The field of single cell continues to evolve at a remarkable pace. In the span of 5 years, this market has transformed from one that was essentially non-existent to one that enables thousands of researchers to better understand the fundamental unit of biology. The most recent evolutions include assessing multiple analytes simultaneously (i.e., multiomics), capturing spatial information, and using functional characterization. IsoPlexis is among the key companies tackling the functional characterization of cells.
IsoPlexis recently reported $17M in revenues for 2021 (up 66% from 2020) and >200 instruments placed, including in all of the top 15 pharma companies. We caught up with CEO and co-founder Sean Mackay to hear more about recent developments at IsoPlexis
Sean, thanks for taking the time to speak with us today. For our readers who are less familiar with IsoPlexis, can you give us some background on the company?
The evolution of IsoPlexis was based on the idea that you could look at single cells the way you might do with flow cytometry, but with an additional layer of meaningful information for the human immune response. This is the measurement of secreted proteins like cytokines, chemokines, and growth factors that are the functional end of every immune cell. So, we built a platform that could uniquely detect the wide multiplex array of these functional proteins per single cell in ways that flow cytometry and droplet-based single cell genomics can't.
If you look at our core business, we've gained traction in the translational and clinical research segments. People are using our unique functional single-cell readouts to do things like advance cell and gene therapy programs and hone in on the most potent immune cells—what we call “superhero” or “superhuman cells”—among their very heterogeneous cell products. We’ve seen recent uptake in cancer immunology where our platform is being used to assess cells from patients undergoing a variety of checkpoint combination therapies, and researchers are finding “super cells” that were closely related to, and predictive of, a durable response to cancer.
We’re hearing excitement about single cell approaches in those fields as well, and it makes sense. We’re seeing companies kick the tires on several of these approaches, to figure out how useful they’ll be. Can you tell us about Isoplexis' core technology and how you're enabling customers to look at secreted proteins of single cells?
The original thought behind the technology was that there are two traditional ways to do analysis of single cells. There is flow cytometry, basically passing cells through a tube. Then there's droplet-based analysis, which is putting the cell in a droplet and capturing the mRNA or ligated surface proteins. Jim Heath and Rong Fan, my co-founders from Caltech and Yale, came up with a way to capture the single cells but also do what we call proteomic barcoding. This means we can barcode down antibodies that would be highly multiplexed per cell, in a highly sensitive and specific manner in that very small location in a chip.
So, if you take one of our chips, you're getting a series of 10,000 chambers that all have these lines of antibodies that cross each of the chambers in exactly the same way. That parallelization is extremely important. What your end readout simplistically looks like is a highly multiplexed ELISA type reaction—so, 30 to 35 proteins from serum. For every small chip, you're getting a thousand single cell highly multiplexed ELISA reactions using our proteomic barcoding.
The interesting thing is that, with the evolution of fluorescence-based detection on our platform and higher densities of chambers and antibody lines, we have the potential to continue this progress. We would start from the original 10 or so proteins, to 20 to 40 and then going pretty far beyond that, just using this combination of fluorescent factors and spatial density factors.
I think the core technology is doing all these amazing things for secretory proteins, but there's so much more room to grow into.
We’ve touched on this a little bit, but can you expand upon the analytes and the cell types that people are excited about?
The cell type that kicked off the growth of the company was T cells. There is a range of different types of cytokines, chemokines, and growth factors that come from T cells and have significant effect on immune function, but no one could measure them simultaneously. Typically, people were measuring three at a time from each cell by flow cytometry.
We expanded that to cover all degrees of effector, regulatory, stimulatory, etc., cytokines from each cell. Most importantly, we showed that in human CAR-T cells and primary T cells, there is a group of rare but important cells (5-10%) that are high simultaneous secreters forming a metric called the “poly functional strength metric,” which is essentially the frequency of super producer cells. If patients have these super producer cells, it’s predictive of how they're going to respond to therapies. That formed the basis for the core interest.
In the last year or so, we launched this program for our customers called the Superhuman Cell Library. Simplistically, it's the functional proteomic equivalent to what the Human Cell Atlas has done so successfully. We’re in the very early stages but we've expanded the cell types people look at, with the help of our customers, to all manners of immune cells, T cells, natural killer cells, monocytes, structural immune cells like fibroblasts and endothelial cells, etc. What our customers are showing, through high impact papers, is that you can get very impactful insights on functional cytokines and how to modulate the cells producing them. That level of resolution doesn't exist on flow cytometry and doesn't exist in bulk.
How do you envision researchers will use the Superhuman Cell Library and what’s the overarching goal?
As we placed more instruments, we started getting more and more questions on the breadth of our cell menu. People would get the technology for one cell type and quickly realize that in order to understand their mechanism of action, they need to look at all immune cells. There was clearly this need to go expansive, rather than just narrowly focusing on certain types of immune cells. We also wanted to facilitate centralized access to data that was being published on our platform across several cell types. This library acts as a research tool with an annotated list of cell types that you can just scroll through and search. You can piece together how to study different cell types without always needing the guiding hand of our field application specialists. Now we have a lot more cell types and functionally relevant cell subsets that matter to a range of diseases and therapies. Since we've put them all in one place, it helps with usage and communication, and it also makes it easy and exciting for people to contribute to. That's our goal. People say the cell atlas has been so successful; we want people to feel that the next frontier is in proteomics and so they should do confirmatory studies on the protein to see if it matches expression.
The open access approach made me think about business models. I appreciate that you've made the library open, but you could argue there's a data play and an advantage to keeping that information for yourself to use it as a competitive edge. Can you elaborate on the decision to create an open platform and if there’s still a data play?
We think that there’s still a data play. There's always the question of how open or closed you want to go. There are benefits of both. We had a lot of data from running services for our customers. We decided that the networking capabilities that we’d get if published, were more important than the data ownership you might get at the cost of driving more growth. That was the trade-off for us and a difficult decision to make. Our belief in the end is that our highly multiplexed functional proteomic data is unique. Even if we can't own all the data, we own the assay. As people publish, they’ll use our assay to generate more of the data.
I tend to agree. We come from the perspective of furthering science and driving innovation, and that's exactly what this does. Great. Let’s talk about the science that your platform is enabling. What are some key studies that you are excited about? There was a recent Cell paper I saw on long COVID. Congrats. Could you tell us more about the insights that came from that work?
There were a couple of Cell papers that looked at the impact of functionally active immune cells. The original Cell paper focused on immediate inflammation in patients, which was driving that very confusing and problematic cytokine release type syndrome when COVID first came into the world. We explained a little bit of that in terms of which cell types were involved, for example, macrophages. The second Cell paper was focused on better understanding long COVID. There was a need for multiomic tools, including ours, to piece together higher-level conclusions that could inform therapeutic treatments for long COVID in the long run. Patients can be categorized based on hyperactive cell types and we played a part in that categorization. With that information, you can start to explore the causes of long COVID.
Over the last 6-12 months, we started expanding beyond cell and gene therapy, which is where people have traditionally used our platform. We published a few papers, one in the Journal of Clinical Oncology, showing you can measure durable response in patients on a checkpoint inhibitor combination therapy using our super cells. We followed up with an MD Anderson paper with another checkpoint inhibitor combination, showing a similar response type metric from our super cells. Then we followed up with an MSKCC paper showing a similar evolution of this poly functionality being a core component of patients with a better response. For us this is important, as the impact we’re having in major clinical centers is becoming more evident and public, helping deconvolute what’s happening with immuno-oncology biomarkers. These publications show that we’re not just measuring CAR product, but immune health in cancer patients. We have a very important and differentiated tool that’s just showing the beginnings of biomarker and mechanistic understanding. This is a big bucket of customers we’re talking about and we’re just getting started exploring this area.
That’s really exciting. We’ve tracked the immuno-oncology biomarker space for a while now and we’ve seen an uptick in immune cell population characterization as a biomarker (I/O BioMAP). We’re always looking to see how novel tools and technologies transition to clinical applications, and it’s often a slow process. It's great to hear that these clinical applications are emerging already. The single cell field is moving rapidly. In just a few years we’ve gone from looking at RNA alone to RNA in combination with cell surface proteins or chromatin accessibility. It’s clear you’re seeing the same trend and keeping pace. Can you talk about some of the additions and improvements you’ve made? What was the impetus for these solutions (e.g., Duomic, Intracellular Proteome) and how are you seeing these approaches being utilized, or how do you envision they’ll be utilized?
I think you put it well when you said that the goal for us has always been to advance science understanding. We were talking to customers very early on about what they’d like to see from us. The number one request was to be able to capture the proteomic data from each cell and to sequence the associated T-cell receptor. That would be the ultimate biomarker to know antigen specificity and potency. It’s always been a goal of ours to be a multiomic player. We’ve made a conscious decision to invest a lot more in that the last couple of years. That field was very small when we were getting those requests, and suddenly in 2019, single cell multiomics became Nature’s method of the year. We’ve seen a trend that once an approach is named ‘method of the year’, in 3-5 years a huge market crops up as a result. So, we got more serious about it, made acquisitions, picked up sequencing intellectual property from QIAGEN that allowed us to create a process to capture mRNA and protein in the same chamber. We put out a lot of data last year, so this is picking up steam for us. No one else has enabled the assessment of cytokines, chemokines, growth factors and gene expression the way that we have. That’s an exciting value proposition to customers. We have a unique avenue to biopharma and clinical customers with this potency part via proteomics, and now we’ve added the gene expression component that’s making the single cell multiomics market more clinically relevant. We’re super excited about this and we’re spending a lot of time on this.
It's fascinating to see how this field has evolved. The pace of innovation is remarkable. It’s a great time to be a participant in the space.
It's exciting but it’s interesting right now because we're in the midst of a lot of concurrent macroeconomic problems. Interest rates, inflation, war—these are things you don't normally want to combine in the same sentence. It's unfortunate for life science companies, in general, at this moment in the markets. However, if you think about the therapies we’ve been able to create over the last several years based on the tools we had access to, imagine the therapies we’re going to create over the next decade with these emerging and enabling tools.
So, maybe a couple of last points. The first is around workflow. I think the continued penetration of single cell approaches will be tied to the ease of the workflow. Can you talk about how you’ve approached the workflow? The second is on your outlook for IsoPlexis. What are some of the key areas of growth in your mind in the next few years?
On the workflow part, we know data is extremely important because the data itself is what adds value. Even with the best data, if you don't have an approachable workflow, you can't sell into pharma and biotech—and this customer group represents 65-70% of our business. The ability to have true, walk-away automation is key. Our system does all the proteomic ELISA washes and workflow steps. It’s all handled in the chip, facilitated by the fluidic system. If we didn’t have that, we would not have any of those industrial customers because they don’t have the time to cobble together a manual process like academics are willing to do. So, workflow is extremely important for our single cell proteomics business. We’re going to try and do this for single cell genomics too, though it’s more complicated as we’re adding a library prep component.
In terms of outlook for IsoPlexis, there are several things. The first is that our main business in single cell proteomics has accelerated a lot over the last two years and it shows no signs of slowing down—which is great. It's so much easier to communicate about the technology now than it was three years ago when no one knew what it was, and we had very few publications. The thing that I love to see, and which I think is just the beginning, is: we hear from our customers all the time that reviewers are asking for more and more proteomic data to validate their findings. That's an amazing thing to hear when you’re a single cell proteomics company in a sea of single cell genomics companies. It shows a directionality I think we’re leaning into very strongly, this rising tide of proteomics.
Secondly, I'm also very excited about the single cell multiomics world. There are new avenues for connecting biology in ways that weren’t possible just a few years ago. The only way you're going to get a true understanding of how diseases work and therapies impact cells of the CNS and our immune system and tumor cells, is with single cell multiomics. This is going to be such a huge avenue, first for early discovery-based research and then for clinical research in the next 10 years. I said it before, but this is an exciting thing for all of us to be a part of.
Agreed. Exciting time. Thanks, Sean. I really appreciate you taking the time to speak with me today. It’s always exciting to talk with people in the space who are creating enabling technologies and pushing the boundaries of the field. All the best this year, and we look forward to seeing what’s in store for 2022.
Images provided by IsoPlexis.