Welcome to the first professional development workshop of end of 2023. This is the business of starting and running a lab. My name is Dr. Daquina Nicholas. I am chair for this session. We will also have two other panelists with us, Dr. Matt Sikora and Dr. Dan Frigo. So how this is going to work today, we're all going to take about 10 minutes and tell you our stories about how we set up a lab. And we purposefully chose panelists, including myself, that span different career positions. So we have more senior member, mid-career, and early career, being myself. After we go over those stories for each of us, we have a couple of slides that are some really quick tips, kind of about things you want to think about when setting up your new laboratory. After that, we will open up for questions and answers. And we want you to be able to get all of your questions answered. So please feel free to come up to the mic, announce yourself. So with that, we're going to go ahead and get started. And we'll begin with our most senior member of our panelist. So a quick 10-minute story about setting up your laboratory, things you wish you had known, things that you learned along the way. First, thank you for the invitation. And I would also like to thank you for pointing out that I'm a senior member. Not appreciated. So my name is Dan Frigo. I'm currently an associate professor at University of Texas MD Anderson Cancer Center down in Houston, Texas. So my primary appointment is in the Department of Cancer Systems Imaging, and I have a secondary in a clinical department, genitourinary medical oncology. I've had the pleasure of starting not one, but actually two labs. In 2010, I came out of my postdoc and started my first lab when I was a brand new assistant professor at the University of Houston. At the time, they were starting this center called the Center for Nuclear Receptors and Cell Signaling, which is what we work on. We do a lot of molecular endocrinology, particularly in the context of prostate cancer. And then in 2017, right around the time that I was going through the tenure process at University of Houston, you'll see this is kind of an interesting phase of life, too, different opportunities popped up, and then I decided to move my lab down the road to MD Anderson because we wanted to have a little bit more of a clinical footprint to our lab, and so that was sort of its own little adventure. So I moved in 2017 to MD Anderson, and then the lab finally got there in 2018. Fortunately, I was able to sort of maintain both MD Anderson and UH labs for a while while setup was ongoing. So I remember when I first started out in my lab, everybody had basically the soundest piece of advice is just stay small, stay nimble, stay focused. And so I remember the very first person I hired was a woman, Jenny Han, who's actually been with me ever since. She's sort of like my right-hand man. And so, because when you start your lab, you know, I had come from a lab during my postdoc, which at one point we were up to around 50 people in our lab, so it was one of these mega labs, and actually we were split out over two campuses on Duke's campus. And so we knew, I knew that whenever we had like a lab meeting, if we didn't have the answer in lab meeting, there's probably just a good chance that it just wasn't known in the field. And then it's kind of crazy that when you start your lab, you know, you're basically an N of one, right? And so you want to make sure that you're just not some crazy person thinking crazy thoughts. And so one of the things that I think when I started out in my lab is that, one, I hired a technician right away, and then I had, I think early on, probably a grad student and then a postdoc in my first year. But, you know, you've got your ideas and you've got to push them forward. I think that was huge for me, and one of the reasons why I decided to go to Houston at the time was Houston had kind of become this mecca for molecular endocrinology, and so I knew that even if the center and the university where I was at didn't work out, I knew that there was a lot of people I knew and support at Baylor College of Medicine, MD Anderson, the Methodists, they were all having these different endocrine groups. And so it was extremely helpful for me. There was a group of probably around, I don't know, six or seven of us that were starting in our labs at the same time, and so we would always have these joint lab meetings, and so this was Pan Houston, and it was kind of like, it was almost as much of a support group as anything else to kind of give us that critical mass of ideas and thoughts that were going along the line. So now if we tried to get together, you know, we'd have to rent out part of a hotel or something. But that was a huge thing, because I think one thing that, as you're starting out, you know, seeking out sort of peer review and outside opinions is going to be huge. So the biggest thing I could say is that when you start out a lab, you know, your researchers do your research on the people that you're hiring. When you'll find that it's always much easier to not hire somebody than to be forced with the uncomfortable position of having to remove somebody, you're particularly most susceptible to this when you initially start out your lab as well. You know, there's this sort of saying that if you, one great, for example, grad student can really take you through tenure and get you rolling. But the opposite is also sort of true to some extent, and the fact that if you have a bad seat or a bad trainee or somebody in your lab, they can also really weigh down the lab. And as you're first starting out, because the lab is small, this has a bigger impact than later on. So just being careful about that, but, you know, knowing that sort of you can make tough decisions and you're not alone, that you can also rely on your chair, other committee members, and certainly human resources if you need to sort of go that route. But don't be, you know, don't be scared to take a look back upon your lab every few months and just say, are we going to where we need to go? So I think I'll start in there. All right. My name is Matt Sikora. I'm an assistant professor at the University of Colorado Antris Medical Campus in the Department of Pathology. I started my lab in 2016, and I'm currently at the assistant associate kind of bridge. My setting's a little, maybe a little bit more unique in that my department is a clinical slash bridge department. So the Department of Pathology at CU is made up of, I think, around 120 clinical pathologists and then around 16 or 17 PhDs doing basic research. So a little bit different mix, and then we have some different support structures coming from a non-purely basic program. But I started my lab, again, in 2016. I did, you know, Dan alluded to some personnel issues that can sink an early lab. I have some stories that we could share a little bit of where, you know, an initial hire started out good and then turned dark very quickly and, you know, almost did sink my career. But we've recovered since then. My lab is fairly small. I haven't had more than five or six, and that's kind of where we're maintaining it now. My balance, maybe a big difference that's changed since I started the lab is where if you'd asked me, you know, when I was a bright-eyed, bushy-tailed, brand-new assistant professor, I was going to have a pile of graduate students, and the lab has actually transitioned to be more driven by some senior folk and technicians more than students, which I didn't expect but has worked out pretty spectacularly in the last few years. I guess I'll leave it there for now. Hello, for those of you who just walked in. I am Dr. Dakota Nicholas, and I'm an assistant professor at University of California, Irvine. So I started my lab in 2021. So we're coming upon our second anniversary. The lab's been open for two years, and my story is interesting in that I set up the lab at the tail end of the pandemic. So I was actually very lucky in that while I was interviewing, I found out I was pregnant, and I was like, doesn't make sense to transition now. So I deferred for a year and did another year of post-doc and kind of like rode out that year when everything was completely shut down. And then from the outside, I could see that, okay, there's issues I'm going to have to get ahead of, and it was really helpful for me to reach out to other new hires on the campus to say, how did you navigate setting up the laboratory? So I do want to touch on your peers. Anyone who is a step or two ahead of you is one of your best, best resources. They just went through what you're about to go through. They know who to talk to, where to find help. They can tell you where they've tripped up, because I've obviously made mistakes too. And so I recognized very early on that the whole supply chain thing is a thing, and it can continue to be a thing. So know the things that you need early to set up the laboratory. So I ordered cold storage even before I was even on the campus. I found out that I could get my ID and my credentials and stuff before I actually started on day one. So it gave me access to work on IACUC protocols, IRB protocols, everything ahead of time before I was actually there in the space. I gave thought to how long renovations would take, so everything is always going to take longer than you think. And you guys already know this. This is how science works. This is how academia works. This is how institutions work. There is administration and paperwork, and it's a lot. And if you thought it was a lot now as a postdoc, just wait until you become faculty. It is what it is. Yeah, they weren't lying about the email. So I have a lot more, in hindsight, grace for my, like, why didn't I answer my emails? I was like, he didn't see it. It was buried under 30, 40, 50 other emails. So I now have a laboratory of about 20 people. So we kind of have this operation that I think at 20 is, like, the critical number to be this well-oiled machine. We have five graduate students, a postdoc, lab technician, lab manager. I hired lab manager, lab technician on day one who I interviewed before I started. And they have been an experienced person, especially if they have institutional knowledge is worth their weight in gold. She already knew how to do the ordering. She understood the systems. And then she was out here haggling with all the vendors, like, give me a better price. You can give me a better price. Right? Bring your prices down for me. And so I expect that she'll be with me forever and ever and ever and ever. And we are very structured in the way that we run the lab. And I'll talk a little more about some of these points in the slideshow. But I was very intentional about the makeup of my team and how I built it and how I envisioned them working. And the other thing I think is really important that I'll also touch on in the slides is I spent a lot of time with mentorship. So right now the lab is funded. We got funded early because we try to take a lot of strategies that would help us be successful early on and try to plan and think big picture where we're trying to get to really mapping out what we wanted to do with the laboratory and the research. So we're well on our way. And if you have any questions about what's going on now in the field and how does it feel to set up a lab when you know there's supply chain issues or ordering issues or if there's any tips and tricks you can use to navigate all these vendors who want to vie for your attention. I can give you some feedback on that. So I'm going to leave it there. We're going to go ahead and start off with some really broad general tips that are important with Dr. Matsakura. All right. So I'm going to touch on money because that's the lifeblood of what we're doing. I think what's really important, one of the many, many things that we don't learn how to do as postdocs necessarily is how to budget. Many of us are doing this for our personal lives, but typically the scale and context for your startup package is a little different than what you're doing in your personal life. But doing this is really important for you to understand how your startup's going to work, how long it can last, where you're going to have bumps in the road. And ultimately you have to write more grants to carry on after your startup and you need to know what kind of mileage you can get out of your startup. But here I just have kind of a mockup of how your spending might look for a generic lab. So I'm using some data from the last few years on median startups across biomedical sciences. The current median startups are somewhere around $750,000, so let's just start there. So what I have here is two different lines, the bottom costs being personnel and the top being supplies. This is all based on real data, I'm not making up numbers. But what this includes is the supply costs I've budgeted for a handful of personnel that I'll walk through in a minute. I've tried to assume that first year personnel spend a little less money on supplies while they're learning, and then I've implied some cost of living increases and 8% annual supply increases, which is an actual thing we're all dealing with right now, is that all of our supplies are jumping substantially every single year. But what this actually breaks down is, let's say day one, like Dr. Nicholas, you're able to hire a technician. Our starting range at University of Colorado is around $41,500 for brand new techs coming out of undergrad. What they don't necessarily tell you as a postdoc is that you are also, as PI, paying for fringe benefits for medical, for retirement, at most institutions, that is your problem. So your brand new tech doesn't cost $41,500, your tech with fringe benefits costs $56,500 a year. And that varies at institution and what healthcare package they pick, et cetera, et cetera. Let's say that as a new faculty, you hit the jackpot and managed to hire a postdoc. Based on the current NRSA scales, your brand new postdoc will cost $56,500 in salary a year. Again, you add on fringe benefits, we're up to $71,000 and change. This is dependent on institution, et cetera, et cetera. Let's say after your first year, you managed to get a rotation student and they join. Stipends are anywhere between $32,000 and $40,000, so let's say $37,000 a year. You add in tuition and, again, fringe benefits, which is all your problem, and you're up to $52,000 a year. So that's in the first year. We've hired three people, which is a small but good-sized lab to get you rolling. You can already see that you're eating into a substantial amount of your supply costs. I don't know if my laser pointer is really working. Let's say after the first year, your grad student is outstanding and they get a T32, so that helps cover some of the budget. T32s don't necessarily cover all of the stipend and tuition. It could use you around 85%, so that's what I factored in here. You can see that even with those modest differences, those three people and a modest supply budget, by four years, you've exhausted your entire startup, and most of that is personnel costs. I think for all of us, around two-thirds to three-quarters of our budget is in personnel costs. I've just added on here, if your grad student didn't get the T32, you lost about six months of your startup in extra salary costs. Little things like that make a huge difference in how your startup's going to work. The good news is, on this projection, I didn't add any additional grants. This assumes that you don't get any pilot funding, you don't get a three-year grant, you don't get an R01. That's the good news. The bad news is that this projection does not include any capital equipment, so it didn't include you using your startup to buy incubators and hoods and centrifuges. I did not include any budget for animal studies, which costs tens of thousands of dollars. I didn't include any omics, and I did not include any salary for the PI, because that may or may not have to come out of your startup, depending on the institution. I think it's a little bit sobering to say, yeah, I got three-quarters of a million dollars, but what can I actually do with that? If you don't do that planning up front, it could bite you when, all of a sudden, in year three or four, you're out of money and haven't transitioned to the next grant. Going back to the startup, though, because that is the lifeblood here, when you negotiate your startup, you need to have really concrete ideas for what you need to succeed. This can't just be a nebulous idea of, I need pipettes, and I need people. You need to decide, okay, I have to do a breeding colony for my mouse model, and that needs to be factored into your startup, so your startup may be larger or smaller based on whether you have those needs, or it's, I do mass spectrometry for metabolites, and I need to have dedicated budget for a mass spectrometer, or things like that. Make sure in your startup, when you're negotiating it, you get what you need, but then also, once you get to the lab on day one, you're already thinking about, what do I need to spend money on in the first two years to get my R01? If there is a big mouse study, if there is a big omics study, you need to be thinking about that cost ahead, so you're not inadvertently spending it on pipette tips, instead of getting your omics and your big data done. In that startup, though, make sure when you're negotiating a position, you get it in writing, especially if it involves some sort of fixed mouse cost. Maybe it's negotiating prices on certain core facilities. Maybe it's shared costs for a big piece of equipment. Get it all in your letter. Anything that's not in writing is going to be at your chair, your division head's whims on whether or not they honor it, so hopefully, you can get any required costs for your science in writing and solidified before you start. I think that's all I have for budget, if I could move on to personnel. So your lab is basically the people, and I talked about the budgets of how you pay for the people, and then the question comes about who should you get, and when should you get them, and how do you go about getting these people, so I'd say I think the advice of basically starting small is wise, because you see how much, that way you have more that's left over for supplies. Having 20 people in a lab in year two is bold, it's very bold, but it also depends on what the mechanisms are, and if there's mechanisms already in place, for example, maybe you don't have to pay for grad students, then you can do these types of things, but you also have to make sure that it's not, you can handle that time-wise and everything. For somebody like Taquino, who is extraordinarily organized, this is doable. I think somebody like me that's sort of haphazard, you never know. I think having a technician is key, because you need somebody to basically carry out your direct vision. I think you've heard already about sort of what the value is of finding the good technician who's really going to be somebody that you can rely upon. How do you find that technician? Sometimes you can get lucky, whether or not there's a lab that's moving, or somebody that's retiring, and you can find somebody that, or just somebody just looking for a better scenario. In my situation, I found somebody that was at a different local institution, and I think they didn't care about the money as much as they just wanted respect. And so they were responsible for having the cover images of several journals multiple times, and she was never listed as a co-author, even though she did the majority of the studies. And so she just wanted to feel like she was part of the team. And so you offer them a little bit more money, and you say, you're going to be on all the papers that you do work on and everything like that, and you contribute substantially too. And so you just make it sound like a welcoming place. For recruiting trainees, it's a little bit different. I think you have to ask yourself sort of, you know, grad students and or postdocs, what's the right ratio? You know, as you're starting out, can you get the level of postdoc that you might have been accustomed to? Chances are you might not be able to get a postdoc. It's more than likely you probably can't get a postdoc that was as good as you were to begin with. So you'll also be competing against other sort of big established labs that have a longer track record or a track record compared to you. And so, you know, but there's also something to be said for, can you get a postdoc that's going to be good for your needs at that time? So I have found it, though, easier that when you start out labs, I think it's typically these recruiting questions with trainees are a little bit easier for graduate students. Graduate students tend to gravitate more towards younger faculty and so it's easier to recruit them, but it's up to you to go out there and be seen and so that means that you have to go to join the graduate program, be active in the graduate program, teach classes, go to the go to the retreats. It's one of these situations where it's it's kind of snowballs. And so you at first you're an unknown entity and so people might be a little bit worried about that. Some people will say, Oh, geez, I want to, you know, get to be a part of something new. However, though, you'll find that once you have, you know, one or two graduate students in your lab, the world trickles down that you're not insane and that this is a good lab to be in and so then it becomes easier for like the next round of graduates to come and join the lab. I think, you know, for recruitment wise, I almost kind of view this as sort of if you ever fall like sports recruiting. I think the biggest thing, particularly for trainees, is that obviously this is a step in their career. And so they want to know how joining your lab is going to get them to where they want to go. And so it's key to basically prevent, present a clear vision in terms of what they're going to do in the lab and how they could be successful. I think during for graduate students, you know, you, they typically will do rotations in your lab for a while first. And so as much as you may want and as much as they may ask for it, they might want an impossible project or something that where they're not going to, it's not going to bear any fruit in a couple months while they're there. I actually have found that there's a direct relationship between the success in terms of having positive data that you feel kind of excited about that you generated about and whether or not they're going to join our lab. And so whenever they actually have data that says, man, I think this actually could be like become a real project, it's, it's, you know, it's always our chances of obtaining that graduate student over very well established laboratories goes up exponentially as well. So, you know, don't ever underestimate having a good focused project for them where you think that they're going to, there's a good chance that they're going to yield some generated data so they could be excited about it because the faster that they come up with basically their own data, then they feel ownership over that project and they can then help, helps them visualize sort of how they can be in your laboratory and how they can be successful there. There's the awkward question of what if it doesn't work out? You know, we, we talked about this a little bit when I, when I first said some words. There is, you know, if you have a lab long enough, there are, there's great people, there's good people, there's medium people, and then there, there are always a few bad seeds. You know, with regards to trainees, I don't think that everybody that goes into grad school is meant for this line of work. And so it will become apparent probably, you know, sometimes in a year, two years or whatnot. And it's, you know, what do you do with that? I think it's much easier to not hire somebody than to have to fire somebody. And so that's the reason why I harped on so much doing your background research for who's joining your lab because what you'll also find is that letters of recommendation, that's a good starting point, but don't rely on those. You must call all, all the, the, the references that are, or names of contact information or the references that are stated because things change and there's a lot of things that end up being between the line and letters that maybe aren't written down, but that you can extract from a phone, from a phone call, or even better yet, an in-person meeting where you can then sort of judge a little bit body, body language, tone of voice and whatnot. Let me give you an example. So a few years ago, I had a friend that actually was a colleague of mine that was another postdoc with me in a different lab. And so he was a very good postdoc, he had published in, in, in EMBO journals and PNAS and it was relatively productive and a very well-established lab. And then a colleague of mine at a neighboring institution asked me, he said, Hey, do you know this person? Would you put in a good word for him? And so myself and another very established person in our, in our field basically put in the good word, be like, Oh yeah, I know this, you know, I know this guy, he was fantastic. He did solid work and everything like that. So he's a very sociable person. So I haven't seen him in a couple of years, but he was, you know, this and that. And so, but the letter from the PI didn't say anything more, just said, Oh yeah, he's good, he's solid, this and that. And if he would have contacted that PI, he probably would have found a different story. So it turned out in the two years that I, I had known him, actually turned into a full blown alcoholic. So we didn't know this and I, you know, I didn't know this. And so, and I was like, eventually I found out because your word is your reputation. And I, let me tell you, I still hear about this sort of the fact that I missed this one from this colleague of mine. And I was like, you know, I had no idea. And I tried to warn him as much as I could. I said, listen, I was like, I want you to know that this is a thing. I was like, maybe we'll turn his life around. Turned out it didn't. But there's nothing in it from his PI at the time that said this. And so, you know, so now the other PI is sort of, people say, well, you know, when he said writes a letter of recommendation, we're like, this doesn't mean anything, you know. And so, you know, you probably could have extracted that information if you just contacted all those individual references. But in that situation, you know, it was, the person relied on the letters and so it was sort of a missed case. I think that's a rare opportunity, or that's a rare case, but I definitely think there's, it doesn't, you know, it doesn't take that much time just to get on the phone and talk to somebody. If you're, if you do have somebody that you need to sort of, you know, you need to part ways. I mean, one, you need to figure out whether or not it's you or them, right? And so, and I would seek, you know, I would encourage you to seek outside opinions. And so from your colleagues and whatnot, but then also getting human resources involved early on is important, particularly for a staff because there's, you know, they're there as an employee of the Institute. And so there's a set number of steps that you have to go through. With trainees, it's a little bit different, you know, particularly graduate students you want to talk to, they have a thesis committee, for example, you need to talk to everybody on the committee. That's the whole point. That's one of the functions of the thesis committee. So it's not only, you know, protecting and making sure that the graduate student is doing well, but then also protecting the faculty to make sure that they're not alone in terms of seeing what they're seeing. So unless it's something like egregious, like somebody is like caught making up data or trying to stab somebody else in the lab, you know, more times than not, I think what the best way to handle that is giving them a clear runway of saying, hey, listen, you know, is this really what you want in life, you know, or let's devise a plan here to like basically give you an exit strategy in six months or what have you. And then, you know, it becomes easier, and so that way it gives them time to sort of land on their feet. And I, in the few situations where we have had somebody that basically has left, let's say they leave with a master's rather than a PhD or something like that, I have never heard any regrets from them ever about like, you know, for example, leaving graduate school and saying, oh, you know, now that they're making, you know, lots of money in industry or something like that, you know, they're sort of like, I don't know why I didn't do this earlier or something like that. And so, you know, but a lot of times people enter graduate school because they're not quite sure exactly what they want to do next, and maybe, you know, we realize it's hard to get your foot in the door in other, you know, aspects of industry, for example. But certainly, identifying this early, getting other people involved, I think, is going to be a huge benefit, all right? So one of the other things is that I want to talk about is sort of when do you write your first grants? Easy answers now. So when you, you know, I'm a big believer that when you're transitioning to your first independent faculty position, you're going to have downtime because you won't have people hired, you won't have supplies. I started my first lab in 2010, that's when I moved there. My lab actually didn't get built until 2011. And then when I moved to MD Anderson, I arrived in 2017, my lab didn't arrive until 2018. And so it's just a fact of the matter is that, as Dr. Nicholas said, the red tape takes time and set up and building takes time and whatnot. And so, you know, that's also a great time to basically collect your thoughts and get some outlines of different ideas that you had to submit some grants. I think that you'll find that when it comes to reviewing your grants and how they're viewed upon, it's different at different stages of your career. Make no mistake about it, still federal grants, things like NIH grants, DOD, what have you, are still viewed as a gold standard because they bring in what are known as indirect costs, and so that's direct money for the institutions, but money is money also. And so if you get it from foundations, wherever, that's all beneficial. I think the important thing is you don't feel, you don't have to feel like you have to go get the R01 immediately. When you first start out, you're in this kind of awesome phase where, you know, you're just starting out your lab, every other faculty member has been through that position, they can relate to you, they're willing to help you. It's a great time to mooch reagents off of other labs because everybody will help you. Plus they also realize this is something that's new that's coming into our field that's going to be probably there for a long, long time and review my own grants and my own papers, and so they want to be kind to you. So you need to harness that, you know, you need to harness that sort of time while you're there. You have early on, before you get your big first major grant, you're known as an early stage investigator. That's when you can also apply for all these different young investigator awards, of which there's a smaller pool that you're competing against, and I think this is the perfect time to like go and try to get a lot of these because the bar is going to be a little bit more manageable for those, and I think showing any track record that you're able to put together ideas on paper and get funding for independent ideas looks as good as papers, plus it lines up and when you have, for example, your third year tenure, P&T tenure review, just to make sure that you're making progress, you have something sort of in place to show, you know, maybe I don't have $50 million in direct costs, but, you know, I clearly can put together ideas and gain independent funding for them, and it's going to be, you know, a huge step for you. It shows that progress in the field. I also think there's something to be said for, now the game has changed a little bit in the fact that back when I started out, you actually were only allowed one resubmission for NIH grants, and so you had to really think long and hard about it. I still think it's a good idea to ideally have one paper published to show that you could, you know, function independently for when you submit that first huge grant. But I also think that there's something to be said for, if you go after all the Young Investigator Awards for the first few years and then later on you go, you know, knowing that maybe it will take a submission or a third try or something like that to get your first big grant, too, if you have a big pile of federal funds while you're going up for tenure, you have this sort of unspoken argument that, like, you can get rid of me, but then you're also going to throw away a whole bunch of costs, you know, or direct dollars also and indirect dollars for the institution as well, and so it's always nice to have some stable source of funding while you're going through the tenure decision. So, you know, keeping in mind that, you know, there's also sort of this, do I go big or do I go little on the papers and the projects. I think that it's much more desirable to have five, you know, smaller studies or that are in tried and well-respected journals than it is to have the one mega, or actually zero mega papers after five years, because then people are going to start worrying, and you know that there's all sorts of things that if you go after cell science and nature, the stars have to align for these things to have. Now, if you feel like you have a project that's worthy of that, you might only get a handful of those things in your career, so you've got to go for it. But certainly, you know, don't forget that having small, or basically, you know, moving the field forward like brick by brick is definitely viewed as a positive and shows that you have a clear vision of where you're trying to go with this, as long as they build a story and you're trying to move the field forward. So I think that's probably where I'll leave this for right now, yeah. Okay, so now you've landed, you have a lab, you're trying to figure out how to get people in there, you have people in there, how do we establish a working group in a lab culture that's actually going to be beneficial? So I do want to spend a little bit of time talking about establishing a lab culture, and I know more and more recently this has become, or it's on the radar of people that we need to be intentional about how the lab culture is established. So one of the first things I recommend, as Dr. Frigo mentioned, that you do have downtime at the very beginning where, like, you just can't do experiments, there's no tissue culturehood, there's no pipettes, there's no stuff. And so one of the things that you can use some of that time for is to create what I call a lab manual. There's plenty of examples online, there's labs that have them, but a lab manual is basically a contract between yourself and your future trainees, future lab members, of how do we expect ourselves to operate in the lab? So as you probably surmise from some of these comments, I'm OCD, highly, highly OCD, and I claim it. In my lab manual, it's pretty lengthy, but my students can attest to, before you can rotate my lab, before you consider joining the lab in any capacity, whether you're undergraduate, grad person, postdoc interviewing, you have to read the lab manual, and then ask me any questions so I make sure that you understand what I expect out of you. In that lab manual, you know what you can expect from me as your PI, so that's my contract with you, you can know what I expect from you at whatever different career stages. You know our policy on going on vacations, and taking breaks, and traveling, you even know our lab music policy, it's like, okay, at 10 a.m. we can turn up, and if you don't like the music, we have another room you can go to and study if you need quiet time. But just understanding how the laboratory operates. So one thing I want to say is that once you have that lab manual and you decide what this lab culture is going to be, and as we know, lab culture is different for everybody, right? There's different types of personalities, and you envision the way that you want to work. I've been in laboratories where everyone has their own individual things, and that's the way that they work. I've been in labs where everyone is super communal, and it's just too much, and people are using my stuff, and I go to plan an experiment, and the things aren't there. That's also happened. So you figure out what you think is the best way for your lab group to operate, and then use that as part of your hiring criteria. It's like, do you want people who want to help others with experiments who will be helpful? Do you want people who are willing to train undergraduates? Do you envision yourself taking in undergrads in the summer? You want trainees who are like, oh, yeah, I want to train undergrads, or there's some who are like, no, I really don't want to train others. I want to focus on this, and I have these goals afterwards. So think about those things when you are bringing people into the lab, especially for that very first hire or very first graduate student. They will set the tone for every other interaction that comes through your laboratory. And once you have a culture, it can be very, very hard to change. So think very much about the size, the composition of your lab group. So I already mentioned, like, my lab group is big, and this is what I have always wanted. And I had a model. I've actually never personally been in a big lab, but I've been, like, big lab adjacent, and I've seen it work very, very well. And I used my co-mentor's tools for how she basically set up a hierarchy in a way that she can get to know every single one of her trainees as one-on-one time with all of them, and can help them get to their career goals. So know what your lab size is going to be. I figured that I want to be graduate student heavy. So I made an intentional effort to really, really strongly recruit graduate students. Right? I took time to set up my lab website. I set up a Twitter. I set up a TikTok. I would go to recruitment events, and I would talk to these students. I would email people and talk to them even before I was a faculty member. I made my presence known so I could recruit the students. And I really love having graduate students because they're so, like, energized and excited, and they can bring all these new ideas, and they have this naivety that really helps bring new things to the forefront. I want to do science in a bold way. So that was important to me. Then we also want senior leadership in the lab. So I wanted to look for a postdoc who was really, really good, and could be someone that the graduate students could look up to. And so I was very lucky to get an amazing postdoc, which is very hard for young investigators to get. So, and that's the sense. So we've already talked about good hires, bad hires. It's okay to wait for the right hire. A bad hire, especially for a postdoc, they're very, very expensive based off of your budget, and they can suck a whole bunch of money if they're not good. Okay, so we said set up the lab to reflect the lab culture. When I say set up, I mean physically. If you get a chance to renovate your space and put in the instruments, think about where you're going to place what instrument, how you're going to place the hoods. Are you going to have a bench that every person gets an individual bench, how they work, and they can organize themselves? Or is it, okay, we're going to do all PCR here and all Western blotting there, and I'll set up for this type of experiment there? Think about physically how you want this space to work, how you want it to run, because it will set itself up if you don't do it, if you're not intentional about it. So expectations for lab culture. Just because you write a lab manual doesn't mean it's set in stone. You can come back to it and revise it, and I suggest once you get more than two people in the lab, sit down, talk about it. Ask them, what do you think about this laboratory manual? Are there things that we could change or update or do better? And really, you want investment from your whole entire group of members in this lab manual and the approach that you're taking for setting up the culture. So the last thing I have up here is that you have to model the culture that you expect out of your trainees. For the most part, you know those photos where you see the dogs look like they're owners type of thing? That's kind of the lab. And for the most part, you will see the energy of the lab usually tends to reflect the PI. But if the PI is not there, if you're not hands on, if you're not involved in any type of way, if you're not... Like I said, if you are not purposeful about the culture in that laboratory, it's going to make its own culture. It's going to become its own thing, whether that's for good or bad. So the main point I want to make just off of that slide is that if you do not create the lab culture, it's going to create itself. And you don't want to let it create itself, because as I mentioned, it is really hard to change culture once it's already entrenched. Okay. Last thing I want to talk about is mentorship. So as postdoctoral fellows, you are very, very keen and aware of being mentored. You have your PI, you have your system. But then when you land, like you do all that EH&S training online and it says, oh, if something happens in the laboratory, then contact the PI. And you're like, oh my gosh, that's me. And then so you realize that when it comes to the laboratory, you get to make all those final decisions. For the most part, you are it. But just because you are at the top of your lab, at the top of the hierarchy, doesn't mean that you don't still need mentorship. As a junior faculty member, you are a baby PI is the way I like to say it. So if your university or your startup package doesn't include this is your mentorship team or mentorship plan, be proactive. Seek out mentorship. Really, really lean into making sure you have people who can help you along the way, people you can ask and answer questions. So one way to do this is to do an individual development plan. And hopefully all of you have heard of that. But essentially, it's just finding a way to map out your long-term goals. As junior faculty, one obvious goal is going to be to get tenure. Make a plan for what you expect, what you see over the next five, six years. Get people who are senior in your department who understand the institution, have the institutional knowledge and ask them to give you feedback about your plan and what you're doing. Does this make sense? Is this logical? Do you have hires? Who is going to interview your candidates if it's just you in the laboratory? Ask neighboring labs or mentors to, can you look at this candidate? Do you think I should hire them? Why or why not? Can you help me? Do not be afraid to ask. And as Dr. Frigo mentioned, at this stage in your career, they're really willing to help you. They want to see you succeed. They didn't spend a year and a whole entire search committee and interview all these people, spending all this money on hotels and going one-on-one interviews and going out to dinner when they wanted to go home just to have somebody come to their institution and then fail. They do not want you to fail. They are invested in your success. So lean into that. Okay, so what I do for myself, I actually schedule annual or biannual formal meetings and I just feed them and everyone has to eat. So it makes it super easy. Like, okay, can you guys have a lunch meeting on one of these days? And they're like, okay, sure. And I present my plan to give me feedback. And it's always been really, really useful, really, really helpful. It's helped me course correct before making a giant mistakes that I thought like were great ideas and they weren't great ideas. Cause you know, obviously I'm always right, but yeah, I'm not. But my mentors, they'll go out of the way to tell me and to help me and to support me. And then the other thing I want to say at the very end is connect with peer mentors. I've mentioned it more than once. They are such a huge resource. Peer mentors can be at your institution, in your department, but they can also be online. They can be on Twitter. Find community, find people that you can ask. And at the end of the day, the more mentors you can get, and there's going to be a whole session on mentorship tomorrow. The more mentors you can get, the more you can spread around these questions. And then the whole feeling of, oh, I don't want to ask, I don't want to bother them. It's like, well, I only asked them one question. So it's not a big deal. If you're asking a whole bunch of different people one question, you get a lot of feedback and you don't inconvenience anyone. So at this time, we're going to go ahead and open it up for questions. Any questions that you have about starting up a lab, whether it's about culture, budgeting, finances, planning, we have a whole breadth of experience over a lot of time and a lot of different models for what we're doing. I am also at a undergraduate institution where I teach undergrads. So I had to consider my teaching plan and setting up, which is also why I kind of went so fast getting everything done, because I had to teach. But if you have questions about that or managing teaching and setting up the laboratory, we can just speak to that also. So at this time, we'll take questions. You can come to the microphone. While you're coming up, I do want to echo the importance of peer mentorship. Becoming a PI is one of the most weirdly isolating experiences in your career, because on Friday, you're a postdoc and you can be friends with everyone in the lab. You can hang out with them, you can go out for happy hour with them. On Monday, you're a PI and you can't do that anymore, because now there's a power differential. And at your new institution, you're navigating, now I'm senior and I can't have the same relationships. At the same time, I'm navigating the power relationships in my own department, in my institution. So having peer mentors and developing that network is gonna help you have a community to navigate this transition. Dr. Frigo has been one of my peer mentors for years now. And I value that immensely. And there's actually, there's a group of us that have made this kind of peer network to facilitate that. And I hope you all can find that kind of thing. But it is, I think you'll both agree, it is bizarrely isolating going from trainee to boss over the course of a weekend. Yeah, it is. Good morning, y'all. Well, thank you for such wonderful and insightful presentation. I guess the number one question for me was, when did you all know that you wanted to start a lab? I mean, I'll admit I'm maybe a bizarre phenotype at this point, but I've known for a very long time, since undergrad, probably. And I think among my postdoc lab, there were 20, 25 of us across the lab group, and I think I was the only postdoc that was academic or bust. I'm pretty sure that phenotype is rare now. That's not me. Yeah. So I actually, I went, where I did my postdoc, the overall, because we had a huge, at the time, we had this huge, more than half the lab was funded by industry. And so most people in our lab actually went industry, and I was one of the few people, and I thought that's what I wanted to do as well. And I was probably one of the very few people that actually swapped and went from industry to academia. And I don't really know why. I think I always wanted to start my own company, but I was too chicken to do so. You know, and I felt like running your own lab was kind of like the best of all worlds. Like, if you're doing well, people will leave you alone, but I didn't have to set up insurance plans or anything like that, because you have the sort of backing. When I was near the end of my postdoc, I thought, I was like, oh man, there's still so much I didn't know. And so I thought I wanted to go, I needed more experience. And so I had thought about doing a second postdoc in a big, and at the time, I didn't have any animal experience, very much animal experience in it and whatnot. And so there's this huge lab that was up in Monroe Sloan-Kettering in New York. And I went up there to interview, and he talked about sort of commitment and everything. And he basically said, oh, yeah, I'm thinking a couple of years and I'll probably be ready. He's like, well, we need somebody for about five or six years. I was like, I'd really like one or two years. We really need five or six years. I was like, hmm, this isn't going how I thought it was gonna go. And one of the people in his lab said, why don't you just start your own lab and just hire somebody that can basically do these other things that you can't do or something like that. And so I came back and I talked to my current postdoc mentor and I was like, you know, I was like, yeah, I was like, should I? I was like, maybe, I was like, it's a decent point. And he said, why don't you go for it? He's like, you're never gonna know until you try. And so sure enough, you know, then I said, well, let me go and at the time I had a K award. So there's a little bit of flexibility that the fact that I could test the waters and if I didn't like it, I can, you know, pull back and like just wait until the right opportunity came forth. And so after going on some things, I thought that there was a good landing spot. You know, as I mentioned, I had this really good support group in Houston at the time of like people that were just starting out. And so then I made the jump and sure enough, you know, I said, I hired my right hand man slash woman, Jenny, who's my lab technician. And the first thing, you know, her strength was actually animal models, which is one thing that I really didn't know how to do. So, you know, I actually wasn't positive, but I, you know, I knew that I sort of like, I liked the independence and I sort of liked what I was doing on it. And I just, I valued the freedom that academics come with. So I admittedly, my wife is in industry as well. So I kind of get to scratch that itch separately by seeing her go through the emotional ups and downs of startup companies and everything. So, but yeah, I, you know, you can always argue that like, you're gonna need more experience or one more paper, this or that. But at some point though, you're just never gonna know until you try. Right. And so, you know, I always say, I was like, well, if you don't think you're ready, listen, if you go out there, put your resume out there and start applying. And if nobody hires you, then, you know, probably you're not ready. But if people are interested, then, you know, it's probably a good time. So. That's true. I did that whole cycle. Didn't get any interviews. Okay. So just a reminder, if you don't wanna come up to the mic and ask a question, if you go in your app on the session, there's like a comment session. So we can see the comments and answer questions that way too. But I knew I wanted to start my lab my second year of grad school. I fell in love with the research question. I just wanted to know like everything about diabetes. And I just decided I had to do this for the rest of my life. And it really was, you know, academia or bust. There was no, there was no plan B. I didn't believe in plan B. It's only plan A. Like I wanted it so bad it hurt. And I just decided I was gonna do whatever it took to make sure that I got there. And in my like scheming type of way, I made my 10 year launch plan, right? And so here I am, I have my laboratory now and it worked out. So I say, once you know this is something that you want, or even you have an idea if that's what you want, like make sure you talk to your mentors, start figuring out a plan, start working towards it. Cause it's not a small feat to land a faculty position. You do want your support network, you want people behind you, you want a really strong application. And you have the researchers, the resources like within your labs, your endo in order to make that happen. Okay. Other questions? You know, there is a, there's a question about whether or not this is going to be available as a recorded session. I believe this is recorded. So at some point it will, right? Yes. Yes. Yeah. Okay. So, so I want to introduce myself. I'm Fei Chen. I'm actually from NIH, NIAMS. I'm a program director. I just wandered in because this is interesting. So I want to ask a question maybe for your comment. We were actually discussing, so I was a PI before I became a program director. So I, you know, a lot of your comments resonated with me. So when you look back, what kind of training did you wish that you had before you became a PI? When you were a graduate student or postdoc, like what kind of skills? I know, like myself, the things, when I was a postdoc, you know, graduate student, I was very good at, you know, experiments, designing, blah, blah, blah. I wrote a, I got an F32. So that's good, but I didn't have a K. And then I became a PI. All the skill sets were just totally new. That, that, that, you know, that's required. So if you had some suggestions, what would you say for people who might be starting before they became a PI, what kind of skill set or what things they should pay attention to? You're gonna explode, go ahead. Isn't that obvious? Okay, so first of all, I was very, very lucky to be in NIH funded programs the entirety of my academic career. So I was in structured programs that started showing me the skills I needed to develop. And specifically when I was a postdoc, I was in the ERACTA fellowship at UC San Diego. And that's where like the whole black box just got opened up. I was like, oh my gosh, it's the holy grail. So there are a whole bunch of other skills that we don't focus on as postdocs. We do like the research, we do grant writing, we know we kind of have to mentor, maybe teach a little bit. But all these other, what we call soft skills that are gonna be really big components of you being a faculty member. One of them that we touched on was budgeting and understanding how grants work, learning like institutional policy. That one's a hard one. And so that one's gonna be like a school of hard knocks. You're gonna learn as you go whenever you arrive at that institution. So just be okay with knowing you're not gonna know how these institutions work on inside and out, but to access any type of administrative support that you have. If they don't have orientation set up for you, ask them for an orientation, ask them for onboarding. How does your grants management work? How does your systems work here? How do you do hiring and personnel? How do you write a job ad? Those types of things. If you can look for, there's the online academic summit. I can probably, I'll find it and I'll put it in the chat for this meeting. They have some webinars about some of these soft skills that I was lucky to have been shown that I needed to learn. One of them is managing a laboratory group. How do you manage personnel? How do you deal with conflict within a personnel? Like my first year in a lab, I had to deal with internal lab conflict. I had lab members secretly dating that they thought I didn't know they were dating, right? And then of course there's a breakup and a fallout. I was like, well, what do you do? How do you manage that? It worked out well, it worked out well. One of them, I got pushed to Berkeley on a Fulbright scholarship. We're good. So that's another soft skills, like how to manage people. And at the end of the day, the most difficult part of your job is going to be managing people. And that's what you have the least experience with. You can't necessarily gain the experience right now. You can have like one or two trainees or mentees, but you're going to have to learn how to manage people. So any resources you can take on that is great. The other thing that I was okay at, but not great at, was strategic planning. Because you really are a small business owner when you have a laboratory. And when I say I was in shock when I figured out how much people actually cost, I was like, oh, no one told me this is how much personnel costs. So I'm happy you're like seeing this now. This is information. People are expensive. And then so you start learning like why sometimes your PIs did things a certain way. And then so finding a way to balance that idea of yourself, like thinking about the money and thinking about like the person, right? You want to make sure you pay people in a way that they can live and that they're comfortable, not struggling and starving and doing side hustles in the middle of the night and like, you know, editing papers and what I do in a postdoc. So you got four jobs at one time secretly. Yeah, don't make your students do that. Think about how much people cost. Like, is it better to have one postdoc at a higher salary or two postdocs because you just want to be able to get the most amount of stuff done? So how are you managing your budget? How are you thinking about the people in your laboratory? Another one of the skills that I think is really important for being a PI is sharing your work in a really, really clear, easy, succinct manner. You get to interact with so many more people once you become faculty that you didn't realize you were going to interact with and you want to be able to share what is your research mission, what is the vision you have and what is it that you do? What is that long-term goal? Like know your research program. When you put together your application materials, you should be thinking about this and this should be really, really clear and concrete by the time you get there. But that's one thing you want to practice is just sharing and communicating your science and in a way that is exciting and gets people on board. The other thing that, so many things, so many things. I want to come back and touch on that I think was really important is how to manage what grant opportunities you are going to apply for. So when you're an early stage investigator, it's a short window of time. You only have so much time and you do have to prioritize. It can be very easy to just write a whole, whole, whole, whole bunch of grants and hope something sticks, but you want to make sure you're putting in the effort to make your grants good and that the opportunities that most likely match that you have the highest opportunity of getting, that you spend the most amount of time putting together. You think reviewers can't see it, we can see it. We can see a grant that was put together well, that was thought out, that was organized, it's clear, it's concise, it conveys ideas that you want it to convey and you cannot do that by just writing last minute and writing a whole bunch of grants. So make yourself a grant writing plan. And I figured that out maybe about six months before I started my faculty position that I need to figure out what I can apply to and what I qualify for. I missed a couple of opportunities that would have been like perfect opportunities and it sucks when you miss opportunities. So contact your grants office. They usually have like a whole repository of things that might match up with your interests. Tell them what your interests are. They'll probably give you a list you can apply to, organize them by due dates, by how much money they would bring into the laboratory and then by the likelihood that you're gonna get it and then spend time on the ones that you have the most opportunity of being awarded. And then so those are the things that I was able to learn by being in a environment where they were constructive or deliberate about the skills that we needed to learn outside of just doing bench research. Let's see, I could share. I'll go ahead, do you have any other comments on other skills? I think, I mean, those are all fabulous soft skills that you have to have as PI but really it's everything to do with people management. I think any courses or workshops you can take on leadership styles and communication styles, the latter being particularly important. I think as PIs, we all kind of fit in a pretty narrow band of how we talk and how we think but the people in your lab aren't going to be you and one of the best things I've done as faculty, sometimes with my personnel, sometimes independently is taking those like communication style workshops, understanding how you talk and think versus how the people in your lab talk and think because it can make a world of difference in maybe empathizing is the right word with how what you say comes across differently to your lab and vice versa. And that's not something we learn as a postdoc. You're just trying to get your science done. And then from the leadership perspective, it's I think so much of being a PI since pretty quickly you're going to be away from the bench because you have too much other stuff to do and to really advance your science, you need the people in your lab to be as passionate about your ideas as you are. They need to own it the same way you do. And it's not trivial to, it's part of building your lab culture but it's not trivial to get those ideas across as a leader that it's, we are kind of a shared goal and you need to learn how to establish that in your lab so that everybody wants to succeed as badly as you do, whether or not they communicate the same way. Yeah, I'll make it short. I just, I'll mention two things that were available to me but I haven't seen available widely everywhere. And then one thing that wasn't that you've heard everybody talk about and sort of what I've done to sort of overcome that. So, the first thing that I think was one of the big advantages for me is that when I was a postdoc, I was given essentially half of lab technician when I got my K award too. And that was huge for me. And because I mean, basically it, even if it's just a fraction of a time having some sort of commitment, if you can talk to your advisor into it, chances are if you're on the job market, you've been pretty good and so you've done good things for the lab. And so you can, now's the time to ask for a couple of crazy things like that and just say, hey, I really want to expand my work here. And that teaches you basically, entry phase sort of how to manage people. And at that point, it's just a one person. So it's pretty doable. I thought that was very valuable for me. The whole sort of how to put together, I mean, hopefully this is something that you'll be getting feedback from your mentor, but then I tried to always, when I was a postdoc, try to soak up as many of these grant writing courses, just scientific writing courses that would always come through. Not every place has that or not every place advertises that very well. But if you can do that, especially at the same time that you're writing a fellowship or a grant or something like that, it's golden. Because even if it looks like a grant that follows almost something formulaic, if you can put your writing in easy ways for people to find what they need to find, and it takes less reader energy to basically go through your grants, I mean, that's, there you go. The thing that was hardest, I think, as was mentioned by everybody else up here too, is personnel. And so I got a headstart in the fact that I had a manager, but still there were a lot of issues in terms of like, well, how do you go about getting, how do you go about finding the good ones? How do you make sure that they're good ones? So something that I didn't know about or didn't really think about much when I first started out, but now I definitely do it, is that if I have, for example, a graduate student or a staff or a postdoc come in and interview with me, I make sure that they actually, I'll ask my fellow faculty members if they can interview them as well to kind of get an independent opinion to sort of think like, give them a thumbs up or a thumbs down and everything. So, because, you know, sometimes you get sort of, when you first start out, right, you just, you're so, you just want to hire somebody so bad, right? And, you know, you need to be a little bit choosy early on because, you know, as we said, it can, you know, it can certainly make, and sometimes in bad case scenarios, break a lab. So the personnel getting sort of surrounding feedback is always very important. Is there a question in the chat? Oh, there might've been. Oh, yes, there is a question in the chat. There we go. Yes, so the question is, hi, do you have any suggestions on when a lab should start looking to hire a technician or postdoc? Our lab is looking to expand and we currently have a lab manager who handles supplies and three grad students. The lab manager that just grad students? Let's see. What's the question again? Okay, question is, do we have any suggestions on when a lab should start looking to hire a technician or a postdoc? And their lab is looking to expand and they currently have a lab manager. The lab manager handles supplies and three grad students. So I'm thinking this is a newly established lab, lab manager, three grad students, and they're thinking that they want to hire a technician or postdoc, when they should start, should they start looking? I mean, I think if you have a need for it, and if you have the, more importantly, if you have the money for it, you know, now's probably a good time as any. So I mean, I think my point earlier was that don't just hire people for the sake of hiring people to have, you know, some people just want to feel like they have, and there's something to be said for having like basically enough people there for a critical mass, but I mean, I definitely wouldn't hire somebody unless you know that you have bona fide experiments or jobs for them to do. You don't want to hire a new technician and then all of a sudden they're, you know, fiddling on their iPhone like 75% of the time, you know, because it would be boring for them too. And so if you have a bona fide need and you've got the budget, I don't see what the hesitation is. Yeah. I mean, I think it's, while you do need to kind of be deliberate about hiring, at a certain point you're being judged on productivity, if you've got the budget, you've got the need. Don't wait for some mythical idea of a person. If you have an opportunity to hire somebody, hire somebody. Yeah. I also say too, like, I'm also a big advocate of, you know, saving a little bit of money to like, there's something to be said for hiring somebody, but it's also nice to have a little bit of a rainy day account and a rainy day fund because, you know, for various reasons, I mean, lab budgets go up and down, up and down, but also you never know. You're going to, maybe at end of 2023, you're going to meet the chosen one, you know, who wants to come to your lab. Like you better make sure you've got money for the chosen one to show up in your lab. So. Okay. And that's one other thing I do want to say about looking for a postdoc. I feel like it's never too early to start looking. Finding a good postdoc does take time and sometimes you want to catch a grad student when they're year three or year four and then like start talking to them, like, okay, you're going to come here. So always be on the lookout for your postdoc. And then a lot of times universities can have like blanket ways that you can pull in a postdoc quickly. You don't have to necessarily post your own posting to pull a postdoc in. So figure out what are those mechanisms to hire. And I would say don't, don't wait, make sure you're actively looking because they are, they are hard to find, especially, especially right now. Industry has their claws on everybody because, you know, they're making good money. But yeah, if you, if you see a postdoc that you like, get them out, interview them, make sure you get all the background resources on them. And then if you have money, the budget and the need, go ahead, pull the trigger. Okay. Hi. Hello. Hi. Hello. I'm Marie Caro. So I'm from Chute-Québec-Université Laval in Quebec, Canada. I'm a new PI since 2019 and I'm a clinician scientist. So I'm doing clinical and research and I'm preparing a six-month maternity leave. So I would ask for your advice of leaving as new PI your lab for six months. What would you do to make sure that your culture persists? That what, what would you think would be very important? Do you have any role model that you've seen that worked well for six months out of your lab as a PI? Well, I have a role model at my institution who just had her, I guess I'm just, had her baby a year ago and then I basically watched how she did it. So she essentially already had her laboratory in a way that most people were pretty independent. So she took her leave and she did stay home and she took like her one-on-ones over, over Zoom and then when she felt up to it, she would come into lab and visit. If you're, cause you're in your just finishing four years. So the people in your laboratory should be pretty well, well trained and like obviously you're here without them and they're doing okay. So the, they're doing okay. So one of the biggest things that I believe from what I've seen from the other women at my institution is being able to trust the people that you put into your laboratory, to trust that you have trained them well and to trust that they know when to ask and reach out for help. That time of course is precious with your child. You cannot get it back. So don't compromise that time. Your lab will be, your lab will be okay. They'll be okay. And you know, you can tell your laboratory, like if it's an emergency, you can text me, but for the most part you guys would be okay. So plan your meetings with them and you can do them over Zoom. Stop in when you feel like you just need a break, when you just want to watch the baby and I just have to like, I need like the lab and I can't be with the baby anymore. Go ahead and go in and take your break, but I, you, you'll be fine. It's really mentally like letting go of the idea of I have to constantly be overseeing it in order for them to be okay. Yes. Hello, I'm Ramon for Albany Med. My question is more like a day by day in the lab because starting a lab, the budget is limited. We don't have a lot of money. I have an idea, the project I want to start, but when you start to think like, okay, this idea is not working, I try different times, I need to kill this idea because once I was listening to a seminar and they say like, the difference between the academia and the industry is the time that they kill the projects because the industry grow really fast in academia like we stay. So how you manage that and how you like, oh, I spent money, time on this and now I'm just going to put this by side. So how you handle this when you're starting? I mean, I, I'm a, I mean like I, the one thing that I will not tolerate in my lab is just being a chicken, you know? And I was like, if you've got an idea, like I'm, I'm all supportive for like having independent ideas, but I was like, you've got to like, we've got to come up with the, the killer experiment that's basically going to, you know, a go or no go experiment that could shoot it down. Right. And you've got to, and if that means you have to expend a little bit more funds, so be it, but you know, you certainly can't be scared to shoot something down, you know, and you don't want to be, you know, spending time and time and time if every answer you get is like in the gray zone, you're like, maybe, maybe if you look at it this way, you know, with a glass of coffee or, you know, a cup of coffee or something like that, then it's, it's going to look this way. So, you know, I, I just say making sure that you design basically the, you know, one or two key experiments that are there. So I mean, certainly, you know, with that too, I mean, you don't need that much data then for a small pilot study project grants that are going to be out there. And that, that's kind of one of the advantages of not just start up at any sort of foundation grants or, or you get, you know, these smaller sort of high risk, high impact proposals. So yeah. Yeah, I, the, I think one of the benefits of being early is that you're going to be eligible for like state foundation funds, institutional pilot funds, like the little grants, like 10, 20, $30,000. And while you do still have to devote time to those things, at least you can, you kind of have a safe little pot of money to blow on a new idea and you're right, you still have to decide at some point to kill it. But when you have that kind of safety net, it's really beneficial. As far as killing, it's hard. I mean, but I have my own projects that after, you know, 12, 16 months of trying to get funded, nobody would fund it. It's like, okay, I'm tired of writing the grant. So it's time to move on. And maybe the idea, you know, percolates and once in a while you write a pilot, you know, a few years later or something, but I've personally, I've been trying to use, if you can't even get a grant, like in the discussion range, maybe it's time to put the idea down for a spell, or if you can't get a pilot award, like that's, if you can't get 10 grand to do an idea, it's probably not that great of an idea at a certain point. There's kind of this general rule of thumb for like, for example, with NIH grants, it's like if you, if your idea gets, if you're, let's say you submit an R01 or something like that, I think it's triage, it's time to overhaul the whole grant and think about whether or not it's a very good idea. Maybe it's possible, you know, you look at the reviews and maybe it's something that was simple that they just blatantly missed and chances are if all three reviewers missed, it means that you probably didn't put it in the right spot. So I also, I very rarely, unless I feel like a grant mechanism like speaks to me and says, you need to apply for this, like I own, every time I write a proposal, I know that it's going to be something that I could submit to like two or three different places, right? So it's kind of like, I mean, there's something to be said for more shots on goal, so. Okay, and then we're going to come a little bit back to the perspective from being early career, you only have so much time, like there's this clock kind of ticking and we don't have like 12 to 18 months to figure out if this idea is going to work or not. We need to try to go where things are going to be productive. And so the whole idea of like having to kill a project, it is very, very difficult. And so what's key is that no or no go, the go or no go experiment. And then so you make sure that whatever question you're asking, the experimental design will give you a very clear yes or no to something to pursue. Then if you get a no answer, you have to be okay letting it go. What happens is that we have this idea and it seems super cool and awesome and then we get the no and we're like, well, maybe if I tested it this way or maybe if I tested it that way. I was like, no, you're gonna have to let it go. I have a folder of what I swore were the most brilliant ideas and it was very obvious from the experiment. I was like, yeah, this is not going to go and I'm not going to spend my energy here because I only have limited time and limited energy. So the hardest part of that whole scenario is letting your idea die because it hurts because it was a cool idea, but sometimes it doesn't work out or the hypothesis was wrong and that's the whole point of testing and being a scientist. So no or no go. When you get the don't go, just let it die, go ahead on to the next thing. You have lots of ideas. Okay. Do we have other questions? I'm Sean Hardick from Baylor. Thanks for the session and the information. I'd like to hear some individual perspectives on the lab meeting and how you think about running it, operating it, because this is an area of lab management that gets very stayed. Thanks. Since my face is already here in the microphone, I will go ahead and start. I have a lot of opinions about lab meeting. When I was a grad student, I was in a lab where for three years I was only a grad student. We had lab meeting religiously every week for two hours. I'm like, what are we talking about for two hours every week and you talk to me every day already. So one of my biggest beliefs is that lab meetings should always add value. And I've also been in a position where I was in a lab where my PI was too busy and we went a whole entire year without ever having lab meetings, so I just ran his lab for him. And then I got in trouble for not putting him in the loop. I'm like, I'm sorry, we didn't have a lab meeting. So also you want to make sure the things that are regularly scheduled, we don't want to overschedule. So whatever time block you're going to use for lab meeting, you want to make it something consistent that students know they have to be at lab meeting. This is not a, oh, I have an excuse or I have an experiment. You plan your experiments around this lab meeting, this is the time when everybody is here in one place. If I'm at the lab or I'm not at the lab and there's not a lab meeting, fine, but we're going to have a schedule. And the schedule, I sit down every single quarter and I set it. We want to make sure that students have a chance to present their work and progress. You can decide whether you want it to be formal or informal, but they need to be able to give feedback no matter where that project is at. And usually I'd like students to give feedback on their project at least twice a year over everything that they're doing so everybody knows. Intermittently, I also believe in planning professional development for your trainees. So here at Endo we're taking the time to put these workshops together because the majority of labs do not do any professional development and students are left on their own to figure out where to get it from. So I always encourage like, okay, maybe once a quarter or twice a quarter put in professional development. I like to sprinkle in journal clubs so that I know the laboratory is getting reading that it's important to core concepts within the laboratory, what we study, but be mindful that you know they have journal clubs for classes. They're reading papers all the time for all their coursework. They have all the other stuff going on too. And the last thing is to make sure that you're incorporating undergraduates into the lab. So have like an undergrad fest. They were undergrads present their work. And I try to use lab meeting as a time for us to do like announcements, updates, celebrations, and that way it feels like a communal time. People aren't dreading lab meeting. We try, we block the room off for an hour and a half, but the rule is if we can keep it at one hour, we're done at one hour so we can get back to the other things that we have to do. So I don't want lab meeting to ever be a drag, but we also want it to be useful and make sure they're getting added value, that we're talking about the science, but we're also developing them towards their careers. I, it was interesting, like during my PhD, we had zero lab meetings. I kid you not. The only time we ever got together was to talk about what's going on on the weekend. So that was something that I craved dearly for when I was choosing a postdoc. And a lot of what I do now for our lab meetings is kind of modeled off of what we did for our postdoc. And so with a few tweaks here and there. So we have our lab meeting like once a week, always Wednesday morning. Whoever presented the week before basically brings bagels and coffee and everything like that, which I pay for. So that kind of entices them to be there. And again, it's mandatory. This is a time that we have announcements. Some people will have everybody in the lab basically present what they've worked a little bit. I actually just have one person at a time presenting so that way we can focus in on the whole story and basically dive in. Because I also feel like there's something to be said for, you know, if you have one person presenting, then they're kind of forced to basically present, still present some of the background. And then you, you don't forget about, you know, you want to see everything in context of the bigger picture anyway. My fear is that if we broke it up and we had, you know, 10 different people in the lab present little, you know, five minute vignettes of what they've done, you know, there's a good chance I might've forgotten this piece of data or that piece of data because you've got things that sort of start scrambling in your head. So but it is, it's, I mean, the biggest thing is it's, it's got to be sort of this critical advocacy where it's like, it's peer, you know, your peers are there, but basically to help it and make it better. And it's kind of like this positive vibe. And so, yes, there's, we're critical of the data and the experiments that are ongoing, but it's all in the sort of spirit of making it better and being supportive of one another. So you know, I, for me, I'm not a big sort of, you have to clock in at such and such a time, you know, FaceTime. I don't really care too much about that, but lab meeting is also when you're held accountable. Like, you know, like if you present lab meeting, you've got nothing to show, you know, you better, you know, have a, have a good reason. And so, and if there's a couple of lab meetings in a row where you don't have anything like that, then it's, we're having a deep discussion afterwards. So I think it's a really great question, Sean. It's one of these things that is, you don't think about it until you necessarily get in charge and you have to actually schedule these things. My lab meeting has definitely changed a lot in the six, seven years I've been in charge and it has kind of morphed based on what personnel I have. I found, you know, when I really only had a couple of technicians, there wasn't critical mass to really have a regular lab meeting necessarily because I was meeting with them, you know, on a regular basis and, and then, you know, through the pandemic, it was next to impossible. Now that my lab has gotten a little bigger, it's, I push very much that I want informality. I don't want only polished stories. I want to see the PCRs that didn't work and where we're having trouble and I want the lab to have that critical mass then to all talk about problems together as much. I almost would rather see the stuff that didn't work than the stuff that did work. So that's what I lean on. And then my lab, we're, part of our lab culture has kind of turned into lab meeting and that's where we spend a lot of time together in one room. You know, we, we're kind of spread pretty far across Metro Denver and all of us, almost all of us have kids, so it's hard to get together. You know, I don't want to, you know, demand people hang out outside of work. So we kind of use lab meeting as our social communal gathering. Usually somebody bakes, you know, and then we do go over announcements, logistics. Like I always start out with logistics, like what's on back order, what's broken, you know, how do we, how do we deal with this stuff? But it definitely like now that I have a postdoc, now we're incorporating journal club because the personnel in the lab now need that and want that. So I have been kind of morphing over the years, but I do have always stressed forever informality. I don't want you spending an hour polishing a talk, but instead I want to see the prism file of the raw data of the experiment that failed. That's what I want to see. One of the things that I want to add about lab meetings too is like when we talk about announcements and everything like that, I also use this, I try to be very, you know, talking about budgets, I'm also pretty, try to be as transparent as I can with my lab about like the state of the lab, so to speak. And so, you know, I let them know, I was like, you know, if, if we didn't get a grant or this or that, you know, sort of, sort of, so I mean they kind of, you know, it lets them know like it's time to tighten up and don't do crazy experiments unless you got that. I mean the converse of that too is I also tell them like when certain grants, of course you want to celebrate when they've been awarded and then people start asking for raises and everything like that. But you know, I feel like that way they feel like they have more skin in the game. And you know, if there's a grant that's going in for a resubmission, say, hey guys, like we got this big grant, it scored well, we're close, something like that, you know, then that way they're, if, I might ask a little extra something of you guys here and there, I mean they know what they're getting in for and sort of, you know, where it sort of fits into the bigger picture. I mean I usually don't ask people to do experiments if it like has no bearing for their own work, so I try to avoid that. I mean that's kind of actually what the technicians are there for to some extent, but you know, just being transparent so that way they feel like they're also kind of part of the team, you know, and all aspects of it. Actually, yeah, that reminds me. So something I've been trying to do now every six to eight months in lab meeting is what is my presentation slot is like a state of the lab address, and what I've been doing is laying out all of the grants that are active, what their goals are, how the grants kind of mesh together, what, and it's, I brought up idea that you want the whole lab to be invested in the success, so I also try really hard when I do these state of the labs to point out this is how we're all working toward the same goal. Even this person's got a genomic project and this person's got a metabolomic project. This is how they're converging. This is where it's working together. This is where our funding is. This is where I see major applications going in, so when I ask you for data in June, that's why I'm asking for data kind of thing. So I don't typically present anywhere other than those state of the labs, but I think they're really important. I think if you follow science Twitter at all, that's kind of been a big movement is a lot of folks are starting to kind of post the general state of the lab ideas, which is fabulous. Ditto. Yeah, I won't say a whole bunch because I can always say a whole bunch. Okay. Any other questions? I know. Well, you've got to get your steps in, too. He's an endocrinology major. We want to make sure that you're— I'm in the conference center. It gets our steps in. My question is, is there any software that you guys learned about after becoming PIs to help with lab management that you wish you'd known about before? Like, for example, our lab uses Slack and SoftMouse and things like that to try to keep everything organized. But is there anything else you're like, everybody should know about this? Yes. First things first, get off of SoftMouse. Okay. Yes. Colony. Transnetics Colony. It's free. It has an app on it. So we use an iPad. We go down to the vivarium. It's great. You can update upstairs from your computer. You can have different members added, and it's all free because their business model isn't for the mouse management, it's for genotyping. So that part's free to have a different way to make money off of you. So you don't need to do that part if you don't want to. LabSpend. So I don't know if all of you have heard of Quartzy. It's great. I got Twitter angry, is what it is, but they lied to me 10 years ago. And so I spent a whole bunch of time investing in, like, setting up Quartzy, and now it's paid. But LabSpend is another option that's free, which you can also set up. So I wish I knew it existed before. It does. Other software that I learned about just for organizing, like, meetings and cards is Trello. Depending on how in-depth you want to use it, there's a free version that works okay if your lab group is smaller. If it's really big, there's a paid version. Let me see. What am I... I have a lot of software set I like. There is... I'm going to go write this down. Okay. Okay. Get the book. I'll second LabSpend. It's... So you use it for organizing orderings. It's a web platform that everybody that has orders can submit to your lab's page, and then you or your lab manager can see, manage, approve, and, like, dictate funding decisions on orders. It tracks inventory. Okay, so in general, too, in looking for software, I have some suggestions in a paper that we recently published about launching a lab. I think it's called The Launch Phase. I'll find that and also drop it in the chat for this session also, so you can have that. So it's a little paper put together of things to consider, timelines that you can use for setting up and getting a lab started. One of the major considerations I want you to think about when you're thinking of any type of software, so for lab notebooks, we use BenchLink. Our lab, our university has subscription to it, so it's free for us. As an academic laboratory, you do not want recurring costs that are annual that are based off of how many people you have in your lab. You cannot have that on your budget. So whatever it takes, whatever you need, if there's something you gotta pay for, it's okay if it's a static and you notice how much it's gonna cost every year, but nothing that's annual, recurring. If you have five people, it's more. Six people, it's more. You can't afford to have it on your budget as an academic lab. It's not okay. So you're looking for free software, and there are plenty of free software that are really, really good for organizing and managing, and if you're going to pay for something, it has to be something that is critical to the operations of your laboratory. The only organizational software that I pay for is we use one called Genifab, but we barcode a whole entire large bioarchive of human samples that we need to be able to manage. So that one is worth us paying, and we know how much we spend on it per year, and it's not a big, large cost that we can't handle that we can't write into grants. I'll just, one of the stupid little things that you don't necessarily think about as PI is so likely you have some sort of electronic storage on your university servers. Depending on that or how your software, like lab manual software might be set up, you need to have kind of ongoing conversations with IT about how the space is managed. Like for instance, the one horror story we have was we had a databasing software for our liquid nitrogen freezers that was housed and it was working fine and it was kind of lived on our department server space. Our department moved the storage briefly out of our department housing to school of medicine space for reasons, which broke everything in our software because of just how pathways were pointed. And even though we've since moved back to the home site and restored all of the points, nothing works anymore. So if you do rely on that kind of software, whether you work out with IT that this path is permanent and never changes, it's little stupid stuff like that where we're trying to write a grant, the last thing you want to deal with is like who moved my server space. It's stupid stuff, but you got to deal with it. Same with like sequencing data, like don't rely on hard disks if you can get dedicated server space. That I think is as important as managing software tools is knowing where your big data is going so you can archive it properly. And now that we have all of our new data sharing requirements, that's going to be a whole nother beast. That's probably a whole nother PDW we could do that I would go to. Okay, so we still have a little bit of time for questions. Any other burning questions while you have us here? Yes. Make the trek all the way back down. All the way back down to the microphone. Thank you. My other question was, do you have any suggestions about how to sort of keep your staff motivated and you, like when you're talking about making strategic plans, in terms of like grants and publication deadlines that are coming up, do you have any way you kind of like, you know, like a whiteboard or something where you keep track of everything and if everybody gets their stuff in at a certain time, like there's some kind of reward or anything like that. Like how do you keep people kind of motivated, productive, but also doing good science to get those things done? It's funny, because my students suggested to me like we need a big whiteboard. That's exactly what they said. That's what they told me, like they want to put everything up. So of course we did, like initially we do that strategic plan, show everyone where their products fit in and what the deadlines are. But I think part of the way, like I try to keep my students motivated is I hype them up, right? I mean, and not for no reason. I'm not just gonna hype them just to hype them. That's not okay. But when they accomplish things, when they get things done, when they overcome a challenging hurdle, like tell them how great it is. Like sometimes mentors don't, I have a friend who's like, oh yeah, we just did this girl's advancement. Don't tell her how proud I am of her. I'm like, why not? Tell them that you're proud. Tell them like, look, this was something that was really difficult to accomplish and we did that. And now we're gonna use it for this. I can't wait to take your data, put it in my grant. And like they get excited to see like how I'm using their data and like writing it up. And it's examples to them. And then so they like knowing that what they're doing is being used and as a part of something. They like seeing how they're advancing and getting closer and closer to that timeline. And in your one-on-one meetings with your trainees, like you go over the data and talk about the progress. And sometimes you have to point out the progress for them, especially when they're in the mud and they're troubleshooting. Had one student basically working on like nanoparticle flow cytometry, looking at viruses, like no one in the world has done this before. And in her mind, she's like, oh yeah, we had this collaboration, we'll start it and I'm gonna finish the whole idea in one month. It didn't take one month, it took six months. And even then to me, I was like, oh my gosh, it was so fast. And then so every time we're troubleshooting, I walked her through like, this is what you tried, this is what didn't work, this is what you learned and you did this next step and you've accomplished something and you have learned something and you've made progress. So you have to take them out of the like, the mud of all the work and like just, this is rough, it's not working and show them how they are making progress and steps they are doing. And like I said, hype them up. Like they are great. You didn't take a student in your lab because they suck. You took them because they're amazing, had all this potential. Let them constantly see that potential and they'll keep on striving and reaching for it. I like to celebrate, the biggest thing that's frustrating is like when you get data and you're like, maybe it is, maybe it isn't, something like that. And so like I make sure that like, if something is clear, clearly has definitively refuted our hypothesis, making sure that they know that that's a good piece of data. You know, that is, the difference between good data, bad data, positive data, negative data, anything like that. I was like, as long as it's good quality data, but it actually gives us a different result. Like that's totally okay. And actually we have learned something from that too. In terms of actually like monetary type things, I do, you know, if there's, and actually our institute does as well. There's a number of different mechanisms. Like if you bring in, for example, your own fellowship, if you're a postdoc or a graduate student, there's extra, you can get an additional bump. You know, whether or not it's a couple thousand dollars, if it's a one-time thing or a few thousand dollars added on top of salary, because you're doing sort of an outstanding job. I mean, obviously it's a huge relief for the lab, right? If you start bringing in a fellowship that pays your way, because that's something that we didn't necessarily plan for in the first place. So that's something to do. You know, again, I think as long as, if you're transparent and keep reminding them and pointing them out, sort of how their data fits into the bigger picture of what the lab is trying to do to make the world a better place too, hopefully they'll take some ownership of that. So. Yeah, same. I think both points, but it's, you need to, yeah, remind them that they're doing a good job. And I think the robust negative data, I think that's one of the things that most folks in the lab will like beat themselves up or, oh, I failed. And it's like, no, this is a fabulous experiment. All your controls worked. We were just wrong. And that's fabulous. But I think, you know, I think one that I struggle with technicians in particular is that it took me a few years to learn is helping them seeing how they're growing, whether that's not just technically, but, you know, especially when you get baby techs out of undergrad, they are also, they're in a different skill development set than graduate students. And they may not have the opportunities to see how they're growing and developing as far as their scientific competencies, their presentations, their independence. Graduate students get more context for that, technicians don't. So I put a lot more effort into building that context myself, whether that's IDPs or just, you know, intentional conversations, but otherwise, yeah, transparency. I'll echo transparency. Thank you. It's a great question. Okay, are there any other questions? We have about three minutes left in the session and I do, oh yes, come, come, please. As we're about to take our final question, please take the time to fill out the feedback forms. You can turn them in on the way out. We really need your feedback. This is how we make this better next year for other trainees. And so we'd appreciate if you fill those out right now. Thank you. It's not a question, but it's a comment. I think getting a grant is very important. Can you? Yeah, microphone. Yeah. Getting a grant is very important. So getting a grant is very important. And I know there are a lot of places for people to get grants, but if you get an NHL one, you're pretty much set in a way. So here I want to emphasize what you have emphasized when people are starting up, when they have the early stage investigator status, take advantage of that, or even new investigator status, because we have reviewer advantage and funding advantage if you're in ESI especially. And the other resource, I was late, maybe I missed it. Talk to the program directors. One of us, from NIDDK, NIAMS, NIA, all these institutes, we are not going to give you anything that's a secret. It's everything, public knowledge, but you'll be surprised. You don't know what you don't know. So we have very good resources. Just don't feel personal if we don't get back to you. We all try our best, but there are so many things. Just be persistent, talk to them, get their advice. We can't help you write your grant, but we can maybe tell you maybe which mechanism will be good and the study section feedback, how you interpret and all these things. It was something that I utilized when I was a PI to a certain extent that I found out to be so valuable, but I could have done much better. And I sometimes see young investigators being shy. Like, I don't want after you, but you need to meet me halfway that way. So I just wanted to emphasize that. Yes, that's an awesome comment. Actually, I want to echo that, because I've seen that amongst my peers too, that they're not reaching out to their program officers, especially before writing your grants, before submitting and trying to figure out what institute it's supposed to go to. And for the most part, program officers are awesome. They are there to help you. They will help guide you. They will give you feedback on your aims page and be like, okay, yes, this is something our institute is interested in funding. This is a good idea or concept. And you want to have that feedback before just sending it blindly to the NIH. As you're learning how the NIH works, it is an intricate system, and it has its rules and its ways, and it is the way it is. And before you actually see a review panel session for yourself, it can be hard to understand how they're judging and evaluating your grants. So we mentioned go to the professional development workshop that talks about writing grants. Like you want to learn the ins and outs of the system, as much practice and advice as possible. I am forever going to grant writing workshops. I will never stop, because you cannot stop benefiting from being reminded of the things that you need to do in order to put together a very, very strong application. So thank you so much for that comment. And I do want to remind, reach out to the program officers. They will guide you through the whole entire process. They are happy to help. And they're masters of reading between the lines. Yes, all lines. Okay, so we are at our time. Thank you so much for attending this workshop, and you can turn in your feedback forms to Jennifer there at the back table. Thank you.

lab management

career stages

setting up a lab

small lab

hiring the right people

budgeting

expanding the lab

COVID-19 pandemic

mentorship

peer support

grant writing

effective communication

early career opportunities