04.10-11.24-HST-Startups-Honeycomb-Biotechnologies

JIM FLANIGON: Good morning. My name is Jim Flanigon. I am co-founder and CEO of Honeycomb. I have three co-founders, all MIT affiliated to our faculty, and I myself am a Sloan alumni. Should've asked how to use this.

SPEAKER: [INAUDIBLE]. At the top.

JIM FLANIGON: Got it. So what is single-cell genomics and why do companies care? So most people, when they think of genomics, are really probably familiar with what's known as bulk genomics. So when you get, say, a DNA test or something, you're really cracking open hundreds of thousands or millions of cells. You do a readout, typically sequencing. And what you get is really kind of the average of what's going on.

In single-cell genomics, you're looking at the genomics of a single cell. In most cases, you're looking at transcripts or which genes are turned on or off. Where that is really important and where we get a lot of traction with our customers is, in particular, say, things like immunotherapies. Why does one patient respond and one doesn't? Why does one patient relapse and somebody else has a durable response? It often has to do with what's going on in the immune system and which genes are turned on or off.

So major challenges at the moment in single-cell profiling are sample collection, cell fragility. Often, certain types of cells are very hard to recover and analyze. And the ability to store samples. And Honeycomb is really focused on all three of these things.

So we really engineered-- and if people want to come by the table, I have some demo. We call these things the HIVE, a play on honeycomb, but they're used for sample collection. And then, we have a whole process to take our customer samples through a readout process, which, again, is typically sequencing.

With our technology, again, we really focused on simple sample capture, the ability to recover the broadest types of cells or the broadest spectrum, and the storage. We have data that goes up to 12 months or more, depending on the sample.

This is just a typical workflow. I won't go in detail here, but happy to take people through at the table. But the upper left is really showing a cross-section of the little device we call the HIVE. It's really an array-based system that has about 150,000 nanowells. Cells are loaded and isolated in those nanowells. And then, we have a whole process for barcoding them and recovering them later. And again, the rest of the workflow is just showing how we-- a customer or us-- would process the samples and take them through library construction for a sequencing readout.

This particular slide is showing a couple of things. One, it's showing human bone marrow. Each little pixel represents a different cell. They're clustered based on like type of characteristics. Bone marrow just happens to be one of these sample types that's very difficult to recover.

And what we're showing here, besides that ability to recover it, is just the three smaller data sets, or just show what a fresh sample looks like one week in our system at minus 20 degrees and then a sample that was not in our system to begin with but put in later. It had originally been put in liquid nitrogen. And you see the loss just through freezing of a large number of those cell types. And again, with ours, a fresh sample versus a one week in our system is statistically the same.

We currently have about 100 customers. We do have global coverage. We have customers all over the world. And the list below just shows a number of, again, unusual sample types that are often difficult to recover and analyze in different platforms other than our own.

And as an ask, you know, we currently are looking for partners or projects that involve immune-based diseases or therapies. We also do quite a number of infectious disease studies. So if companies or groups are working on those, we'd be very interested. And a new use case that we're really interested in is cell-based therapies that we could use our system for quality control and post-treatment monitoring. Thank you.

[APPLAUSE]