The Health Pulse

[AUDIO LOGO] NEVINE ZARIFFA: The work that my team, my colleagues, and I did had to be done well and quickly. There wasn't a trade-off between those two things.

ALEX MAIERSPERGER: Today, we learn from Nevine Zariffa, former Senior Vice President of Biometrics and Information Sciences at AstraZeneca, who gives us her formula for work done well and work done quickly to save lives.

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Well, Nevine, we're so happy that you're here today. You say you are retired, but then you list seven current roles that you have among having written books and still writing books and other things. Can you share a bit about your professional background, and then maybe how that translates to being so bad at retirement?

NEVINE ZARIFFA: [LAUGHS] Thank you, Alex, I'm delighted to be here with you today. And that's an excellent question to get us started with. I think most of us who have had long careers in big, complicated segments of health care have come to develop a lot of different skills. And so retirement, I always put that in quotes because I had this goal of doing more for health care. I felt very strongly I still had a lot to contribute. But I wanted to do some of my personal projects, which, as you can imagine, got subsumed in the big executive roles that I had previously.

And so, yes, in my retirement, I have focused on vexing scientific questions that need to draw people and data, and advanced statistical methods together. I have focused on wanting to do good for the world during the pandemic, working with the FDA, and the Bill and Melinda Gates Foundation. And now I'm turning my attention to healthtech startups as they try to bring innovation and penetrate the impenetrable large pharma ecosystem, and, of course, a little bit of advising, and something near and dear to my heart, which is fiction writing.

ALEX MAIERSPERGER: But how exciting, but also uniquely bad at retirement. The seven things sounds like 17. To outsiders, AI is largely a new thing, to put that word in quotation marks of new. You have talked about having artificial intelligence and machine-learning teams pre-2019 and pre-then even. What's changed in the AI work from a decade or more ago?

NEVINE ZARIFFA: Yeah. You know, I was reflecting on this. And if you think a decade or more ago as you're suggesting, I'll tell you a little story about what that looked like in almost every single large organization. An executive would fire up the BBC app in the morning and see that there's thing called blockchain, or deep learning, or neural nets, or whatever the heck it was, and immediately want to spring into action and do a pilot.

And so we had all of these pilots, each one of them in a silo, where these PhDs in math would come in and spend an inordinate amount of time wrangling data, and then a little bit of time doing some analysis. They'd get some insight. And then you know what? It wasn't portable. It wasn't scalable, it wasn't reproducible. It was learned, And then the memory would go from the organization until the executives saw something else pop up on their phone.

What we see today is quite demonstrably different. What we see is attention to that data-layer foundation because without that, you pretty much don't have anything. You see an interest and maybe a humility in the workflow. And by that, I mean the understanding that if you're doing research, some things are going to work, some things are not going to work. The important thing is to learn.

So you might have a sandbox environment where you're testing out multiple different approaches. You might promote some of these approaches to prototype. You might talk about that with the business leader. And then you might move these into production algos and track the algos over time and their performance and whatnot. So very different way of working from what I've previously described.

And then last, I think we've all understood the value of something I call connection. And connection, Alex, is about that business leader knowing enough about what could be on offer, and then, on the other hand, the data scientist understanding enough about the business problem that they don't run astray or 180 degrees in the opposite direction. And that glue, that translational ability between the two parts of the system, the business, and then the data scientist, has evolved.

And organizations have invested in that translational role. Sometimes it's in project management, or on educating both sides to each other's discipline. So it's a fascinating evolution around data, around the workflow, the method of working, and then also the ability to really be embedded in each other's area of expertise.

ALEX MAIERSPERGER: What great insight from pilot to platform to production. Really exciting to hear that evolution of how data is being used in these large, complex-- I think you described them already as impenetrable-- complex, big organizations on the life sciences side. And you've been part of great organizational overhaul in your time at large corporate pharma, and in your current roles advising and management consulting for both pharma and healthtech companies. Are there common themes that you pull from, or that you've seen from organizations who are growing and accelerating, and innovating versus organizations who aren't doing those things?

NEVINE ZARIFFA: Oh, yeah. And I think every single person listening to us will say, yeah, I've seen good change, I've seen, you know, sort of OK, disruptive, and then I've seen some pretty bad change programs. So we've got the gamut. We've got the gradient. But your question is really what are those common elements that might be predictive of success? So I think about this and I think, where have I seen it really come to fruition?

Well, I would say in the clarity, crispness of the articulation from the leaders around what they're aiming for and how they're going to get there. So there's something about being coherent and clear, and linked to that, to get the trust and the confidence of your organization, has to be you walk the talk so your actions line up with your words. Number one.

Number two, anything we do in drug development, pretty much anything we do in drug development, has a three to five-year lag for us to really know that we've impacted meaningfully. So your strategy has to be respectful of that lag, have some milestones along the way, have to have some risk mitigation for the many things that could happen in that very long period of time. And then the last thing you're going to see-- I like three, so the third and last thing I'm going to put up-- is people. Change program, strategy, even development, but certainly, execution is all about people.

So you have to arm yourself in the senior spheres, the frontline managers, the teams on the ground with the tools for that transformational leadership. And those, I think, are my top 3's, the clarity of the vision, the planning, and really embedding yourself in a longer-term period to make it happen, to see things come from it, and then attending to the people part of it. Because if you can be genuine just on the people, yourself, your genuine, your next layer is genuine, that's what people respond to.

ALEX MAIERSPERGER: Clarity, planning, and people. You succinctly articulated those three things so easily that I love listening to you and learning from you. You have a personal story with cancer. How does the professional and that personal experience change having cancer while working for an organization discovering and developing drugs to fight diseases like cancer?

NEVINE ZARIFFA: [SIGHS] It's so humbling. It is so humbling. I'll tell the story very briefly just so we can all have the context. So at the age of 33, I was diagnosed with something called chronic myeloid leukemia. Treatment options were pretty crappy, and soon, I was taking medicine that wasn't doing a whole lot in terms of keeping the disease at bay but had a ton of tolerability issues. And I was still trying to work and do my thing and fly around the world and be on my FDA panels and you name it. Had great, great, great support from my team, and colleagues, and family, of course, and friends.

And I'm just not doing as well as I should be. And I'm starting to plan for making things easy for my family. And out of nowhere, my oncologist says you know what? You weren't sick enough to be in the phase III trials of this new medicine, but I could get you in at Hopkins in the compassionate use trial. As I jump in the car with my friend, and we go down there, and now I'm part of a trial. And I had been doing trials my whole career up until then.

And this thing worked. And this drug is called Gleevec. And it revolutionized the treatment of CML. Side effects are reasonably benign. There's a minority of patients that don't benefit the way I did with a 25-year remission. They have second generation. There's now even a third generation to try and tackle that resistance. It's an absolute-- I posted on this recently-- it's a miracle of science. That's what that is.

And so I take that experience, and I brought it with me in my second half of my career. And it came down to something very simple. The work that my team, my colleagues, and I did had to be done well and quickly. There wasn't a trade-off between those two things. We needed clarity on what the drug did or didn't do for patients, and we needed to do it and get the answer as fast as possible. And that was my mantra all the rest of my career and still is today.

ALEX MAIERSPERGER: That connection between work done well and work done quick and saving patients' lives, what an incredible story. And so excited to hear about the years of remission for you.

NEVINE ZARIFFA: Thank you.

ALEX MAIERSPERGER: You've made it from one sensitive subject to we'll take your mind to a far further place on our speed round and give you some quick-hitting ones here. Are you a morning or a night person?

NEVINE ZARIFFA: OK. So when I was younger, I was a night owl. And [LAUGHS] as soon as I started working, it's like wham! I have to be up and going. And now I'm a morning person after all these decades.

ALEX MAIERSPERGER: That's that work done well and done quick, probably requires some of that little-sleep efforts. What's your favorite type of exercise?

NEVINE ZARIFFA: Pilates. Love Pilates. They can accommodate any kind of injury or difficulty you're having, but you can still press on and get benefits. I think it's great exercise.

ALEX MAIERSPERGER: Physical book or audiobook?

NEVINE ZARIFFA: Audio, no. Kindle versus paper? That's a harder one. I still gravitate to paper, but I see the benefit and value of having a portable library,

ALEX MAIERSPERGER: Favorite breakfast food?

NEVINE ZARIFFA: I like fruit and yogurt in the morning.

ALEX MAIERSPERGER: That sounds delightful. Favorite app on your phone?

NEVINE ZARIFFA: OK, I'm totally old-school. I like my mail app. [LAUGHS]

ALEX MAIERSPERGER: Oh, just messages, or email. I like that.

NEVINE ZARIFFA: Exactly.

ALEX MAIERSPERGER: Favorite vacation place or favorite place that you have not yet visited?

NEVINE ZARIFFA: Well, my husband and I just came back from New Zealand. And I have to tell you, it was on our bucket list. And three trips were canceled before we finally got there. It's unbelievably beautiful with wonderful people. So that would be my number one place.

ALEX MAIERSPERGER: Exciting to hear when it lives up to the hype. That's so exciting. Maybe the three trips canceled built up the anticipation. I'm glad that that was such a good trip. So you're off the hot seat on the fast and furious questions of the speed round. But you've given us a little bit of the storyline of AI a decade or decades ago, a little bit of where it's at now, and then what does the future hold? What does the next decade look like for pharma companies and healthtech investing in AI?

NEVINE ZARIFFA: Well, I'll tell you, for the pharma companies, and so as a consequence, for the health tech, the number one thing that's happening today that is definitely going to come to fruition in the time frame that you've mentioned is operational efficiency. I mean, if anyone looked under the hood into the belly of what it takes to get all those little widgets lined up for a filing with the regulatory agency, your hair would be on fire.

And so anything that automates, speeds up that operational side is of incredible value. Why? Because you can take the smarts and the capabilities of all these colleagues that you have working and redirect their energy away from the rote turn the crank into the thinking of what else could be valuable for patients. So that's how I like to redirect the time of all these expert colleagues working in pharma.

So for health tech, the flip of that is come in, solve a problem that's probably going to be a pretty deep problem. So it's going to take time to get it right. And then you have to be modular, and you have to be able to plug in with any other solutions the pharma folks already have in play. So it's a little tricky for health tech on the operational side, but nonetheless. And so I'm hoping we get to see end-to-end operation automation within that time frame that you've described. But who knows?

And then the other big wow that I really hope we get to, so we talked about speed and quality earlier. So speed here, you can't speed up getting two years' worth of data on a molecule in a patient. That's two years. I can't make it one year magically. It's got to be two years. What comes before, what comes after, I can speed up in the ways we've described. But the other thing I can improve with insights is which molecule we choose to invest in.

Because if we pick the molecules that really have the most promise for patients and not waste our time and effort on the ones that are least promising, we're going to get increased throughput. So we're going to get some speed from the operational efficiency, and then we might double our throughput or triple our throughput of new medicines. And all of that together brings incredible value to patients. So that's where I'm hoping we're going to be in the next 10 years. Part one, definitely within our grasp. We're already seeing it. Part two, I don't know. I think I'm going to hold the executives accountable for delivering on that.

ALEX MAIERSPERGER: You talked so much about the people that they're in every process and in every change management opportunity and at the heart of all of the innovation. How does this change the workforce or building a team around the next-gen capabilities of data and AI? Is it going to be more distributed globally? Are there going to be non-coders that are able to do some of the work of coders? How do you see the workforce changing for those insights that you talked about needing?

NEVINE ZARIFFA: Yeah, no, that's a great question. So we talked about that ability to translate. So I don't think it's any good to have coders or modelers that have not a blessed clue about the business they're trying to penetrate. I don't think you get anywhere. And vice versa, if you have business leaders who don't appreciate the value of data foundational layer, that doesn't help us either. So talked about that.

Your question is can you distribute? Do you have to embed? Do you centralize? I don't know. And these things change. They change for existing disciplines of today that have a history of five decades long. Companies make all sorts of decisions about where they're going to put their workforce, what they're going to try and treat as execution, what they're going to do and flip it to the thinking part of the design part of the work. I don't know about all of that. What I do know for sure is that we live in a world that is super fast-paced, and we're seeing things that are new and innovative all the time.

The thing that I really would like to impress upon those who are embarking in their career is you will be learning for the next four decades. You'll be learning in your own discipline of choice. You'll be learning how to work with other experts in their discipline-- very important. And then you'll be learning other adjacent disciplines to the one you started in. So I started in pure math. I then went to statistics. I then went to biostatistics. And I kept adding the data AIML. So all of those are adjacencies. It's a gradient, if you will, or a Venn diagram. Get ready for it. Embrace it. Be open to it. Don't start with the "no because," think of the "huh," and "maybe" instead.

ALEX MAIERSPERGER: I love that. Back to the people again. I love that you speak directly to the audience and the incredible advice that you have, and the incredible experiences that you have. All of the things that you've seen, both personally and professionally, the fiction world that you get to live in as well through book writing, what makes you most optimistic for the future?

NEVINE ZARIFFA: Young people. [LAUGHS] You know, I have my godchildren. I have my grandchildren, I have my nieces and nephews. And whenever I interact with them, I get a different sense of the world. I think they're challenging the status quo in a whole different way. So that gives me some faith in the future. I just hope that the rest of us haven't screwed the pooch too much and made it too much of a challenge for them.

But they are a force to be reckoned with, Alex. And if we can, I don't want to say help them be all that they can be, but at some point, that's what it is. If we can make their own sense of purpose and their own view of the world as expansive as possible, we might just have a chance.

ALEX MAIERSPERGER: Quality and speed and work done well and work done quickly to bring meaning to patients' lives is something that I'll take away so strongly from this conversation. Thank you for all that you've done and all that you continue to do to bring drug discovery and to bring new drugs to market, and to really be a blessing and a miracle of science in individuals' lives.

NEVINE ZARIFFA: Thank you, Alex. It was a pleasure being here with you today. And I hope the audience enjoys this conversation of ours as much as I did.

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ALEX MAIERSPERGER: Thank you for listening or watching. If you have comments, or if you want to join us as a guest, please email us. Thehealthpulsepodcast@SAS.com. See you next time.

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That really does not-- Biometrics and Information Sciences does not roll off the tongue. Former Senior Vice President of Biomedical-- oh, Biometrics and Information Sciences, Biometrics and Informational-- Information Sciences. I was so close. [CLEARS THROAT] "Bio-metrics." Oh my gosh. Did you say something or was that me?