even if they're good talkers. So keep the cameras rolling.
[00:21:59] Speaker B: That's right. Well enough. That's one of the things, as we've evolved to a preferential video format for pods, that does add the additional. The showmanship factor.
Yeah, for sure.
Well, I am excited about this next part, which is always my favorite moment in every podcast is the lightning round. And so if you're ready for it, let's do it. I'm ready for it. We're going to go for the lightning round.
It's fun to have you on this side of the equation. All right, best guest you ever booked. Oh, you never booked. That's even better question.
[00:22:33] Speaker C: Best guest I ever. I'm not, I'm not willing to say no.
[00:22:36] Speaker B: That's not a fair question. Let's go with best guest you never booked.
[00:22:40] Speaker C: Yeah, there's, there's, there's too many good ones. But the best guess that I, that that I. Or like a dream guest that I would have liked. I can think of two good answers there.
One is Siddhartha Mukherjee, the author of the Emperor of All Maladies.
One of the Kind of definitive stories of cancer, I guess you could say. I think he would have been an amazing guest to have on. And another is Nubar Afayan, the founder of Flagship Pioneering, I think one of the most interesting versions of venture capital and incubation. The guys who created Modern Moderna among so many other companies. And so one example, a thinker who can provide context on cancer broadly that title, the emperor of all maladies. It's such a beautiful and apt phrase. And the other, somebody who created an innovation center. There are a few others who've done that and those are some of the most, I think just the concept of how they did that, that and achieve that, that would be fascinating.
[00:23:44] Speaker B: I agree. Yeah. All right. What's the biggest myth about running a CRO?
[00:23:50] Speaker C: I think the biggest one is probably that it is primarily a bioscience business.
So many CROs were started by doctors for obvious reasons. I am not a doctor and so, you know, I will accept the, I will accept the brick bats from any MDs who don't agree with this. But I think we're probably primarily in the data business and our job is to get actionable, high quality data to our sponsors as efficiently as possible so they can figure out if the experiment worked or did not work. It's as simple as that. And doing that requires great people, processes and technology and it sort of shifts the way you think about it, I believe. So. One of the things that we've worked hard on at Bayora is having a standardized data model so that the information that a CRA is recording in Germany and the information somebody in California is recording mean the same thing. And the data are organized in a consistent way. And that's what enables our Beeline platform, our ability to report out transparently to sponsors about what's happening in quasi real time with their study.
So I think a data view, a data framework, which is not to say that medical expertise and therapy area depth are not important, they definitely are, but I think everybody knows that part. And the thing that maybe folks are not as that's contrarian in our view, is to think of it primarily as we're in the data in the quality auditable data game, as it were.
[00:25:26] Speaker B: Yeah, well said. All right, how about this? What's one thing that biotechs get wrong about patients?
[00:25:33] Speaker C: Okay, not all biotechs get this wrong. I'm sure, I'm sure many would disagree with this point. But I do think that some biotech companies tend to view patients as data points rather than as partners in a development process or as dare I say it, human beings. And this shows up sometimes with, in the form of protocols that we think are unnecessarily complex and a high patient burden.
And so one of the things that we're often trying to do is make suggestions that will not undermine the integrity of the protocol, but will reduce the demand on the patient. I also really admire biotech companies that build relationships with patient advocacy organizations and in the community. It's especially common in rare disease and in rare cancer. But we do see it in other places. And if you're listening and you run a biotech company and you're in one of those spaces and you're not talking to patients, we would encourage you to do so.
[00:26:30] Speaker B: That's right. Well, and you don't want an unrecruitable protocol. Let's make them recruitable. Yes, indeed. Yes.
[00:26:37] Speaker C: And, and we see a lot of those, don't we? That, that and sometimes from highly credentialed CMOs who have not run commercial trials. They may have run an academic trial before or been involved in something. They may not have structured something on their own.
And there is good advice out there from, from Biro and from other places that can help you to sort of, you know, optimize your, your trial for execution. And that includes the ability to recruit.
[00:27:05] Speaker B: Yeah.
All right, what about an overrated trend right now?
[00:27:09] Speaker C: I think the most overrated trend right now is clearly AI press releases. There is, there is a sense that every CEO feels like they need to say they're doing something with AI. And some of them are. There's. There was a really funny cartoon I saw. I don't. It was a New Yorker style cartoon. I don't remember if it was from the New Yorker. And it had a group of men, all men, and it said CEOs. And they were like raising their arms and chanting and they were saying, what do we want? And then the next one said AI. And then they said, why do we want it? And they said, we don't know.
There definitely is still some of that. So we're separating the, the wheat from the chaff on the AI. Stuff that people are doing is.
Yeah, there's, there's a lot of chaff out there.
[00:27:57] Speaker B: There's a lot of hype and a
[00:27:58] Speaker A: lot, A lot of reality.
[00:27:59] Speaker B: Yeah, indeed. All right, well then on the flip side, what's an underrated trend that you're seeing?
[00:28:04] Speaker C: So I think the underrated trend are practical AI implementation. So we are seeing lots of people providing existence examples of point solutions of things they are Automating that used to be done in a more cumbersome way. And we see it in clinical research, especially in the data management world and in medical writing, but you see this all over the place. So I think that's maybe the hack there is to look for. The.
It's less the press release of a stand back, we've added AI to our thing and it's more the case study on hey, here's something I did that worked that automated and made faster or more accurate or less expensive. Something that we used to do manually.
[00:28:48] Speaker B: Yeah. The real impact. Right. That's the thing we're missing is the impact.
[00:28:51] Speaker C: That's right.
[00:28:52] Speaker B: All right, so what do you read that has nothing to do with biotech?
[00:28:57] Speaker C: So I read a lot of fiction and I made a concerted decision a couple of years ago when on a day when I was feeling overwhelmed by the news, dial down. I still read the news. It's not that I don't do it at all, but a bunch of time that I used to allocate towards.
I don't know if it was sometimes doom scrolling. I guess doom scrolling is probably accurate enough.
I have given over to or even just reading long articles about the end of the world, you kind of get.
You're spoiled for choice with options about whether situation or AI or whatever it might be.
So I read a lot of fiction and I range pretty broadly, but I grew up reading a lot of science fiction and I'm back to reading science fiction again.
I read, I'd say detective novels are my place and. Yeah, so lots of fiction and follow
[00:29:53] Speaker B: up question, do you read it in a visual way or do you audiobook it?
[00:29:58] Speaker C: That's a good question too. So I do both.
[00:30:00] Speaker B: Okay.
What's the differentiation?
[00:30:02] Speaker C: Yeah, well, it's an interesting question. Sometimes it's. I will listen to books that are nonfiction that are like, you know, how to books on something. I do some of that.
Or if I, honestly if I hear that if it's a narrator that I think is going to be a really good narrator, I will, then it's really fun to listen to. So I just, I, I just listened to Get Shorty, which is an old Elmore Leonard novel that I read a long time ago. But I listened to it and I'm now blanking on. It's an actor, great actor who does
[00:30:35] Speaker B: the, the voice acting. Yeah. Oh, neat.
[00:30:39] Speaker C: And that's. I love him and I love that, that style. So that's really fun. And then I read, I read on my Kindle, you know, and I physically read. That's the, that's also going on any
[00:30:50] Speaker B: given day, all, all versions, which is great.
All right, here's one that I, I always love this question. Who's an industry leader you would most want to have a beer with?
[00:31:01] Speaker C: Yeah. Okay.
So the truth is I have had beers with a whole bunch of guests on the podcast.
I would have to guess we're at roughly 10 to 15%. 10% probably I've had a beer or coffee with.
And there's another 30% that I would love to do that with. So if you're listening and you've been, again, assuming we're in that group.
[00:31:26] Speaker B: That's right.
[00:31:28] Speaker C: I, you know, I just saw Mike Tolentino, who's a past guest on the podcast. He was in Miami.
And, you know, and I very much enjoy conversations with other, other folks that we've had.
So we're spoiled for choice there because it's such a great, great subset of humans. The people who go out and do this, both the start the company type people and the deep thinker types are a joy to spend time with. So tough to narrow it down.
[00:31:59] Speaker B: I would say you're doing great on the lightning round. A couple more questions before we wrap up. So what's a recent thing that has genuinely surprised you in this industry?
[00:32:11] Speaker C: Great question.
I think that if you asked me two years ago how quickly AI would go from conceptual to something real that we were using, that I was using on a day to day basis, I would not have expected it to have happened as fast as it has.
It has not surprised the people who are paying attention and we're working in those frontier labs, they were saying this is what's going to happen two years ago.
And in fact, when we had Zach Kohane on, I asked him to score himself on his predictions that he made bravely a couple of years ago and his held up pretty well. He's a tough grader on himself, so I think he gave himself a half score a couple of times, but he held up pretty well because he was really paying attention to the straight line inference that you could draw from where we were then to where he expected we were going to go. And so the, the, the challenging thing there for all of us is to try to do that, to try to look in a clear eyed way at what's coming.
And it can be daunting because it's changing really fast. It's easy to sort of just try and look in another direction.
So that's what has surprised me the most. And I want to again, I'm really, I'm really shilling for Jack, for Zach here, but he said, I think we put this up in the, in the teaser. He expects more change in the next six months than we've seen in the past three years. And he added, we've seen more in the last three years than in the previous 20 in AI. And I, I think, I think so that has surprised me. I guess now I'm expecting to continue to be surprised.
[00:33:53] Speaker A: Right. Yeah.
[00:33:54] Speaker B: Oh, goodness. All right, last question.
And this is a more general one, not necessarily podcast oriented, but I get to say this with my bio. Rossi, hat on. What do you want people to say about your tenure here?
[00:34:08] Speaker C: So I hope that I think what we all want when we leave a place and let me not duck it, I will say what I want is I want to leave a place better than I found it.
And so I hope that people will believe that they, that that has been true with the podcast and with Barossi more broadly. It's been a joy to be. Both have been a joy. They've had their ups and their downs and their challenges and their good days.
But I've had an opportunity to work with you and a whole bunch of other just spectacular humans at Biorossi.
And so I hope people carry away a sense that we have gotten better together.
And yeah. That I've played a role in that for them. That would be my hope.
[00:34:58] Speaker B: Well, I think I can concur with that. Your hope will be rewarded with the feedback that our team has for you and we wish you all the best. We know you won't be far, but with the reflection on the last number of years and what you've built in this organization, you're leaving a very strong legacy. And we've got the physical evidence of it here with few and far Between. It's an honor for me to carry this forward. Perhaps we'll have to check in with you as a future guest again on the topics that are exciting in your world because, you know.
[00:35:27] Speaker C: Yeah, that'd be great. Yeah, it'll confidence in your leadership for the company and that the pod is going to continue to be a lot of fun. So indeed, I'm looking forward to being a listener.
[00:35:38] Speaker B: Wonderful. Thank you, Chris.
[00:35:40] Speaker C: Thanks, Melissa.
[00:35:42] Speaker D: Hi, Melissa, Congratulations on your appointment to president and host of Few and Far Between. Welcome to the podcast.
[00:35:50] Speaker A: Thank you. I'm so delighted. It's an exciting time for us.
[00:35:53] Speaker D: Yes. Very, very much so. So I'll start with that. So you're in the envious position of being the new leader of Bio Rossi and being the new host of the pod. It brings up an underlying theme that we've had in our 70 plus episodes.
Where you are now and where you're going. And so I wanted to ask you, how do you determine what to keep and what to innovate?
[00:36:16] Speaker A: And that's always the tension, right? Because there's so much that's valid in both of those.
To me, it's about what principles guide me and the things that are important for me. Integrity, client, first thinking, and certainly intellectual curiosity, which so many of these conversations feature.
But the willingness to tell the truth, even when it's uncomfortable. And I've seen that theme played out at Biorazi and with few and far between, those are absolute keepers across the board. I think from the opportunity to change, I look at that from an innovation perspective. So there are ways that we can deliver those principles that we will continue innovating. How we use data, how we use AI, a very common and ever present conversation now.
How we can make faster those decisions that translate to clinical trial success and ultimately the ownership around how accountability is defined. That's always room for innovation and new ways of working.
So that's how I divide those two out from my perspective.
[00:37:17] Speaker D: Very cool.
So let's talk about Chris a sec.
As the previous host, he's not here so we can talk about him.
Chris has evolved the podcast from very much a rare disease focus to one that provides more of a behind the scenes view of evolution in biotech and now AI in biotech. Is there a topic in the industry that's very important to you?
[00:37:46] Speaker A: Well, that is one of the biggest right now. Certainly AI data and the innovation that brings these tools into drug development are critical topics. And having expertise and the curiosity, as I mentioned before, to dig into these will be an important thing. But to me, it's also the practical truth of these things over the hype, especially when we are looking at that important intersection of biotech, advancing the data and execution that's needed for it.
My goal for us here is that founders and operators and scientists will walk away thinking that was honest, that was useful and applicable, and hopefully not overwhelmed.
[00:38:24] Speaker D: No, and that's an excellent point. You know, in, in what we're doing and trying to get that information out and hopefully, and in most cases I think this happens, is making sure that biotech leaders or people who are interested in getting into this market get kind of a taste of what it's like to be a CEO, to bring a product in for drug development stuff. Like that.
[00:38:48] Speaker B: Indeed.
[00:38:50] Speaker D: So I did want to touch on something that Chris mentioned about the myth of CROs and what they do.
So he was very clear about saying that what CROs really are in most situations are data companies.
And so I wanted to find out what your thoughts are on data sciences as a core competency for a company as well as something that you know as part of the main thing, but also as maybe a standalone solution as well.
[00:39:25] Speaker A: Well, and that's certainly a place where we have a lot of experience is in evaluating where you go from standalone to perhaps a more full end to end relationship around the data science for a program.
But I completely agree with Chris in terms of the myth around a CRO, and I think there's a similar one around the data science component specifically. It is absolutely a core competency when you're in the clinical trial services business. But data needs context. It also needs ownership. And I think the operational integration that we often see is the place where there's friction or drift or flowing is the space where we seek to continue to improve. The magic that I get to see happen is when the data science aspect is embedded into trial design, into trial monitoring, into the adaptations, and not treated as just a downstream activity toward the end of a program.
There's a lot of value in standalone, of course, but long term impact, I think fundamentally comes from that integration when we've partnered in execution and we don't just have the analyst only role.
Excellent.
[00:40:35] Speaker D: So, last question. Put you putting you on the spot.
I've been doing marketing in different roles for about 25 years and I've seen my share of leaders.
So one of the things obviously is that Chris has made a big impact on the roles of so many people at Bio Rossi.
And coming in new to a company can sometimes be a little difficult. But how do you fill that role for Biorazi team members and stakeholders?
And what does that entail for yourself, but also the company?
[00:41:11] Speaker A: Sure. Well, and this is also a theme that Winifred between has tested throughout the many conversations. I don't believe you replace a leader, but you extend their impact and you do it in a new way through the authenticity of who I am. It will be new, but it's not to say there needs to be corrective or drastic change. It's about continuing to focus on impact. And one of the last conversations that Chris and I had before he officially exited his role as CEO, I said to him, we will make you proud. I know you've spent a lot of energy and time and investment in this organization's journey, and we're taking that forward. And my goal is to make you proud, Chris. That's a big, important part of my value system.
And to me, what I talk about with internally here and I'm sure is not unique. To me as a leader, it's how we show up, what we do consistently that translates. And as long as you have clarity about where we're going and we're honest about what it takes to get there, that journey is valid. And it's also energizing. And I've certainly seen a lot of energizing responses in Bayarazi.
My leadership style is very execution oriented. I like their ownership defined.
I'm not interested in heroics. I'd rather we do things in a systematic fashion so that we do great work without burning out. And I know that our team feels supported in that. Informed, trusted. These are important values. When those are in existence, I know that I'm doing my job for them and the stakeholders that are part of our ecosystem. So for a reflective moment, I would say that if there's a common thread across how I lead and how I have the opportunity to host this podcast, it's that it's honest conversations grounded in reality, in service of people who are trying to do difficult and meaningful work. And that's invigorating.
[00:43:07] Speaker D: Well said. Well said. All right, well, thank you, Melissa, and we'll be back with our next episode later this month.
[00:43:16] Speaker A: See you then.
