[Summary] Join the disruptors of health science (Insel 2018)

TLDR; We need deep partnerships between tech companies, clinicians, and researchers to bring product and data science expertise to the healthcare system's experience in treatment and science.

https://www.nature.com/news/join-the-disruptors-of-health-science-1.22918

TLDR; There are significant opportunities to improve healthcare with access to new technology and data, but we need deep partnerships between tech companies, clinicians, and researchers to act on them. Along with billions of dollars in cash, tech companies bring product and data science expertise to the traditional health care system focused on treatment and fundamental science.

“These companies have transformed the worlds of information, entertainment and commerce. But by moving into health care, they face some formidable challenges. In my view, solving them will require deep partnerships between technology companies, clinical experts, patient advocates and academic scientists.”

A financial frontier

Public funding for science has decreased while private-sector (specifically tech companies) funding for biomedical research has increased; and tech companies have billions of dollars of cash to spend.

• “In the United States, public funding for science has not kept up with inflation over the past decade. The proposed 2018 budget from the White House recommends funding cuts for the NIH and the National Science Foundation of more than 10% each. Appropriations may ultimately be more generous, but no one is expecting Congress to repair a decade's loss of purchasing power.”

• “Meanwhile, private-sector investment has become a bigger piece of the research-funding pie — increasing from 46% in 1994 to 58% in 2012 for biomedical research1. Tech companies, in particular, have been ploughing more funds into research, and moving into areas such as health and life sciences that have typically been the domain of the NIH, pharmaceutical and biotechnology companies. By any measure, tech companies have enormous sums to spend. The collective cash reserves of Apple, Microsoft, Alphabet and Facebook — roughly $500 billion — exceed by tenfold the annual federal investment in biomedical research.”

Tech companies are making big moves into health care: IBM has moved into cancer-care, Fitbit is heavily involved in FDA research, Apple launched ResearchKit to make it easier to do research with their devices, Google launched Verily, and Facebook announced Building 8.

• “In health research, the landscape is still evolving. Three years ago, IBM began selling a software suite called Watson for Oncology to cancer-treatment centres around the world. The program is built around what IBM call cognitive computing and is designed to help clinicians to select the best treatment. The company claimed that by using its cloud-based data on cancer, Watson could recommend interventions for individual patients, although some say the effort was premature and oversold3.”

• “Over the past 12 months, Fitbit, the developer of several fitness trackers, has expanded into a health-care and health-research company. With more than 50 million registered users, it is involved in 400 research projects, including studies of diabetes and heart disease. In fact, Fitbit has just been listed as one of nine digital health companies to be considered by the US Food and Drug Administration (FDA) in its precertification pilot programme — a new, supposedly more agile, approach to regulation that will focus on the software developer rather than on individual products.”

• “Since March 2015, Apple's ResearchKit has made it easier for developers to create health apps for the iPhone or Apple Watch. It has also provided a platform for enrolling thousands of participants remotely in clinical projects, for instance in diabetes, cancer and diseases of the central nervous system. A study at Johns Hopkins University in Baltimore, Maryland, for instance, has used ResearchKit to capture data just before and throughout seizures in nearly 1,000 people with epilepsy”

• “Also in 2015, Alphabet launched Verily — a company focused on creating software and hardware to transform health care. After growing to more than 500 employees in just over 2 years, Verily seeks to address diabetes, heart disease, cancer and diseases of the central nervous system using miniaturized sensors in smart devices — such as a contact lens that estimates blood sugar levels.”

• “Just six months ago, Facebook revealed the existence of Building 8, a division focused on delivering consumer “hardware products that are social first”, including brain–computer interfaces designed to aid people with disabilities.”

Venture investment in health tech has also accelerated.

• “Meanwhile, health tech has become one of the hottest areas for venture investment in the United States: more than 1,000 new digital-health companies have started up since 2012. A report from Rock Health, a US venture-capital fund headquartered in San Francisco that invests in digital-health start-ups, estimates5 that $15 billion has poured in to the sector over the past 5 years, up from $1.5 billion in 2012 and $1.1 billion in 2011”

The biggest difference between tech and traditional health companies is the attitude to iterate and execute quickly. 

• “But what struck me most on moving from the Beltway to the Bay Area was that, unlike pharma and biotech, tech companies enter biomedical and health research with a pedigree of software research and development, and a confident, even cocky, spirit of disruption and innovation. They have grown by learning how to move quickly from concept to execution. Software development may generate a minimally viable product within weeks. That product can be refined through 'dogfooding' (testing it on a few hundred employees, families or friends) in a month, then released to thousands of users for rapid iterative improvement.”

• “During my first month working at Verily, I returned to Bethesda for the winter holidays; when I went back to work in early January, I found that a group of engineers had developed an entirely new product between Christmas and New Year's Day. Contrast that with the NIH-funded world of research, where it usually takes at least 18 months to go from proposing an idea to getting a project funded, or the years it can take to transform the discovery of a molecule into a marketable drug.”

• “This intense focus on the rapid development of consumer products is very different from the pursuit of fundamental knowledge that has been a hallmark of academic research. And as a newcomer (what Google calls a noogler), I found the language of product development and the drive towards 'quarterly OKRs' (objectives and key results) a bit off-putting. But the truly disruptive impact of tech companies is not the rapid-fire push for consumer products or their deep pockets; it's their focus on AI and data resources.”

Mining data

Tech companies are transforming data science and they are already showing promising results in detecting diseases

• “A by-product of this is that tech companies are transforming data science — much as pharma and biotech transformed medicinal chemistry and molecular biology in the last decades of the twentieth century. In an era when biology is increasingly an information science, the tools being created by tech companies can provide insights that will almost certainly be translated into advances for health.”

• “First, in 2016 a team at Google used a version of machine learning called convolutional neural nets to create an algorithm to detect diabetic retinopathy6. The researchers started by having 54 ophthalmologists rate 128,175 retinal images.”

• “Third, a team at Microsoft has used anonymous Bing search histories from 9.2 million users to predict cases of pancreatic cancer several months before people are usually diagnosed with the disease7. The team identified characteristic patterns of historical symptom searches in more than 3,000 anonymous users who subsequently indicated a probable diagnosis of pancreatic cancer — indicated by searches such as 'just diagnosed with pancreatic cancer'. “

Sticking points

Even though tech companies have scale and speed, they do not have the expertise or deep understanding necessary for developing better solutions.

• “In short, tech companies have scale and speed: an experiment can involve millions of people and be completed in months. But scale and speed aren't everything.”

• “They usually do not have the regulatory expertise needed to develop medical products, they rarely have access to clinical samples and they often lack a deep understanding of the clinical problem to be solved.”

However, they have taken steps by hiring clinical and healthcare experts. 

• “Various moves are being made to try to address these issues. In May, Verily hired Robert Califf, former chief of the FDA, to help with its personalized-medicine effort called Project Baseline. In 2015, 23andMe, a personal-genomics company based in Mountain View, California, recruited Richard Scheller, former head of research at the biotech company Genentech in San Francisco, to lead its research programme. And in 2016, Apple brought Stephen Friend, an open-science advocate from the non-profit research organization Sage Bionetworks in Seattle, Washington, to assist with its health projects”

• “How a culture built around engineers and designers will incorporate people from different sectors remains to be seen, and whether companies that build consumer products will be able to work with health-care payers and providers is unclear. But the willingness of tech companies to hire national experts on health, regulation and health data to aid in discoveries that will have clinical utility is a hopeful sign.”

4 major areas of uncertainty: (1) will tech companies contribute to open science and the public domain (2) will business models sustain rigorous science (3) trust and privacy (4) will companies prioritize research over profits in the long term.

• “Open science increasingly drives innovation in the public sector. It is unclear to what degree the drive for intellectual property and profits will limit the transparency of research in the tech sector8. The stereotype is that for-profit companies will focus only on commercial end points. But there are notable counter-examples from AI research, in addition to the biomedical examples above. In 2015, Google made its machine-learning software library, TensorFlow, open source, and AI researchers across the board quickly adopted this powerful tool. Likewise, the Apple Machine Learning Journal launched in July to provide more transparency about the company's current projects (see go.nature.com/2yckpi9)”

• “Another uncertainty is whether the business model in tech, which is often based on advertising revenue or the sales of devices, will limit the rigour, generalizability and validity of the science carried out. Especially in start-ups that are dependent on rapid returns for their investors, the financial runway may be too short for lengthy or large clinical trials.”

• “And then there's the issue of trust. It has become the norm for tech companies to use personal shopping or geolocation data for commerce. It's unclear whether the public will be as accepting about the use of personal health data, especially by behemoths such as Google or Facebook.”

• “The recent commitments of big and small tech companies to discovery and clinical research are exciting. But during an economic downturn, these projects could be the first to be axed to protect the company's bottom line”

Partners in time

Over time each sector will do what it does best: tech will drive research that is intense in data and product, while traditional health will drive research on fundamental science.

• “The practical questions are these. What will each of the sectors in the evolving ecosystem do best? What can be done across sectors? How can bridges be built between companies with unprecedented access to data and massive computational resources, and academic scientists who may have a deep understanding of a clinical problem or access to unique clinical populations?”

• “It seems likely that the academic sector will continue to lead on those aspects of fundamental biology and clinical research that do not require big data or machine learning — the purification of an enzyme, perhaps, or the development of a mouse model for a rare disease. Pharma and biotech will continue to be the source of new medicines. The domain of the tech industry will be research that is data-intensive, and product development that requires a legion of software engineers working with designers.”

To transform the industry, we’ll need deep partnerships across tech and pharma-bio companies, and academia.

• “Transformative medical products that require clinical testing, regulatory standards and insights about the health-care marketplace, including the practical constraints faced by providers in the clinic, will almost certainly require partnerships between public research entities and private companies. These must include precompetitive partnerships across tech, pharma–biotech, academia and patient-advocacy groups. Developing these partnerships will not be easy, given the different stakeholders, cultures and incentives.”