Cambridge, UK-based biotech startup Mogrify, which is working on systematizing the development of novel cell therapies in areas such as regenerative medicine, has closed an initial $16 million Series A.
Put simply, Mogrify’s approach entails analysis of vast amounts of genomic data in order to identify the specific energetic changes needed to flip an adult cell from one type to another without having to reset it to a stem cell state — with huge potential utility for a wide variety of therapeutic use-cases.
“What we’re trying to do with Mogrify is systematize that process where you can say here’s my source cell, here’s my target cell, here are the differences between the networks… and here are the most likely points of intervention that we’re going to have to make to drive the fate of an adult cell to another adult cell without going through a stem cell stage,” says CEO and investor Dr Darrin Disley.
So far he says it’s successfully converted 15 cells out of 15 tries.
“We’re now rapidly moving those on through our own programs and partnership programs,” he adds.
Mogrify’s business has three main components: Internal program development of cell therapies (current cell therapies it’s developing include enhancing augmented cartilage implantation; non-invasive treatment of ocular damage; and for blood disorders). It’s also developing a universal source of cells for use in immunotherapy — to act as “disease-eaters”, as Disley puts it.
Speculative IP development is another focus. “Because of the systematic nature of the technology we’re in a position very rapidly to identify areas of therapy that have particular cell conversions at their essence — and then drive that IP generation around those cells very quickly and create an IP footprint,” he says.
Partnering deals is the third piece. Mogrify is also working with others to co-develop and bring targeted cell therapies to market. Disley says it’s already closed some partnerships, though it’s not announcing any names yet.
The startup is drawing on around a decade’s worth of recent work genomics science. And specifically on a data-set generated by an international research effort, called Fantom 5, which its founders had early access to.
“We started with that massive Fantom data-set. That’s the baseline, the background if you like. Think of it like two cities in America: Chicago and New York. There’s your source cell, there’s your target cell. And because you have all the background data of every piece of the network — every building, every skyscraper — if you look at the two you can identify the difference in the gene expression, therefore you can identify which factors will regulate a wide array of those genes. So you can start identifying the differences between the two,” explains Disley.
“We’ve then added to that massive data sets in DNA-protein and protein-protein interactions… so you start to now overlay all of that data. And then we’ve added on top of that new next-gen sequencing data and epigenetic data. So you’ve now got this massive data-set. It’s like having a network map between all the different cell types. So you’re therefore then able to make predictions on how many interventions, what interventions are needed to drive that change of state — and it’s systematic. It doesn’t just recommend one set. There’s a ranking. It can go down to hundreds. And there is some overlap and redundancies, so for example if one — you’re preferred thing — doesn’t work the way you wanted it to you can go back and select another.
“Or if there’s an IP issue around that factor you can ignore that piece of the network and use an alternative route. And once you’ve got to your target cell, if it needs to some tweaking you can actually re-sequence it and take that back and that’s your starting cell again. And you can go through this optimization process. So what comes out at the other end… you’ve got a patent that it like a small molecule composition of matter patent; it’s the therapeutic. So you’re not coming out with the target, you’re actually coming out with here is the composition of matter on the cell.”
In terms of timeframe for getting novel cell therapies from concept to market Disley suggests a range of between four and seven years.
“Once you’ve identified the cell type that can be be the basis of your GMP manufacturable process and then you can tweak that to take it to the therapeutic indication you can develop a cell therapy and bring that to market in five years,” he says. “It’s not like the old days with small molecules where it can take ten, 15, 20 years to get a serious therapy on the market.
“When you’re treating patients… is because there are no other treatments for them, when you go into phase two and do your safety study [and] efficacy study you’re actually treating patients already in terms of their disease. And if you get it right you can get a fast track approval. Or a conditional approval… so that you may not even have to do a phase 3 [testing].”
“We’re not using any artificial intelligence here,” he also emphasizes, pointing to his experience investing in companies in the “big extreme data space” which he argues do best by using “unbiased approaches”.
“AI I think is still trying to find its way,” he continues. “Because in its essence it will be able to get to answers with smaller amounts of data but it’s only as good as the data you train it on. And the danger with AI… it just learns to recognize what you want it to recognize. It doesn’t know what it doesn’t know.
“In combination, once you continue to generate this massive cell network data etc you can start applying aspects of machine learning and AI. But you couldn’t do Mogrify with AI without the data. You have to do it that way. And the data is so complex and combinatorial — 2,000 transcription factors, in terms of regulation of those genes, they then interact in network to do the protein-protein interactions, you’ve got epigenetic aspects of that, you could even start adding cell microbiome effects to that later — so you’ve got a lot of factors that could influence the phenotype of the cell that’s coming out the other end.
“So I think with AI you have to be a little careful. I think it will be a more optimizing tool once you’ve got sufficient confidence in your system.”
The plan for the Series A funding is to ramp up Mogrify’s corporate operations and headcount — including bringing in senior executives and expertise from industry — as well as spending to fund its therapy development programs.
Disley notes its recent appointment of Dr Jane Osbourn as chair as one example.
“We’re bringing in more people with a lot of cell therapy experience from big pharma, around then more on the manufacturing and delivery of that — so really building so that we’re not just a tech company,” he says. “We’ve very strong already, we’re already 35 people on the tech and early stage drug discovery side — we’re going to add another 30 to that. But that’s going to be increasingly more people with big pharma, cell therapy development, manufacturing experience to get products on to market.”
Partner search is another focus for the Series A. “We’re trying to find the right strategy partners. We’re not doing services, we’re not doing products — so we want to find the right strategic partners in terms of doing multi-programs in a partnership,” he adds. “And then a series of more tactical deals where people have got a specific problem with a cell conversion. These more turnkey deals, if you like. We still get up-fronts, milestones and royalties but they’re smaller.”
Despite now having enough money for the next two to two and half years it’s also leaving the Series A open to continue expanding the round over the next 12 months — up to a maximum of another $16M.
“We have so many interested investors,” Disley tells us. “This round we didn’t actually open our round. We did it with internal investors and people we’re very close to who we’ve worked with before, and there were investors lining up… [so] we are leaving it open so that in these next 12 months we may choose to increase the amount we bring in.
“It would be a maximum of another $16M if it was an A round but we may decide just to go straight forward if we progress very fast to a much bigger B round.”