Jason has some answers to that question. In the interview below, he makes some excellent points about the value of having early adopters, and the differences between an academic and a commercial perspective.
Simon Sinek says that most people know what they are doing, some however don’t know how they are doing what they do, and very few know why they do what they do. So, what is your ‘why’?
My personal ‘why’ is entangled with that of the company. It's around understanding that epigenetics is such a powerful, powerful field that has potential to really revolutionize the way we think about healthcare. The ‘why’, is making that a reality. Why do we get up every day? Why do we come into work? Why do we work as hard as we do? It’s to leverage all the potential of epigenetics, and translate that into the clinic, because it hasn't happened nearly to the extent that it should. There have been years of research and millions of dollars poured into what has been a relatively niche field of study, but now that we've got the right technologies, we are able to further understand just how important epigenetics is and we need to translate that into some real benefit for humankind.
When I started with the company and we were selling our first TrueMethyl oxidative bisulfite sequencing (oxBS-Seq) technologies to the research market, we wanted to target the labs that were at the cutting edge, who really understood this field and could then start to answer some questions about why epigenetics is so important. What we quickly found out was that there are many reasons why those insights have not come to bear.
One of the reasons was the fact that the sequencing tools weren't up to scratch. Early tools could get you part of the way to an answer and help you gain some insight, but these fell short of the full picture. It's one thing to know that there are modifications occurring to the genome that don't change the underlying sequence but if you don't know how many there are, how to measure them accurately, and what they're doing, then it's not likely to translate into anything real.
There are also more practical things to consider such as the expense of doing these experiments. For example, the first sequence of the whole human genome cost billions of dollars and when I started, it cost tens of thousands of dollars, today that’s improved to about $1,000 and the use of this technology is widespread. By reducing the cost of doing these experiments, the number of people who are able to afford the technology is going to increase, and consequently our knowledge and understanding too.
Another key factor which I’d say is still a significant hindrance for the field today, is informatics. Having the technology, making it affordable, and making it compatible with any kind of clinical sample type is a great start, but if you can't analyze and interpret the data, that's a major roadblock. Having the right informatics tools to not only interpret the epigenetic information but integrate it with other omics data is essential.
Even if all of those things have to come together it is still vital to ensure that people understand the importance of epigenetics to our health. Because if there's no understanding, you don't get the research dollars, you don't get the air play and you don't get the general interest of the public, all of which has a significant impact on driving the science towards clinical utility.
So, rather than it being just one barrier to translating new science into clinical applications, I’d say it's a combination. Sometimes you get a perfect storm, and there's a tipping point. You say, "Okay, now we're at the point where we've got the right technology, sequencing is affordable enough and we have the informatics in place to interpret the data. People are starting to recognize the influence this has on our biology and there's a buzz around epigenetics. Researchers have demonstrated some key case studies where epigenetics provides valuable insight. Okay. Now we're ready to go." And we're reaching that point now.
Even when the science and the technology are in place, do you think there is also a barrier for getting researchers and ultimately the clinic to adopt new approaches?
Naturally for any technology, any new field, there's always that barrier, and the same thing happens when it comes to adopting it in the clinic. Of course, you're going to have the early adopters. You have those groups who are really excited to be on the cutting edge all the time, and then those who are waiting for the wealth of evidence to catch up. The same thing is happening in epigenetics.
You have a handful of companies who are focused on clinical epigenetics and a small number of epigenetic-based tests on the market today. A small cry compared to what you see with genetic testing but then it's taken years for genetics to become mainstream, and epigenetics is going to have to endure a similar path. We're trying to do everything we can to accelerate that, but there will always be those groups who are waiting for the evidence to come through i.e. the clinical trial evidence, the longitudinal data, before they'll adopt. All you can hope to do is make sure you get those key early adopters on board to help you prove your case. Neither us nor any other company should expect that people should just take your word for it. You have to demonstrate the value, always.
How are you getting those key early adopters on board?
Well, we impressed them with the science basically. Once you see the data that we've produced, that our collaborators and partners have produced, and in fact the data coming from other groups looking at other aspects of epigenetics, it is easy to become convinced. We're focused on DNA modification, but other researchers are looking at histone modifications, and RNA, etc. When you bring all that to the table and sit down and say, "This is in a practical sense what epigenetics is doing, how it's physiologically relevant, and for the problems that you're saying that you want to address in the clinic, here's how we believe we can actually help you." That's how you get them on board.
Carefully identifying and knowing the profile of an individual who's going to be that early adopter and a key opinion leader is crucial because once you get some great work done with them, they will then be a positive reference for you for the rest of the field and can help get everybody else on board.
That's much more of a considered and strategic approach than the scatter gun of all comers. Whoever wants to have access, you can have access, and hopefully something will sprout. That kind of crowdsource innovation can work in certain fields but I've found from my personal experience, that it's best to be very targeted and focused. Who are the decision makers and the real mavericks out there who understand and can appreciate the power that we have, who are going to help us demonstrate it to others, and spend more time focused on the quality of your collaboration rather than the quantity of people you're reaching in the beginning.
So, your strategy is to collaborate with a small group of leaders and work on projects with them?
Exactly. So, let's say we're in the cancer space. We're looking at a variety of different cancer applications. and we find the leaders in those particular cancers. We proposed a pilot study with those researchers to generate some data to demonstrate our capabilities, but also the utility. Once you have that pilot data, you can roll that out in posters and presentations at conferences, and depending on the depth of the data, you might be able to get a publication out of it. Now you have somebody who's independently commercially validated what you do, utilized your tools for a discovery, and ideally, found something that's fundamentally new and novel. It's not just the me too. What we do isn't me too. It's bringing new insights that are valuable, but were never made possible before. So that's the other key. You have to design your pilot in such a way that it's robust, and it will hold up to scrutiny because people will question the benefit of your technology over others. You have to be able to present a very clear case of where insights were provided that were previously impossible to generate. That's really the win. By collaborating with a small group of leaders on pilot experiments we can then use those discoveries and endorsements to help bring others into the fold.
Are these 1:1 collaborations, or do they take place in a group of early adopters or collaborators?
It really just depends on the scenario. There are some early adopters that are so early or so independently minded they'd prefer a one-on-one collaboration. In other cases, there is a group of physicians and scientists working together on a particular problem.
Do you work with other technology providers?
Yes, we innovate internally and develop our own technologies, but we do have collaborations with others who have technologies that are complementary to what we have and synergize. For example, one of our first technologies, oxBS-Seq was the first method to allow you to accurately sequence different epigenetic marks with single-base resolution. In particular, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). Those are the markers that we're interested in as they're very prevalent and important for regulatory pathways. Traditional bisulfite chemistry would not allow you to distinguish between those markers, and our chemistry allows you to do so bringing new insights to the field.
We have partnered with a company in California called NuGEN Technologies, who have bundled our oxBS-Seq kits with their next generation sequencing library preparation kits and sell those directly to academic research labs. Not only does NuGEN have the reach globally, and the reputation to be able to help us distribute our chemistry more widely, but our technology synergized really well with their workflows, offering a more comprehensive solution for researchers.
We also have other cases where we're partnering with R&D groups, to combine our technologies with automated workflows, etc.
In those partnerships and collaborations what is the biggest challenge?
I would say the biggest challenge is time. The timescales that we work to in industry are not necessarily the same timescales we worked to in academia. Having previously worked in the tech transfer field, I know firsthand that the expectations for what we as a company are trying to achieve and the deadlines set to achieve it, don't always match what's happening when you give your technology to an academic group. A data set that we would ideally have in three months might take up to a year depending on who you're working with. However, what you get in return is you get the expertise, you get the considered thought, you get access to what those key opinion leaders are predicting will have influence in the future, and that makes it infinitely worth it. So you just have to balance. If we brought it all in house and did the work here, well we may get it done faster, but it would take up our resource, and we wouldn't have access to that expertise. The trade-off will be maybe the results won't come out as quickly as you would have hoped, but you have all the insights that come with it.
When does the term open innovation mean to you?
When I think of open innovation, I think of it as reducing the barriers to innovation to make it more collaborative, and therefore ideally more productive. In my past lives, and even in my current roles here at Cambridge Epigenetix, I've seen open innovation can work, but there's some downsides to it as well.
What are some of those downsides?
Well, I think some of the downsides can appear when you put the commercial focus on it. It's all well and good up front if everybody's being open and collaborative but when you want to translate some of those initial insights into a commercial opportunity, or take it through the rigor that you would need for an FDA approval, you need to make sure that you have a partner(s) who is prepared to help you do that. Making sure that everybody agrees upfront if anything does arise from your work together makes for a much better open innovation environment. You don't want to leave it to the end after the innovations have developed, and then sort out the details after. It's much better to discuss beforehand, how you're going to go about translating it for the good.
Working through the downsides to unlock the potential of open innovation and collaboration
As Jason points out the different perspectives and goals of external partners make open innovation challenging. Yet there are ways to overcome those challenges and realize the high level of productivity that results from effective open innovation.
If you would like to reach out to Jason the best way to contact him is firstname.lastname@example.org
If you are looking to get your research or innovation across the translation gap, get in touch. I would be happy to jump on a call with you and share some best practices specific to your situation.