At the first annual summit of the Cambridge Rare Disease Network we saw examples of collective intelligence making real impact; new technologies, platforms, and networks supporting decisions, analysis, and discovery; speeding progress on the route towards new treatments and cures.
On Monday 14th September I attended the first annual summit of the Cambridge Rare Disease Network, to see examples of collective intelligence ‘in the wild’, where new technologies, new platforms, and networks are being innovatively deployed to speed progress on the route towards new treatments and cures.
Developing and using our collective intelligence - using digital and social technologies to support and enhance the work of thinking beyond the capabilities of any individual person- will be vital as we take on the key challenges of coming years; our climate, managing our resources, health, ageing population.
Many of the most famous examples of collective intelligence - Wikipedia, much open source software including the Linux operating system - require that participants have the skills, resources and confidence to redesign the tools they are using and building at the same time as they use and build those tools. Participants in these networked publics self-select for these skills and interests, and for confidence in their abilities and in the importance of their contributions.
The achievements of these communities are profound and world-changing. But collective intelligence has the potential to solve problems and support the work of communities beyond this sphere.
Seeking examples of the use of collective intelligence ‘in the wild’, tackling offline problems, we have been exploring the use of collective intelligence in patient organisations. People facing health problems can face complex, urgent challenges which require them to acquire and navigate many kinds of information from test results to appointment schedules, negotiate with institutions and individuals, all while managing the effects of ill health, and while often, still, being denied access to their own records, and struggling to have their wishes and skills recognised.
“They didn’t tell me what I had. I didn’t ask for details, as they were obviously bad”
- Stephen Hawking
These challenges are particularly stark in the arena of rare disease, where a correct diagnosis may take years to find. There is then often no roadmap for the condition’s progression, no available treatments or cure. People with rare diseases, their parents and carers, are hugely motivated to draw on new social and digital technologies to speed progress towards treatments and cures. There may be no other route to lifesaving answers.
At the Cambridge event, three keynotes and thirty-five panelists speaking on six panels contributed to a whirlwind of ideas, an atmosphere of highly informed, if somewhat overwhelmed, hope.
“In the event of the inactionable you can do science”
- Matt Might, father of a child with a rare disease
Matt Might, the father of a child born with a disorder so rare it had no name before him, spoke first, describing the series of networks involved in the ongoing work of supporting his son. A huge network of specialists and technologies were involved in the hunt for his son’s diagnosis, culminating int he description of a new disorder. He then used a viral social media campaign to find other patients, and with his wife founded a patient organisation, NGLY1, and drove a collaboration between their organisation and a collective intelligence platform developed by Stanford data scientists. The Mark2Cure tool allows lay people to contribute to biomedical discovery by having them identify concepts and concept relationships within biomedical texts, then uses statistical algorithms to identify potential relationships, and speed scientists’ hunt for patterns and speed discovery.
There were many other initiatives supporting the effective pooling of intelligence across disciplines and borders. We heard about the Orphanet platform, which co-ordinates nomenclature and directories of expertise and resources across the EU, the EURORDIS platform, which facilitates communication between patients and patient organisations across language barriers, the Cure Accelerator platform which encourages and structures discussion of opportunities to repurpose drugs, the ASTERIX project, in which statisticians are working with biomedical researchers, regulators and patients to design better clinical trials for small populations, and many more. There were also calls from parents for further tools: platforms which could co-ordinate information and discussion of individual children's progress across the huge number of specialist doctors, researchers, therapists, carers, teachers and support staff as they met milestones and moved through the education system.
“I’ve been in rare diseases for 25 years, and I still see people speaking different languages - doctors, researchers, patients; how are they going to learn a new way of thinking for real collaboration?”
- Question to Panel
Panels also addressed social technologies involved in developing collective intelligence- issues of power relationships, respect and trust, the different needs and incentives of participants, including the market incentives driving pharmaceutical companies, the incentives of NHS institutions and the individuals within them. These covered alternative funding strategies, engaging with pharmaceutical companies, the potential of the Cambridge cluster to assist unmet therapeutic need.
In Nesta’s collective intelligence team we are committed to engaging with these brutally complex challenges, where participants are ambitious and innovative as they share information, ideas and resources because they cannot be solved by individuals, or by individual companies, institutions, scientific disciplines.
A final keynote by Stephen Hawking reminded us all what was at stake. Not just the lives of those affected by rare disease, but the contributions that those affected by rare diseases can make to the global community, if only their energy and intelligence is unlocked.
image: Human embryonic stem cells only A, Vojtěch Dostál, CC BY 2.5, via wikimedia commons