In this episode, I talk with Mat Davies from Jazz Pharmaceuticals about the powerful intersection of company culture and data-driven decision-making.

Have you ever wondered how a company’s culture can drive its success?

Or how aligning personal values with company values can lead to more fulfilling work?

Mat describes his unconventional career path from a middle school math teacher to leading the data science organization at Jazz. We explore how Jazz Pharmaceuticals cultivates a unique culture that prioritizes patients and employees, fueling both innovation and collaboration.

Our discussion highlights the challenges and benefits of unifying quantitative teams and the importance of aligning company values with personal values to create a fulfilling and impactful work environment.

Tune in to learn how Jazz’s culture-first approach shapes their strategies and decisions, benefiting patients and driving the company’s success.

Key points:

  • Unconventional Career Path
  • Company Culture
  • Patient and Employee Focus
  • Harmonizing Quantitative Teams
  • Bayesian Statistics and Innovative Designs
  • Speed and Agility
  • Internal vs. External Innovations
  • Psychological Safety
  • Change Management
  • External Partnerships
  • Decision-Making Processes
  • Patient-Centered Outcomes

This episode provides invaluable insights into the powerful role of company culture in driving innovation and making data-driven decisions. Mat’s experiences and strategies offer a blueprint for creating a fulfilling and impactful work environment.

If you found this discussion enlightening, share this episode with friends and colleagues who can benefit from these insights, and help spread the word about the importance of a culture-first approach in the workplace. Tune in, get inspired, and be part of the conversation on how to make our work environments more innovative and patient-focused.

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Mat Davies

VP, Data Science at Jazz Pharmaceuticals

Mat Davis, PhD, vice president and head of data science, presented at the 2023 STAT Summit where he shared a key moment in his career when he learned the necessity of breaking down silos to fully embrace the value of data science across R&D organizations. As the use of data continues to increase and evolve, as well as the potential of multiple sources of data to inform development and regulatory pathways – including real world evidence, clinical trials and model informed drug development – the need for integrated data science is even more important today. Jazz is taking a unique approach to data science with interconnected data scientist teams who have broad exposure to our quantitative disciplines that can approach the three avenues together, rather than apart.


From Company Culture To Data Driven Decisions

[00:00:00] Alexander: Welcome to another episode of The Effective Statistician and today I’m super happy to talk with [00:00:10] Matt Davies from Jazz Pharmaceuticals. When I first learned about Jazz Pharmaceuticals, I thought about Jess, that’s an [00:00:20] interesting name for a pharma company, but we’ll touch base on that a little bit later.

[00:00:26] Alexander: So first over to you, Matt, maybe you can introduce [00:00:30] yourself to the listener. 

[00:00:32] Mat: Absolutely, Alexander. Thank you so much for having me. It’s an, it’s an honor to be here. So I’m excited to be able to talk to you. My name is Matt. I run the data science organization [00:00:40] here at Jazz Pharmaceuticals. I’ve had kind of an interesting career journey to get here.

[00:00:44] Mat: I actually started off my career as a middle school math teacher, so I used to teach 7th, [00:00:50] 8th and 9th grade. So 12 through 14 year olds were my, were my sweet spot and did that for a couple of years, decided that I wanted to leave and get into the pharmaceutical industry because I was getting my [00:01:00] master’s in applied statistics at the time, ended up working at a CRO for about seven years.

[00:01:05] Mat: When I realized how much I love this job, but I did not really enjoy the [00:01:10] consulting side of it. I preferred at the time to be on the pharma side. And the only way I knew how to do that was to go get my PhD. So I got my PhD in biostatistics from UPenn [00:01:20] at the same time as I worked full time. So I did school full time and worked full time, which was a nightmare.

[00:01:25] Mat: And while you see all this gray hair on my head, and I finished that up, I [00:01:30] got hired as an individual contributor at Teva Pharmaceuticals. And in a span of a number of years went from a statistician to a therapeutic area head, to the head of [00:01:40] statistics, to the head of biometrics at Teva, before leaving there to join a small company called GW Pharmaceuticals.

[00:01:46] Mat: GW was acquired by Jazz and I was named as the head of biometrics [00:01:50] at Jazz about three years ago, and then became the head of data science now. And just because data science means statistics, different things to different people. We’re responsible for [00:02:00] bioinformatics, clinical statistics, statistical programming, medical affairs and value statistics, real world evidence, and pharmacoepidemiology.

[00:02:06] Mat: So that’s the background and that’s the team. 

[00:02:09] Alexander: [00:02:10] That is pretty awesome that you have all these quantitative scientists all together. Which in many other companies Work quite [00:02:20] isolated from each other and sometimes more against each other than rather than together. 

[00:02:26] Mat: I would share that’s one of the hardest parts that I’ve noticed even in previous jobs [00:02:30] is when you have so many quantitative individuals that aren’t actually working together.

[00:02:34] Mat: It’s actually a huge deal. Disaster and nightmare. You might have two or three different quantitative groups [00:02:40] working on the exact same problem, but they do using different definitions, and they all get an answer that’s conflicting. And then nobody knows who to believe. And it’s not very efficient. So we’re trying to solve [00:02:50] that by harmonizing them under one shot.

[00:02:52] Alexander: Yeah, I’ve seen that before and where, whereas in kind of the different departments had kind of [00:03:00] fight each other, says that well my message is wrong and is right and your is wrong, and you should only believe me, but not these guys over there. And which of course [00:03:10] kind of doesn’t help anybody. Yeah.

[00:03:14] Alexander: So that is actually very closely related to the topic that we want to talk about [00:03:20] today. I recently stepped over an article on LinkedIn that you also highlighted. It is a Forbes article by your CEO [00:03:30] about jazz culture. And I read it was A lot of interest because there’s a lot of [00:03:40] talking about culture and trading culture.

[00:03:43] Alexander: And in the end, very often culture is a product of decades of [00:03:50] hiring, firing and all kinds of other decisions that happen within the company. And for Jess, that’s a little bit different. Can you [00:04:00] tell us a little bit about how Jess. Got its culture. And why is that so important for the company?

[00:04:07] Mat: Yeah. So I’ll start by saying, you [00:04:10] know I respected him. I, or Bruce Cozette, our CEO very much. He says that he started this company based on culture, that he wanted to have a company that was culture first, [00:04:20] and he is a man that has lived up to that. Aspiration. I’ve gotten a chance to observe him publicly and privately and can tell you that this is a man that walks that walk, [00:04:30] which I’ve seen other people that can’t and he and he can and it permeates itself through all of the organization.

[00:04:35] Mat: I’ll just give an example of how that I mean, the Forbes article kind [00:04:40] walks through a number of the things that he thinks are important in the culture, which admittedly is putting patients first. Our purpose is to innovate, to transform the lives of patients and [00:04:50] their families. I’ve memorized that because it’s central to everything that we do, but they also talk about wanting to make jazz the best experience of the career of every jazzician, which [00:05:00] is what we affectionately refer to as anyone that works at jazz.

[00:05:04] Mat: But there was actually a story a couple of years ago. I actually applied for a job at Jazz before [00:05:10] my career led me here. And in the application process, they sent another article that Bruce had written for another magazine a couple of years ago. And it outlined his [00:05:20] expectations in the culture and basically right up front, they said, if your values don’t align with this publication, this probably isn’t the job for you.

[00:05:28] Mat: Because we’re a culture first [00:05:30] company. And I was blown away by that, especially walking out of a culture that I didn’t love to say that it was culture first was just transformative in terms of how I thought of a workplace. [00:05:40] 

[00:05:40] Alexander: Yeah. And I think it’s really, really interesting to have both the the employee focus and the patient focused on it.

[00:05:48] Alexander: Most [00:05:50] companies, especially the bigger ones focus first on the shareholders. Yep. And talk mostly about them. Of course, they also talk [00:06:00] about the, the patients. But when push comes to shoals, it’s usually let’s sell our drugs. That’s right. 

[00:06:09] Alexander: [00:06:10] And so What really kind of stood out for me is that he was, for example, speaking about the the role of the sales [00:06:20] representatives and said their role is predominantly to be educators and help the physicians.

[00:06:29] Alexander: They [00:06:30] support the HCPs. It’s a kind of typical pharma abbreviation to make the right decisions, not to just, you know, [00:06:40] prescribe our drug. And I think this is really very much aligned with what my vision is to provide [00:06:50] the right evidence at the right time to make the right decision. And how is that reflected with Your organization said supports [00:07:00] also data for, for that.

[00:07:03] Mat: Yeah. Well, I think that it’s kind of like the shining beacon that we all work towards. [00:07:10] Right. And it’s a filter that we view every problem that we come against as what is best for the patient at the end of the day. And as data scientists, [00:07:20] statisticians, programmers. The whole umbrella. I think we’re faced with a lot of those problems often, especially if you’re on the more medical affairs value side [00:07:30] of things, because you know that when you’re trying to present data, you’re trying to interpret a clinical trial.

[00:07:35] Mat: You can interpret it through a lot of different lenses. You can interpret it through the lens of what’s best for the [00:07:40] company, what’s best for yourself, what’s best for the product, or what’s best for patients. And you can tell different stories based on that. And we live this [00:07:50] mantra right up front that says we do what’s best for the patients.

[00:07:52] Mat: And if that means that we interpret a post hoc analysis or a clinical trial readout or real world evidence study as [00:08:00] not being favorable to us, but it’s very informative to the patient, that’s really important for us to strongly consider because it’s patient first. So [00:08:10] it, And I’d say the other side of that, maybe sometimes, you know, that there’s always a temptation for us as data scientists to put that little spin or just [00:08:20] that little extra piece of the analysis that would make it more favorable to us to get that e value under 0.

[00:08:26] Mat: 05, for example, when we know that’s not the best way to do it. We don’t do [00:08:30] that. Because it’s not what’s best for the patients. And so I think at least as much as we can try to do that, it really makes us live. Just view all of our data [00:08:40] outputs and communication about our data as being patient focused first.

[00:08:45] Alexander: That’s a pretty cool thing about it because [00:08:50] I know that lots of, lots of people, especially statisticians in that space very much love that perspective yet still [00:09:00] struggle very often to, you know, Fight against company, internal culture. Although of course the official policies always say that [00:09:10] your, our publications are well balanced and so on.

[00:09:14] Alexander: Yeah. So speaking about it and doing it. Are two very, very different [00:09:20] things. So how does that kind of materialize in the everyday doing? Can you give an example? 

[00:09:28] Mat: So, so a couple of [00:09:30] things, I mean, the biggest example I can give is Not that I can give a whole lot of specifics about it, but being in higher level governance situations where you’re discussing [00:09:40] one of these different outputs and there’s a lot of opinions around the table on what we should and what we should do with it.

[00:09:46] Mat: And then having the voice of Bruce or somebody else that steps up and says, [00:09:50] Hey, everyone, We are here to do what’s right for the patients first. So how do we make this decision in terms of what’s right for the patients first? And I think [00:10:00] that’s what’s so unique here. It’s as soon as that sentiment comes out as we’re debating on what to do with this, it kind of reshapes everyone’s [00:10:10] focus.

[00:10:10] Mat: And I think Because we all believe this so much in our hearts, you know, sometimes even if your head isn’t in the right space while you’re making that decision, as soon as [00:10:20] someone says that, you’re like, right, of course, patient first, let’s focus on patient first. And I think it’s just the common vocabulary, vernacular, and also shared [00:10:30] values that say that that’s where we, that should be the guiding light for our decision making process. So that’s just one way that I see it. 

[00:10:37] Alexander: Yeah, I think that is actually a very, very [00:10:40] powerful way. If people always speak up when things don’t go along with this culture, and they are acknowledged, and [00:10:50] then everybody appreciates it, and comes back on the ship. That is really, really important. Yeah, that actually I think makes a big difference.

[00:10:59] Alexander: Yeah, [00:11:00] because there’s always going to be someone that, you know, violates goes off, off track, you know, comes from another company, doesn’t know the culture [00:11:10] yet has been measured differently. 

[00:11:12] Mat: Yeah, and it’s also interesting when that happens. I think the other way that you can determine how well a company is doing with this is what happens in those situations, [00:11:20] right?

[00:11:20] Mat: Is it just swept under the rug? It’s like, oh, that’s just how this person operates. Or, or is there something really done about it? Do people really care? Does compliance step in? Are there [00:11:30] other ways that happens? And it’s like the other side of that coin. It’s so when invariably, There’s a bad actor or something like that happens.

[00:11:37] Mat: What does the company do to help fix that [00:11:40] culture? And I think that speaks volumes on the other side as well, because we all know that’s going to happen at some point. 

[00:11:45] Alexander: Yeah. And I think the, you know, unfortunately we all have [00:11:50] these kind of compliance departments but the more you don’t need them.

[00:11:55] Alexander: Yeah. That’s right. Yeah. So it’s kind of, if. [00:12:00] People within the teams directly correct it and don’t kind of call the compliance number anonymously. That is a much, much better [00:12:10] way and more powerful way to, to correct it. 

[00:12:13] Mat: Yeah, because if you really think about what that means from a cultural perspective, I mean, we want to build a cultural culture where people [00:12:20] feel safe to speak up, that they have the right relationships, that they have the autonomy within their teams to be able to solve their problems and self correct, so to speak.

[00:12:28] Mat: And when you have team members [00:12:30] that respect each other enough to do that with one another, there’s not a whole lot of compliance phone calls in that case, because you’re actually able to solve it. Person to person and be more autonomous to be [00:12:40] successful, which is, which is some of the things that we strive to do.

[00:12:43] Alexander: Yeah. And I think that is a great fundamental thing for you to also have a [00:12:50] place where people strive. Psychological safety is so important for all the different things that we do. Yeah. To speak up when there [00:13:00] is a weird signal and the safety data or when there’s a. Certain parts of the population that look like they get more harmed and then [00:13:10] benefit from being struck or all these kinds of different things.

[00:13:13] Alexander: So there’s conflicting data, yeah, that people can bring that up irrespective of where [00:13:20] they come from and so on. That makes a huge difference. 

[00:13:23] Mat: Absolutely. There’s something that I learned when I was teaching that I use a lot as I think about setting [00:13:30] the culture and leadership and everything, at least what we try to do for our team.

[00:13:33] Mat: And that’s Maslow’s hierarchy of needs. I don’t know if you ever heard of this, but, you know, that concept [00:13:40] of, you know, If for anyone that isn’t familiar with this that’s a gentleman in Maslow that put this out as terms of like, what do you need for somebody to actually be their best self? And we used it in [00:13:50] teaching when you have a child that wasn’t performing at their best.

[00:13:52] Mat: It was like, why wouldn’t they be performing at their best? And the very lowest level of the hierarchy of needs is your physical logical leads like Okay. [00:14:00] You can’t expect a child to do well on a math test if they don’t have somewhere to sleep at night, or if they don’t have somewhere to eat. Like, that’s not a fair thing for them to expect.

[00:14:09] Mat: I think the same thing [00:14:10] happens at work. I mean, you’ve got the physiological needs, which many of our people have that are covered just due to the nature of the industry we work in. But then you build off of that [00:14:20] safety needs, which is where that psychological safety comes in. Right. It’s like, I don’t feel safe to be able to speak up or talk to another employee or be able to work something out within my team.

[00:14:29] Mat: I’m [00:14:30] never going to be successful and be innovative and speak up about the safety signal. And then you build on that love and belonging and then esteem. And then at the very top [00:14:40] after safety, love, belonging, esteem is the ability to innovate. And that’s it. You can never expect people to truly innovate unless you’re [00:14:50] building the whole pyramid up, right?

[00:14:51] Mat: And so that’s where, like you mentioned, trying to really be intentional about how we’re building the culture by making people feel cared for, supported, [00:15:00] belonging, that they have all the tools they need to have the support from us as management. Now you go and change the world. And I think that’s how we really can build a culture that [00:15:10] supports this purpose of innovating.

[00:15:12] Alexander: Yeah, innovation is also mentioned quite a lot in this Forbes article, and your [00:15:20] CEO speaks about taking risks and learning quickly from failure so that you can. Move forward and have success. [00:15:30] How does that work within your organization? When it comes to learning from failure, learning from data, learning from from evidence, [00:15:40] how does that, you know, help you to make better decisions about your pipeline?

[00:15:48] Mat: So one of the things I [00:15:50] love about jazz is the size of the company it is. I think at this point jazz is somewhere between 3, 000 and 3, 500 employees and it’s, it’s well funded. So I think the [00:16:00] good, the good part about that is that we have. The ability and the resources to do a lot of exciting things, but it’s not so big that it’s this huge ship that we have to be [00:16:10] able to steer.

[00:16:10] Mat: So I think one of the ways that we do that is by maintaining agility, not only in our programs, but in all of the different ways that we work. So, for [00:16:20] example, you know, there’s this concept of double blind sponsor open studies. I don’t know how familiar we are with those, but it’s where we try to keep a blinding at the site.[00:16:30] 

[00:16:30] Mat: And the investigator. But then we at jazz keep a number of internal people unblinded to it, like in a phase one or a phase two, a study. So we might be able to look at the [00:16:40] data more often and make a decision about where we want to go. And other companies that concept might take. Years to be able to come up and running and how do we get that straightened out at [00:16:50] jazz?

[00:16:50] Mat: I think it took us about two months to be able to say yes that fits right in with what we want to do We want to make these decisions as we go. Let’s let’s make it happen So I think [00:17:00] that it’s a company that just maintains agility at its core to look at data on an ongoing basis in Obviously scientifically rigorous compliant ways, but [00:17:10] that is not afraid to pivot from a strategy when it makes the most sense for the compound.

[00:17:15] Alexander: Agility for you means making decisions fast, [00:17:20] sticking to it, and then reevaluating as you get more data. 

[00:17:25] Mat: Yeah, I think, I think the biggest focus is the speed of, of the [00:17:30] speed of data and the speed of decision making. The sticking to the decisions is key. is always something that we’re continuing to grow in.

[00:17:38] Mat: But I think definitely the speed [00:17:40] and how we make the decisions is really important, which lets us to use to not only progress our compounds the fastest, but also allocate our resources to different things. Because obviously [00:17:50] we’re not You know what? We have a lot of resources. They’re not infinite. So in some cases, a decision on one program means that we have to shift our resources toward a completely different program.

[00:17:59] Mat: [00:18:00] That’s something we’re doing well now and able to shift things across as needed, and the only way to do it is through these more rapid decision making processes that the data scientists [00:18:10] actually are leaned on quite heavily to make sure it has that rigor and has the right information that’s interpreted correctly so we can make those larger portfolio decisions.

[00:18:19] Alexander: So [00:18:20] that’s really interesting what I know from lots of other companies said to make a decision. You usually [00:18:30] go through many different layers of governance. Yeah. How does that work at Chess? 

[00:18:36] Mat: We have two layers of governance. So [00:18:40] that that’s your answer. So we have a layer of governance that focuses more on the on the portfolio level of governance in terms of what are the [00:18:50] large decisions that we need to make for this compound.

[00:18:52] Mat: Think how should we spend 50 million or a hundred million on this compound? Should we go after, you know, This large indication or a smaller [00:19:00] indication. So a governance level that hinders that piece and then a governance level that’s more tactical, more clinical development, R& D focused governance level of [00:19:10] how much money should we spend on each project?

[00:19:12] Mat: Should this project move forward? Is option A better than option B? If we stopped this product, where would we move that money [00:19:20] towards? And those are your two governance levels that, that would monitor those types of 

[00:19:24] Alexander: Okay, that’s pretty cool. So when you make these [00:19:30] decisions of course you have your internal compounds, but of course externally also a lot happens.

[00:19:37] Alexander: And in the, your CEO [00:19:40] talks about, well, you want to move forward with the best Molecule for the patients. So what do you do if you have a, if you see that there’s [00:19:50] an external molecule that’s actually much better than yours? 

[00:19:54] Mat: Yeah, and that’s, that is something we evaluate often, not only from a patient benefit perspective, but [00:20:00] also from a commercial perspective.

[00:20:01] Mat: I think one of the things that’s important to remember is that when you’re early in clinical development, just because something looks better than your molecule, doesn’t mean that it [00:20:10] actually is better than your molecule, right? So, I think there’s, I think there’s that element to it. But even if you have a molecule that makes it out to market that, [00:20:20] that might not be as good as another one in some area, a lot of times it might be better in some other area, like maybe it’s not as efficacious, but we have a more convenient dosing schedule, or maybe [00:20:30] it’s picked up by more.

[00:20:31] Mat: Providers. So more patients have access to it, or maybe we’re approved in a different country than the other ones not approved in. So I think it’s hard to [00:20:40] say that you ever have a molecule that is just flat out worse than another molecule. It’s usually the benefits and trade offs of what this means to individual patients and making sure that we can [00:20:50] confidently say for some element of this molecule that there’s real patient benefit to this.

[00:20:55] Alexander: Yeah. Yeah. And that’s a very, very important point. What is a [00:21:00] patient benefit very often depends on the preferences the patients have. And of course, also the choices the patient has.

[00:21:08] Mat: It really does, doesn’t it? And [00:21:10] those, and those aren’t always the easiest to quantify. You know, I think that’s where the whole realm of like patient centered outcomes and patient focused drug development is moving towards is [00:21:20] what we think or what the prescribers think or what the payers think is important about this specific disease to cure might not be the same as what the patients [00:21:30] actually think.

[00:21:30] Mat: And sometimes you get a patient involved and they think very differently. Hey, you know, yeah, you’re focusing on caregiver impression scales and PROs, but [00:21:40] all I want to be able to do is eat my breakfast. You know, like that level of thing or get dressed in the morning. So I think it’s so important that we keep the holistic [00:21:50] perspective of what the patients really need and make sure that we’re actually addressing those areas.

[00:21:55] Alexander: So if you compare internal to external [00:22:00] innovations how do you do that actually from a technical point of view? 

[00:22:04] Mat: From a, from a data science perspective? 

[00:22:06] Alexander: Yeah. 

[00:22:07] Mat: Yeah. So this is again, I think is [00:22:10] if we’re staying on the focus of culture and innovation, this is something that I’m really proud of our team for.

[00:22:15] Mat: And so I’m going to take a minute to brag about the group. Our [00:22:20] team’s awesome. And I’m so proud of everybody in our team, but we, we have a group of people that really do care for and respect each other. And I think that, so [00:22:30] we’re talking about that kind of pyramid of, of needs, I think for most people, not everyone.

[00:22:34] Mat: And I’m sure I was thinking about this lining up to the podcast. Like I’m sure someone’s going to listen to this and say like, [00:22:40] that was not my experience at all. And that happens with some people, but we try. So we try to build that layer of. Respect and care and [00:22:50] belonging for individuals. But then when it comes to the innovation element, you know, one of the things that we pushed really hard from the stats perspective a couple years ago was making sure that everybody [00:23:00] was at minimum conversant with Bayesian statistics, right?

[00:23:03] Mat: Yeah, you you have to be able to at least talk about it and know it. But then I created a complex, innovative drug [00:23:10] development course or complex innovative design course that I got a chance to walk everybody in our team through not only Bayesian statistics, but the most cutting edge, like master [00:23:20] protocols and like biomarker driven drug development and things, and we actually got invited to the complex innovative design program from the FDA and got to participate in [00:23:30] that, which was really exciting.

[00:23:31] Mat: But the innovation comes now is that now that’s part of the culture. So now everybody is expected to not only do this, but our clinical [00:23:40] development teams are now expecting that of us. So it just kind of happens naturally that you start talking to people about it and you teach them it and they get it and then they practice it and then they can do it.[00:23:50] 

[00:23:50] Mat: But the way I like to do things like that is also combine it with the right partners externally that are the experts in this. So if you have a consultant that [00:24:00] is an expert in complex innovative study design, for example, we partner with them to do a couple of projects with the hopes that those statisticians that are partnering with them can then [00:24:10] eventually do it on their own.

[00:24:11] Mat: I think the answer to your question is we expect our people to do this, but we teach them how to do it, right? So you don’t have [00:24:20] to do it on day one, but maybe by six months that you’ll, that you’ll know enough, you’ll have the right money, you’ll have the right partner to do it. And then you can really take off from there to do it [00:24:30] on your own.

[00:24:31] Alexander: I love. The way how you kind of introduced it by teaching it to your colleagues by getting the external support [00:24:40] with the FDA and all these kinds of different things. This is exactly what I talk about when I speak about change management. Yeah. You need to have [00:24:50] resources that the regulators are on top of it, that they agree with it.

[00:24:55] Alexander: You need to make sure that the people that you talk to actually understand [00:25:00] what you talk about. And you can’t just think, well, they have a MD or they have a, you know, a high degree. No, you know, [00:25:10] all these things that are, you know, not even standard for statisticians definitely are not standard for the non statisticians.

[00:25:18] Alexander: And so if they see [00:25:20] something new, they will not believe you if you don’t explain it to them. 

[00:25:24] Mat: No, they don’t. And I think that’s, you know, when we, we’ve, we struggle, I think just as much as [00:25:30] anybody else does, even with our great culture of getting the right seat at the table and being included in the right decisions.

[00:25:35] Mat: And that’s something I know a lot of groups struggle with. We struggle with that too. But I do tell the team [00:25:40] members, like when you can do something that your partners cannot do, and they know they can’t do it, just watch how fast it takes off, especially if it has a real benefit to them. When [00:25:50] you talk about a Bayesian study design, where you’re doing an interim every month.

[00:25:54] Mat: For example, your part there. Your first clinical development lead will look at you and say, that’s actually not possible [00:26:00] and you’re like, I know it is possible, but let me walk you through it. And then the next time you work together, they’re the first ones that come to you and says, Hey, we need one of those Bayesian designs like [00:26:10] now, because otherwise we’re not going to be successful.

[00:26:12] Mat: It becomes the norm. And it’s amazing when you show something they feel like they can’t do. All of a sudden, it just catapults your status within the company, [00:26:20] your ability to be influential. Thank you. 

[00:26:21] Alexander: Yeah. Yeah. And you talked about it, you explained it in their benefits. Right. So that is a [00:26:30] really big part. It’s not about, Oh, I want to do this fancy statistics and I want to kind of stand out and have, you know, present at that conference about [00:26:40] all the cool things that I did.

[00:26:41] Alexander: That is not convincing to your regulatory or your clinical counterpart. They want to know, will the FDA like [00:26:50] it? Is it possible? Has it been done before? Can I trust you? Can I actually understand it or will I look stupid when I explain it to someone [00:27:00] else? 

[00:27:00] Mat: Great, you know, I think I was, I was listening to one of your recent podcasts on the open source transition from SAS to R or how those, how those relate.

[00:27:09] Mat: [00:27:10] And, you know, this fits right in with that concept as well. So we. Our programming team has started to develop a lot of shiny apps that are used for our, our [00:27:20] tables, listings, and figures. Actually, what my hope is, is that we kind of get away from TFLs altogether. And just use shiny apps because I prefer to look at figures than anything else.[00:27:30] 

[00:27:30] Mat: But it was amazing. If I told our clinical colleagues, Hey, we’re going to do this app and replace it with TFLs, they would have never bought into it until we showed them the app. And we’re like, okay. [00:27:40] Here you go. Here’s the app. Why don’t you guys go play around and look at all your information? And they’ve come back to us now and said, can we not have tables anymore?

[00:27:48] Mat: Can we just have the app? [00:27:50] And it’s amazing, but we had to show them the value. And again, it’s just what you said before is you have to show them. In whatever way you can, [00:28:00] what value this innovation is going to create, because once you convince them, you’ll never go back. It just flips them a hundred percent.

[00:28:07] Mat: So they know, yeah, you were right the whole [00:28:10] time. And it’s just amazing when you have the ability to be able to do things like that. But the hard part, just, you can’t let them drive it all the time either. Right. A lot [00:28:20] of times we know what’s best for these innovations and we have to push it a little bit.

[00:28:24] Mat: I don’t think any. Any clinical development leader, medical affairs lead would [00:28:30] ask us for a shiny app specifically that lets them explore subgroups. But when we give it to them, they say, thank you so much. It’s exactly what I’ve been looking for. So it’s just another area for us as [00:28:40] data scientists to lead holistically when we’re really that value innovation driven.

[00:28:44] Alexander: Absolutely. Well, they will not ask for anything that they don’t even know exists [00:28:50] or it’s possible. Yeah. So nobody asks Steve’s job to create the iPhone. Yeah. When there’s, there’s kind of this quote about Ford that [00:29:00] if he would have listened to customers, he would have made faster horses. Yeah.

[00:29:06] Alexander: But, but that’s not, that’s not the point. [00:29:10] Yeah. 

[00:29:10] Mat: Their, their idea of innovation was, you know, I know what you want, and I’m going to show you what you want. You don’t always need to ask yourself what you want. And it’s a tricky balance, I know, [00:29:20] but like you said with the iPhone perspective, like, here, let me show you what you’re going to love.

[00:29:24] Mat: And they did, and I think, I think as data science grows faster and faster, and we have more [00:29:30] capabilities, we’re probably going to be more in that second camp of, let me show you what you’re going to love, and you’re going to, going to really change your perspective on things. 

[00:29:37] Alexander: Yeah, and don’t [00:29:40] only rely on your internal knowledge.

[00:29:42] Alexander: Yeah, look for the external experts that you can bring in and help with it. Yeah, I think that is a [00:29:50] that’s another great feature of culture. So it’s kind of being humble that we don’t know everything. So there’s, [00:30:00] there’s other companies that have said if it’s not invented here then it’s not worth it.

[00:30:05] Alexander: Yeah. And that is a very, very bad thing, I would say. [00:30:10] 

[00:30:10] Mat: Yeah, I want to talk about that for a minute because I see that I see that in my team members. I see it in a lot of different groups is this fear of saying that you can’t do something [00:30:20] or for asking for help, right? Like we have to as data scientists get over that fear and to be able to be in a supportive environment where you can go to your manager or to somebody else and say, [00:30:30] Hey, I don’t know how to do this.

[00:30:32] Mat: And either I need to learn how to do it, or we could benefit better from going externally. I’ve seen, I’ve seen data scientists, I don’t know if [00:30:40] you’ve seen this, that would rather, like, miss a timeline, or not share that there’s any issue, just because they didn’t want to speak up and say, I was having a problem.

[00:30:49] Mat: And it’s going to [00:30:50] kill, Innovation, not to mention a road trust and be not a great place to work for them and their teammates, etcetera. But what you’re saying about the external innovations? I mean, we [00:31:00] as data scientists, I think a lot of times we want to do cool stuff, right? We are good at coding. We’re good at programming.

[00:31:06] Mat: We’re good at mathematics. We’re good at stats. We want to do it, but you have [00:31:10] to realize that There are a lot of people that do these types of things for a full time job that are completely invested that you could tap them for a couple hours their expertise and [00:31:20] catapult you hundreds and hundreds of hours of work and you can’t be afraid of that.

[00:31:23] Mat: You have to embrace that and it’s going to make you move so much faster and be more innovative. 

[00:31:28] Alexander: Yeah, [00:31:30] and you just talked about the speed and the money side. Yeah. It may take you quite a long time. Yeah. A lot of your time to get better at [00:31:40] it. And just by working with someone else, you learn it from the best and then you move so much faster.

[00:31:46] Alexander: Exactly. Yeah. 

[00:31:48] Mat: It’s true. Like I hate to, I hate to break [00:31:50] it to everyone, but like you, at the end of the day, you are actually an expense as well. Right? So if it takes you three or four months to do something, that’s still money you’re paying to do it. Not to mention, [00:32:00] I think sometimes what we don’t think about is what we don’t think about, like the lost opportunity costs of something, right?

[00:32:06] Mat: If you can get something three months faster and you can [00:32:10] make faster decisions, you know, we’re operating on. We’re putting together an advanced analytics and AI strategy for R and D right now, and we’ve got four value drivers on this. [00:32:20] So this is taking me about two years to figure out what our fourth value drivers are.

[00:32:24] Mat: But the four value drivers for our strategy are. Increased number of shots on goal in our pipeline, [00:32:30] increased probability of success for our compounds, increased profitability for the company, and the fourth, which is very jazz focused, is the best experience for patients, providers and employees [00:32:40] and anything that we can do from advanced analytics and AI that helps any four of those values is considered like valuable in our book, right?

[00:32:48] Mat: And so I think [00:32:50] that like, as we’re thinking about where we can innovate these, like getting things done faster, if you can get a faster probability of success, the [00:33:00] ENPV of your portfolio goes up, your company’s more valuable. Externally, you have more shots on goal in the pipeline. You can say that externally, like.

[00:33:07] Mat: You don’t want to wait three months for those. You need those [00:33:10] now. So if you need help with that, like push it to happen now because the entire company and your patients will actually benefit from that. 

[00:33:17] Alexander: Yeah. Love it. That is a [00:33:20] great summary and maybe at some point we need to talk about this strategies that you have put together because these four drivers sound really, really interesting.

[00:33:29] Alexander: So we [00:33:30] talked about the corporate. Culture and said jazz was founded with having this culture first in mind and [00:33:40] builds a company around the culture. And by the way, jazz is just 20 years old. So it’s not a, you know, Eli Lilly [00:33:50] or Merck or whatever that are hundreds of years old. Yeah. It’s quite a new company.

[00:33:55] Alexander: And therefore I think it’s, this is really, really interesting with the [00:34:00] speed at which it has grown and yeah, really build it on this culture of patient first. employees, making [00:34:10] sure that employees are happy and how that translates into all these different decisions that you make, like from hiring the right [00:34:20] people, what kind of successes do you celebrate?

[00:34:23] Alexander: What do you talk about in company meetings? What do you measure success in all these kind of different things are in the [00:34:30] end really culture and I love that you talked up about this or talked about this example, where someone, you know, spoke up in a [00:34:40] important key decision meeting to say, let’s make those decisions that are best for the patients.

[00:34:47] Mat: Okay. 

[00:34:47] Alexander: So what is your [00:34:50] key takeaway for the listener from this episode? 

[00:34:54] Mat: I think the key takeaway that I would encourage you all is to, is to evaluate the [00:35:00] culture that you’re in and how that aligns to your values as an individual. For me, Why I went from education to health care is because I want to be in a [00:35:10] job that helps people.

[00:35:11] Mat: And it’s at its core. That’s why, you know, I don’t choose to go into finance. I don’t choose to go into sports as much as I think sports would be really cool to go [00:35:20] into. I don’t do that because I want what my job is at the end of the day to really matter in the world and matter for people. Because jazz has a culture that [00:35:30] innovates, transform the lines of patients and their families.

[00:35:32] Mat: I know that the work that I do meets the values of the company and my values. And I think the biggest takeaway I would say is [00:35:40] evaluate where you are in terms of how your work and how your work culture marries with your personal values and see what you can do to make it a more patient [00:35:50] focus.

[00:35:50] Mat: culture. I think the more people that step up and say, let’s do what’s right for the patients, the better the whole industry is going to be and the more patients that are going to benefit. So that would be my takeaway for [00:36:00] all of you. 

[00:36:01] Alexander: Love it. Thanks so much for being on the show. [00:36:04] Mat: Thank you, Alexander.

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