We are joined today by Aneesh Acharya, the CCO of Molecular Instruments. Molecular Instruments is a biotechnology company focused on pioneering innovative solutions for clinical applications. Their technology centers around novel methods for high-resolution bioimaging, enabling researchers and clinicians to visualize and quantify the abundance and location of specific molecules within any sample type.

Thank you so much for taking the time to speak with us, Aneesh. Can you please start off by giving a brief description of your background and how you first got into the spatial biology field? 

Of course! So today, I'm the Chief Commercial Officer at Molecular Instruments, but my background is really as a scientist and engineer in the field of synthetic biology and molecular programming. I did my PhD at Caltech, and within Caltech, there was a community that pioneered the field of molecular programming, which was really around building computers out of DNA and making DNA do some interesting things. My thesis work, which built upon the research of our CEO, involved developing a DNA-based amplification tool that we then applied to bioimaging techniques like RNA-ISH and IHC. So, I guess that was my entry point into the field of spatial biology. Although, I have to say we never really refer to it as spatial biology, because it's IHC and ISH, and that's really been done since the 40s. Spatial biology is the latest term to be put on that.

That makes sense. Diving into the more commercial side of things, can you tell us a bit about Molecular Instruments and the role that they play in the spatial biology space?

Caltech is an interesting place for new technologies to incubate, particularly as there's no hospital associated with Caltech. Consequently, there's not a ton of translational or clinical research. And so, when we were building tools for bioimaging we would hear, not from translational scientists, but rather from the world's leading early developmental biologists on what their challenges were. And they're not using samples that look anything like patient samples; instead, they use samples like whole-mount chicken embryos and zebrafish embryos to better understand early developmental principles. So, we built a tool that catered to that market in the 2010s.

Today, we have a strong foothold as the only branded product serving the RNA and protein imaging market in this phase of research. A couple of years ago, we also launched our first translational research product aimed at entering the clinic. A lot of what we learned from the developmental biology space made life easier in this clinical space because that market is challenging in different ways. We view ourselves as enabling new workflows with this compelling platform technology that we built at Caltech called HCR.

That’s really interesting to hear. Taking a step back and thinking about this space more broadly as the use of spatial biology continues to gain traction, what are the main advancements you've seen in the past year?

Spatial biology is getting its foothold in early discovery, when people are getting started with drug development screening for potential druggable targets. It’s cool to see progress in turnaround time, sample throughput, and the robustness and size of the panels that can be screened. It’s not a very competitive field when you consider what happens downstream. Once you identify 5 or 10 potential targets to study in more detail—whether with subcellular resolution or through hundreds of experiments—it’s challenging to scale those “spatial biology” methods. People really do turn to those 1 to 4-plex based products, and we’re trying to push that forward. I don't think there are a lot of companies like us who are doing that, and so that's really what excites us - the chance to push the boundaries of this technology. We’re constantly asking ourselves: how do we make products that are better performing, cheaper, and faster, and continue to push the technology forward there as well?

Considering the range of technologies available, I’m curious how your platform compares to others. What sets your approach apart, and what are its main advantages over the methods used by other companies?

Our technology is based on Hybridization Chain Reaction (HCR). RNA-FISH is the product that we use to make it. I like to use the analogy of Tesla: are they a battery company or a car company? It’s similar for us, where the core technology that enables what we do is HCR. The cool thing with that technology is it’s a simple one-step reaction, which is quite different from many others. Some companies use rolling circle-based amplification or TSA-based amplification, but HCR is completely enzyme-free. This makes the technique very stable, compatible at room temperature and permissive conditions, and gentle on samples. HCR can scale from our current 10-plex capability up to 500-plex. There's not really a technical limitation there – it’s more where we chose to focus. One strategic decision we made a long time ago was to not build our own box and then run this 5,000 plex assay on it where each assay costs thousands of dollars. We chose to focus on the bread-and-butter assays used in clinics today – mostly low-plex IHC-based assays. And we're really trying to make ISH important as well in the clinic. 

Looking across different customer segments, we've seen different applications and use cases. How do the technology needs differ between Academia and Pharma?

We typically find academic users like to be on the bleeding edge of things. They will take your kit and break it, and find new ways to apply it. Biopharma typically wants something pretty turnkey that they can run with predictable and consistent performance. Biopharma also tends to be a lot less price sensitive –  that's another thing that we keep in mind– whereas academics are pretty price sensitive. Sometimes we call biopharma our “professional users” of our assays and academics our “hobbyists.” We find a lot of our academic users can turn to other methods that aren't even ISH. Typically, with biopharma, if they need to do RNA-ISH, they’ll do RNA-ISH. With academics, if they need to understand RNA expression, they may turn to 7 different types of assays that may not even be spatial. In many ways it’s a harder market, but they are quite different in that way.

Beyond reimbursement, what are the biggest obstacles hindering the application of spatial biology in a clinical setting?

I think the primary concern is– what's the point? What are you doing with that multiplex assay? The treatments aren't there yet that require it. So you don't even get to the reimbursement conversation because people just ask “why do I even need to do this in the first place?” One of the historic problems with ISH that we solve and that has become our calling card in the biopharma space, is that typically ISH and IHC are not compatible. IHC is like the bread-and-butter for diagnostics, and ISH has promise but no one wants to give up IHC in order to fit ISH into their assay. We have this workflow that enables easy integration of the two methods on the same patient sample. 

 One case study that we think about a lot is HPV testing. Today it's a combination - sometimes it's RNA based, sometimes it's protein, and sometimes it’s DNA. Usually, people need to run several of these tests on multiple patient samples. We have a pitch where you can combine it all on one, and you can reduce the turnaround time, reduce the amount of patient samples you need, and potentially reduce costs. But there aren't many of those examples. There aren't many of these indications or treatments that readily need multiplexed diagnostics. That's why we begin with the research side. By providing better tools for drug development, we enable the creation of more advanced companion diagnostics. I feel confident that if there is an example of a drug that requires these, then I think reimbursement will find a way. 

From that perspective, what do you see as the key milestone that would need to be achieved in order for something a spatial diagnostic to be developed?

We believe that better research tools are needed, because you can't possibly make a clinical diagnostic unless you have the enabling research tool that lets you measure it. Our viewpoint is typically that if you don’t have a tool that lets you study multiple RNA or proteins at once in a low-plex high volume way, you’ll never develop a diagnostic that relies on it because you'll never know. I think that will be the big milestone. We're continuing to try and push out these tools and enable new kinds of research.

That makes sense. And thinking about that first companion diagnostic, do you think there’s one particular application that might have more clinical potential than others? 

I think that the bispecific drugs are really interesting in terms of companion diagnostics. We also find that ISH can be a useful backup to IHC, as there are a lot of protein targets that don't have good antibodies. Even the way we develop new primary antibodies for treatments or for even just diagnostics is pretty old school. You don’t really know if it's going to work until you try it, and then there’s the question of “how do you validate it?” ISH is really nice because it's programmable, and you can design probes against the target you care about in a really robust and specific way. Another promising area could be identifying diagnostic targets that lack reliable antibodies. ISH can serve as a useful alternative in such cases. That’s what I bet would come first, but I guess we’ll see.

I guess only time will tell! Taking a step back and thinking about spatial biology as a whole, what’s the impact of spatial biology on the field of precision medicine?

I ask this question to so many of our users who have experience with the full breadth of all the spatial tools that are out there. We typically hear something pretty consistent. A lot of the really high multiplexing tools are very useful in early discovery, but they don't scale well to active drug development. So when you're trying to do even safety and tox studies, you need a low-plex tool. It's almost like the pickup truck of these histology and pathology facilities. And we're just part of that – we're not the whole thing. I think the whole field of spatial biology should include everything. I don't think it's about being 500-plex and above; spatial biology can be 1-plex or more as it's imaged in a sample. I think people have to put these different tools together and have time to just develop new drugs. It's a long cycle, and we may not see some of that for years.

On that note, one theme we’re hearing more often in spatial biology is that the market is becoming a multi-platform ecosystem, with different platforms occupying their own niche. What’s your view on that and where do you think the space will head over the next few years?

It feels like an abnormally competitive space. There's been a lot of investment in the higher-plex area, which I think has led to many competitors trying to duke it out for the same set of customers. There's a weird phenomenon when you talk to scientists – they like to stratify a bit and say “this platform is good for one thing and that platform is good for another” to rationalize their purchase, and I don't know if it's always true. A lot of the high-plex spatial platforms are similar, but with slightly different flavors. But it usually comes down to going with whichever one you bought first. I think a few of them will disappear, and I don’t think the market can sustain 6-7 different companies all selling half million-dollar instruments with really expensive reagents. The closer you get to translational, the more that companies like Danaher, Agilent, and Roche have a foothold, so it’s unclear what’s going to happen. One reason we chose not to go down that path 3-4 years ago is that we weren't sure what the outcome would be. It may just be a useful discovery tool that a drug program uses once, and then continues with a more targeted and specific low-plex assays afterwards. We're very interested to see what happens here.

Molecular Instruments has made a strategic shift towards clinical grade solutions. What does the path look like towards offering a clinical grade solution, and how would more research-oriented tools need to be adapted to be applied to clinical applications?

To us, clinical-grade means it should have the same status as IHC – a tool that clinicians or drug development companies will turn to for being useful with real patient samples. Like I mentioned before, the framework we have for thinking about clinical grade is robustness, speed, and price, and that matters a lot for the academic market as well. Our goal now is solving the problem of how to validate this. Even in the well-established world of IHC, accurately tracking the location of RNA therapeutics spiked into samples remains a challenge. No one has solved this problem definitively yet. Today, people run one of these assays, look at the data, and make a call. There’s not really any validation that you’re definitely targeting the right thing.

We’re working on making products that are cheaper and faster since we need to compete with IHC. It’s not enough to be the best ISH product, since ISH hasn’t succeeded in the clinic. 

When you say RNA-ISH hasn't succeeded in the clinic historically, taking out the cost and speed component, what's really the issue there?

I think it's still a pretty new tool– it didn't really get popular until the 2010s. So I think the acceptance of it as a rock solid assay is still low. Pathologists love their IHC, they trust it, they know it works every time, and it makes sense since they have a patient's life on the line. So why turn to something that you may not trust? I think time will help, as well as showing that it's reliable, consistent, and high performance. What we’re learning in the clinic is people won’t do ISH if they can do IHC, so figuring out how to make the case for ISH is key. If you can’t do IHC since your sample is degraded and the proteins aren’t there, or if you don’t have a good primary antibody against that target, these might be cases where it’s better to do ISH. We’re trying to find those places where it makes sense to do ISH, rather than just shoehorn it in. 

For our last question here, we're curious if there's anything that you can share with us about what to expect for this year. Do you have any technical advances that you're working on or any fun announcements?

We're rolling out this clinical-grade messaging. We have a lot of interesting ideas that I think are new to people on how to validate – how to ensure you're doing high quality staining of your tissue, mostly on the biopharma side. We're also really excited on our academic side. We're introducing up to 10-plex parallel imaging, and these are real images with subcellular resolution. These are not like the spatial transcriptomics or spatial omics approach of more computational images, and we’re really excited about this. We're growing every year – we've been growing at about 40-50% year over year since we spun out in 2018 – so we’re excited to work on the big things we think are important. I think the next big thing is defining what clinical-grade is. We really like that term because nobody uses it, so we can put it out into the world and then also define it. So that'll be a big part of what we do not just for the rest of the year, but in the years to come.

We’re excited to watch and see how that all unfolds!