I’m pleased to be joined today by Peter Fromen, CEO of biomodal. biomodal (previously Cambridge Epigenetix) is an omics-based life sciences technology and analytics company, developing products that bring biological dynamism into focus. biomodal has developed +modC, which uses enzymatic, single-base resolution sequencing technology to enable simultaneous reading of genetic and epigenetic information on the same DNA fragment, in a single low-volume sample – in one workflow, using any sequencer.
Tell us a little about your background.
I've been within the genomics and life sciences space for roughly 25 years now. And one of the things that I've seen over time is the epigenetics field has always been on the horizon and has captured quite a bit of interest, but there have been limitations from a technology perspective, a methods perspective, to fully realize the potential of epigenetics. And so, through my engagement with the team at biomodal and the founders and the board before I joined, I saw an extremely elegant technology that satisfied this unmet need and provided potential energy in the space that was limited by the lack of a technical solution. So having spent my career at companies like PacBio, 14 years at Illumina, also before that Applied Biosystems and Agilent, I saw real potential to apply this technology into a market where epigenetics, I would argue, hasn't fully reached its potential by any means. And also in a backdrop where a multi-omic kind of readout is becoming more and more the norm and a requisite in order to either drive to discovery or diagnosis for that matter.
Can you elaborate on biomodal and the company's focus here in the space.
So one is that given where we were and where we are with respect to our technology, the company had done quite a bit historically in creating novel technologies and making advances in the genetics and epigenetics space. The company sort of pivoted for a bit into more of a biomarker discovery objective and strategy squarely in the oncology space and really in the liquid biopsy space as well. And in doing so, went down the fortunate path to license some incredibly important intellectual property around the enzymatic conversion of the cytosine base. And so looking at that foundational IP plus this novel and elegant technology and that capability of being able to integrate an epigenetic perspective and a genetic perspective into a single workflow -- with this IP -- teed us up with an opportunity to introduce a solution and meet that unmet need in the oncology space across a range of applications. But very specifically also in the liquid biopsy space, really across the application stack within liquid biopsy. So we felt that it was also imperative to move and acknowledge that shift in focus and shift in strategy. It was imperative to acknowledge that through a rebrand of the company as well so that the brand of the company was indicative and commensurate with our objective as a company. Our mission is really to deliver and develop technologies that help customers elucidate the dynamism of biology, through various modalities of epigenetics and genetics, -omics together in a single sample. So that was a big initiative around the rebrand, and the focus has squarely been around delivering this novel capability, epigenetics and genetics in a single solution, predominantly into the oncology space, but into a number of other incredibly important segments as well, namely neuro and immuno and cellular development and reprogramming.
What hurdles do genetic and epigenetic testing face in precision medicine applications?
I think it goes back to what I was saying earlier about some of the limitations of the technology. And if you go back historically and look at the progression of genetics and epigenetics, you saw with the technology, genetics was always the sort of dominant field. And the technologies followed where the research funding was going and these elegant solutions started to evolve. And we went from CE-based or capillary electrophoresis-based sequencing to map the human genome, and then started to really interrogate the genome through more genotyping-based studies that led to the whole era of GWAS (genome-wide association study). That then started to migrate to exomes and to genomes. And while the genomics technology continued to advance and advance and advance, there still wasn't necessarily an elegant solution to apply sequencing to methylation or to epigenetics more broadly. You had to perform numerous complex workflows and nothing was really scalable. So epigenetics and methylation was largely relegated to the world of arrays, and it's still, for the most part, still there.
And so that's also one of the opportunities we see. And while it's a hurdle, it really is sort of that gating coefficient that's leading to the unmet need. So we think that there's this huge potential to help the epigenetics field migrate from the EWAS (epigenome-wide association study) phase on an array-based technology, and take those findings over to a sequencing-based platform that allows, again, low-input single sample and a more holistic approach. So you're not limited to an a priori data set that you're interrogating, but you can really drive discovery by taking off the masks, if you will, and looking without any hypothesis, in a hypothesis-free perspective across the genome.
What do you think are the benefits of capturing genetic and epigenetic information at the same time?
At the end of the day, the simultaneous capture allows researchers to better understand gene expression, cellular function, environmental adaptation, and disease development, all which could really help to identify therapeutic potential targets for therapeutic intervention. But at the base level, being able to integrate a perspective where you can actually look at gene regulation on top of the canonical bases. So you're looking at the regulation information simultaneously and at the same time you're actually sequencing the canonical bases. So that gives you the ability to understand, at the molecular level, with base resolution, what's modifying any variant within the genome and start to understand mechanistically how that's going to translate to regulation and ultimately transcription downstream. So the ability to do that with higher accuracy and greater sensitivity to show this sort of interplay between genetic variants and DNA methylation markers is of huge value.
What kinds of diseases or fields would this analysis be appropriate for? And how can it be applied to precision medicine, for example in cancer?
First and foremost, we think the most significant opportunity here is in the oncology space. We think our technology aligns extremely well there, because of, again, this combinatorial power of including genetics and epigenetics at the molecular level with single base resolution. So you can really look at allele specific methylation in the context of somatic mutation. But then also we are able to really sequence through, on average, the entire fragment within a cell-free DNA extraction. You're looking at your average fragment read length of cell-free DNA at about 147 bases or so. And so we can sequence through that entire fragment and pick up end motif information, which is highly relevant in the context of fragmentomics. But we also have extremely low input, so we can get exquisite data down to two nanograms of input, which tees up the assay to be right in the wheelhouse of a lot of liquid biopsy applications. And then furthermore, we translate the canonical four base states into 16 states of information by doing some two base encoding, basically, where we look at each base twice in order to make a call. We're only using six of those states for modal information or genomic and epigenetic information. We use the other 10 states to suppress errors. So we get exquisite data quality as well, in excess of Q35s across the genome. So with that, oncology is teed up extremely well.
But if you also look at the role of methylation in a number of other biological areas, development is unquestionably a key area. As the body starts to age and you see the impact of age and environment on starting to unravel our developmental biology, you start to see disease arrive. And so the entire aging space is an area that we're focused on. You know, the Horvath epigenetic clock is sort of paramount within the epigenetics field. So we're seeing quite a bit of demand within the aging and cell reprogramming space.
And another area I mentioned earlier also is neurodegenerative disorder. We published in Nature Biotech earlier this year, in February, that our technology has the ability to look at or discriminate between 5-methylcytosine and hydroxymethylcytosine. So neuro is an area that we're excited by because of the relative abundance of hydroxymethylcytosine in neuronal tissue. We think that the brain is one of the major last frontiers within human biology, particularly from a omics perspective. So we think we can offer a huge amount of value to researchers in that space.
Are there any specific applications of interest within precision medicine, for example liquid biopsy?
If you look at the application stack within liquid biopsy, we know that methylation is highly relevant in the context of detection and enabling earlier detection based on methylation markers, not just for detection of disease, but also looking and aligning back to the tissue of origin without needing to go into any more invasive procedures. But when you think then about adding the methylation profile to genomics, you start opening up additional application space in terms of actual comprehensive genomic profiling and actually looking at and profiling a tumor in a liquid biopsy context. So then therapy selection becomes within the wheelhouse, as does “MRD” or minimum residual disease detection and monitoring. So we think being able to look at the in-depth genomics associated with any sample provides a therapeutic context and monitoring that also provides the ability to look at the impact of therapy on methylation profiles and also any potential additional somatic mutation. So MRD is unquestionably an area that we think we can add a lot of value in.
How is +modC designed to address these applications?
I think one of the big perils in the space is, as I pointed to earlier, because of the limitation of a lot of the technologies, you have to divide sample if you want to actually be able to capture all this information. So if you're starting with extremely low volume and low fraction of cell-free DNA in your sample, the last thing you want to do is have to split that up and run multiple workflows, let alone the additional cost of multiple workflows as well. Given that we can take down to two nanograms of cfDNA into our assay, and show incredible sensitivity and specificity uniformly throughout the genome, we think that's a huge value add. Plus, by keeping or delivering Q-scores in excess of 35 and beyond, we think there's a significant benefit there.
What's next for biomodal?
We've rebranded the company, and we launched our first product this year at AACR. We started shipping in May of this year. So we're really focused on expanding our customer base within the cancer research space and also the cancer diagnostic space. But, going forward a lot of the future is opening up additional modalities on that same assay construct and platform. So I mentioned the publication in Nature Biotech earlier this year where we talked about and showed the ability to discriminate between 5-methylcytosine and hydroxymethylcytosine. And so we'll be launching products into the beginning of next year that facilitates that. Given that and given what we think is the importance of hydroxy in cancer and also early detection within cancer, we think there would be a significant application there. And, as I alluded to earlier, in the neuro space just given the relative abundance of hydroxymethylation in neuronal tissue.
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