Unlocking Scientific Data with Mike Tarselli at TetraScience

Today we’re talking to Michael Tarselli Chief Scientific & Knowledge Officer of TetraScience. Mike was the Scientific Director for SLAS, a global professional society dedicated to lab automation and an Associate Director at Novartis building an external scientific collaboration platform. You can read the full bio in the show notes. 

TetraScience is bringing the future of scientific data to today and has built the largest integration network of lab instruments, informatics applications, CRO/CDMOs, analytics, and data science partners, creating seamless interoperability and an innovation feedback loop that will drive the future of life sciences and the delivery of life-saving therapeutics.

More about Mike Tarselli
Chief Scientific & Knowledge Officer of TetraScience, Mike Tarselli, explores the Tetra Scientific Data Cloud™ through knowledge capture, GxP compliance, and use case research. Previously, Mike was the Scientific Director for SLAS, a global professional society dedicated to lab automation and an Associate Director at Novartis building an external scientific collaboration platform. Mike received his Ph.D. from UNC Chapel Hill, completed postdoctoral work at Scripps Research, and his MBA through Quantic School of Business & Technology.

Show Notes:

• Tetra Science Website - https://tetrascience.com/
• Demo of TetaScience - https://www.tetrascience.com/demo
• Benchmark Data from TetraScience  -https://go.tetrascience.com/researchreport_Scientific-Data-Imperative-Establishing-a-New-Benchmark-After-Two-Decades.html
• GXP Solution Brief - https://www.tetrascience.com/solution-brief/gxp-with-tetra-scientific-data-cloud

Qualio website:
https://www.qualio.com/

Previous episodes:
https://www.qualio.com/from-lab-to-launch-podcast

Apply to be on the show:
https://forms.gle/uUH2YtCFxJHrVGeL8

Music by keldez

Transcript

Kelly Stanton: 0:17

Hello and welcome to a new year at another episode of From Lab to Launch by Qualio. I'm Kelly, your host, and I'm happy to be here today. It's been a delight to share behind the scenes stories of some of the most innovative and advanced companies in life sciences from around the world. Before we jump in, uh, just a reminder to please rate the show and share it with your friends who are science nerds just like us. We know you have. Also check out the show notes if you have a story or a product that you'd like to, uh, connect with us over. All right, so today we're talking to Mike Tarselli, Chief Scientific and Knowledge Officer of Tetra Science. Mike was the scientific director for SLAS, a global professional society dedicated to lab automation and an associate director at Novartis, building an external scientific collaboration platform. You can read his full bio in the show notes. Tetra Science is bringing the future of scientific data to today and has built the largest integration network of lab instruments, informatics applications, CROs/CDMOs analytics and data science partners, creating seamless interoperability and an innovation feedback loop that will drive the future of life sciences and the delivery of life saving therapeutics. We'll get into, a little bit more of this now. thanks for joining us today, Mike. Welcome to the show.

Mike Tarselli: 1:35

Hello Kelly. Thank you very much for having me.

Kelly Stanton: 1:38

So Chief Knowledge Officer seems to be an emerging role Can you tell us more about that role and uh, and a little bit about your background?

Mike Tarselli: 1:45

Sure. I'd love to. Thank you. Um, I'll rewind back a little bit to say, because there's a lot of weird words in there and an ampersand, which I actually asked for. Um, so the, the scientific was my very first role here at TetraScience. Um, I'll say that in its, its previous evolution of, of the company. TetraScience was handling a different kind of business and was looking more in the tech side for being a cloud platform for relaying. Instrumental measurements. Um, but our, our sort of real tetra, uh, journey with this cloud-based data platform has started really in earnest in 2019 to 2020. Um, and I brought, I was brought in somewhere in the middle of 2020 to be our, our chief Scientific officer. And of course you say, why does a data platform need one of those? And the answer is, if you're going to serve biopharma scientists and you're going to say, Hey, what do you need to do with your data? Where does it need to? And how does it need to be integrated into discovery and development workflows so you can actually get things done? Well, then you're going to need a scientist to look at that. So, um, under, under this sort of title, I worked on our external integrations. I worked on our, um, product marketing message. I worked on our initial stabs at our quality system, which has evolved leaps and bounds thanks to my very talented team now in the past two and a half years. Um, and. In mid 2022, actually late 2022, I was, uh, very, very humbled and honored to be called our, our initial, uh, chief Knowledge Officer as well, which means that my remit now expands past just, Hey, can you get scientists to work with our platform and tell us their use cases to now more holistically, how do we train people for this new world? We talk about GAMP five second edition and, and CSA procedures versus csv. We talk about getting people into being data science literate upfront. We talk about science as not just being, you know, Hey, can you pour fluids together or pipette cells on a lab bench, but can you also look at the data at the backend and figure out whether your conclusions are statistically relevant? Right? So how are you gonna train people? How are you gonna train people at the interface of science and tech? Um, we have a, a acute house term we call Cyborgs, S c i, Borgs because you gotta be at that interface like a bioinformatician, right? Or a Chemin Matician or a systems biologist. Um, if you can't get both of those sides, it's going to be hard for you to interact in this new world. We think so. So my chief Knowledge officer role allows me to expand into training and then into how we know what we know.

Kelly Stanton: 4:08

Nice, nice. Yeah, we're, uh, we're on a similar mission here at CUO with, um, you know, bringing data sets together and those kinds of things. Cuz again, from a quality systems perspective, you know, you're right, there's, there's so much data to be had out there, but if we can't, you know, see it and get it and touch it and handle it and, and process it, you know, if it's still sitting on a spreadsheet somewhere or it's in the lab. You know, on a, on an instrument somewhere, and nobody's really looking at that from a bigger picture perspective. It's amazing to me that, that we've gotten so far as an industry and yet I, it feels like baby steps from a data

Mike Tarselli: 4:44

perspective. Yeah, it's an excellent point. You, you think about your, you know, academic training or, or if you did, you know, a postoc or an early internship, what you were doing for, for data, quote unquote. And if you can't see, I'm making air quotes. Um, and it was, you know, you would print out a piece of paper or maybe you'd hand write in a lab notebook or, or maybe you'd, you know, take a carbon copy or get an actual screenshot from something and send it to yourself and move it on a US B stick. this is craziness. Um, and you'd say, didn't that go away in 1995? And the answer is no. Um, maybe every couple of weeks we still have a company that will come to TetraScience and say, Hey, help me. My entire manufacturing CGMP suite is still on paper. Um, we don't yet have an MES or a limb selected. We really need to go that direction. We're still in a CSV world. We need desperately to modernize and digitize. What can you do for. They wanna leap, they wanna go two or three, you know, technological levels up in one go Right? They wanna go past, yeah. Past El n limbs. They wanna go past, you know, the, the sort of clunky point to point integrations world of the 2010s and they wanna go right to cloud data and hey, great, we're here to help you. That's awesome.

Kelly Stanton: 5:55

So, uh, so yeah. Um, Tetra Science's mission there, you know, solving humanities grand challenges by accelerating and improving scientific outcomes. Uh, and as you said, you know, bringing bringing the industry along into 2023, that's, that's a big mo that's a big, bold mission. Um, how, how, what are some good examples of how that's, how that's

Mike Tarselli: 6:19

happening. Great question. So, so mission statements are inherently big and bold. They've gotta be, or else, you know, you're not going to achieve what you set out to do. So in ours, right, we wanna solve humanities grant challenges, but we're gonna start the place we know best, which is biopharma, biopharma workflows, especially those in, in discovery, development, manufacturing, um, at this time, um, 2023, not a forward-looking statement. Investors, um, we are not playing in clinicals or patient data or patient safety. We're, we're completely issuing that. And, and that actually, Sort of less complicates our space. It makes it a little easier to handle, right? Yeah, definitely. No p h i, no, p i I at least limited if nothing else. Um, because of that, we are able to take that mission and say, can we, um, we actually just asked this in a survey of, of 500 life sciences execs who were very kind and responded to us with great, great data. Um, Things emerged in there that I've never heard before. Like if, if you don't have a cloud system handling your data, you are seven times more likely to repeat experiments. That's nuts. You know, that is nuts. Wow. And, and they would they say they, you don't even have to like truncate the drug development and discovery process, you know, from that current 10 years,$4 billion to, you know, they're not looking for two years or five years. They're looking to shave off months to a. that's something we can do, right? We can immediately have a direct impact both on those companies, bottom lines, you know, if Biopharma wants to save some bio bucks in order to get their development going faster. And also to help accelerate things to patients, you know, um, every two or three months, something goes in is another cohort of patients that could have been saved if that was approved earlier. So you, you, you think that data management, you know, as a strategy doesn't have that much impact, but it does, you know, being able to access. In a fair way, being able to get at it and, and, you know, accelerate it, interrogate it, and then make decisions upon it to release therapeutics faster is the way to go. So, so that's what we're here to do. We, we do one thing and we do it well, and that's, take data outta systems, put it somewhere you can find it, and then put it where it needs to go in your internal systems.

Kelly Stanton: 8:23

Nice. Nice. So, uh, you know, it is the beginning of the new year. Um, what are some of your projections, uh, for this space in the, in this year and, and maybe into the next five to 10 years?

Mike Tarselli: 8:34

Sure. Uh, pwc, um, much larger consulting organization, uh, has a very broad range and look, said that this is gonna be the year of digitization. You know, in this space. They said this is gonna be the year where everybody wakes up and says, we're in a post covid pandemic world. We are, you know, A wash in data as you know. Um, you probably know this already, but it, we're going to take all the data that's ever been done in human history around 50, I think it's exabyte, no, sorry, zetabytes now. Um, and we're going to literally triple that in the next five years. Um, who's gonna handle all that? Right. Wow. Um, somebody's gotta, and, and biopharma by the way, and healthcare generally generates about a third of that. So this means anybody who's doing data and integration work and storage work and computational work right now is gonna literally see their work three to five x in terms of both impact and amount. In the next three to five years. I mean, this means you gotta get ahead of that curve. So, so this is the year where, you know, um, every pharma's gonna appoint if they don't have it already, a chief information security officer, a chief data officer, probably multiple CIOs, right? Um, and they're gonna start really looking at how to take every single workflow that can be automated and trying to automate it. right. This is from robotics on the discovery side to looking at paperless trials and, and animal list testing in the development side to looking at, um, high end manufacturing and some VR and AR and things in the manufacturing realm. Um, all of these are things which unsurprisingly generates diverse data. you gotta put it somewhere. Definitely. So we're kind of hoping that, that somewhere is, is Tetra Science's Scientific data

Kelly Stanton: 10:12

platform. Definitely. Well, and thank goodness that, uh, we are moving into the C SSA realm cuz holy cow. Could you imagine applying C SV principles to all of this Admittedly mean it's, it would, it would shut it down. It would bring it to its

Mike Tarselli: 10:24

knees. Admittedly, when I first started, um, I, I inherited what I could from sort of the, my predecessors in these roles. Um, and we had a couple of procedures of SOPs and policies and we had, and, and being honest, an IQ O Q P Q, you know, trajectory we just did that was what was DEGER in 2020. So that's what we went forward with. Um, and we quickly found ourselves in a. We said, okay. Um, so we, we, we installed this, we qualify it, and now somebody wants us to pass data through that's theirs and kind of do us a validation. But are we allowed to do that? I don't know. Validation isn't our responsibility. Right? Can, can we admit to that? Is that a thing we can do? So we quickly pivoted. Upon the publishing of the new GAMP regulations to a full CSA and to saying, look, you know, there's so much going on. You maybe have in, in a given lab here. I'm gonna, I'm gonna ballpark this. In a given biopharma lab, they probably have somewhere between 50 and a hundred different kinds of instruments going. I don't just mean vendors or, or independent, I mean kinds, you know, flow cytometers, mass specs, h hps, particle sizers. Yeah. Yep. You gotta have data coming in from all of. all the time, and you have to verify that each of those connections operating in spec and that the platform's handling them when they come in, that no data's being duplicated or overwritten, and that you have a full audit trail. Oh. And that those are publishing to where they're supposed to go all in real time or near real time. Right. How are you gonna do that with a CSV approach? You, you can't have a, a human with a piece of paper looking at each independent workflow. You think you might do that. They're just gonna. You know, an explosion of options, and you, you're not gonna be able to have PQ on all of that. So, so the better way is to go c s a with that.

Kelly Stanton: 12:04

Definitely. Definitely. Well, that's a tough sell, but, you know, although I say I say that, I mean, it's a tough time in the economy right now. Right. And a lot of founders, we, we have a lot of founders in our audience. Um, and so, you know, curious for any thoughts or advice you'd give, uh, to those who might be facing some headwinds, right?

Mike Tarselli: 12:23

Admittedly, I'll be honest, I mean, I'm a scientist by training. I'm not an economist and I'm not in a titan of industry. Um, I'm, I'm doing my best, uh, to learn and, and adapt my roles as we're going. But, but we as an executive team here at Tetra Science are, are definitely taking the long. Run approach, right? We know what we need to do, we to deliver for our customers. We're going to be, you know, looking at absolutely every spend, every, you know, every investment, every everything very carefully. Cause we wanna be good stewards of our capital. Um, and so we're going to be, you know, in it for the long haul. Um, we, we don't we don't throw those lavish startup parties. Um, we don't give crazy like, uh, you. Uh, Fang company type salaries out at, at a whim. We, we can't, you know, we, we have to be fiscally prudent. We have to be conservative with our management strategy, but we have to keep our eye on, on our broad mission, right? Which is to accelerate and improve, you know, human life. You gotta be around and you gotta get outta the headwinds of the economy section to do that. So, so we are, we are in, in buckle down, look for efficiencies, automate everything mode this year, and, and that, that's gonna be our, our sort of canvas to play on.

Kelly Stanton: 13:32

Yep. Yep. That all sounds very familiar to me here, I'm sure it does. All right. Well, to pivot a little bit, if you could go back to the start of your career. Sure. What would you tell yourself based on what you know now?

Mike Tarselli: 13:45

Which career should I start from? I'm, I'm actually, uh, I, I may, I maybe don't look all that old on camera if you see this on YouTube in the future, but, um, I'm, I'm in my 27th year of, of working world. Um, and, and that goes all the way from, you know, uh, getting trash outside of dumpsters for my old apartment complex to washing dishes in our dining commons to, you know, taking part in data entry studies in college and, you know, working as a paramedic for a little while. Um, working as a hospital assistant, then working in in labs as, as an intern, you know, and then sort of graduating into my informatics roles maybe about 10, 15 years ago. Um, but it's been a, it's been a very interesting and varied career. Uh, so first thing I'd say is to, to younger me is don't aim at the outliers. What I mean by that is you might want to win a Nobel Prize, or you might wanna be a billionaire or to have your own island in Greece, but those are not the usual outcomes for 99.9% of the population It just, they, they aren't things you get, you know? So the best you should do is to, you know, adopt a set of values, adopt a set of working norms, try to get better every year, but you're, you know, if you say at the end of your life that if you haven't won a Nobel Prize, then your life's worthless. Probably not a great idea, Um, second thing I'd say is, is, you know, appreciate the bumps more than the ups you know, you actually learn an awful lot in, in downturns. You learn a lot if you get fired, you learn a lot if you botch a big project or if you fail. Um, the, the old saw goes that good judgment comes from experience and experience comes from bad judgment. You know, I'm not gonna say I've always made the right decision every time I've tried, but, you know, things have not always gone my way. And I've actually learned a lot more in the things that I've, you know, failed at than I have in the things that have gone amazingly. Um, and then the third thing I just say is, you know, uh, look at what's most important. You know, um, you, you don't actually have to again, have tons of money or five cars or seven houses or fly around the world or be a big thought leader. Um, having really committed good relationships with friends and colleagues, um, having enough, without having too much being gracious for what you have, um, and knowing that you're getting better every year is, is well enough reward for me. That, that's what I tell myself.

Kelly Stanton: 15:59

Awesome. Awesome. Those are all, uh, good advice, uh, for sure. Um, another fun question that I always like to ask if, uh, if I walked into Barnes and Noble. Hmm. Uh, where would I find you? What section would you be

Mike Tarselli: 16:14

that in Uh, you did introduce this podcast with a science nerds motif, so you're gonna also find me in the scientific biographies. You know, that's a st that's a starting point. I love learning about how people before me went and how, you know, SOC was doing with this polio vaccines, or how pester was doing when he was, you know, looking at the sewer systems under Paris. Um, that's really neat stuff to me. Um, but I also love, uh, trivia and puzzle. So you'd find me in the, in the jokes section and looking for, you know, um, the, the 17 best ways to complete Crossword X. Um, I might be buying a puzzle on the wall cause I also love puzzles, my free time. Um, and I just also love, um, looking at broad-based non-fiction. You know, how to do X better. whether that's how to build a business better, how to build a garden better, how to do lighting better. Um, I love those self-improvement things that say if you just did this 10 minute thing, you'd probably be doing better in your life. So probably those sections. Nice,

Kelly Stanton: 17:10

nice. Yeah, I think I'd, uh, have, we'd have a lot of overlap there. That would be fun.

Mike Tarselli: 17:15

No. Tell me yours. You should. Where,

Kelly Stanton: 17:16

where's your sections? Oh my gosh. Well, yeah, definitely the. Type sections. Um, I love, you know, fantasy sci-fi type books. Um, you know, I, I think I have read everything Michael Kreton ever wrote, like, you know, awesome five times cuz yeah, even the pseudonyms So yeah. Not as much his pseudonym books, but you know, any of the ones. And the other one I always loved was, um, Robin Cook. Cause he was a medical doctor. Cont awesome. Yeah, exactly, exactly. Great stuff. Yeah, no, I, you know, my degree is in biology and chemistry as well. That's my background. So I love all the, you. The biology and the science nerds sorts of things, which is part of what I love about this industry. And I love what you were saying about, you know, my, my goal certainly wasn't to, to grow up and get rich and win a Nobel Prize. I just, honestly, I needed a good job that paid well that could support my horse habit cuz I have horses and that's a whole other convers. But yeah. You know, but, But it's been incredibly rewarding to be, you know, 25 years into my career and getting to see some of the drugs that have made it into the market or medical devices. Awesome work for some of those organizations where, you know, cuz I didn't wanna be a medical doctor, um, Kind of situation, but I'm fascinated by all of those things. And so to have found this industry, I, I didn't even really know it existed. I mean, I exactly think my totally true my, when I graduated from college, things said I wanted to go into, uh, either medical research or be a teacher. You know, you are, that's what you think, that's what you think you're gonna do with a biology degree, right? And here we are. So, yeah, it's, it's, it's fun and, and I, again, I particularly love now here at cuo, you know, where I used to just help, you know, I had a consulting business, so I had three or four different clients at any given time. we have over 500 customers, so I get to kind of see across what everybody's doing and Sure. And it's so, it's just amazing. It's amazing to be a part of and,

Mike Tarselli: 19:06

and get to the platform economics, it's a real thing. Yeah. Watching what happens around the world and knowing that, you know, you're looking at a dashboard for somebody's, you know, risk-based profiling who lives in, you know, Sri Lanka or Australia or South America is, is craziness. And I, I love it. That's one of the aspects of my job I really, really like.

Kelly Stanton: 19:25

Yeah. Yeah. And, and it's, it's fascinating too as well, because in our, you know, situations, then we have the opportunity to learn from those different mm-hmm. customers and locations and help bring that broader perspective across. Uh, cuz it just benefits everyone to be like, Hey, you know, I, I've seen this before and obviously, you know, you've gotta protect some confidentiality and all that kind of stuff. Of course. Which you can be like, I've seen this before. Here's, here's some ideas on how it got resolved last time I saw it. You know, and, and people can collaborate on those things and it just makes everything better.

Mike Tarselli: 19:56

Totally awesome.

Kelly Stanton: 19:57

I love it, abs. Absolutely. Well, um, so where can folks go to connect with you, uh, follow along with, uh, Tetra Science Progress?

Mike Tarselli: 20:06

Sure. So, so I am a, a LinkedIn guy. I love to post there to talk about different papers. I've read different standards and regulations, um, different things and Cool, um, places our company pops up and, and who we've helped success stories. So please, I'm the only. Tar in science in LinkedIn, and that's T A R S E L L I. So, you know, if you can't find me, then I've done a very bad job. Um, for, for, for Tetra Science proper, we have obviously a Twitter engagement. I believe it's at TetraScience. Um, we can be found, I believe on Instagram and LinkedIn as well. We have several posts that, um, highlight what's called our Tera. Partner network, which is where, um, other companies that are in our space, so not biopharmaceutical companies, but rather more on the software devices and hardware side, um, congregate with us and say, Hey, we see this future evolving as well and we wanna be part of it. So, um, we actually look at these companies as being, you know, part of our extended canvas of what we can offer. And so they, they get together with us, they sign letters of intent with us. We, we get integration agreements together and we start literally building APIs together or exchanging code or saying, Hey, you know, let's collaborate and make. Tetra built into this new version of an E L N. It's good stuff. Um, and, and then I'd say we have a very, uh, good web presence. Um, you know, you can find obviously our corporate website and that's fine, but a better one for most people on here because it's a quality audience, is looking on the resources tab of our website and looking for our G X P and our 21 C FFR part 11, um, white papers. Um, we do self audits. We do, you know, a standard package, CSA based mm-hmm. Um, I should credit my team. They're the ones who pushed me into this world, which is good. Um, and then we have a ton of open developer documentation at developers.tetrascience.com. Um, you can see all of our API calls, all of the services we handle, all of the Python based integrations we support, you know, where we're going next. Um, we try to be very open and transparent so it's all out there in the world.

Kelly Stanton: 22:05

Awesome. All right, Mike. Well, thanks so much for your time today. It's been a real pleasure.

Mike Tarselli: 22:09

Thank you so much, Kelly. It's been a wonderful being here as a guest. Appreciate it.