No Priors Ep. 140 | With Benchling Co-Founder and CEO Sajith Wickramasekara

(music plays) Hi, listeners. Welcome back to No Priors. Today, I'm here with Saji, the co-founder and CEO of Benchling, the system of record for biotech R&D. Today, we talk about the state of AI in bio, Benchling's bet on AI agents to help scientists make better decisions, experiment faster, and deliver drugs more effectively, why drug programs are so expensive and fail so often, and how to build a culture of science and software together. Saji, thanks so much for being here.

Thanks for having me, Sara. Excited to be here.

Okay, so for our general listener base, can you just give us an overview of what Benchling is and sort of the scale of the business today?

Sure. Uh, so I'm one of the co-founders of Benchling. Uh, we make modern software for scientific progress. Uh, so I started the company about 13 years ago. It's been, been a long time.

Oh my God, yeah.

I know. Uh, so I, I'm a software engineer by background, but I worked in a biology lab. I was like really interested in medicine, um, and coming from the world of software, uh, and software developers have amazing tools for working on code and for, for collaborating. And when I got to the la- the biology lab, I found that scientists had paper notebooks and spreadsheets that would sit on their desktops, and like, it was terrible. Uh, and so it was really hard to work together, and I think that was really frustrating for me personally and, you know, I thought, a little bit naive at the time, I, I thought like, "How hard would it be to build good tools for, for scientists?" And so I started working on Benchling, uh, which helps scientists design molecules, plan their experiments out, run those experiments in the lab, get the data, organize it, analyze it, and then share it with their colleagues. Today, we work with about 1,300 biotech and pharma companies, uh, scientists at over 7,000 academic, uh, institutions, universities all, all around the world, and, uh, our software powers, you know, household names like Moderna and Sanofi and Eli Lilly and, and Regeneron but also, like, cutting-edge biotech startups, you know, the, you know, future AI biotechs like Isomorphic Labs and Zera and, and, and companies like that. So we get to, we get to see the innovation happening across the entire biotech sector and then build software that helps power it.

I'm super excited to, like, actually use that vantage point and ask you a bunch of questions about bio in the macro, but just so people who don't come from the domain can picture it a little bit better, I think, like, you know, I can picture like gene sequences-

Sure.

... and like the assay like said yes or no. Like what other types of... What is the data that's actually in Benchling?

Uh, I think w- what's really interesting for everyone to understand is like making a drug, there's like 9,999 steps in making a drug after you come up with a molecule. So you have to... To, to make a medicine, you have to find a biologically meaningful target in, in the body, something you want to drug.