Elizabeth Holmes Through the Director’s Lens
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
"The Inventor," a chronicle of Theranos's storied downfall, premiered recently on HBO. Leapsmag reached out to director Alex Gibney, whom The New York Times has called "one of America's most successful and prolific documentary filmmakers," for his perspective on Elizabeth Holmes and the world she inhabited.
Do you think Elizabeth Holmes was a charismatic sociopath from the start — or is she someone who had good intentions, over-promised, and began the lies to keep her business afloat, a "fake it till you make it" entrepreneur like Thomas Edison?
I'm not qualified to say if EH was or is a sociopath. I don't think she started Theranos as a scam whose only purpose was to make money. If she had done so, she surely would have taken more money for herself along the way. I do think that she had good intentions and that she, as you say, "began the lies to keep her business afloat." ([Reporter John] Carreyrou's book points out that those lies began early.) I think that the Edison comparison is instructive for a lot of reasons.
First, Edison was the original "fake-it-till-you-make-it" entrepreneur. That puts this kind of behavior in the mainstream of American business. By saying that, I am NOT endorsing the ethic, just the opposite. As one Enron executive mused about the mendacity there, "Was it fraud or was it bad marketing?" That gives you a sense of how baked-in the "fake it" sensibility is.
"Having a thirst for fame and a noble cause enabled her to think it was OK to lie in service of those goals."
I think EH shares one other thing with Edison, which is a huge ego coupled with a talent for storytelling as long as she is the heroic, larger-than-life main character. It's interesting that EH calls her initial device "Edison." Edison was the world's most famous "inventor," both because of the devices that came out of his shop and and for his ability for "self-invention." As Randall Stross notes in "The Wizard of Menlo Park," he was the first celebrity businessman. In addition to her "good intentions," EH was certainly motivated by fame and glory and many of her lies were in service to those goals.
Having a thirst for fame and a noble cause enabled her to think it was OK to lie in service of those goals. That doesn't excuse the lies. But those noble goals may have allowed EH to excuse them for herself or, more perniciously, to make believe that they weren't lies at all. This is where we get into scary psychological territory.
But rather than thinking of it as freakish, I think it's more productive to think of it as an exaggeration of the way we all lie to others and to ourselves. That's the point of including the Dan Ariely experiment with the dice. In that experiment, most of the subjects cheated more when they thought they were doing it for a good cause. Even more disturbing, that "good cause" allowed them to lie much more effectively because they had come to believe they weren't doing anything wrong. As it turns out, economics isn't a rational practice; it's the practice of rationalizing.
Where EH and Edison differ is that Edison had a firm grip on reality. He knew he could find a way to make the incandescent lightbulb work. There is no evidence that EH was close to making her "Edison" work. But rather than face reality (and possibly adjust her goals) she pretended that her dream was real. That kind of "over-promising" or "bold vision" is one thing when you are making a prototype in the lab. It's a far more serious matter when you are using a deeply flawed system on real patients. EH can tell herself that she had to do that (Walgreens was ready to walk away if she hadn't "gone live") or else Theranos would have run out of money.
But look at the calculation she made: she thought it was worth putting lives at risk in order to make her dream come true. Now we're getting into the realm of the sociopath. But my experience leads me to believe that -- as in the case of the Milgram experiment -- most people don't do terrible things right away, they come to crimes gradually as they become more comfortable with bigger and bigger rationalizations. At Theranos, the more valuable the company became, the bigger grew the lies.
The two whistleblowers come across as courageous heroes, going up against the powerful and intimidating company. The contrast between their youth and lack of power and the old elite backers of Theronos is staggering, and yet justice triumphed. Were the whistleblowers hesitant or afraid to appear in the film, or were they eager to share their stories?
By the time I got to them, they were willing and eager to tell their stories, once I convinced them that I would honor their testimony. In the case of Erika and Tyler, they were nudged to participate by John Carreyrou, in whom they had enormous trust.
"It's simply crazy that no one demanded to see an objective demonstration of the magic box."
Why do you think so many elite veterans of politics and venture capitalism succumbed to Holmes' narrative in the first place, without checking into the details of its technology or financials?
The reasons are all in the film. First, Channing Robertson and many of the old men on her board were clearly charmed by her and maybe attracted to her. They may have rationalized their attraction by convincing themselves it was for a good cause! Second, as Dan Ariely tells us, we all respond to stories -- more than graphs and data -- because they stir us emotionally. EH was a great storyteller. Third, the story of her as a female inventor and entrepreneur in male-dominated Silicon Valley is a tale that they wanted to invest in.
There may have been other factors. EH was very clever about the way she put together an ensemble of credibility. How could Channing Robertson, George Shultz, Henry Kissinger and Jim Mattis all be wrong? And when Walgreens put the Wellness Centers in stores, investors like Rupert Murdoch assumed that Walgreens must have done its due diligence. But they hadn't!
It's simply crazy that no one demanded to see an objective demonstration of the magic box. But that blind faith, as it turns out, is more a part of capitalism than we have been taught.
Do you think that Roger Parloff deserves any blame for the glowing Fortune story on Theranos, since he appears in the film to blame himself? Or was he just one more victim of Theranos's fraud?
He put her on the cover of Fortune so he deserves some blame for the fraud. He still blames himself. That willingness to hold himself to account shows how seriously he takes the job of a journalist. Unlike Elizabeth, Roger has the honesty and moral integrity to admit that he made a mistake. He owned up to it and published a mea culpa. That said, Roger was also a victim because Elizabeth lied to him.
Do you think investors in Silicon Valley, with their FOMO attitudes and deep pockets, are vulnerable to making the same mistake again with a shiny new startup, or has this saga been a sober reminder to do their due diligence first?
Many of the mistakes made with Theranos were the same mistakes made with Enron. We must learn to recognize that we are, by nature, trusting souls. Knowing that should lead us to a guiding slogan: "trust but verify."
The irony of Holmes dancing to "I Can't Touch This" is almost too perfect. How did you find that footage?
It was leaked to us.
"Elizabeth Holmes is now famous for her fraud. Who better to host the re-boot of 'The Apprentice.'"
Holmes is facing up to 20 years in prison for federal fraud charges, but Vanity Fair recently reported that she is seeking redemption, taking meetings with filmmakers for a possible documentary to share her "real" story. What do you think will become of Holmes in the long run?
It's usually a mistake to handicap a trial. My guess is that she will be convicted and do some prison time. But maybe she can convince jurors -- the way she convinced journalists, her board, and her investors -- that, on account of her noble intentions, she deserves to be found not guilty. "Somewhere, over the rainbow…"
After the trial, and possibly prison, I'm sure that EH will use her supporters (like Tim Draper) to find a way to use the virtual currency of her celebrity to rebrand herself and launch something new. Fitzgerald famously said that "there are no second acts in American lives." That may be the stupidest thing he ever said.
Donald Trump failed at virtually every business he ever embarked on. But he became a celebrity for being a fake businessman and used that celebrity -- and phony expertise -- to become president of the United States. Elizabeth Holmes is now famous for her fraud. Who better to host the re-boot of "The Apprentice." And then?
"You Can't Touch This!"
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
Genetically Sequencing Healthy Babies Yielded Surprising Results
Today in Melrose, Massachusetts, Cora Stetson is the picture of good health, a bubbly precocious 2-year-old. But Cora has two separate mutations in the gene that produces a critical enzyme called biotinidase and her body produces only 40 percent of the normal levels of that enzyme.
In the last few years, the dream of predicting and preventing diseases through genomics, starting in childhood, is finally within reach.
That's enough to pass conventional newborn (heelstick) screening, but may not be enough for normal brain development, putting baby Cora at risk for seizures and cognitive impairment. But thanks to an experimental study in which Cora's DNA was sequenced after birth, this condition was discovered and she is being treated with a safe and inexpensive vitamin supplement.
Stories like these are beginning to emerge from the BabySeq Project, the first clinical trial in the world to systematically sequence healthy newborn infants. This trial was led by my research group with funding from the National Institutes of Health. While still controversial, it is pointing the way to a future in which adults, or even newborns, can receive comprehensive genetic analysis in order to determine their risk of future disease and enable opportunities to prevent them.
Some believe that medicine is still not ready for genomic population screening, but others feel it is long overdue. After all, the sequencing of the Human Genome Project was completed in 2003, and with this milestone, it became feasible to sequence and interpret the genome of any human being. The costs have come down dramatically since then; an entire human genome can now be sequenced for about $800, although the costs of bioinformatic and medical interpretation can add another $200 to $2000 more, depending upon the number of genes interrogated and the sophistication of the interpretive effort.
Two-year-old Cora Stetson, whose DNA sequencing after birth identified a potentially dangerous genetic mutation in time for her to receive preventive treatment.
(Photo courtesy of Robert Green)
The ability to sequence the human genome yielded extraordinary benefits in scientific discovery, disease diagnosis, and targeted cancer treatment. But the ability of genomes to detect health risks in advance, to actually predict the medical future of an individual, has been mired in controversy and slow to manifest. In particular, the oft-cited vision that healthy infants could be genetically tested at birth in order to predict and prevent the diseases they would encounter, has proven to be far tougher to implement than anyone anticipated.
But in the last few years, the dream of predicting and preventing diseases through genomics, starting in childhood, is finally within reach. Why did it take so long? And what remains to be done?
Great Expectations
Part of the problem was the unrealistic expectations that had been building for years in advance of the genomic science itself. For example, the 1997 film Gattaca portrayed a near future in which the lifetime risk of disease was readily predicted the moment an infant is born. In the fanfare that accompanied the completion of the Human Genome Project, the notion of predicting and preventing future disease in an individual became a powerful meme that was used to inspire investment and public support for genomic research long before the tools were in place to make it happen.
Another part of the problem was the success of state-mandated newborn screening programs that began in the 1960's with biochemical tests of the "heel-stick" for babies with metabolic disorders. These programs have worked beautifully, costing only a few dollars per baby and saving thousands of infants from death and severe cognitive impairment. It seemed only logical that a new technology like genome sequencing would add power and promise to such programs. But instead of embracing the notion of newborn sequencing, newborn screening laboratories have thus far rejected the entire idea as too expensive, too ambiguous, and too threatening to the comfortable constituency that they had built within the public health framework.
"What can you find when you look as deeply as possible into the medical genomes of healthy individuals?"
Creating the Evidence Base for Preventive Genomics
Despite a number of obstacles, there are researchers who are exploring how to achieve the original vision of genomic testing as a tool for disease prediction and prevention. For example, in our NIH-funded MedSeq Project, we were the first to ask the question: "What can you find when you look as deeply as possible into the medical genomes of healthy individuals?"
Most people do not understand that genetic information comes in four separate categories: 1) dominant mutations putting the individual at risk for rare conditions like familial forms of heart disease or cancer, (2) recessive mutations putting the individual's children at risk for rare conditions like cystic fibrosis or PKU, (3) variants across the genome that can be tallied to construct polygenic risk scores for common conditions like heart disease or type 2 diabetes, and (4) variants that can influence drug metabolism or predict drug side effects such as the muscle pain that occasionally occurs with statin use.
The technological and analytical challenges of our study were formidable, because we decided to systematically interrogate over 5000 disease-associated genes and report results in all four categories of genetic information directly to the primary care physicians for each of our volunteers. We enrolled 200 adults and found that everyone who was sequenced had medically relevant polygenic and pharmacogenomic results, over 90 percent carried recessive mutations that could have been important to reproduction, and an extraordinary 14.5 percent carried dominant mutations for rare genetic conditions.
A few years later we launched the BabySeq Project. In this study, we restricted the number of genes to include only those with child/adolescent onset that could benefit medically from early warning, and even so, we found 9.4 percent carried dominant mutations for rare conditions.
At first, our interpretation around the high proportion of apparently healthy individuals with dominant mutations for rare genetic conditions was simple – that these conditions had lower "penetrance" than anticipated; in other words, only a small proportion of those who carried the dominant mutation would get the disease. If this interpretation were to hold, then genetic risk information might be far less useful than we had hoped.
Suddenly the information available in the genome of even an apparently healthy individual is looking more robust, and the prospect of preventive genomics is looking feasible.
But then we circled back with each adult or infant in order to examine and test them for any possible features of the rare disease in question. When we did this, we were surprised to see that in over a quarter of those carrying such mutations, there were already subtle signs of the disease in question that had not even been suspected! Now our interpretation was different. We now believe that genetic risk may be responsible for subclinical disease in a much higher proportion of people than has ever been suspected!
Meanwhile, colleagues of ours have been demonstrating that detailed analysis of polygenic risk scores can identify individuals at high risk for common conditions like heart disease. So adding up the medically relevant results in any given genome, we start to see that you can learn your risks for a rare monogenic condition, a common polygenic condition, a bad effect from a drug you might take in the future, or for having a child with a devastating recessive condition. Suddenly the information available in the genome of even an apparently healthy individual is looking more robust, and the prospect of preventive genomics is looking feasible.
Preventive Genomics Arrives in Clinical Medicine
There is still considerable evidence to gather before we can recommend genomic screening for the entire population. For example, it is important to make sure that families who learn about such risks do not suffer harms or waste resources from excessive medical attention. And many doctors don't yet have guidance on how to use such information with their patients. But our research is convincing many people that preventive genomics is coming and that it will save lives.
In fact, we recently launched a Preventive Genomics Clinic at Brigham and Women's Hospital where information-seeking adults can obtain predictive genomic testing with the highest quality interpretation and medical context, and be coached over time in light of their disease risks toward a healthier outcome. Insurance doesn't yet cover such testing, so patients must pay out of pocket for now, but they can choose from a menu of genetic screening tests, all of which are more comprehensive than consumer-facing products. Genetic counseling is available but optional. So far, this service is for adults only, but sequencing for children will surely follow soon.
As the costs of sequencing and other Omics technologies continue to decline, we will see both responsible and irresponsible marketing of genetic testing, and we will need to guard against unscientific claims. But at the same time, we must be far more imaginative and fast moving in mainstream medicine than we have been to date in order to claim the emerging benefits of preventive genomics where it is now clear that suffering can be averted, and lives can be saved. The future has arrived if we are bold enough to grasp it.
Funding and Disclosures:
Dr. Green's research is supported by the National Institutes of Health, the Department of Defense and through donations to The Franca Sozzani Fund for Preventive Genomics. Dr. Green receives compensation for advising the following companies: AIA, Applied Therapeutics, Helix, Ohana, OptraHealth, Prudential, Verily and Veritas; and is co-founder and advisor to Genome Medical, Inc, a technology and services company providing genetics expertise to patients, providers, employers and care systems.
Your Prescription Is Ready for Download
You may be familiar with Moore's Law, the prediction made by Intel co-founder Gordon Moore that computer chips would get faster and cheaper with each passing year. That's been borne out by the explosive growth of the tech industry, but you may not know that there is an inverse Moore's Law for drug development.
What if there were a way to apply the fast-moving, low-cost techniques of software development to drug discovery?
Eroom's Law—yes that's "Moore" spelled backward—is the observation that drug discovery has become slower and more expensive over time, despite technological improvements. And just like Moore's Law, it's been borne out by experience—from the 1950s to today, the number of drugs that can be developed per billion dollars in spending has steadily decreased, contributing to the continued growth of health care costs.
But what if there were a way to apply the fast-moving, low-cost techniques of software development to drug discovery? That's what a group of startups in the new field of digital therapeutics are promising. They develop apps that are used—either on their own or in conjunction with conventional drugs—to treat chronic disorders like addiction, diabetes and mental health that have so far resisted a pharmaceutical approach. Unlike the thousands of wellness and health apps that can be downloaded to your phone, digital therapeutics are developed and are meant to be used like drugs, complete with clinical trials, FDA approval and doctor prescriptions.
The field is hot—in 2017 global investment in digital therapeutics jumped to $11.5 billion, a fivefold increase from 2012, and major pharma companies like Novartis are developing their own digital products or partnering with startups. One such startup is the bicoastal Pear Therapeutics. Last month, Pear's reSET-O product became the first digital therapeutic to be approved for use by the millions of Americans who struggle with opioid use disorder, and the company has other products addressing addiction and mental illness in the pipeline.
I spoke with Dr. Corey McCann, Pear's CEO, about the company's efforts to meld software and medicine, designing clinical trials for an entirely new kind of treatment, and the future of digital therapeutics.
The interview has been edited and condensed for clarity and length.
"We're looking at conditions that currently can't be cured with drugs."
BRYAN WALSH: What makes a digital therapeutic different than a wellness app?
COREY MCCANN: What we do is develop therapeutics that are designed to be used under the auspices of a physician, just as a drug developed under good manufacturing would be. We do clinical studies for both safety and efficacy, and then they go through the development process you'd expect for a drug. We look at the commercial side, at the role of doctors. Everything we do is what would be done with a traditional medical product. It's a piece of software developed like a drug.
WALSH: What kind of conditions are you first aiming to treat with digital therapeutics?
MCCANN: We're looking at conditions that currently can't be cured with drugs. A good example is our reSET product, which is designed to treat addiction to alcohol, cannabis, stimulants, cocaine. There really aren't pharmaceutical products that are approved to treat people addicted to these substances. What we're doing is functional therapy, the standard of care for addiction treatment, but delivered via software. But we can also work with medication—our reSET-O product is a great example. It's for patients struggling with opioid addiction, and it's delivered in concert with the drug buprenorphine.
WALSH: Walk me through what the patient experience would be like for someone on a digital therapeutic like reSET.
MCCANN: Imagine you're a patient who has been diagnosed with cocaine addiction by a doctor. You would then receive a prescription for reSET during the same office visit. Instead of a pharmacy, the script is sent to the reSET Connect Patient Service Center, where you are onboarded and given an access code that is used to unlock the product after downloading it onto your device. The product has 60 different modules—each one requiring about a 10 to 15-minute interaction—all derived from a form of cognitive behavioral therapy called community reinforcement approach. The treatment takes place over 90 days.
"The patients receiving the digital therapeutic were more than twice as likely to remain abstinent as those receiving standard care."
Patients report their substance abuse, cravings and triggers, and they are also tested on core proficiencies through the therapy. Physicians have access to all of their data, which helps facilitate their one-on-one meetings. We know from regular urine tests how effective the treatment is.
WALSH: What kind of data did you find when you did clinical studies on reSET?
MCCANN: We had 399 patients in 10 centers taking part in a randomized clinical trial run by the National Institute on Drug Abuse. Every patient enrolled in the study had an active substance abuse disorder. The study was randomized so that patients either received the best current standard of care, which is three hours a week of face-to-face therapy, or they received the digital therapeutic. The primary endpoint was abstinence in weeks 9 to 12—if the patient had a single dirty urine screen in the last month, they counted as a failure.
In the end, the patients receiving the digital therapeutic were more than twice as likely to remain abstinent as those receiving standard care—40 percent versus 17 percent. Those receiving reSET were also much more likely to remain in treatment through the entire trial.
WALSH: Why start by focusing your first digital therapeutics on addiction?
MCCANN: We have tried to build a company that is poised to make a difference in medicine. If you look at addiction, there is little to nothing in the drug pipeline to address this. More than 30 million people in the U.S. suffer from addiction disorders, and not only is efficacy a concern, but so is access. Many patients aren't able to receive anything like the kind of face-to-face therapy our control group received. So we think digital therapeutics can make a difference there as well.
WALSH: reSET was the first digital therapeutic approved by the FDA to treat a specific disorder. What has the approval process been like?
MCCANN: It's been a learning process for all involved, including the FDA. Our philosophy is to work within the clinical trials structure, which has specific disease targets and endpoints, and develop quality software, and bring those two strands together to generate digital therapeutics. We now have two products that have been FDA-approved, and four more in development. The FDA is appropriately cautious about all of this, balancing the tradeoff between patient risk and medical value. As we see it, our company is half tech and half biotech, and we follow regulatory trials that are as rigorous as they would be with any drug company.
"This is a new space, but when you look back in 10 years there will be an entire industry of prescription digital therapeutics."
WALSH: How do you balance those two halves, the tech side and the biology side? Tech companies are known for iterating rapidly and cheaply, while pharma companies develop drugs slowly and expensively.
MCCANN: This is a new space, but when you look back in 10 years there will be an entire industry of prescription digital therapeutics. Right now for us we're combining the rigor of the pharmaceutical model with the speed and agility of a tech company. Our product takes longer to develop than an unverified health app, but less time and with less clinical risk than a new molecular entity. This is still a work in progress and not a day goes by where we don't notice the difference between those disciplines.
WALSH: Who's going to pay for these treatments? Insurers are traditionally slow to accept new innovations in the therapeutic space.
MCCANN: This is just like any drug launch. We need to show medical quality and value, and we need to get clinician demand. We want to focus on demonstrating as many scripts as we can in 2019. And we know we'll need to be persistent—we live in a world where payers will say no to anything three times before they say yes. Demonstrating value is how you get there.
WALSH: Is part of that value the possibility that digital therapeutics could be much cheaper than paying someone for multiple face-to-face therapy sessions?
MCCANN: I believe the cost model is very compelling here, especially when you can treat diseases that were not treatable before. That is something that creates medical value. Then you have the data aspect, which makes our product fundamentally different from a drug. We know everything about every patient that uses our product. We know engagement, we can push patient self-reports to clinicians. We can measure efficiency out in the real world, not just in a measured clinical trial. That is the holy grail in the pharma world—to understand compliance in practice.
WALSH: What's the future of digital therapeutics?
MCCANN: In 10 years, what we think of as digital medicine will just be medicine. This is something that will absolutely become standard of care. We are working on education to help partners and payers figure out where go from here, and to incorporate digital therapeutics into standard care. It will start in 2019 and 2020 with addiction medicine, and then in three to five years you'll see treatments designed to address disorders of the brain. And then past the decade horizon you'll see plenty of products that aim at every facet of medicine.