Lindsay K. Pino

CHAPTER FOUR: COMMUNITY

I’ve been pulling together a social circle of chief technology officers (CTOs) in the Seattle area, with the intent of building a similarly-minded community of people to share triumphs, failures, and general camaraderie. It’s not a huge lift, beyond setting a calendar event and adding contacts as I meet them, and hoping that people make the time to come out on the prescribed date at the designated location; however, even this effort is perceived as a community-building accomplishment. To be honest, it’s pretty selfish on my part, because whether I’m giving advice to help someone avoid my own past failures, or I’m receiving advice from someone else’s triumphs, anything that helps the overall startup community in Seattle succeed is a “rising tide lifting all boats” and ultimately helps me look better.

There’s a thing here called the “Seattle Freeze”. It’s supposed to be a particularly region-specific thing where people just don’t want to make new friends, so we all just hole up on our own. There’s additional specific layers to it, like saying to someone “Oh yeah we should meet up again sometime” but then totally ghosting them forevermore, and the “Seattle Freeze” is about building the long-term, regular-frequency connection to other people to build a new relationship.

I’m not sure if it’s really a region-specific thing. Having been a military brat growing up, moving hundreds if not thousands of miles away every 2-3 years, I got pretty accustomed to being a transplant and needing to reform a social circle regularly. It helped me out a lot when I went to college, and of course when I moved again internationally to South Korea (language barrier and all), and I’m not sure there was anything uniquely regionally specific to Seattle when I moved here for graduate school.

I would ascribe it more to the “transplant”-heavy nature of Seattle. Many residents aren’t natively Seattle-ites, but rather moved here for job or otherwise economic opportunity. So with many people not growing up here, with the inherent benefits of making friends through shared childhood experiences like being classmates in school, there’s not that regular, forced intersectionality, sharing the same space with similar goals on a predefined, regular schedule to see each other. That’s pretty common across all “middle-aged” relationship-building. Without the shared space (physical and mental) on a regular schedule, it’s hard to meet new people and build a relationship regardless of the geographic region. Any time there’s a bifurcation in life, it gets harder to maintain an easy relationship without committing dedicated effort. For example, pairing up with a significant other or having children pretty drastically changes the day to day routine for an individual, and that makes it harder to maintain a previously-established status quo like going out for happy hour beers after work or going to shows or concerts on the weekends. Similarly, less positive life changes cause a shift in status quo, like losing a job or having significant health issues. All of those changes can lead to altered relationships, and make it hard to “make” or “keep” friends.

So all of that said, I don’t think it’s unusual to make new friends for Seattle specifically, it’s maybe more a specific demographic that happens to move to and live in Seattle that has more of those changes in status quo without the easy historical relationships of growing up and going to school together as native Seattleites.

Instead of depending on those easy relationships, you have to build your own community. Being the perpetual “new girl” in school growing up, I built some positive and negative responses to community building. The maybe more negative side was retreating into escapism, mostly in devouring fantasy and sci-fi books; the more positive side being having some resilience to loneliness and enjoying my own company enough to put myself out there when I wanted more of a connection.

At least here, where I am, building community has not been much of a challenge. I have fortunately found that most people want to build community themselves, and will respond pretty favorably if you give them a seed to nucleate their socialization around. Sometimes this is as simple as dropping a suggested time and place to meet and then disseminating that to people; other times it’s more devoted efforts to invite specific individuals and incentivize them to attend a more elaborately planned event. Either way, in my experience, the response has been overwhelmingly positive when I put in some effort to organize something for people to gather.

That effort doesn’t even have to be something huge. It can be as simple as throwing up an event URL – sites like Luma make it super easy to plug in a time and place, and then just disseminate the link for people to register themselves – or it can be as involved as essentially planning a wedding, with all the associated catering, invites, and venue logistics to fund and secure. Either way, the intent is the same: giving people a central “seed” to nucleate around. The level of effort put into setting that seed might differ, but it’s a nucleation point either way.

In the end, I think there’s something to be said about the quote from Jim Rohn going “You’re the average of the five people you spend the most time with,” or something like that. It’s not absolute – you obviously are also influenced by people in your past, and people you’re yet to meet in the future – but there’s a lot of value in intentionally building out the type of community you want to be involved in, curating who those people are and deliberately setting time and place to connecting with them regularly. Sometimes you don’t have to do that yourself, there’s already communities built up, like run clubs or gym classes or woodworking studios, but sometimes there’s still value in starting something new, especially starting small with a niche but dedicated group that has shared values or motivation.

Building a community isn’t particularly easy, and requires a lot of rejection, whether people just are not interested in actually showing up or people flaking out at the last minute because there’s not enough incentive to be there or life just gets in the way, but maintaining some empathy and focusing on the people who do show up leads to a core relationship you can rely on and build a network of community around.

CHAPTER THREE: PRACTICE

Today is Day 4 of my November Writing Challenge, and I struggled to sit down and type out something, anything. To be honest, I figured I’d struggle most within this first week, since I’ve always heard that building daily habits is the toughest on day 3 of starting out – well, here we are, technically Day 4 but that first day was really just an introduction. That was the whole point, though. By writing every day, even if just a little, it would help build up a habit of writing, something that professionally I need to do more of but these casual (creative?) writing exercises would serve to build the habit.

I have such massive respect for people who have creative talent. I mean that pretty broadly, not specifically writing or art or music, just the act of “creating” something from nothing. The “talent” half of that doesn’t necessarily mean innate, inborn talent, and from what the artists in my life tell me, almost all creative talent is built from lots and lots of practice rather than being naturally gifted. The rest of us don’t see much of the practice pieces, only the “masterpieces”, I’m told. Still, I have a lot of respect for creative talent and especially artistry that is broadly appreciable. There’s an argument that even science experiments are creative, but even the most elegantly designed experiments are hard to appreciate unless you’re already deep in the niche of that field. Prepping a “perfect” experiment, with <20% coefficient of variation and p-values < 0.05, just doesn’t hold the same kind of broad appreciation as cooking an amazing meal or painting a beautiful landscape. It’s all creative talent (in the sense of creating something from nothing) and requires mastery in their own respects. But the former can’t really be as broadly appreciated as the latter.

The rate and visibility of “failure” in science is probably similar to creative arts. Hardly anybody speaks about their failed experiments; there’s a survival bias of only the experiments that worked since those are the ones being published and presented. Sometimes the failures aren’t even because the science was bad, it might just be bad luck, or that there weren’t enough resources, or the idea was otherwise ahead of its time. But the failed experiments are also “practice” for a scientist, I guess, so it doesn’t matter so much whether every experiment works or not, it still can count for practice.

Not all experiments are tangible, which makes it harder to feel like “practice”. For some reason, doing something creative feels more real to me when it’s making something tangible, rather than the sometimes esoteric nature of science experiments. (Most of my science is mixing clear colorless liquids, so it’s “creating” something in the literal sense, but there’s not cool color changes or gently smoking beakers or glowing slime like some media portrays.) In the last year of my PhD, I got the wild hair to teach myself how to make macarons (NOT MACAROONS) in part because the Great British Bake Off insisted it required a lot of practice. I made a batch almost every week for nearly a year, and I finally got a recipe down good enough to serve an assortment of macarons at my thesis defense party.

That kind of practice made progress feel more concrete and measurable. I had a clear product to compare, week after week. I even stored some “representative” macarons in the freezer to lay them out the next week and see where they improved or where they got worse. Each iteration was clearly comparable to the last. It’s similarly easy when I “practice” running (more like jogging, to be honest), since I can see my speed or time change week over week and gauge if I’m improving.

Seeing how “practice” helps (or doesn’t help) in my science profession is a bit harder than macarons or running. But maybe that’s why writing felt like a good thing to practice – I can measure my progress by word counts. Whether any of the words are worth reading is a different metric.

CHAPTER TWO: MANAGING UP

I mentioned in PEDAGOGY that my preferred teaching style mirrors my personally preferred learning style, and that I’d write a bit more about how this probably also seen in how preferred management style mirrors how you like to be managed, how you mentor others mirrors how you prefer to be mentored yourself, etc. I never actually got to that in the EPILOGUE to that post, so maybe we tackle that today.

Much like a teacher-student relationship, mentor-mentee relationships and manager-managee(?) relationships have an inherent power dynamic and status imbalance. I think there’s quite a bit of good advice out there on how to be a better manager or mentor, and I think there’s also a lot of good advice about taking charge of your own development, like individual development plan (IDP) templates. (I love IDPs, I just don’t know if I would fit IDPs in here. Maybe later.) So instead I’m going to write about managing up – how you can manage your own supervisor and/or mentor to make the most of the relationship.

Sometimes I think “managing up” as a concept gets twisted into somehow manipulating your manager. That’s not really what I mean. Because of the power dynamic, though, I think a lot of focus is put on optimizing “top down” management/mentorship and how to improve being a manager, which is very valid and of course crucial to strong leadership. But there are also things that a mentee or direct report can do to build the relationship with their manager for the benefit of everyone involved. (This, of course, assumes your manager or mentor isn’t jealous or somehow in competition with you, their junior, or otherwise sabotaging, since that brings a whole layer of dysfunction to all of this. I’m assuming a healthy relationship, where there’s an inherent power dynamic or hierarchy, but everyone is generally a good person.)

By understanding how your own mentor or manager prefers to be mentored or managed herself, you can get some pretty powerful insights into their motivations in how they mentor or manage you. This can help color your interactions with more context and perspective. For example, I know that I myself prefer a “pacesetting” management style, where I’m generally trusted to do my own thing and make my own decisions along the way, and will proactively reach out for help when and where I need it. But that management or mentorship style can seem to my reports or mentees that I’m too aloof or hands-off, and not delegating tasks clearly. To me, it just feels like I’m avoiding being a micromanager, but to my coworkers it can create confusion and lack of clear expectations. So establishing a two-way communication stream between mentor and mentee, even in light of the power dynamic, can really help ensure that everyone is on the same page and getting what they need or want out of the relationship.

I haven’t always preferred the “pacesetting” management style. My preferred management style (the way I like to be mentored/managed) has evolved over the years, for sure. Early in my training and career, I craved a high-touch, frequent-communication style as I built confidence in my skills. I wanted a lot of feedback and I wanted it often, since I was unsure of my work. I still reach out for input more often than usual when I’m plunging into something I’ve never done before, but most often I want to be left to my own devices and be trusted to reach out with updates when I’m ready to give them.

Anticipating what my manager needs from me is helpful, too, though. A big moment for me in my career was the moment I realized that my managers were just people with their own careers and their own personal development trajectories. Basically just realizing I’m not the main character, and while I’d love for everyone around me to mold to my exact needs and desires, it was probably going to be a lot easier to meet my managers halfway. One of my first managers, for example, was working on writing some high-profile manuscript at the same time I was picking up my first independent project, and looking back it would have been an amazing learning opportunity if I had asked if I could help them, even if just by reading drafts or asking questions that would help them plug in the next block of text. I certainly couldn’t write the paper for them, even if we both wanted that, but instead of just doing my own thing, I could have reached out a bit more to see how I might help them like they helped me. As another example, you might see how your manager is gauging their own productivity to get an idea of what they might be expecting from you. If their own measure of success is submitting reports, then making sure your own reports are thorough and timely is probably going to impress them. If their measure of success is some output metric like lines of code written, then they’re probably going to be checking your commits. Stuff like that.

It’s not all altruistic. Making your manager look good usually makes you look good. Understanding where you fit in your manager’s trajectory can help your own trajectory. If your manager is gunning for a promotion, and gets it, that can in turn help you in the future by having a more senior network to pull from. Your manager doing well can mean more opportunities that you might not have gotten, especially if you’ve proven yourself trustworthy and capable of representing them. (I’m thinking especially of scientific lab settings, where your PI might get invited to give a lot of seminars or conferences and, not having enough time in their schedule or desire to travel, can pass some of those opportunities to you.)

I don’t have a real “manager” at this stage of my career, since I think of my co-founder as more of a colleague or peer than a true manager even if he’s “above” me on the HR org chart. But in the past, I’ve been able to leverage some great opportunities by taking an interest in the things my mentors and advisors have been passionate about, and figuring out how I could help them with their own professional goals. It’s also really helpful for me to get an idea about what motivates my mentors and advisors these days; sometimes, there’s opportunities to help them look good that makes me look good, too. That kind of bi-directionality in the mentor/mentee or manager/report relationship is helpful for build deeper mutual respect and I think managing “up” like that helps you to get more out of your manager, too.

ASIDE

A lingering thought on pedagogy: I meant to write more about learning objectives, since that’s the point of “Step 1: Decide on the 2-3 main things you want the participants or students to remember” since the 2-3 main things for a lecture may be the 2-3 learning objectives. Specifically, with setting learning objectives, there’s a hierarchy of subject mastery. The lower tier is rote regurgitation of facts; the higher tier is applying the materials learned to make something new. I usually try to avoid the lower tier of regurgitation, because in the real world, most of my participants will always have an “open book” to look things up, so I try instead to set learning objectives that are more applied.

CHAPTER ONE: PEDAGOGY

Top of my mind today was getting my lecture slides submitted for the ASMS Fall Workshop on Fundamentals of [Mass Spectrometer] Instrumentation. Although I first got my lecture topic assigned back in June (“Instrumentation for Quantitation of Large Numbers of Analytes”), I honestly didn’t think too deeply about it until early October when we were asked to submit a rough draft on October 14. The rabbit hole here is the theme of “procrastination”, but in an attempt to stay on topic, let’s explore my approach to building lectures.

First, a disclaimer that I’m not formally trained in education or teaching. I got a crash-course on putting together lesson plans and curricula, and general teaching/learning approaches when I first arrived in South Korea for my Fulbright scholarship to teach English, specifically, speaking/listening to English at a rural high school although I also prepped a smaller group of high schoolers for the Test of English as a Foreign Language (TOEFL). (Hello out there, Chungnam Internet High School!) This was back in 2009, so all our materials were paper print outs and chalk boards, and unfortunately I don’t have anything besides my memory to pull from, but a few things did stick with me and I keep them in mind when I’m putting together lectures today.

Second, I never have to teach from a textbook or follow a prewritten curriculum of learning objectives, so I have a lot of freedom on what exactly I deem “important”. I assume that if I had to teach specific exam materials or follow a textbook, a lot of my approach would fall apart. I usually am lucky to get even a general theme/topic to teach about, let alone have specific objectives or test materials.

Third, these days I’m always teaching professionals who are for the most part self-motivated to learn the material, so classroom management isn’t much of a concern. When I was teaching the high schoolers in Korea, classroom management was much more of a challenge. Punishments were handled primarily by their “real” teacher, who accompanied them to my classroom, but it was still expected that I make an effort to maintain the students’ attention and discipline where/when needed. These days, I might teach some undergraduates here and there, but usually I’m working with professionals who are paying good money to take my courses, so my motivation is more my own desire to make sure they get their money’s worth of material.

Finally, all of this is predicated on and influenced by my own personal learning preferences. I think, in general, preferred teaching style complements preferred learning style; similarly, your preferred management style mirrors how you like to be managed, how you mentor others mirrors how you prefer to be mentored yourself, etc. More on that in a later post, I think.

With all that established, here’s how I approach putting together a lecture or workshop.

STEP 1. Decide on the 2-3 main things you want the participants or students to remember.

Generally, starting at the end is always a good idea with any kind of presentation or communication. If you set the objective before you get carried away in the details (or in recycling old material), you can keep that “North Star” in mind in building out the background, proof, and conclusions for each of the main points you need to make. (Note: The idea of having a “North Star” as specific verbiage is something that is talked about a lot in the startup space, in the sense of keeping some guiding principle or vision and tying everything you do back to that singular goal.)

These 2-3 things become your “home slide” (a term I’m shamelessly stealing from the seminar course at the University of Washington’s Genome Sciences department), which is a slide that you’ll use as a recurring anchor point throughout your lecture or presentation. It’s a sort of agenda or syllabus, which reinforces the points that you’ve made, the points that you’re going to make, and then is a summary reminding the participants or audience what you want them to remember from your lecture. (This ties into “Step 3: Repeat everything three times”.) Sometimes I’ve seen this so that each of the points on the home slides is a question that is answered at the end of the section, which also works.

Structuring your lecture around key concepts allows you to set up multiple break points for the participants to check in with themselves and make sure they understand each point before you move on to the next. It also makes it crystal clear what you want the participants to learn so there’s no ambiguity.

STEP 2. Incorporate more than one learning style.

This whole entry is pretty poorly cited (actually, there’s not really any references) but I recall some learning styles being visual, auditory, and hands-on. (There’s probably real pedagogical terms for these, but again I’m not formally trained.) Personally, I learn best with the “hands-on” approach – I can read a text book until I have it memorized, or listen to hours of lecture, but I won’t really grok something until I have to use/apply/do it myself. For example, learning a new experimental protocol or how to calibrate an instrument. I could read about the theory and watch people do it dozens of times, but it won’t really sink in until I’ve done it myself.

It’s almost always a given that a lecture will consist of a slide deck and presenting said slide deck, so arguably there’s always at least two learning styles accommodated. However, some slide decks seem to be entirely text on slides, which I think goes against the spirit of visual learning. I try to keep text minimal on my slides and use more pictures, schematics, or even just icons to communicate the core vocabulary I’m using verbally.

And when building a workshop agenda or a lecture that’s more than 30 minutes long, getting at least one “hands on” or applied piece worked in. A lot of workshops I teach involve software usage (specifically, how to use the Skyline software for mass spectrometry data analysis) so there’s a whole slew of step-by-step tutorials and demonstrations I’ve built up over the years. But for conceptual lectures or workshops, sometimes this can be done by posing a thought question that bridges into application. For example, when I’ve taught statistical design of scientific experiments, I’ve posed some sample sets and asked participants to either think for a minute or divide into groups to talk about how they might block and randomize those samples, given a particular experimental question. When I’ve taught day-long workshops, I’ve closed out the day with a good ol’ Kahoot quiz, focusing on the 2-3 main points of each of the day’s lectures to reinforce the most important things I wanted people to remember from the day.

As a super-niche technical aside, I think this is one of the hardest barriers with (almost) all the mass spectrometry and proteomics workshops out there. I can think of only three that include a wet-lab “hands on” component: Cold Spring Harbor’s Proteomics course, MRM Proteomics workshop, and Brett Phinney’s proteomics school at UCD. To my knowledge, there’s no undergraduate, masters, or PhD program specifically for mass spectrometry or proteomics, unlike genetics, so to break into the field the only real options are to start out in analytical chemistry or biology, and pick up the mass spectrometry or proteomics through research experience.

STEP 3. Repeat everything three times.

We were drilled at Fulbright teacher training to repeat everything at least three times, ideally once in each learning style (Step 2). Thinking back, this is also how I was officially trained in assays during my internship at Wyeth Pharma (purchased by Pfizer since then) with a “watch one, do one together, do one being observed” triplicate before I was signed off as being trained. I still try to do training in the Talus lab with that in mind, and don’t expect independence on any task or protocol until we’ve done at least one iteration of “watch one, do one together, do one observed”. This also follows Step 2 of using more than one learning style, with one being visual and one being hands-on.

As a personal aside, it also follows some of the parenting books I’ve read, like Hunt Gather Parent which (although problematic in some ways, in my opinion) raises a good point that toddlers and young kids learn a lot by observing and then mimicking.

This is maybe something I took too much to heart, because some of the faculty feedback I recall receiving during my PhD training was that I repeated myself too often in my research report presentations. Habits die hard, I guess.

FAILURE MODE 1. Firehose of information.

A lot of really smart people seem to have a hard time placing lecture material in context and default to a tidal wave of information. I’m definitely guilty of the firehose approach, especially on super condensed course timelines where I’m trying to cover as much ground as possible in limited time, hoping that my Step 1 2-3 main points per lecture will be an oasis for participants to hang onto while I barrage them with references, rabbit holes, and random factoids that might be jumping off points for them to dive deeper in the future. Without having those 2-3 main points to anchor the core take-home messages and reiterate the high level objectives, getting a deck crammed full of paper citations and heavy content is disorienting and disheartening for participants, in my opinion.

FAILURE MODE 2. Overwhelming jargon.

Mass spectrometry and proteomics is hugely guilty of jargon overload. It becomes almost a second language, and teaching in a “second language” makes it even harder for participants trying to learn core concepts. Lecture material should strip away as many acronyms and jargon as possible, and ideally provide a dictionary or quick reference for participants to keep handy as they navigate the content.

FAILURE MODE 3. Failing to connect to the audience.

The exact same lecture topic should be presented completely differently if the audience changes. A lecture on “figures of merit” given to a room full of analytical chemists looks completely different from a lecture on “figures of merit” to a room full of biologists. And even more so if that room goes science-adjacent, like operations or business development. This kind of reframing is hard to do without empathy – the audience isn’t more or less smart, they just come with a different set of prior knowledge and a different motivation for learning the material. The 2-3 main points that an analytical chemist should walk away with from a lecture on “figures of merit” should be different from the 2-3 main points that a Vice President of business development walks away with. Starting from that very first Step 1, then, the entire content shifts to match the learning objectives.

SUMMARY

I wouldn’t call myself an excellent teacher, but over the last 16 years (yeesh, that math hurt to realize) since I got that initial crash-course on teaching and pedagogy, I’ve continually refined my specific lectures and my overall approach, and I’m getting pretty good course reviews these days. I’ll always be iterating and incorporating new feedback, but I think these core concepts will probably always remain a foundation in how I put together teaching material.

EPILOGUE

On my run today, I let my mind wander and spiral across the idea of “pedagogy” and teaching. Below are some of the things that spun out of the main theme as I jogged through the park on a beautiful autumn afternoon.

I struggled quite a bit in college as I worked for my bachelor’s in biochemistry and molecular biology. My degree required multiple chemistry courses: inorganic, organic, physical (thermo and quantum); however, hilariously, I did not have to take analytical chemistry, which is the one I’ve basically landed in professionally. It also required multiple physics courses: mechanics, electricity and magnetism, wave motion and quantum. My grades were, as the now-classic Chernobyl HBO series meme goes, “Not great, not terrible.” Started pretty strong but more and more C’s as I got deeper into the trenches. I wonder if part of it was that the lab portions got less and less “hands-on” and more abstract as the semesters went by. I love the inorganic and organic chem labs, where you got to “make” things; the physical chem labs were more mathematical proofs and practice problems than the hands-on stuff that helped me learn. (Not that I’m suggesting I know of any hands-on labs for quantum that would have helped me in the exams, but just reflecting back on my own failures and wondering what I could learn from them.)

While having a “hands-on” preference might suggest that I don’t learn well by reading or listening, I do love to read, although I’m not sure I really fully read every word. Instead I kind of skim over the lines and pages and get the general vibe, which is great for leisure reading but pretty terrible for studying. When I applied for the Fulbright to Korea during my senior year of undergrad, I started studying the language with two semesters of Korean classes. Nothing stuck quite as much as when I moved there and was suddenly fully immersed – my home-stay family spoke some English, but obviously used Korean with each other so I was surrounded at home, at work, and going about my day. I picked up so much more Korean with that kind of hands-on practical experience, even things I should have learned during undergrad Korean classes like simply introducing myself.

It’s no surprise then that when I went to graduate school, under the advice from my excellent post-bacc PI to learn statistics and programming, I ended up with my PhD joint-advised in a machine learning laboratory having only just learned the very first basics of coding ~6 months prior. (I did, technically, take some visual BASIC in high school and then again in college, but that’s a poster for another day.) To learn the language of statistics and computational biology, there was no better method for me, personally, than to go “full immersion”, sink-or-swim by throwing myself directly into the deep end. I wouldn’t say I ended up the strongest computational biologist that ever graduated from that machine learning lab, but I also wouldn’t say that I couldn’t hold my own. I still keep the physical print-outs of my performance reviews from that PI at my desk as a reminder to do hard things.

(PS – I may return to this topic, or branch off it at least, since I already have a few more thoughts about how it relates to science communication. Nevertheless, today I got to ~2300 words, about 3x more than yesterday! Whether it was the theme, or the run, I’ll take it.)

INTRODUCTION: November Writing Challenge

After failing to secure a tenure track professorship, I figured I was closing the door on being a Principle Investigator (PI) even as I opened the door to entrepreneurship and founding Talus Bio. It turns out that being an academic PI and being the cofounder/CTO of a biotech startup looks pretty much the same at the day-to-day agenda: finding out how to pay for the science that will make a difference to the world. The funding sources might be a bit different (although we’ve been really lucky at Talus to have a decent track record securing non-dilutive funding from the NIH and NSF) but at the end of the day, it’s a lot of writing proposals, making slide decks, and communicating science to different audiences.

I still find it hard to sit down and get into a writing groove, despite writing (and rewriting) probably thousands of pages over the years. There’s usually some elaborate, ritualistic nature to my writing sprints (“sprint” because I can’t remember the last time I sat down to slowly, methodically write a grant or a manuscript that’s not imminently due within a week or so). For example, the setting and the mood has to be _just right_ for me to really crank out a word count. Coffee shops and bars are a particularly favorite atmosphere, and I need at least a few hours blocked off, rather than gradually chipping away with a thousand words here, or a few hundred there. Getting myself more into the habit of writing a bit every day is why I decided to take the spirit of the various November writing challenges in the form of short-form blog posts, with the ultimate goal of tapping out 50,000 words over the 30 days of November. (The controversy of NaNoWriMo as an organization aside, I think the spirit of a month-long “challenge” to write [organically, not through ChatGPT prompting, more on that later] is admirable.) Writing 50,000 words comes out to about 2,000 words a day, or ~4 pages. I imagine some days will be a single piece, albeit lengthy for a blog post on average, but I also figure some days I’ll have shorter pieces, or a series of pieces, whether due to time constraints or just how deeply that day’s theme is speaking to me.

Over the past few months, I’ve been preparing by jotting down themes, topics, and general shower thoughts that I’m using as inspirational seeds, but I’ll probably be meandering. I’ve also got plenty of “in progress” manuscripts that could use some love, but I’ll try to work on those in the background while getting my ~2,000 words in here. Generating four pages of content feels pretty daunting at the moment, but I guess that’s part of the exercise – getting to the point where four pages feels natural and is just putting my thoughts to keyboard, rather than getting caught up in a mental spiral of trying to edit my writing before I’ve even written it down. Some of the prompts are things I’ve been meaning to write for ages, like a general “Lindsay README” for colleagues and collaborators to learn a bit more about how to most effectively collaborate with me and a breakdown of scientific communication that I wish I’d learned when I was in school. Beyond professional or personal development, there will probably be some hot takes and some general musings, and some unhinged, disconnected rants.

One rule I’ve set for myself is that I won’t use ChatGPT. This year, it’s become so pervasive that I “feel” ChatGPT in just the cadence or the word choice in a piece of prose and it’s disappointing because it feels like everyone’s thoughts are being pushed through a uniformity filter, and getting stripped of personality. That said, these posts will probably end up being a bit more rambly and disjointed than if I gave them some LLM gloss. Sorry not sorry. I probably also won’t edit these very much, if at all, both in the spirit of breaking my “blank page syndrome” and also because of time.

(PS – This was not even 1000 words, so I’m definitely going to need to work my writing muscles this month!)

Productivity and time management

I’ve been asked this a couple times now, so I’m putting my response here for future Lindsay to quickly reference.

For personal productivity, I follow the Inbox Zero + Getting Things Done methods. My tool of choice for this is Todoist. I have the Chrome plug-in and the phone app, and I use it with the Gmail, Google calendar, and Slack integrations so I can add tasks immediately when I see them (per Getting Things Done).

I've been using the same productivity/time management software for a while now. I was surprised to see the quantitative shift from academic trainee to startup/PI! pic.twitter.com/ODMyYVHslD
— Lindsay K Pino – @lkpino@genomic.social (@lkpino) March 12, 2022

I like to check-in with myself every few months to see if my time is being spent on the things I think it should be spent on. Doing these time audits has been easy with Todoist because, if I categorize my tasks into the general themes I want to track, then I can use that data to plot how I spent my time. There used to be some nice apps to do this, but they’ve shut down. In the mean time, I’ve been looking into some of these alternatives.

[UPDATE 11/6/2023: Twitter/X issues with the embedded tweet. Here’s a screenshot (below).]

Two new podcasts after a year’s hiatus

I’ve neglected to update my latest ramblings! I’ve recorded two new podcasts. Well, both were recorded at least 6 months ago, but one released a year ago now and the other released just in December.

The first is Talk is Biotech with Gugu Singh from Scispot.io — I’ve been using SciSpot ever since I met founder-brothers Guru and Satya Singh in Y Combinator (summer ’21). You can check out the recording and some highlights from the chat here.

The second is a new podcast called The Proteomics Show, hosted by Ben Orsburn and Ben Neely. We get a bit more into the weeds with the proteomics, rather than the business, but as always there’s plenty of hot takes. It’s listed basically everywhere podcasts can be listed.

“From idea to startup”, a panel discussion sponsored by US HUPO

Last fall, I hosted a panel on startups as part of the US HUPO Early Career Researchers (ECR) organization. This year, the ECR invited me to sit on this panel as a participant!

Here’s the Q&A from that event:

Q1: Starting your journey as an entrepreneur, did you feel the need to undetake any business related courses coming from a Scientific/medical background?

A1: I personally didn’t feel the need to take formal business classes. My co-founder (Alex Federation) and I are both technical founders, but benefitted from many excellent business mentors that we met through

Q2: Do all incubators/accelerators provide the same type of support- or does it vary from institution to institution? What’s the universal support that a start up can count on in any incubator?

A2: I think most incubators/accelerators follow a similar pattern: workshops/courses, 1-1’s or small group “office hours” with mentors, and some kind of “Demo Day” capstone at the end of the program. For a lot of the bio-focused incubators/accelerators, the workshops/courses tend to be about business development. The 1-1’s or small group is an opportunity for you (and your co-founders) to meet with the program mentors — and network with them! Finally, the “Demo Day” is usually a short pitch to an audience of multiple venture capital investors where you get maybe 1-5 minutes to hook investors into scheduling a deeper conversation with you, and hopefully invest!

Here’s a list of bio-focused incubators and accelerators (just off the top of my head, check out others!)
– Your institution/university!
– NSF/NIH iCORPS: https://beta.nsf.gov/funding/initiatives/i-corps
– Indie Bio: https://indiebio.co/program/
– Y Combinator: https://www.ycombinator.com/biotech/
– Creative Destruction Lab: https://creativedestructionlab.com/
– BioFoundry: https://www.venturelink.org/biofoundry

Q3: To translate your idea into a business product and start up a company, do you first need to patent the idea and register your intellectual property?

A3: While intellectual property (IP) isn’t strictly required to start a company, it’ll probably be tough to secure funding if you don’t have your core idea/technology/method protected. Most investors won’t be interested if someone else could come in and do exactly what you’re proposing! If you’re looking to start more of a contract research organization (CRO)-style company providing services, you may not need to have any IP at all, but you’ll need to convince your customers why your CRO is better/cheaper than other CROs out there.

The recording should be up soon, I’ll update the page with that link when it becomes available!

Lady Scientist Podcast: From dropping out to starting up

Check out the podcast here!

I got to hang out, virtually, with Dr Jocelyn Pearl of the Lady Scientist Podcast team. We talked mostly about my career journey, from almost leaving science during a TOEFL teaching stint to South Korea, to founding a biotech company during a pandemic.

I especially liked this theme because it gave me an opportunity to share some of the personal story behind where I am now, which has been anything but a straight shot. At this time 10 years ago, I had just repatriated to the States, moved back in with my parents at the age of 24, and was sending 100s of job applications to any and all research associate positions in the Boston area, desperate to find a job.

It’s okay not to have it all figured out as an undergrad student (or even a grad!) and to take some time to find what it is you love doing — for me, I can’t imagine doing any job other than science, but I certainly didn’t feel that way as a post-bacc until I had tried a few other things.

Preparing for careers in start-ups/spin-outs

For most scientists, it seems like our training focuses on just two career paths: tenure-track academics or industry scientists. Sometimes you’ll get a career discussion about patent law, but those two trajectories seem to be all that trainees hear about.

So when Alex Federation asked me if I wanted to help him launch Talus Bio, I absolutely had no idea what I was doing or getting myself into. All I knew was that I loved the science and I loved working with Fed, so we pushed ahead with the shared vision of what we wanted the company/lab to do.

Over the last year with Talus, I’ve had the opportunity to meet a ton of amazing people in the start-up/spin-out world, and I’ve been blown away at the range of career opportunities there are beyond company founders themselves. And also dismayed that I’ve never even heard of most of them because they sound like perfect fits for the skills that a PhD cultivates beyond churning out papers for your boss.

That’s why I organized the latest Career Explorations panel for US HUPO’s Early Career Researcher group and focused on some of these jobs. I invited four panelists, ranging from startup founders to tech transfer officers to due diligence scientists:

Emily: https://linkedin.com/in/emily-hartman-guthrie-0b013437/
Susan: https://linkedin.com/in/susanmockus/
Marco: https://linkedin.com/in/marco-lobba/
Steve: https://www.linkedin.com/in/steve-ouellette-b93b1561/

During the 1-hour conversation, we touched on many aspects of spin-outs and start-ups. Of course there was plenty of interest in how to launch a startup company from a university research project, but there was also discussion about how exactly patenting and IP plays into startup companies, how tech transfer and commercialization are handled from the university or research institute, and how funding is secured from venture capital and investment firms.

I’ve compiled four main highlights from our discussion, but US HUPO will be sharing the recording of the panel shortly, so check there for the full conversation!

Q1: How do you build non-lab skills, like management, leadership, etc, during your academic training?
(1) Read books on management and leadership skills (*see recommended reading below)
(2) Take courses from your university’s MBA program, both to expand your knowledge but also to meet people (potential co-founders) with complementary business skills
(3) Look for incubators or entrepreneur support programs at your university, which typically include workshops on leadership, management, and business development
(4) Internships at VC firms (commonly posted on LinkedIn, so have your LinkedIn profile up to date!)

Q2: How do you get started with a potential spin off?
(1) iCORPS program is a great place to start and will give you opportunities to practice business development
(2) Find product market fit through “user/customer” interviews (something that iCORPS will also help you with)
(3) Report all your inventions/discoveries to university patent/IP office BEFORE publishing a paper or sharing at a conference — having intellectual property will make it easier to fundraise for your company
(4) Draft a commercialization/business plan (again, something that iCORPS can help you with)
(5) Read Jared Friedman’s How to spin your scientific research out of a university and into a startup

Q3: Investment in proteomics is booming — pros and cons?
(Pro) Proteomics can solve problems that genomics couldn’t; next generation sequencing is cheap now so there’s more investment opportunities for proteomics; there’s more mainstream interest in proteomics these days
(Con) hard to explain proteomics and especially mass spectrometry; orthogonal validation for proteomics is tough; there’s a history of failed companies and overpromised/underdelivered projects; hard to define a proteomics product (methods and software patents are trickier than a product or chemical/compound, for example)

Q4: What business models seem to work for proteomics?
Hybrid platform/fee-for-service + internal therapeutics dev is a popular model now with early stage venture capital. However, it’s tough to stay lean and hard to stay focused when you’re essentially trying to run two businesses: one as a CRO and one as a pharmaceutical. In the future, maybe there will be more proteomics-based diagnostics companies?