Writing the operating manual for humans
Alphabet owner of Google also owns a company called Verily that plans to use in technology, software, machine learning and the skills of biologists, geneticists and psychologists and even philosophers to model what makes for a healthy human. In their own words, they plan to map humans the way they have mapped the world.
Once we have a better sense of what healthy is and how to monitor we can faster and more accurately determine when something is wrong.
The ultimate goal is to understand how and why we age and potentially overcome it.
The reason they are in the news at the moment is an overstated undertaking by US President Trump that they would be rolling out Covid-19 testing to all Americans. They had actually planned an online survey and a pilot screening test, which is up and running with the plan to expand it as the need and the ability improves.
This is one component of what they hope to do but there is quite a bit more.
Who wants to live forever? More tech companies are looking to not just extend life they want to defeat ageing. Join @brucebusiness and @colincullis just after 7pm for how it may impact on #COVID19SouthAfrica— 702 (@Radio702) March 18, 2020
If you remained healthy, how long would you want to live?
Here is how they are looking to do it.
The first part is signing up volunteers that are diverse and representative of the human population. At the moment they are only using US citizens but plan to run it globally.
The company is not even 10 years old and only started its first major project in 2017. Project Baseline is a four-year study of 10 000 people to determine how they are doing physically and psychologically. They will use sensors on their devices, by using wearables and taking regular surveys about their emotions and behaviour.
Once that is done they will try to determine who and when the volunteers were at their healthiest and happiest.
They are also doing other surveys in conjunction with established drug companies hoping to one day make trials easier to run and possibly even run on models using machine learning. A major delay at the moment is in testing potentially life-saving drugs and procedures that have to go through multiple and highly controlled trials before it may be released for public use.
The Seti@Home program which used idle computing time on over a million private computers would process the huge amount of data hoping to find broadcasts from other intelligent life in the universe. It now also allows for testing how to find useful drugs or understanding chemical processes in cells. The most recent release allows you to test for potential ways to beat the SARS-Cov-2 virus.
Another study tracked glucose levels in diabetes patients. In the past testing required blood to be repeatedly drawn and tested on a separate device. Their model used a small sensor inserted into the arm which continuously monitored glucose levels and transmitted them to the user’s phone for capture and further distribution.
For many in South Africa, it will resemble the methods Discovery Vitality uses with wearables to track activity and subsidised testing and surveys to create a health profile of their members. Using incentives they can not only keep members healthy but reduce the medical costs they would otherwise need to pay.
In the same way, Verily aims to nudge and gamify behaviour change to shift users from bad habits to good ones
Who owns the data
One aspect that has not had enough consideration is how to handle the huge volume of very personal data that will be generated. One argument is that volunteers and users will have full access to their data, but the concern is that it could lead to obsessive behaviour and cyberchondria which is using the internet to self diagnose and typically turn a potentially minor symptom into a perceived major illness.
Currently not much is shared with participants in medical trials unless there is a medical need for it, these trials might last longer or volunteers could actively be used for multiple trials at the same time. The company would generate revenue from the discoveries of using the data so it will require a more comprehensive answer. There was concern that volunteers could use their Google accounts to register which some feared may be used to expand on the advertising profiles to allow marketers to target them. Verily says their data will not be used for any advertising purposes.
Data breaches remain a concern but being part of Google suggests that they would have access to some of the most secure servers.
The scientific community relies on meta-studies and replication to confirm findings, how best to ensure that continues while keeping volunteer and patient data sufficiently private.
An issue with another Google company DeepMind which was granted access to British cancer patient records for a machine learning in order to improve early and accurate cancer detection. That was resolved and hopefully will reduce the chance of it happening again, but it is unlikely that all countries will learn from this mistake and so we can expect for it to happen again.
A further point on data is its quality, typically trials had a bias towards certain groups that may not share reactions to certain medications as other groups. Better recruiting would address this but so would very large data sets. Tech companies have favoured using big data in the past and so are likely to scoop up a huge amount of data. How they may be used by private companies is a concern but so is how some governments might use it.
Who pays and who gets paid
Another aspect is how to charge for the services. Clinical trials would be voluntary or come with a payment, but if the devices are packaged into a form of health service for early detection of medical conditions you may see people compelled to pay for the service in order to qualify for insurance or credit.
European countries have a strong state health system and so might see it being either paid for by taxpayers or have parts made freely available to citizens in return for being able to operate in restricted medical fields.
Emerging markets would certainly benefit, but large companies often have an outsized ability to create a scenario that is tipped in their favour.
What could go wrong?
There are far more benefits than pitfalls, but those affected by something that fails would understandably not see it that way.
In 2011, $10 million was offered for the creation of a device that could diagnose 13 medical conditions without being invasive, the Tricoder X Prize took its name from the amazing medical instrument used in Star Trek to diagnose and treat patients. It was lo larger than a mobile phone and Qualcomm thought humanity might just be able to pull it off. After 6 years part of it was awarded to a team that managed to come close. A testing kit the size of a home printer could do many of the tests and would be very welcome in middle-class homes and small doctor’s practices.
The flip side would be a company like Theranos, at one point valued for billions of dollars by being able to test blood using just a tiny amount of it. It did not work and now the owners are facing criminal charges for their actions.
The stakes are high and those that would like to see this succeed may choose to believe rather than be shown it to be successful.
How long till nirvana?
Despite our long medical history, for the most part, it could do as much harm as good, even now we are only just beginning to understand how we actually work. These are lofty ambitions and even the most optimistic of the companies know it will take years before the big breakthroughs will be possible.
Even so, the time has never been better for humans to focus on improving our health especially as we now have an ancient reminder of just how damaging something like a simple cold virus can be for us.
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