The problem with Silicon Valley medicine

The biotechnology sector is based on the premise that we can “hack” our biology, but that risks oversimplifying disease and medicalising normal physiology, writes Rohin Francis

Modern medicine has been shaped by technology, but there’s no guarantee that the newest iteration of a medical therapy or device will be an improvement. We are frequently susceptible to novelty bias, the belief that something new is superior to what preceded it. Yet unlike the rapid evolution of our computers and smartphones, the history of medicine is littered with exciting new technologies that turned out to be less effective than first hoped.

The immensely lucrative biotech sector is where two contrasting mentalities interact. Tech innovators claim that medicine is a slow moving, Luddite industry in desperate need of disruption, whereas many working in healthcare suggest that Silicon Valley’s unofficial motto of “move fast and break things” is entirely the wrong model when people’s lives are at stake.

Tech giants like Google and Amazon owe their primacy to their mastery of data, and the same faith in data—as a means to unlock untold secrets about health—buoys the enormous amount of money invested in biotech. The era of the “quantified self” was ushered in only about a decade ago,1 and now many of us regularly record our heart rates, oxygen saturations, steps, heart rate variability, macronutrients, and even details of our microbiomes. The volume of data we’re collecting grows ever larger, but knowing what to do with it remains an unrealised challenge.

Several key beliefs underpin the Silicon Valley approach to medicine. The human body is regarded as nothing more than a complex machine, with DNA as its source code, akin to a computer code. As with any algorithm, it is believed that with sufficient processing power, we can “hack” our biology and finally achieve the long awaited goal of true precision medicine. Waiting for evidence gained from clinical trials is often deemed too slow a process for venture capitalists hoping to see a return on their investments, so therapies are endorsed and sold based on theoretical or mechanistic evidence. These “breakthroughs” are enthusiastically promoted at events more similar to the launch of a new Apple product than a medical innovation.

Many biotech companies are guided by these principles, but none has been as high profile as the failed blood testing startup Theranos, once valued at more than $9bn.2 Theranos was also an instructive example of other problems with Silicon Valley medicine. Biotech “unicorns,” startups with a meteoric rise to prominence, attract enthusiastic investment thanks to their impressive claims about what they offer. Yet much of their output is so called “stealth research” that isn’t published in academic journals, and thus is not open to scrutiny from the wider scientific community. An overly optimistic faith in technology, sometimes called automation bias, coupled with the cult of personality that often surrounds founders of tech companies, caused people to invest in Theranos and its blood testing machine without seeing any hard evidence that it worked.2

Theranos’s subsequent collapse has been widely publicised, but enthusiasm for the biotech sector doesn’t seem to have diminished. In recent years, a proliferation of health devices, therapies, and services has been marketed directly to the public as wellness products that offer a path to improved health. Wearable technologies such as fitness or sleep trackers, DNA testing kits, personalised supplement programmes, and full body screening scans are popular with people interested in learning more about their bodies and cultivating their wellbeing. All invoke scientific sounding language that promises to offer important insights into your health. In reality, the benefits are often exaggerated and the risks downplayed or concealed. The idea that by gathering more information about a person, we can more specifically tailor health advice to them is alluring, but it can oversimplify the many factors involved in the development of disease.

Even technologies that were designed to be used for a specific clinical condition have been co-opted in our embrace of digital health and appetite to optimise every bodily function. For example, continuous glucose monitors have dramatically transformed diabetes care,3 but have also been adopted by health enthusiasts who don’t have diabetes and use them to inform their dietary choices. This runs the risk of users reaching conclusions that run contrary to evidence based advice, such as forgoing fruit to avoid a transient elevation in blood glucose.4 Without adequate understanding of how to interpret biological data, people can start seeking to optimise unhelpful metrics, while missing the huge benefits offered by following conventional health advice.

Technology has incredible potential to improve medicine, but it achieves most when developed for a specific health need or condition. The rise of consumer directed biotech products that are designed to appeal to as many healthy people as possible opens new avenues for overdiagnosis and overtreatment, and risks neglecting those with the greatest need. In forthcoming years, this could result in the increasing medicalisation of normal life. Yet as long as targeting the healthy is more profitable than helping those with existing illnesses, we can expect this trend to continue.