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open science platform

7 questions with Frankl Open Science founder

Frankl founder, Dr Jon Brock with neuropsychologist and dementia researcher, Professor Greg Savage.

Vast amounts of scientific data are collected every day, but a lack  of data sharing among researchers is resulting in a major research replication crisis. Luckily, startup Frankl Open Science,  the world’s first blockchain-integrated open science platform, has stepped up to address this major opportunity cost.

The platform integrates data sharing into the scientific workflow, allowing for automated, trackable data sharing. Frankl Open Science is the brain-child of cognitive scientist Dr Jon Brock and blockchain guru Peter Godbolt, who set out to create it easier and more rewarding for time-poor scientists to share data. We sat down with Jon to find out about the genesis of Frankl, the startup’s biggest successes and challenges and how open science will benefit the global research community.

1. What’s your career background?

I’ve spent most of my career in academia. I did a PhD in Psychology studying a rare genetic condition called Williams syndrome. I’ve also done research on Down syndrome, dyslexia, and autism.
I worked as a post-doc at Bristol and Oxford Universities in the UK and then spent 10 years at Macquarie University in Sydney where I was an ARC Australian Research Fellow in the Department of Cognitive Science and a Chief Investigator at the ARC Centre of Excellence in Cognition and its Disorders.

2. How did you first identify the business gap that led you to create Frankl?

Frankl is really the intersection of two ideas that arose from my experience as a researcher.
Back in the early 2000s, I was working on a couple of projects with kids with Down syndrome and then kids with autism. I noticed that when I gave them tests that involved using a touchscreen, they seemed to perform much better than they did on more traditional pen and paper tests we were using. It was as if the touchscreen was getting at their true abilities. And so when iPads came out and parents started saying that they were “unlocking” their kids’ abilities, it seemed obvious to me that iPad-based cognitive assessments were the way forward – not just for autistic kids but for everyone.
At the same time, I’ve been getting increasingly involved in the world of open science. Open science is really just the idea that science works best when it’s done transparently. But there are a number of barriers to open science – one of which is that it takes time and effort to do well and there’s actually very little incentive for researchers. For example, the time you spend curating your data, making sure that other people can find it, make sense of it, and actually use it, that’s time that you’re not doing other things like writing papers and grant proposals. A couple of years ago I was talking to a friend, Alex Holcombe, who’s a professor at the University of Sydney. He told me how he programmed his experiments so that all the data curation was effectively built into the data collection. Most people don’t have Alex’s technical skills. So our idea was to build all of these data curation capabilities into the apps we’re making so that anyone can be an open scientist and can share their data in a way that’s meaningful and useful.
It’s good for researchers, but it’s also good for the organizations who are funding research, whether that be government, philanthropy, or business. Ultimately, they want the best return on their investment in science. And giving scientists the tools they need to collaborate and share their data more openly is one of the best ways of achieving that return.

3. What have been the biggest challenges in your first year?

For me personally, the biggest challenge has been getting my head around the technology side of things as well as the business and legal aspects. Frankl co-founder, Peter Godbolt, has been working in tech for a long time – in web and app development and then more recently in blockchain and cryptocurrencies. There are huge opportunities in bringing together the worlds of science and tech, but it’s been really important to make sure we’re not talking past each other or proposing solutions that make sense in one world but not in the other.
This is all made even more challenging by the rapid changes in the tech space over the last year. There’s a lot of uncertainty. For example, we’re using blockchain as part of our solution, creating a supply chain from raw data to scientific paper. When we started Frankl in January, there was a huge amount of excitement about blockchain and cryptocurrencies. Since then, that the bubble has burst. In the long run, that’s a good thing. It means that the projects that survive are going to be the ones who provide a genuine use case for the technology and who actually build products that people want.

4. What’s been the best part and your biggest successes?

The most exciting part for me has been really getting to know some of the tech and then thinking about how that can be applied to solve problems in science. One of the things we’ve been saying all along is that a lot of the solutions already exist. We don’t need to reinvent the wheel. I really believe that.
Probably our biggest success so far was getting an Open Research Fund grant from the Wellcome Trust. The grant was for a simple memory test designed by our collaborator, neuropsychologist Professor Greg Savage, for use with patients with Alzheimer’s and other forms of dementia. But it incorporates lots of features that make it easy for people to store their data securely and share with the right people, both in a research context and as a clinical tool. There were 96 applications and I think just 8 awards, so it was really fierce competition. It’s allowing us to move quickly now on building the software. But it’s also really validating for us to have an organisation like Wellcome say that they believe in what we’re doing.

5. What is your advice for people working in research and looking to move into a startup?

If you’ve got a good idea then it’s definitely worth thinking about a startup. Academics are often quite dismissive of commercialisation – we think of science as this noble pursuit of knowledge and the idea of making money is somehow dirty or a distraction. But sometimes, turning an idea into a business is actually the best way to move things forward and translate an idea or finding into something that actually makes a difference to people’s lives. It might also be more sustainable in the long run. The problem with relying on research grants is that eventually they run out and all your hard work can go to waste if there’s no continuing support. So having a sustainable business model can be a good way of ensuring that you have the most immediate but also the longest lasting impact.

6. How can open science benefit the science research community as a whole?

One way that open science benefits the research community is by giving greater trust in research findings. Science works because you don’t have to trust scientists – you trust the evidence, the data – and because you know how the data were collected and analysed. So the more open it is, the less you have to take on trust. There’s a lot of concern at present about the trustworthiness of scientific findings. When people try and replicate other people’s studies, they often get quite different results. Conducting research more openly is one way of addressing those concerns.
But there’s more to open science than that. Isaac Newton famously talked about “standing on the shoulders of giants”. Science isn’t something that can be done in isolation. We gain new knowledge more quickly if we can build on other people’s work – their ideas, their methods, their data. So open science means more rapid discoveries as well as more reliable findings. For example, we’re increasingly seeing major discoveries being made by people who haven’t actually collected the data themselves but have re-analysed existing data that other researchers have shared openly.
That’s why the organisations that fund research, particularly the big philanthropic organisations like the Gates Foundation and the Wellcome Trust are really pushing researchers to behave more openly. Open science means that they get the biggest knowledge return on their investment in scientists.

7. What does the next 2 years look like for Frankl?

Our priority right now is to push forward with the development of our prototype application. Once people have something concrete – an app they can download and they can run and see where all the data is going – it becomes easier to imagine how the same concept and the same principles can be applied to other scientific contexts.
It also means that we can easily repurpose the code from that first app to build other apps that test slightly different things. That’s where my academic connections are really useful. We’ve got a queue of researchers with apps that they want building. And so in parallel to the app development, we’re busily building relationships with research organisations whose goals align with our own and who see value in Frankl for their researchers. There are lots of opportunities here for cooperative research partnerships, linkage grants and so on.
We’re also increasingly thinking about the direct clinical applications of what we’re doing. The solutions we’re creating for researchers – user-friendly assessment apps, secure data management and permissioned data sharing – are also directly applicable to clinical contexts. For example, parents of kids with disabilities tell us that one of the real challenges they face is getting bounced from one specialist to another, with very little communication between them. Having an app that facilitates sharing of assessment results between clinicians and parents could be incredibly powerful – and empowering.
In the longer term, we’re thinking about the bigger picture in science. It makes sense for us to focus initially on psychology and cognitive science because that’s where we have expertise and we know there’s a big market for cognitive tests. But the general principles of making open science part of a frictionless scientific workflow is something that translates to lots of different areas of research. So we’re always very happy to speak to people in any area of science, tech, or business who can see broader applications for what we’re doing.
Learn more about Frankl Open Science  on their website, Twitter, Facebook and  Bitcoin Talk Forum.
university-industry collaboration

Blueprints to a collaboration boom

Featured image above: Robin Knight (right) and Patrick Speedie (left) are cofounders of university-industry collaboration platform IN-PART. Credit: IN-PART

Robin, you’re four years into the IN-PART journey, and you’re already connecting 70% of your university opportunities with potential partners. Can you take us back to the start, and tell us how you first came to be interested in university-industry collaboration?

Prior to setting up IN-PART I was in academic research at King’s College London. I was always interested in collaborating with industry partners, especially when working in an area with potentially translatable outputs.

While undertaking my PhD I started working on an academic-to-academic platform with a couple of colleagues, and during that time I had a conversation with my now co-founder and long-time friend, Patrick Speedie, who was working in IP management and publishing. Our shared experiences and discovery of the need to better connect the two worlds of academia and industry motivated us to form university-industry collaboration platform IN-PART.

Tell us a bit more about IN-PART and how it gained traction?

At its core, IN-PART a tool to help Tech Transfer teams (and by extension researchers) find external partners interested in their research. The translation of academic research into impactful outputs is key to the advancement of society, and we wanted to be a key part in increasing those outputs.

So we began by building a network of individuals in industry who were both capable and motivated to interact with universities about research. Then we had to figure out the best and most efficient way to showcase opportunities to them.

After piloting a minimum viable version of IN-PART with six UK universities in 2013, we managed to find 25% of provided opportunities with potential industry partners in just two months. Three years and two investment rounds later, we now provide over 70% of each university’s content with potential partners.

IN-PART is all about university-industry collaboration. Why did you choose to focus on universities in particular?

We use the broader term of universities to represent publicly-funded research. Amongst these we will also include research institutions, and notably we recently welcomed Public Health England to IN-PART. They are a very interesting case as the outputs from a government lab differ from those of a traditional research institute, owing to the more hazardous bio-projects they undertake and different potential technologies that result.

Our industry audience are often seeking to access the academic behind available IP, especially if considering a license. It’s rare that a company would be able to take a technology and have it fit directly into their research pipeline – expertise is required for guiding that fit and this makes universities and research institutions such an attractive resource.

An important element of what we do is making sure all the content we have is ‘available’. This means we do not ‘scrape’ websites for technology nor trawl the internet, which turns up expired patents and technology where the academic is no longer associated. Instead we keep in close communication with university teams to make sure everything we have is relevant and up to date.

We do not work with company or industry generated IP seeking licensees. We also never want to be in the industry of trading IP for the sake of litigation, which from my personal point of view seems to counter our progression as a species.

I’ve noticed that at IN-PART, you restrict your platform to particular industry professionals. Have you found this to be important to the success of your collaboration model?

Yes, very important. When we first piloted IN-PART in the UK under a beta-test with six universities, it was clear that we wanted to only provide introductions to end-users in industry. By restricting our audience in this manner it meant that every contact we passed along was meaningful and high-value. What we didn’t want to do was pass on opportunities to work with consultants. That being said, consultants provide a valuable component within the ecosystem and we’re currently exploring how they can be included within our community.

To hear more from Dr Robin Knight about the key drivers behind successful commercialisation and collaboration, click here.

profile_inpartrobin

Dr Robin Knight is Co-founder and Director of UK-based university-industry collaboration platform IN-PART.

Click here to find out more about opportunities with IN-PART. To find more industry-ready technology from Australian universities, visit Source IP.