Today on Health in 2 Point 00, Jess and I power through a whopping six questions. In this episode, Jess asks me about the merger between Cambia Health Solutions and Blue Cross NC, Alex Azar getting grilled by Rep. Joe Kennedy on Medicaid work requirements, Omada Health adding connected blood pressure and glucose monitors, 23andMe’s new Type 2 Diabetes predisposition test, and raises by Akili Interactive and MAP Health Management. —Matthew Holt
Jessica DaMassa asks me about single payer polling high, big VC for women’s pelvic floor digital therapeutic Renovia, 23andme cutting off API access to its data, plus guest mentions for Shafi Ahmed and Glen Tullman. All in 2 minutes (more or less!)–Matthew Holt
After the longwinded-ness of last episode, Jessica DaMassa runs a tight ship today. Lantern’s demise, GSK & 23andme’s huge deal, yet another big chunk of change for American Well, and what was going on at #GoogleNext18 with Google Cloud in health –all asked by Jessica and answered by me, in under the 2 minute wire–Matthew Holt
You’ve probably seen by now both that the WSJ’s John Carreyrou has run a well researched hit piece on Theranos and that the company, led by wunderkind Elizabeth Holmes, has somewhat muffed its reply. If you haven’t, best thing is to read the Roger Parloff Fortune piece which summarizes the pay-walled piece so you don’t have to do the painful task of sending Rupert Murdoch money. Now in the spirit of FD I need to let you know that we’ve invited Holmes to speak at Health 2.0 twice and her PR handlers have been unbelievably hard to communicate with. They’ve either flat out ignored us or taken forever to turn us down, even though she’s appeared often at (what I at least consider) much less important or relevant venues. I have no idea if she’s badly advised, wanting to stay away from sophisticated health tech audiences, or if her handlers decided that we and our 2,000 strong crowd are just not cool enough for her. Or maybe simply her calendar hasn’t allowed it. Either way I have no first hand knowledge of her or the product–although Elizabeth our invite is still out there! But I do know five things.
1) Lab business decentralizes & democratizes. Whether or not Theranos is lying, cheating, not using its own tech, or its cool stuff just doesn’t work, the trend towards comprehensive, cheap and soon at home lab testing is clear. More than 5 years ago a company called BioIQ was selling at home fingerstick based cholesterol & glucose tests. In the past year the two stage Nokia Sensing XCHALLENGE (of which we hosted stage 1 at Health 2.0 in 2013) has revealed a plethora of companies taking minute quantities of blood, pee or spit and doing complex diagnosis from them. And it’s not stopping there. The next phase is using light and other sensors to diagnose direct from the skin. Whether or not the locus of activity ends up using Theranos at Walgreens or the kitchen table using something else, the dam holding back continuous, cheap multi-faceted testing is going to burst soon.
2) Theranos and Holmes are not the most important thing in health care. There, I’ve said it. While Holmes has talked a lot about revolutionizing health care access and has given lots of transparency into Theranos’ pricing if not its testing technology, what they’re up to is getting easier access to lab tests. I think this is very important and a very good thing, but no one can seriously believe that this is the biggest change in health care. It’s part of a trend towards consumerism. But I’d argue the most important trend in health care is the redesign of chronic care management, on which we spend a shed-load more than lab testing. I may be wrong but if you insert your pet issue here, I’d bet it’s not cheaper lab testing. The media has been a tad snowed by the “youngest female billionaire” and “blonde Steve Jobs” analogies, but even if she runs the field and takes over most lab testing, it’s an incremental change not a huge revolution in health care.
Today we’re starting a series of more personal stories, looking at what makes interesting people in health care tick. Alex Carmichael is a rare multiple time CEO in health technology, and she has a very interesting tale to tell–Matthew Holt
Don’t worry, this isn’t your typical, syrupy founder story. Matthew asked me to share my experience selling my startup CureTogether to 23andMe, what ensued after that, and how I ended up at uBiome today.
So I thought, if I’m going to share, I might as well *really* share. Let you in behind the scenes to see what it was actually like.
(Bonus: at the end I’ve listed my top 11 life lessons, so make sure you read all the way through for that!)
The story starts…
October 1, 1976: I came into the world in Toronto, Canada, with striking violet eyes. My lawyer/politician mother and management consultant father gave me the name Alexandra, which means “leader of all mankind,” as they often reminded me. Talk about a family having high expectations!
Childhood: I remember loving to read and walk my dogs, who were probably my best friends. I went to a progressive Montessori school with an amazing teacher who believed in me and taught me the power of patience.
Teenage years: The “best” school in Toronto was a repressive and aggressive all-girls private school. My insane work ethic was drilled into me there, as well as at my mom’s political campaign offices, where I would work after school until late into the night.
College years: I met my first love, Danny, in a biochemistry lab at the University of Toronto. I chose the most difficult major (Molecular Genetics and Molecular Biology), because it would drive me hardest. Masochist much?
First startup, 1999: I dropped out of grad school, much to the horror of my extremely educated parents, to join a bioinformatics software company Danny had started in his bedroom in 1997. I taught myself how to code, design, sell, and run a company. We worked so much that we hardly left our apartment, except to get married, have a baby, and occasionally go to Tai Chi class. We lost most of our money in the dot com bust, and scraped by on rice and beans for a few years. It was so isolating and intense that I got really depressed and even suicidal once.
First exit, and move to California, 2005: We were seriously running out of money, so one day I made a big wall chart of all the possible companies that could acquire us, and we started going after each one relentlessly. After a few months, we got a meeting with Hitachi. They were interested, but didn’t seal the deal until we decided to put our stuff in storage and just show up in California, baby daughter Samantha in tow. One way or another, we were determined to make it work. They did end up acquiring us, for a few hundred thousand dollars. Not much for 8 years of invested time and energy, but really we just wanted to get to California, where the sun shines and the opportunity abounds. We finally made it!
An advantage astrologers have over genetic testing is that the prediction of astrologers are personally verifiable. An astrologer once emphatically stated that I had no chance of a career in international cricket or Bollywood. So far both claims have turned out to be remarkably accurate.
How does one personally verify a “12.5 %” increased chance of lung cancer, the sort of number the vendor for genetic testing 23andMe produces? If one develops lung cancer how would one know that the chances were indeed 12.5 %, not 6.25 % or 25 %?
We die only once. Whether one ends up with lung cancer or doesn’t, the veracity of the claim can be made only empirically. Meaning we need to see how many develop lung cancer out of 10, 000 people just like us.
Yet there is an element of scientific precision in the number, augmented by the decimal point. And it is precisely because genetic testing tends towards science not metaphysics that it falls within the dominion of the Food and Drug Administration (FDA). FDA does not regulate palm readers.
FDA has asked 23andMe to stop sales of its genomic testing.
As a libertarian seeped in the Austrian school of Economics, I am generally disposed against regulations. I also share the sentiments of the monetarist Milton Friedman that the true costs of the FDA must also include the treatment opportunities foregone in their lengthy review process.
So it hurts me to be somewhat sympathetic of FDA’s stance on 23andMe, even as I think an outright ban was a tad harsh.
Genetic testing is a powerful tool. Two years ago, with the help of my colleagues, it was this tool that helped us identify a new disease. The disease, called Ogden Syndrome, caused the death of a four-month old child named Max. But the rules and regulations for genetic testing in the US, laid down in the CLIA (Clinical Laboratory Improvement Amendments), meant I could not share the results of the family’s genetic tests with them.
Since that time, I have advocated performing all genetic testing involving humans such that results can be returned to research participants. This I believe should extend beyond research, and some private companies, like 23andMe, are helping to do just that.
For as little as US $99, people around the world can send a sample of their saliva to 23andMe to get their DNA sequenced. Their Personal Genome Service (PGS) analyses parts of a person’s genome. This data is then compared with related scientific data and 23andMe’s own database of hundreds of thousands of individuals to spot genetic markers, which the company claims “reports on 240 health condition and traits”.
Earlier this month, however, as I had feared, the US Food and Drug Administration (FDA) has ordered 23andMe to stop marketing their service. In a warning letter, FDA said: “23andMe must immediately discontinue marketing the PGS until such time as it receives FDA marketing authorisation for the device.” By calling PGS “a device”, the FDA fears that people may self-medicate based on results they receive from 23andMe.
Somehow the US and UK governments find it acceptable to store massive amounts of data about their own citizens and that of the rest of the world. They are happy spending billions on such mass surveillance. But if the same people want to spend their own money to advance genomic medicine and possibly improve their own health in the process, they want to stop them.
Recently, the US Preventative Services Task Force reiterated its recommendation that women not undergo routine screening for ovarian cancer. This was remarkable, not simply because it was a recommendation against screening, but because the task force was making the recommendation again, and this time even stronger.
The motivation for the recommendation was simple: a review of years’ worth of data indicates that most women are more likely to suffer harm because of false alarms than they are to benefit from early detection. These screenings are a hallmark of population medicine—an archetypal form of medicine that does not attempt to distinguish one individual from another. Moving beyond the ritualistic screening procedures could help reduce the toll of at least $765 billion of wasted health care costs per year.
We already know the common changes in the DNA sequence that identify people who have higher risk of developing ovarian, breast or prostate cancer and most other types of cancer. Consumers can now readily obtain this information via personal genomic companies like 23andMe or Pathway Genomics. But we need to do much more DNA sequencing to find the less common yet even more important variations—those which carry the highest risk of a particular cancer. Such research would be easy to accomplish if it were given top priority and it would likely lead to precision screening. Only a small fraction of individuals would need to have any medical screening. What’s more, it will protect hundreds of thousands of Americans from being unnecessarily harmed each year.
A lot, a little, not at all?
Scenario 1 (big help): You discover you have a greatly elevated risk of Disease X. You do various things to reduce that risk that actually reduce it.
Scenario 2: (a little help): You discover you have a greatly elevated risk of Rare Disease X. You do various things to reduce that risk but they don’t help. At least, when Disease X starts, you will be less upset.
Scenario 3 (no help): You discover that you have a greatly elevated risk for a common easily-noticed disease (such as obesity). You already watched your weight, this changes nothing. Scenario 4 (harm): You discover that you have a greatly elevated risk of Scary Disease X (e.g., bipolar disorder). It is depressing news. Later studies show that the gene/disease association was a mistake. (Many gene/disease associations have failed to replicate.)
A recent Wired article tries to answer this question for one person: Raymond McCauley, a bioinformatics scientist who had his genome sequenced four years ago and learned he was “four or five times more likely than most people to develop age-related macular degeneration (AMD)”. The article says “of all the ailments described in the 23andme profile, AMD has one of the strongest genetic associations”. If I found this in my genetic profile, I would want to know the confidence interval of the increased risk. Is it a factor of 4.5 plus or minus 1? Or 4.5 plus or minus 8? This isn’t easy to figure out. In addition to the question of variability, there can easily be bias (= estimate is too high). Let’s say I do 100 gene/disease association studies.
Reductions in the cost of genetic testing and improvements in what we know about what it tells us produce obvious benefits; if you know you are likely to have some particular medical problem, you may be able to take precautions against it. But they also have at least one potential downside.
The more is known about the chance of bad things happening to us, the less able we will be to insure against them.
A solution to this problem that is sometimes proposed is to permit individuals to have their genes tested but forbid insurance companies to require testing as a condition of insurance or to use the information it produces. The problem with that is adverse selection. If the customer knows his risk and the insurance company doesn’t, high risk and low risk customers are charged the same price, making insurance a good deal for the former and a bad deal for the latter. Insurance companies, realizing that most of those who choose to buy their insurance are bad risks, will charge accordingly, driving more of the low or average risk customers out of the market. In the limiting case, insurance is bought only by high risk customers, at a high risk price. A famous description of the problem is Akerlof’s article “The Market for Lemons.”
If we allow both insurance companies and their customers to make use of genetic information, then both high risk and low risk customers can buy insurance, but at different prices. The risk of having genetic variants that make you more likely to suffer some expensive medical problem is uninsurable, although you can still insure against the risk that, given those genes, the problem will actually appear.