The conventional wisdom goes that health care is notoriously slow to adopt new technologies. The explosion in the past few years of sensor and app-filled health startups is starting to prove that wrong (emphasis on “starting”). But what about the large-scale stuff that will really make a difference in patients’ lives? Genomic medicine has long been promised to the masses. And what about precision medicine, which integrates genetics, blood tests, medication and therapy response, and lab discoveries to make better treatment decisions?
For two days in May, the most important executives in the country got together with health care leaders at a UC San Francisco gymnasium to come up with the solution to a thorny problem: How can we revolutionize medicine? Mark Zuckerberg stopped by to contribute. Francis Collins, director of the National Institutes of Health, contributed his thoughts. So did GE Healthymagination CEO Sue Siegel. And at the end of the day, everyone walked out with some clear-cut steps forward.
Genomic medicine is slowly starting to be used with cancer patients, but it has a long way to go. Precision medicine–a term invented in 2011–is even further from reality. In a recent report from the National Academy of Sciences (NAS), UCSF Chancellor Susan Desmond-Hellmann lamented the gap between scientific discoveries and what’s used in doctor offices. Making that leap requires all the brainpower from disparate industries that health care can muster.
And that’s why I find myself sitting in front of Salesforce founder and CEO Marc Benioff–who recently contributed $100 million for a new children’s hospital at UCSF–as he discusses the promise of precision medicine to a crowd of over 150 people at the OME Precision Medicine Summit. I was witnessing the tail end of the two day event, which matched participants into teams that worked together on precision medicine-related ideas for a final pitch session. At the end, participants were encouraged to volunteer their resources (money, brainpower, access) to move the ideas forward. Not everyone had the chance to pitch; in the end, 11 of the best ideas were selected for presentation. There were some clear highlights.
The first idea pitched to the audience was also the only consumer product. The basic idea: a smart toilet that analyzes stool samples, letting the user know if they have anything wrong with them–giardia, the nasty bacteria C. difficile, you name it, the smart toilet can find it. The creators estimated that they would need $1.5 million to create a smart toilet device that can analyze stool samples on a chip–but the technology is within reach.
An amazing 95% of drugs never reach patients. All the data from those failed drugs is essentially left unused; laws prohibit the FDA from making failed trial data public. This team proposed crafting an agreement with pharmaceutical companies to open up their data, ensuring that other researchers can learn from what doesn’t work to more quickly make useful drugs. Big Pharma would obviously be concerned about confidentiality, but the team maintained that eventually, opening up data would lower the economic burden of getting drugs to market. Whether this idea can gain any traction is questionable, but both the FDA commissioner (Margaret Hamburg) and high-ranking representatives from pharmaceutical companies were present at the UCSF event–so it’s possible.
The easiest way to further genomic research is to gather lots and lots of data. This team proposed creating a data donor drive to collect 1 million genetic data sets. The first volunteers would be health care practitioners and members of disease advocacy–after that, the hope is that the first donors encourage their family and friends to join in.
Nobody is quite sure what happens now. That will depend largely on what kinds of commitments participants made to furthering each of the projects (they submitted commitments on slips of paper at the end of the event). “We didn’t set any notion of next steps,” says Desmond-Hellmann. UCSF has already offered to get onboard with some of the projects, including one called the Global Biological Data Consortium that proposes a consortium to establish standards for analyzing biological data. We’ll know more in the coming months about whether any of the projects get off the ground.