Bionano Genomics, Inc.

code applications, they'll be familiar with not only the methodology, which is what the focus of the CPT code process is on, but of the value and utilization. And that's driving coverage. And so I think CPT codes will be important. They're going to get out there eventually down the road. They're certainly going to be important when FDA cleared, mapping systems are available and labs that are adopting them are using FDA-cleared versions of the system. Our focus is on unlocking coverage right now because we see plenty of coding happening.

That's helpful. And in terms of the publications regarding the hematological malignancy publication that came out, the three of them, what are the next steps? Do you need additional studies in terms of you know, starting conversations with guideline bodies to make OGM first here. I'm wondering what the next steps are.

No, it's a great question. I think that the strategy to evolve optical genome mapping from a basic research tool into something that's used routinely and regularly in translational research, I think that that's what we're seeing now, into something that eventually gets recommended and becomes part of the standard of care, involves getting a lot of data out, what I call critical mass of data, and a key component of that strategy is to work with folks in the field who are associated with the teams that make recommendations to these medical societies. So if you look at some of these publications that are coming out, the three that we talked about earlier this quarter are from European sites, but we have others. There was a really amazing publication last summer that came out of MD Anderson Cancer Center. All of these authors have an affiliation, or several of these authors have affiliations with guideline-setting agencies, such as the World Health Organization, NCCN here, National Comprehensive Cancer Network in the United States. And those those agencies set those guidelines. And so by working with key opinion leaders who are already affiliated there, it's a way of accelerating the process.

Okay, that makes sense. And finally, a quick one from me. The decrease in anticipated new hires for the remainder of 2023, any specific department those hires were going to be in or if there's a cross the board?

I think it's really an effort to, I think, be just prudent about the hiring and making sure that wherever we're expanding the team, it's on a critical need basis. So there isn't a specific department or team which is singled out. And it's really a process of hitting our goals from an expense reduction standpoint, but staying on track to hit the milestones that we've reiterated here today.

Great.

Thanks for taking my questions.

You're welcome. Thanks, Dan.

Thank you. And as a reminder, ladies and gentlemen, simply press star 1 if you have a question. And our next question comes from the line of Michael Okunowich with Maxim Group. Please go ahead.

Hey, guys. Thank you for taking my questions, and congrats on the quarter. Thank you. So I guess I'd like to start out and just talk a bit about, with all the process improvements that you guys have made to the end-to-end OGM workflow, and I think most recently, as we saw at ACR, with VS streamlining the analysis step, can you talk about what you currently view as the main bottleneck for OGM end users, and what efforts to further optimize and stream on the workflow you're currently working on?

So thank you, Michael. And I want to acknowledge Carmen, who did a great job at pronouncing your name. That was impressive. So I appreciate you calling in and following along. you know, AACR with a focus on cancer research is really an area where we're starting to build momentum. And I think if you look at cancer research in particular, there's two really challenging elements to it. Outside of the mapping process itself, it's certainly doing the data analysis. And one of the reasons that the data analysis is complicated in cancer research is that a lot of this utilization is guideline driven. And so when somebody goes to analyze a data set, it's not really a process of simply looking at what is present in the sample, what variants are called, but it's really comparing those calls to a specific list of variants that are called out in these different guidelines. And that can be a very tedious and manual process. It can take hours and hours to do. And I know this because we do it in our own laboratories as part of our clinical studies and as part of a LDT that we've developed in BioNano laboratories. And so our new software, which our team is beginning to use and work with, automates that process. And so it's still something that's user driven. We're talking about a research product here, but the user decides how they want to construct these panels that are driven by guidelines and then they're able to sift through the variant calls in an automated fashion and save so much time. It's not only a matter of time savings in cancer research, but it's cost savings because the people who are doing this analysis tend to be the most expensive people in the process flow going from sample to answer. So data analysis is a huge bottleneck, and something that's unique about optical genome mapping is even our existing software is extremely streamlined compared to data analysis for next-generation sequencing. We hear all the time that labs that adopt NGS have to have whole bioinformatics teams to analyze the data, and with optical genome mapping, it's the same team that processes karyotyping, fluorescence in situ, hybridization, FISH, or microarrays. It's really comparable to the routine that exists today, and we're just making it really fast. So, data analysis is a bottleneck, and we're addressing it with VIA, first in hematologic malignancies this quarter, and then in constitutional genetic diseases later this year. The other bottleneck is around the DNA isolation, and that's something that we're addressing with isotacophoresis, which is technology that was invented and then commercialized by Purigen, a company we acquired last November. And we currently sell a Purigen product for isolation of nucleic acids from formalin-fixed paraffin-embedded tissues. And we're developing a cartridge and protocol, including reagents that will work for optical genome mapping, starting with blood and bone marrow samples. So it'll be able to work with kind of our existing applications in genetic disease and cancer. And so we're really streamlining the front end, which is a unique process for optical genome mapping, the back end, which is just really challenging because it's guideline-driven. And then I would say that throughput, it depends on your lab, right? So SAFIRE addresses the throughput for a great number of laboratories, and we estimate that those laboratories are processing somewhere between 40% and 60% of the total volume on a global basis. But they make up a substantial number of the labs, whereas a much smaller portion of labs process about 40% of that volume. They need ultra-high throughput. And so this new high-throughput mapper is going to address that need. And so I think we're really elevating overall the end-to-end process in significant ways. making it substantially more automated, streamlined, robust, and fast. And that's what the market is demanding.

All right, yeah, thank you for that really comprehensive answer. I'd like to just get one more, and then I'll hop back in the queue. So in terms of the cost reduction measures, could you just provide a bit more granularity on where those are coming from and what Is that $20 million? Are those recurring expenses on an annualized basis, or is that just over the four to five quarters? Just help me better understand that.

Sure. So we're targeting cash savings in both operating expense, cost of goods sold, and through an inventory reduction. We do expect OPEX in the second half of the year to be down from Q1. And again, it's across those three different areas. And the inventory reduction isn't recurring. The other reductions will be recurring until such time as our financial position changes and we can increase our investments again as appropriate.

All right. Thank you very much. And once again, congrats on the quarter. Thanks, Michael.

Thank you. And I see no further questions in this session. I will hand it back to Eric Homling for final comments.

Well, great. Thank you, Carmen. And I want to thank everybody for following along and participating today. And we look forward to updating you with all of the progress that we're making here in the second quarter in due course. Thank you very much.