Fulcrum Therapeutics - A Single Repository For Collaboration, Compliance, and Control

Chris Moxham, Ph.D., is the Chief Scientific Officer at Fulcrum Therapeutics, an innovative biotech addressing the causes of genetically defined disease. By developing treatments that address the root cause of disease, Fulcrum goes a step further than creating therapies that just manage symptoms and develops treatments that alter the genetic expression of disease, enabling life-changing outcomes.

Like many in the Life Sciences, the challenges that Fulcrum face are similar to those across the drug-development industry. The outsourcing of specialized tasks is increasing, and the data that is generated from these efforts is massive, often unstructured, and scattered across repositories. Maintaining GxP compliance, creating a secure environment for collaboration, and ensuring there is a single source of truth are becoming more and more of a hassle.

“There has been an explosion of data types and the data sets we work with are quite large, things like high-content imaging and sequence data. The ability of Egnyte to store the data files on a compliant platform and provide seamless access to scientists so we can create knowledge and move forward has been invaluable.”

- Chris Moxham, Ph.D., CSO at Fulcrum Therapeutics

Fulcrum has turned to technology to help automate many of these processes in order to streamline collaboration with third-parties and the organization of data into a single repository. Listen in to Chris’ talk with Alok Tayi, Ph.D., VP of Life Sciences at Egnyte:

Transcript:

Alok Tayi, Ph.D.:

Hello, everyone. Thanks so much for joining us today. My name is Alok Tayi. I'm the VP of Life Sciences here at Egnyte. Really excited to moderate. Today's fireside chat with Dr. Christopher Moxham from Fulcrum Therapeutics. I will be talking a little bit today about the modern world of drug development and some of the innovations we're starting to see come to the forefront along with how technology is playing a much more critical role in bringing new medicines to market. So we'd love to maybe just kick off introducing our guests. Chris who's a senior vice president of drug discovery at Fulcrum Therapeutics. Chris, thanks so much for joining us today.

Chris Moxham, Ph.D.:

Oh my pleasure. Thanks very much for having me.

Alok Tayi, Ph.D.:

Yeah, well, you know, maybe to kick us off, we'd love it. If you could perhaps just give us a quick intro on yourself and your background and how you got to where you are today.

Chris Moxham, Ph.D.:

Yeah, sure. I'd love to, I'm a pharmacologist by training PhD in pharmacology. I've been at a Fulcrum Therapeutics as you noted for just about two years now. Prior to that, I was at Eli Lilly and company where my last role there was the vice-president of quantitative biology. I was at Lilly for about 20 years and during the course of my career, I've worked over, worked in multiple therapeutic areas utilizing both small and large molecule drug discovery approaches as well as led translational groups. And so it's really a pleasure to be here with you today and talk more

Alok Tayi, Ph.D.:

Wonderful. Well, you, you know, maybe I think a great step might be to learn a little bit more about Fulcrum, some of the interesting work the team's doing there, that's some of your programs and we can sort of dive in thereafter.

Chris Moxham, Ph.D.:

Yeah. So Fulcrum Therapeutics is just about five years old. Now we were launched from Third Rock Ventures. We went public in July of last year and we're a company that focuses specifically on rare disorders. And we built an R and D capability to utilize and discover and develop small molecule therapeutics to address those rare diseases at their root cause by modulating gene expression, either up or down to deliver a clinical benefit to those patients. We have three clinical programs. As of today, we have our first program in muscular dystrophy called FSHD or fascia scapula humeral dystrophy. This is a program that's currently in phase two. We discovered a P38 map kinase inhibitor and licensed that molecule from GSK and again are in phase two of that program. We have a phase three program that we just initiated earlier this year in COVID-19. And then we're just initiating now a phase one program in sickle cell disease. Again, a program that we discovered both the target and the medicinal chemistry were all done in-house and are very hopeful about this based on the preclinical data that we've generated thus far have a stable of portfolio pro programs in the pre-clinical phase, all with the same sort of flavor of focusing on where genetically defined disorders and trying to discover and optimize small molecule therapies.

Chris Moxham, Ph.D.:

Wonderful.

Alok Tayi, Ph.D.:

Certainly sounds like a you know, Fulcrum’s off to a pretty good start. And I've always been impressed with how quickly the organization has been able to reach pretty critical milestones like clinical programs and going public. So it must be quite an exciting time for you in Cambridge.

Chris Moxham, Ph.D.:

It really is. And I think a lot of our early success stems from the fact that we are focused on the root cause gene or the root cause of these diseases. And so we're starting from a highly validated disease proposition if you will.

Alok Tayi, Ph.D.:

So, you know given that much of the audience today is probably really interested in learning more about this intersection of drug development and life sciences along with technology. I'd love to just maybe get some of your thoughts and experiences about what you've been seeing in the space around data, collaboration, compliance, et cetera, and some of the interesting trends or tactics you and your team at full commitment.

Chris Moxham, Ph.D.:

Yeah, I think in terms of trends and needs certainly the trend in terms of the different types of data that we're generating the amounts of data that are being generated both internally and externally, right? So certainly there's been a large boom over the last decade and a half in outsourcing. And so the ability to manage data internally, as well as coming from external sources in a secure fashion, the ability to organize that data intelligently within the company so that we can translate it into knowledge is just, is a major factor. And that's really where the unite Egnyte framework comes into place for us becomes a great help to us in achieving that,

Alok Tayi, Ph.D.:

You know, on that topic, you know, given that Fulcrum has grown so quickly and you have both in licensed and internally developed programs, as well as, you know, most of the major sort of key functions like clinical and obviously research and regulatory, any initial tips or suggestions you'd provide to the broader audience around how to organize that data in a somewhat logical you know, scalable manner.

Chris Moxham, Ph.D.:

Yeah, I think the key there is so I think as individuals begin to organize their own data, everyone starts to customize how they do it. And while that works for the individual, it doesn't necessarily work for the organization either because they've organized, organized it in a way that's only logical to them or that they perhaps aren't instituting the proper security and compliance procedures in place that, that are required either to protect information within the company or to be compliant as a publicly traded company. So Egnyte really for, from my perspective and fruitful can therapeutics has really allowed us to, to organize the data in an architecture that makes it logical in terms of how do we access it who has control or the ability to access that information both again, as we're conducting internal experiments, but also as we're doing clinical trials and certainly want to be compliant in terms of regulatory procedures and how we're storing and protecting that data.

Alok Tayi, Ph.D.:

Yeah, no, that makes sense. And definitely seems like ensuring that you have sort of consistency with how you manage a lot of that data, as well as perhaps some elements of scalability as you bring more programs into the clinic makes a, is a key focus. Is that fair?

Chris Moxham, Ph.D.:

Very fair. I think scalability is another great point that you are generating more and more data and the hope is that we'll scale the portfolio as well. And so the ability to scale that architecture is critical. Yeah.

Alok Tayi, Ph.D.:

Awesome. Well, you, you know, given that you focus mostly on the discovery side of the organization, I'm curious to hear a little bit about sort of how the organization is currently structured and where you're sort of doing much of your work, whether it's internally or externally and how you're sort of facilitating collaboration and, and seamless flow of data and that sort of,

Chris Moxham, Ph.D.:

Yeah. So as a small molecule R and D organization from the preclinical side, you know, we have work going on within the biology realm, obviously from a medicinal chemistry perspective, designing molecules internally, a lot of that synthesis is conducted externally. And from my team's perspective, we do a lot of outsourcing and we've worked closely with a company called science exchange that helps us not only get access to CRS and providers, but also through that platform, we pull data back into the organization. And I think one of the clever things that we've done in partnership with Egnyte is to Institute a framework where as requests are accepted within the science exchange platform immediately, a folder is created automatically within Egnyte. That is specific for that request to a defined location it's created there every time. So it creates a very logical and standardized process around how data will be structured and located.

Chris Moxham, Ph.D.:

Secondly, as that data comes back in from the CRO again, through the science exchange platform, that data, again, based on our integration with Egnyte, that data automatically goes into that specific folder. And so from my standpoint, there's no more sort of hide and seek around where the data is. And certainly, you know, within a small biotech, you can have churned in personnel or people aren't available when you want to access the information. And so it's very helpful to know where that information is without having to dig through email threads and all sorts of things to find it. So again, that that example of working with Egnyte and science exchange has really been a very, I think, useful one for us and a very productive,

Alok Tayi, Ph.D.:

It was wonderful. And, you know, we're certainly proud to have a deep close collaboration, obviously both with Fulcrum, but also at science exchange and, but 130 other sort of software companies to ensure data can flow seamlessly, right. Between different pieces of software. Really interesting to hear how you've sort of really focused on the automation and the linkage, right from those external players to your internal teams. So, you know, I'm curious then in terms of how the organization has operated recently, especially over the past year, given the myriad of different changes that have sort of taken hold. I'm curious if you could share some insights or experiences in terms of remote work or the impact COVID has had on the organization.

Chris Moxham, Ph.D.:

Well, certainly it has many of us working remotely, right? And so it's not easy to get together and talk about data and look at somebody's computer screen and see what looks at data in that way. And so again, the ability of storing files within Egnyte sharing links to where that data is stored while we're all in this remote scenario has really been very helpful and it's helped us honestly maintain our productivity at very high levels. So I think the, again, the ability to use Egnyte in that fashion knows where the data is and be able to share it seamlessly, with colleagues both internally and externally. I think it served us well during this period of COVID. And certainly, I think as we've all realized that COVID is going to introduce changes into how we work moving forward, the ability to, to work remotely and music night to the, to our advantage will serve as well.

Alok Tayi, Ph.D.:

Yeah. And you know, I'm curious given that you have a team of, you know, several dozen, how do you sort of lead in this unique time when everything is done remotely and you probably rarely see folks at least face to face in person any best practices you could share with the audience?

Chris Moxham, Ph.D.:

Yeah. I see someone hand, we do have a team of scientists still coming into the lab. And so being able to get in there and see them on occasion is great. But when that's not happening, what we've really tried to do is make a very deliberate effort to have more team meetings and more one-on-ones as a means, just to maintain that contact. So people aren't working in isolation as it were and just keep the conversation going. So I've actually found it in some ways to be more productive time because you eliminate some of the bureaucracy with just having meeting after meeting, but it's also been a challenge and something we have to be intentional about in terms of staying connected.

Alok Tayi, Ph.D.:

Yeah. I'd imagine, especially when it comes to things like onboarding and, you know, external collaborations, definitely wanting to think differently there.

Chris Moxham, Ph.D.:

Yeah. And we certainly had several employees who've been onboarded without having met anybody, given the current situation. So it's again, just trying to stay in touch with each other and, and keep everybody up to date on moving parts and what's important and priorities.

Alok Tayi, Ph.D.:

Yeah, absolutely. Well, you know, one of the interesting things that I think it also touches upon is that obviously within your team, it sounds like things have been moving along pretty well, which I'm really excited to hear, but the other part is, you know, as a broader organization you know, there are other pipe parallel functions like finance and HR that you probably have to collaborate with as well as activities like being a publicly-traded company that perhaps put other types of compliance and regulatory type requirements on the organization. Curious how you know, from other data perspective or from a remote work standpoint Fulcrum a sort of tackled some of those

Chris Moxham, Ph.D.:

Yeah, well certainly from a data perspective and a compliance perspective, and I'm not a regulatory expert, but certainly we are instituting all of the appropriate security and permission controls as it were within Egnyte to protect that information in a compliant fashion. And certainly as a publicly traded company. Again, I think within Egnyte, it's a nice uniform platform to share data internally, but it's also one in which you can control access obviously. And so whether it's various HR topics or the like it's very fungible to, to the needs of the organization in terms of how we want to share information and store data.

Alok Tayi, Ph.D.:

Yeah. Makes sense. You know, in that regard then I know at Fulcrum and given you know, your perspectives around imaging and high dimensional type measurements and datasets there's been some really interesting work. Your team has performed, we'd love to hear a little bit more about how you're starting to bring data in a unique way to the forefront when it comes to analysis and moving your programs forward.

Chris Moxham, Ph.D.:

Yeah. So, you know, as I mentioned at the start, certainly there's been an explosion of data types, but also varied content technologies and the data sets themselves are quite large. So we do a significant amount of high contents cellular imaging. We're using high throughput, three-prime RNA seeks in our platform that we're calling Fulcrum seek we're generating single nuclei, RNA seek data as well. And so it's, these are high content platforms. They generate a lot of data and we are deploying machine learning on the back end of that, on these data sets. And so the ability, again, with an Egnyte to not necessarily process the data, but then store those data files and provide again, logical and seamless access for scientists to, to those data sets one, to do the analysis. And then on the backend of that, of course, is how do we convert that data into knowledge, right. And integrate different datasets and again, store those files and then provide access to the appropriate people so that we can as an organization create knowledge and, and move forward. Right.

Alok Tayi, Ph.D.:

Yeah. Interesting. No, you know, I know it strikes me as interesting in that these different types of measurements have historically existed. Right. We could have done high content imaging decades ago, gene sequencing, right. Decade plus ago. But it seems to be that at this point in time, it's lower in cost and more accessible. And there is more analytics and data oriented manipulation that needs to happen in confluence together compared to before. So given your experiences at other companies prior, if you had these sorts of capabilities, what would that experience have been like before you had sort of that data unified?

Chris Moxham, Ph.D.:

Well, two things, I think, the ability to process that information right. Would, would, would be just the cycle times would be far slower, right. I think even worse off yet, it would have been the ability to integrate all of that critical data into an understanding of what's happening in the context of a disease. And what's the effect of an, of a treatment. How do we build better models and integrated models that better reflect the disease, all of that knowledge that we're trying to create by integrating data sets, datasets, and having, you know, humans talk about it I think would be lost for those insights wouldn't be made as rapidly, or you wouldn't have it codified in a way where it's stored appropriately and you can access it at a later date. Right. So you lose, I think also some of that institutional learning that comes from having ready access to the information, not just now, but a couple months from now or years from now, that help you inform you

Alok Tayi, Ph.D.:

Makes sense. So if I'm hearing you correctly, it sounds like one data would be siloed historically second. It would be harder to process and extract insights from, is there also an aspect of cross correlation, right. Relationships between some data type or measurement and another one that might've been, might've been harder to do historically than today.

Chris Moxham, Ph.D.:

Yeah. Either correlations in the sense of, if you're only looking at one data Titan type and not looking at an orthogonal one, you end up going down the wrong path, right. Or those two data types give you some new insight that one on its own doesn't provide. Yeah. So, yeah, I think it's a matter of, you know, saving preventing loss time going down the wrong path. But again, for me, it's also just, it's rapid rapidly generating new insights that keep the organization moving forward and ahead of the competition

Alok Tayi, Ph.D.:

In that regard I'm curious, imaging is obviously certainly an approach that you and your team has really excited about. What other types of measurements or techniques or capabilities have you seen really be disruptive for your discovery phase programs?

Chris Moxham, Ph.D.:

No, I would say, you know, these single cell technologies are really, you know, we focus on muscular dystrophies as I pointed out and single cell technologies are really being helpful and use will be useful in terms of unraveling the heterogeneity within that skeletal muscle. For example, we know that skeleton muscle is composed of muscle, multiple different residents, cell types. They all contribute to the proper functioning of a skeleton muscle say in the context of regeneration after an injury. And so single cell technologies are going to be highly useful for us in terms of unraveling that heterogeneity, understanding what each of those key cell types are, what they're contributing and also how they might be dysregulated in a muscular dystrophy, for example. So I think single cell technologies will be, are, and will continue to be a really important advance as we think about preclinical drug discovery, as well as integrating those types of datasets from our clinical side.

Alok Tayi, Ph.D.:

Interesting. And, you know, from a, you made a comment earlier about data velocity, but also data variety, right. You know, imaging sequencing, you know, we've certainly heard about and worked with in the past, but I'm just curious if you sort of see, you know, moving sort of different hierarchies in, within the cell from genomics and DNA to say proteomics as having as disruptive of an impact as people claim it to be

Chris Moxham, Ph.D.:

Certainly we've been much more focused on the genomics part of it. I think there absolutely is a space in a play for proteomics where I would really like to see, go to is more of a global proteomics platform that allows us to sort of similar scale assess the global proteome, whether it's in the blood or, or even within a tissue. The other layer that we're kind of approaching is using technologies like imaging sites off on cryo sections, right? To get really high dimensional images, multi-spectral images of a tissue cross-section to understand how the different cell types are interacting with one another, for example, which ones are lost perhaps in the course of a disease. And so that you're right, there are different layers and, and managing those layers effectively, not only, again, the content of data and securely managing that, where when it's coming from an external source and efficiently managing it, but again, converting that and integrating it into knowledge on the back end is really critical.

Alok Tayi, Ph.D.:

Yeah, very interesting. And so, you know, as we sort of think about the future of drug development, especially from a technology perspective beyond I've seen, you know, genomics and, you know, some of the aspects of proteomics we just discussed, what do you see as sort of the most promising technological trend or a capability that will enable the next generation of direct development?

Chris Moxham, Ph.D.:

I think that the trend that we're in right now is probably the element of using clinical data to build models that are more informative and hopefully more predictive. I think that's the area where generating this type of high dimensional data, clinical data sets, building the appropriate models, using machine learning and the like, and then using those models to inform how we build cellular models in vitro is, is probably a really good, the trend where we, where we find ourselves today

Alok Tayi, Ph.D.:

Makes a lot of sense. You know, I think there's a lot to be done in the context of taking the data we've gleaned in building a model. I think those sort of first principles types understanding I think is so rare, especially in a biological context. But you know, certainly it sounds like an aspirational goal for the industry. Yeah. So, you know, before we wrap up here I think the last question I'd love to ask you is from what you've seen today and historically, do you feel like we're in the golden age of biotech right now?

Chris Moxham, Ph.D.:

I think we are honestly, I think just the intersection of technological advances, you understanding of disease people with good ideas and certainly venture capital to support that that clearly hasn't waned. And so I think it's really just a really could be characterized as the golden age. I think it's really just a great time to be involved in biotech.

Alok Tayi, Ph.D.:

Well, certainly a lot of promise and obviously given what's going on globally, I think a lot of import to the work that you and your team is doing. So, you know, with that, Chris would love to thank you for joining us on this discussion today and sharing some of your insights and you know, we'll certainly be both rooting for you and Fulcrum and hope you have another conversation soon.

Chris Moxham, Ph.D.:

Yeah. Thank you very much. I appreciate the opportunity to talk with you today. Thanks.

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