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The Role of Automation and AI in Lab Operations
Episode

Todd Edwards, Strategic Advisor for Environment Molecular Sciences Laboratory Automation at the Pacific Northwest National Laboratory

The Role of Automation and AI in Lab Operations

Scientists and LabOps workers need one another, and automated processes require that network behind them.

 

In this episode, Todd Edwards, Strategic Advisor for Environment Molecular Sciences Laboratory Automation at the Pacific Northwest National Laboratory, talks about task assignments and process automation within the lab. Throughout his journey in teaching, engineering, and automation management, Todd learned how balancing tasks between scientists and LabOps workers is crucial to boosting their engagement and satisfaction, allowing everyone to excel in what they’re passionate about. Todd explains how he was able to do this at his previous position at Zymergen thanks to the data-driven nature of the synthetic biology industry, which allowed him to distribute tasks backed by data analysis and documentation. Now that he’s transitioned to his new role as Strategic Advisor for EMSL Automation, he discusses how AI-enabled tools, robots, and established communication structures help with the lab automation processes.

 

Listen to this episode and learn more about keeping LabOps workers fulfilled and lab environments efficient and productive!

The Role of Automation and AI in Lab Operations

About Todd Edwards:

Todd Edwards holds a Ph.D. in Bioengineering and is a former Biophysics professor. After leaving academics, he spent over twenty years involved with laboratory automation. He then got into leadership and recently directed laboratory automation and operations at Zymergen, a synthetic biology company. Now he is starting in the Environmental Molecular Sciences Laboratory (EMSL) at the Pacific Northwest National Laboratory as the Strategic Advisor for EMSL Automation.

 

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Kerri Anderson:
By building a platform to share challenges, thoughts from leaders, and network together, the LabOps Leadership Podcast is elevating LabOps professionals as well as the industry as a whole.

Samantha Black:
With the intent of unlocking the power of LabOps, we deliver unique insights to execute the mission at hand, to standardize LabOps, and empower LabOps leaders.

Kerri Anderson:
I’m Kerri Anderson.

Samantha Black:
And I’m Samantha Black. Welcome to the LabOps Leadership Podcast.

Samantha Black:
Hi everybody! Welcome back. We’re here today with Todd Edwards, who is Strategic Advisor for EMSL Automation, which is the Environment Molecular Sciences Laboratory at the Pacific Northwest National Laboratory. Oh, my goodness, what a mouthful. Welcome, Todd.

Todd Edwards:
Thank you.

Samantha Black:
Um, so we’ll get into that in a second, um, but just to kick us off here, maybe tell us before the mouthful, it is a job, tell us how you got to where you are today.

Todd Edwards:
Okay, sure. Well, thanks for having me. I’ve done a lot of different things over the years. I started out in college, actually, I was interested in physics and biology, and so did my research with a biophysicist, and so that steered me towards bioengineering in grad school, and from there I always wanted to teach. And so after that, I got a job teaching at a small college out in eastern Washington, Whitman College, and I started a biophysics program there. And it was interesting, but I learned that academics was not the right fit for me because, you study, you know, you go very deep into one particular subject, and I was interested in a wide range of things. In college I was, I almost went with a professor who did chaos research, right? So I wasn’t, I was passionate about science, but not about any one particular part of science, and so as an academic, I would be really focused on one subject and I wanted to see and do it all. So I went from there and worked at the Lawrence Livermore National Lab and did a postdoc, and that’s where I got into automation. They had robots that had been left behind when the Joint Genome Institute was started. And so my advisor there had grabbed some instruments but didn’t know how to use them, and so I brought them back to life and programmed them and put some biological scripts on there, and from there I got hired by a company that sells robots. And so the laboratory automation at the time was kind of ten years behind industrial automation. So when you think of a lab robot, they’re, you know, they’re slower than what you would think of if you look at like a cell phone manufacturing plant. And so this company that I joined Protedyne, they were coming from that industry and they saw the state of the art in biology automation, and so they decided, oh, we can do better, and so they hired me to help sell the robots. So I would go out with the salesperson and do the technical part of the sale. And it was perfect because I got to meet tons of different scientists doing all sorts of different things and talk to them about their research and then figure out, okay, well, what kind of automation do you need so that you can get your work done? And then it was a small company, and as it grew, I got kind of roped into also fixing them and building them, and because everyone does everything, and eventually, that became the West Coast Service guy. And so I spent many years just traveling around fixing them when they broke, training people on how to use them, things like that. And then after years of that, I was getting a little tired of it, the travel was tough. Um, and also it was getting kind of boring. Like I would see a ticket and I knew exactly what the problem would be and I would go and fly somewhere and then fix a few little things and fly home, and so I decided it was time for a change. Right around then, Zymergen came along and they said, hey, we’re we have automation, but we don’t have an internal support team. And they were growing, and so they hired my previous manager to build a new support team, and then he hired me and some other folks to help start this out. And so that, this would be a great opportunity to build a support team from scratch rather than just doing the support. From there, you know, as Zymergen grew, I was able to, you know, make a difference and get noticed by some of the higher-ups, and so got more and more opportunities as I would, you know, start by fixing the robots and then realize, okay, the reason they’re breaking is because, the way we train the robots is suboptimal. So I came up with a better system for that, okay, and it’s still having problems. So people are doing the wrong thing. Okay, so let’s train the people. Let’s make better materials for training and sort of kind of digging deeper and deeper into why things are breaking. That eventually led me into doing more management-type stuff, helping people use the robots better rather than just fixing it when it breaks. I became a manager, eventually managed the support team, but we had, by that point we had broadened and we weren’t just fixing it when it broke, we were improving them, and so we changed our name to Sustain because we’re sustaining engineering. Um, we see, we analyzed the data, the ticket data, figured out, okay, where are the problems, where the pain points for the people and change it so that it’s better and then, and improve. We weren’t really doing new developments as much, we did a little bit, but it was more improving what was there. So when COVID hit, well, right before COVID hit, um, there were some safety incidents and then COVID hit and the whole company kind of took an opportunity to think about, okay, how are we doing? What are we doing in the lab? How can we do it better? And the EHNS, the head of HNS proposed an idea for creating a governance structure for the laboratory. And there were going to be four components, sort of the kind of the room level, like a room leader level, a level they called the lab leaders, so people who either in the lab or they manage people in the lab, the director level and then the executive level. And so the folks who were putting it all together asked me to head the council of lab leaders, sort of people who manage people in the lab. So they’re close to the action, but they’re not down there doing the work every day. And so during COVID, we created this structure and we looked at everything we were doing and tried to figure out a better way because each lab kind of had its own way of doing things. And as we were going back into the lab with the new COVID changes, we decided it would have been a bad idea for everyone to just kind of wing it and do their own thing, right? We needed a consistent company-wide policy and, you know, signage and everything. So if you went into a lab, you knew, okay, this is a place I can work, this is a place I can’t work. We didn’t have enough benches for everyone and having space to keep them separated. So we had to do hot benching, which people don’t like, but it’s necessary. So we had to figure out a way how do we make this, make a policy for hot benching which keeps people able to do their work but keeps them safe at the same time, and there was no one who could answer these kind of questions. So our group was there to tackle questions and problems that came up that didn’t have a group already there to fix it, and as part of that, the LabOps team was sort of tasked with a lot of things that were maybe tasks that other people didn’t want to do, you know, right? They were there to help enable the science, right, so it’s what support people do. But it wasn’t clear what exactly their job was, what is their task versus what the lab users should be doing versus what the lab leaders should be doing. And so we, a few years in, we put together a giant RACI matrix. So have you seen RACI Matrix before?

Samantha Black:
Yes.

Todd Edwards:
Yeah, so, um, responsible, accountable, inform and consult. And so we made this giant sheet and we worked with all the LabOps folks, the leaders, the scientists, everyone, and we got everyone on the same page for how the work should be divvied up. So it was clear, right, because we didn’t want people thinking, that’s not my job, someone else should be doing it, but we wanted an agreement amongst everyone. And so that was kind of the crowning achievement of this group, was to kind of sort all that out and make a plan going forward so that we could hire properly. Because part of the problem was what the scientists were being asked to do, they were spending a lot of time on stuff that was not science, and they, their leaders were saying, well, we need more people because we have to do all this. Meanwhile, the LabOps team was being asked to do a lot of stuff that, you know, if they did it all the way they were being asked, they were going to need five more people. And so by putting it all in a spreadsheet and figuring out the hours and all that, we could then go to the executives and say, this team needs this many more people. This team needs this many more.

Kerri Anderson:
Now, that’s incredible to hear because that’s something I have had to go through as well at my own company. I think it’s something, especially if you come into a place that has never had a lab operations team, you know, the scientists have been doing all those things. And so you do have to do one of those RACI matrixes to figure out, you know, okay, now that we have LabOps, who’s going to do what? And it’s an important part of that.

Todd Edwards:
And, you know, as a small company, when you first get a LabOps person, it’s very easy to kind of say, hey, can you take this on? Can you take this on? And the kind of people who go into LabOps are going to support you want to help people, right? So your natural reaction is, oh, yeah, let me do that for you. Yeah, you focus on the other thing, I’ll take care of that. And so it’s very easy to take on kind of too much, or you set a precedent like, okay, this person or this group is doing these kinds of things. And as things ramp up, they might not be able to ramp up their team fast enough to keep up. And then they get overwhelmed and, you know, they can often get overwhelmed with tasks that are maybe less engaging, and then that team has a lot of turnover because they’re just doing tons of stuff. And it’s a lot of the day-to-day, which is a part of the job, but they also need a chance to grow and learn new skills, and if they’re not getting it at one company, then they move on to somewhere else, and so that kind of team can have a lot of churn. And it’s very, very similar to what we saw on the automation support team, because a lot of what you do is tickets and PMs and you’re, you know, that’s pretty straightforward work usually. And if you’re, you know, at some point you’re going to stop building your skills because you’ve seen all the problems before and you’re not doing anything new, and then you either leave the team or you leave the company. And so both of these groups, to be successful, you, I found, just through this experience, was either you need to plan for churn and develop a system where people can come in and get up to speed and be effective very quickly, and you have to have a pipeline of people like so developing relationships outside the company, with school, local schools or wherever, so you have people who can, you can hire and bring them in, work them, you know, get them in, get them up to speed quickly, and then when they leave, be ready to pull someone else in or you need to make a good career ladder so that they want to stay and they have room to grow. But even then, right, eventually they’re going to grow to the point where they want to become an engineer. If you have a technician, they want to become an engineer or an RA, or a scientist. But I think that’s the better path, right? Like as I started with teaching, right? So I want people to come in and grow and sort of graduate to another team. And on our team, we actually have a alumni group, so on LinkedIn, because we think of people who left fondly, like, yeah, we celebrate, hey, you know, you learned a bunch and now you’re a software engineer, it’s awesome, or you were a technician and now you’re an engineer, right? Like, that’s great. Uh, sad to see them leave, but glad to see them, you know, progressing in their career.

Kerri Anderson:
Yeah, that’s great to hear because I think it’s something that makes a company incredible is when they really value their employees in that way and they support their growth even if it means, you know, leaving the company, but you’re there for them and whatever their career path takes them to.

Samantha Black:
Yeah, and I think in LabOps specifically, I feel like, you know, it’s still developing. I feel like, you know, you could become director of operations, but I feel like it’s one of those areas where you, a lot of people do go to different places. It’s, you know, it’s just kind of natural in that sense. You learn and you work in a company and you have to go different places. And so it’s not like a scientist where you just keep on doing more science. I feel like it’s more, it more tends to go other places or, you know, there’s not as much vertical growth as there maybe is lateral growth in that case. So just interesting, I love it though. I think it’s awesome that you guys are so connected and support each other that way. I think that’s something that even not in LabOps, I just think that’s a really cool thing to do. So, um, awesome. So I want to focus on, you know, maybe how your automation experience played into this whole LabOps RACI Matrix was, did you leverage any types of like technologies or like automation things in this process? Did you have anything in mind there or was it, were you approaching it just from like the people side of it and your management experience? I’m really intrigued by that.

Todd Edwards:
So I take a very, I guess. I try to solve all problems very similarly. I look at the, you know, how is it operating, how is it supposed to operate, and why is it not operating the way it’s supposed to operate? And, you know, with a robot, you might, if you have two of the same robots, you run the same program and you watch, okay, this one’s moving at this speed and it’s going to these steps. And this one, it’s moving slower and it kind of jerks at this one spot on the deck, it pauses. Okay, maybe there’s a problem with the rail and I check the rail, and sure enough, there’s a spot that needs to be lubricated. Okay, so, yeah, I look at this, okay, we had a lot of people on the LabOps team leave the company and so we were left with no one doing LabOps. And so, of course, all of that work still had to be done. And so the scientists were doing it and they were complaining, rightfully so, like, hey, need to be doing science. I’m spending all my time ordering chemicals, this and that. And so people would say, hey, Todd, you need to get someone to do this. I’m like, okay, how do we get someone to do it? What do we what do they need to do? Oh, well, you know, all that stuff. Okay, well, what stuff is that? So kind of asking questions, and then eventually the spreadsheet grew and grew. Here’s all the things that everyone wanted people to do, and then we kind of binned them into sort of similar categories and then went around and said, okay, well, how much time does it take to do that? And I quizzed all of the scientists and they all put in their answers. And yeah, we built a spreadsheet sort of organically that way. And then we had everyone check it like, okay, does this seem about right? And it did. And so from there we were able to say, okay, here’s how much work is being done that could be done by a different group. And, yeah, so this is how many hours a week it takes, so here’s how many people would need to be hired in order to do that. And then we were in the process of kind of getting executive approval to hire people, and then the company got purchased by another company. So it, ultimately we didn’t do that. They had, the company that bought Zymergen had their own processes and their own way of doing things, so they’re now handling that. But I think it’s still a fundamentally good approach to sort of step back and analyze the problem rather than sort of have the knee-jerk, okay, let’s just hire someone and have them do it, right? Because then you wind up in the same situation where you have people who are doing stuff that is for whatever reason, not engaging enough so that they stay, right? So we’ll just have another people, group of people leave, but really asking lots of questions and not stopping at that first question. In automation, we do, they call it the five whys? Like, okay, why is it working? Okay, well, why is that not working? Why is that? Why is that? And sort of dig back to the, really, the root cause. And what I saw as the root cause was the amount of work and the type of work being asked of the team was not engaging enough for them to want to stay at the company. So I was trying to build something that would be engaging enough, um, or at least have enough people so that they’re not just always swamped with work, they have time to breathe, they have time to maybe do some sort of stretch projects, like we were going to have them handle some of the automation side. We have daily tasks that we have to do, and my team didn’t have enough people to do it, so the scientists were doing it, but it was easy enough that we could have trained the LabOps team to do it. So they would then build up some experience with the automation, right? So sort of a job has to be done for some people it’s busy work, for some people it’s, you know, kind of, you know, I should be doing something better with my time. For some people, though, it’s, hey, this is a new opportunity, I’m learning something new. So finding the right group to do the right work is kind of matching it up is the hard part.

Samantha Black:
Yeah, that’s the soft people skills you have to know and have conversations with people, and that alignment is probably a manager’s most difficult job, right, in any case.

Kerri Anderson:
And so in this situation, you know, your company had you as a leader to be able to ask why and help develop this. Would you have any advice for, say, like a lower-level lab manager who is experiencing that burnout right now and how they can approach their leadership to do this in their company?

Todd Edwards:
I guess it varies company to company, but Zymergen was very data-driven, right? That was a big thing. So that’s why we did these spreadsheets. We did it in the automation team as well. Like, here’s all the tasks, here’s all the instruments we have to maintain, here’s how many hours per week it takes. And we show, you know, we tracked our time for a couple of years, like whenever we did a task we would put in our ticket system how many hours we spent on it. So we had a couple of years of data, we were able to parse it and say, here’s the numbers, here’s what it takes to do it right. You can either give us more people so we can do it right, tell us it’s okay to not do it right and then suffer the consequences later, or have fewer machines. Like, that’s reality. Like, you know, we can argue with the numbers, but that’s going to shift it a little bit. But really having some documentation about what it takes to do the job right and then go to them and just say, here’s where we’re at, we have this many people, takes this much time to do the job, so either we need to have more people, we need to cut the job, or we have to understand that we’re going to burn people out and either pay them more so they stay or, you know, just plan for this churn, but every time you bring in a new person, you got to train them up. They got to learn how things go here, so we’re going to have a very bumpy ride over the years. And then that’s where this governance structure was great because people could bring problems to me or to the council of the lab leaders. We could try to help, and if we couldn’t, then we would go to the department leads and let them deal with it, and if they couldn’t solve it, they could go up to the executives. So we had a pathway for these kind of, I guess, broader problems to be resolved.

Samantha Black:
Yeah, I think that seems really advanced, and I mean, I think you have to be of a certain size to do that too. That’s the other point. The part here, um, you know, some places only have one lab manager and that can be really tough. And so it’s great to hear that, that companies are doing that though, and, and are thinking that way because I think, you know, support team members, they they have a lot on their plate and they all are people people, you know, like they love to help people, and so I feel like they maybe take on a lot, you know, and take it very seriously and personally. And so it’s great to know that people are looking out for them in that way and think, you know, it’s helping to like, the more good experiences that LabOps people have, the more that people are going to want to do that and we need those people. So I think it’s great for the LabOps career path as a whole to, more companies doing this, the better you know? My 2 cents on it.

Todd Edwards:
Yeah those, in those small labs, yeah, there’s just one person there. So we had the, Zymergen had a big campus in California and a small one in Boston, which had a lab manager and, and two LabOps people. And then a very small one in New York was just one person who was the, you know, the site manager, lab manager. So we had kind of like that all three of those situations. And when it’s just one person, it’s usually well, not usually, but for us, it was small enough that everyone knew everyone, and so the, kind of the work sort of balanced out like they could see when he was overstressed and they wouldn’t add too much more or they’d add it say, but don’t need it until next week. So, you know, and like hopefully that kind of relationship builds up that they all feel part of the team and it bounces. When it’s a little bit larger, you can start to run into the problems of others, sort of too much work and everyone’s trying to help, and so, they kind of multiple people who aren’t talking to each other are asking the same person to do things. And that’s where the person has to be better about saying, okay, I can do that, but I’m already working on this. So can you two talk and tell me which one of these needs to be done first? Because can’t get them both done. And then when you get to the bigger side, that’s when it becomes a bigger web of interactions and dependencies that really need some sort of higher level person to look at it and kind of handle that load balancing. That’s where I was a director, so that’s kind of where I saw my job is that load balancing. And then we had the lab manager and the LabOps people to handle the details and actually get the work done.

Samantha Black:
I just want to make sure that we touch on the science about Zymergen just in case people don’t have a context here. So for that company since that’s a large majority of what we’re talking about here, um, can you just briefly touch on and give us a little background or color on what types of science Zymergen was doing and maybe how LabOps, you know, in that organization was contributing to that science?

Todd Edwards:
Yeah, so there were roughly three phases. So there was kind of the ER, the research phase, which would be like a small lab or an academic lab where it’s a group of people focused on, you know, a small problem or very focused problem, and they were, you know, kind of changing it up every day. Like this week they’re doing this next week they’re trying something else, and so there’s needs changed over time. And so we had those research groups. We had a development group which operated more like a mini-production facility, so they were making DNA or doing their screenings, and so they had a very consistent workload and they knew exactly what was going to like, next, in the next three months, they had a plan for what the work was going to be. And so they had a different need, which was, we need to make sure that we have the right material and the right consumables and everything in place so that the RAs could come in and run the processes. And then the third group was, back to more of the research side but, so those were all biology groups. So we had a whole set of chemistry groups which were doing chemistry research. And so their lab was very, very different in the sense that they had a whole different set of dangers, you know, potential safety hazards because of the chemicals. And so somebody knew the biology side, they might not understand the chemistry side. And so if you’re in a lab where you don’t necessarily understand all the risks that could lead to, you know, potentially dangerous situations. So, but they also have the same, they still need supplies, they still need chemicals ordered, they need things to be stored and sorted. So there was sort of overlapping, there was an overlap, but also more knowledge that needed to be gained in order to work in there effectively. And so Zymergen, as a whole, did synthetic biology, so designing new microbes, new genes, creating those, and then testing them to see how they did they produce what they’re supposed to produce. Like imagine a brewery, right? You’re, you have your, your strains of yeast. You have your production where you’re feeding them sugar and they’re converting into alcohol, and then you have your downstream area where you’re taking the alcohol and you’re producing new drinks, new flavors, right? That’s sort of the, you know, keeping the, you know, designing new strains of yeast, that’s the research side, the brewing part is the development side, and then the drink development is the chemistry.

Kerri Anderson:
I love that analogy. I’ve never heard it compared in that way, but that was a good one.

Todd Edwards:
I had the first two but then realized I needed some for chemistry, so.

Samantha Black:
No, that’s, I mean, that’s really cool. And I think circling, tying everything back together, you know, I think synthetic biology is one of the industries that have really embraced like the data first approach and data science, and I mean everything that we’ve talked about today has tied into that theme. Like they’re very data-driven, they want to make sure everything’s organized and based on, you know, solid information, and I think that, it seems like that has that translated all the way down to even like the people management side of it, so I love to hear that. I think, you know, it’s exciting to see that that’s happening but wanted to just know like what you’re excited about in terms of, you’re going to a different position now so what are you going to carry through to your new role from this experience working with LabOps teams in automation? You know, it’s not every day that we talk to somebody in the automation realm. So just curious, what you’re going to bring from your past experiences into the future?

Todd Edwards:
Yeah, I think the biggest thing is that it’s a team sport. The, you know, if you don’t have scientists doing the research side, we’re never going to make new products, right? But for them to have the time to do that, they need somebody else making them gallons and gallons of media, or liters and liters of media, and they need someone to make sure that they have all of the right supplies. And so some jobs are more technically, you know, a higher technical need for background, but all of the jobs are critical. Like if you just got rid of a whole department, yeah, the whole thing is going to fall apart, like it’s not going to work. And with the, with COVID and all the supply chain issues, we found that the pipette tips were a real headache because with a piece of automation, you need consistency. So when you have a liquid handler, when it goes into the plate, you want to go as close to the bottom as you can so you can get all your sample out, you don’t want to leave a lot of dead volume because that’s going to be wasteful. But that means you have a large machine and it’s moving down and it’s trying to get within a, you know, a millimeter or a couple millimeters of a hard surface. And so if you get a tip, if your tip that you’re used to is not there anymore, because you can’t buy it and purchasing says, oh, here’s an equivalent tip, it might be equivalent in specs, but when you actually put it on the machine, maybe even the same length, but one goes on farther than the other. And so if you’ve taught it with this one, the one that doesn’t go on as far, the tip is now lower than you would expect. The robot doesn’t know that, so it’s going to still go to the same spot and it’s going to crash. And then your samples going to, you know, maybe get sucked into the pipetting head and you can have all sorts of problems just based on, you know, buying the wrong tip. And so having people who understand all these little nuances throughout the company, like an automation LabOps team, the folks who are stocking the tips, you need to make sure they get in the right spot. The folks who are buying the tips need to understand, but there’s no, you know, sourcing person is not going to have automation experience most likely. So being able to know that and talk and have structures where everyone can communicate back and forth, you can have a team approach and then make sure everything gets done the way it needs to be to avoid problems. So the new job is, so the Environmental Sciences, Environmental Molecular Sciences Laboratory at the Pacific Northwest National Lab is a group that does a lot of research right now in soil. So they’re trying to get automated and the first thing they want to automate is a process where they take soil samples and then they look at the chemical and physical and biological properties of the soil. So what … especially specifically, what are the organisms living there and what is their phenotype? What are they expressing? And so there’s a lot of steps to processing these samples and people are doing it by hand right now, and so they want to scale up and so they want to get automated to do that. And so they don’t have a lot of automation experience in-house. And so they hired me to help make a strategic plan and figure out what’s the right automation, what’s the right software. And I was very excited during my interview, they asked me like, what would you do? And I talked about, you know, the specifics of the hardware. But I said, but you know, these robots don’t run themselves. You need a team that’s going to support the robots, you need people who are going to, you know, run the robots, you need people who are going to support the folks who are doing that. Like you need this whole network in order for it to be successful because of all the reasons, you know, sort of the automation adjacent things that have to happen. And they maybe hadn’t thought about that or at least not crystallized on that as an idea, even though it was sort of in the background. And so they were all very excited like, oh yeah, that makes a lot of sense. And so they brought that up to me as something that they were glad that I had brought up. So I think they’re the right mindset that it’s not just we’re buying a fancy robot and we can all watch it run like we need to build a system to support that and support the process.

Samantha Black:
Yeah, I mean it’s, it’s just like AI. They say the word and people are like, I’m not going to have my job anymore, so I think it’s all a great reminder that, you know, these tools are great, but they’re tools that we still need people to make sure that they are doing their job right, you know? And so I think that’s just a great reminder that, you know, central to everything is still people, and so I’m really glad that they appreciate that and that you’re going to be able to make a big impact there. So really excited for that. You know, I know this is all new for you, but the last question that I have is just, if people want to find out more about either your past or your future opportunities or places that you’ve worked or even you, how can they find you? How can they connect with you and get to know you better?

Todd Edwards:
The easiest thing would be on LinkedIn, Todd Edwards there. I don’t have the the link handy, but I can share it with you later. I’m happy to connect with anyone and chat, I love chatting about science or technology or what I’ve done. Like, you know, I was a teacher, I still have that in me. I love helping people who are looking for advice on how to get started or how to grow in their career. The in, EMSL is the government website, so it’s www.EMSL.PNNL.gov, or you can just search for Pacific Northwest National Lab and you should be able to find it there. One thing that’s exciting about this is kind of getting back into the more fundamental research side rather than industry where you know you have to be making money, so here they’re more about getting the science done and partnering. So if you’re interested in doing science, soil science research, I know they have a lot of grants and partnerships that they do. Check that out. I’ve started forwarding their posts on LinkedIn, so if you connect with me, you’ll see some of those things.

Samantha Black:
That’s great, thank you.

Kerri Anderson:
Awesome.

Samantha Black:
I look forward to seeing where the lab is at in a year with your automation.

Todd Edwards:
Yeah, it’s exciting because they have a whole process and so they’re not looking to just piecemeal it, they want to get a system that’s going to be able to do as much of it as possible. And then over the years, they want to do more, you know, either more steps or on that process or automating other processes. So yeah, it’s exciting, exciting challenge for me personally because, you know, the biology stuff I’ve been doing for so long, it’s pretty straightforward, but working with something like soil is a very different problem and also doing more chemistry-oriented things. You’re not just using water and things that are pretty much like water using more volatile chemicals, things that might maybe need special tips or special plates.

Samantha Black:
Well, best of luck. Well, we look forward to checking in and seeing how it’s going. Thanks again.

Todd Edwards:
Thank you.

Kerri Anderson:
Thank you for tuning in to this episode of the LabOps Leadership podcast. We hope you enjoyed today’s guest.

Samantha Black:
For show notes, resources, and more information about LabOps Unite. Please visit us at LabOps.Community/Podcast. This show is powered by Elemental Machines.

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Things You’ll Learn:

  • A RACI matrix is an assignment chart that establishes who is responsible for a task, who is accountable, and who needs to be consulted or informed about it.
  • In labs that have never had an operations team, scientists do all those operation tasks that take time for science. 
  • Matching the right teams to the proper work is a challenge a manager has to take.
  • LabOps is an area where it’s natural for people to grow and go to different places afterward.
  • The more LabOps people have great work experiences, the more others will be attracted to that type of work, which is very important as LabOps teams are crucial for science work.
  • Zymergen is a synthetic biology company that designed and created new microbes and genes.
  • The Environmental Molecular Sciences Laboratory at the Pacific Northwest National Lab is researching soil and trying to automate processes with soil samples where they look at its chemical, physical, and biological properties.
  • Automation tools still need people to make sure that they are doing their job right.

Resources:

  • Connect with and follow Todd Edwards on LinkedIn.
  • Follow EMSL Automation on LinkedIn.
  • Discover the EMSL Automation Website!
Visit US HERE