Zach joined Fulcrum Genomics in May 2024. Previously Zach has contributed to research on gene and cell therapy, genetic toxicology, spatial transcriptomics, cancer minimal residual disease, and HIV. We recently sat down to chat about work and life as a bioinformatics consultant.
What’s your area of expertise, and what excites you about your work?
Zach: My area of expertise is helping wet lab scientists pair their questions and experimental designs with an appropriate software solution, figuring out what we can do to help. That specifically requires a decent understanding of the biology. I have a background in genetics, ecology, and evolution, so for a lot of the different kinds of questions people might ask I can help work out how we will answer them using software. My first position out of grad school was at a gene editing lab and I got to work with many Postdocs there, doing a variety of experiments. I helped them work out how we would answer their questions and get their results published. In my next role I got to work with wet lab scientists building entirely new products, which is something I really enjoy and I think I’m good at.
The thing that excites me the most is being involved early in the R&D phase and getting to see that concept go all the way to product and launch!
What’s a common challenge in our industry that people don’t talk about enough?
A big challenge people don’t talk about enough is how you take a concept and turn it into a real, functioning product. There’s so much involved, and it’s critical that people on the technology side are tightly integrated with wet lab and software experts. You need all the pieces to fit together and you need to be thinking about how it’s actually going to deliver value to your customers.
One part that often gets overlooked is how, at some point, you have to lock in your design — especially if there’s a physical component. I’ve seen projects where there was a strong urge to keep improving right up to the last minute. But when you’re going to market for the first time, that’s just not feasible. You have to commit, build a bunch of units, and be ready to ship, even if you know you could make it a little better.
What’s one tool, tip, or mindset shift that has made a big impact in your work?
This is one that may be common for those with a software background but for me coming from a genetics background I found it very exciting. There’s a whole set of tools that are linters, and they auto-format your code for you, so you no longer have to worry about all the nit-picks. This helps particularly when you’re a consultant and bouncing around different languages, different repositories, different client environments. It’s nice to have that set up to handle formatting for you.
What’s a recent project or insight you’re particularly proud of?
We’ve been able to stand up pipelines for teams developing new technologies and hand them off to their teams to keep running with limited need for our continued support of those pipelines. I am thinking of one in particular to QC an oligonucleotide product. I think that’s a really good example of how we can tailor what we are delivering to our clients’ needs, so they can continue in-house after our primary work is done. It’s really exciting to see people have continued success with things we built for them.
If you could give biotech startups one piece of advice, what would it be?
Science and software = same team!
If your startup bridges wet lab and software, where the software is essential to unlocking the value of your technology, it’s critical to engage your software team early. A strong, well-integrated software team can spot opportunities where a small tweak to the wet lab design can make the downstream analysis faster, more scalable, or more robust.
You’ll end up with a better product overall if your scientific and technical teams stay in close collaboration from the start.
What’s something outside of work that inspires how you think about problem-solving?
Magic: The Gathering, especially the Limited format, is surprisingly relevant. In a draft you’re working with a small, fixed card pool and trying to infer what others are picking. There’s a ton of statistics involved, both in building your deck and playing it well. There’s even a site, 17lands.com, that dives deep into the data collected from players.
What I find fascinating is how your individual experience can deviate from the broader trends. The stats might say one card is better, but in a specific moment context matters more. That’s a lot like gene annotation. Just because a gene has a label doesn’t mean that’s the key to your question. You need both the contextual data and the bigger picture to make smart decisions.