The Algorithm Will See You Now
Artificial intelligence in medicine, still in an early phase, stands to transform how doctors and nurses spend their time.
There's a quiet revolution going on in medicine. It's driven by artificial intelligence, but paradoxically, new technology may put a more human face on healthcare.
AI's usefulness in healthcare ranges far and wide.
Artificial intelligence is software that can process massive amounts of information and learn over time, arriving at decisions with striking accuracy and efficiency. It offers greater accuracy in diagnosis, exponentially faster genome sequencing, the mining of medical literature and patient records at breathtaking speed, a dramatic reduction in administrative bureaucracy, personalized medicine, and even the democratization of healthcare.
The algorithms that bring these advantages won't replace doctors; rather, by offloading some of the most time-consuming tasks in healthcare, providers will be able to focus on personal interactions with patients—listening, empathizing, educating and generally putting the care back in healthcare. The relationship can focus on the alleviation of suffering, both the physical and emotional kind.
Challenges of Getting AI Up and Running
The AI revolution, still in its early phase in medicine, is already spurring some amazing advances, despite the fact that some experts say it has been overhyped. IBM's Watson Health program is a case in point. IBM capitalized on Watson's ability to process natural language by designing algorithms that devour data like medical articles and analyze images like MRIs and medical slides. The algorithms help diagnose diseases and recommend treatment strategies.
But Technology Review reported that a heavily hyped partnership with the MD Anderson Cancer Center in Houston fell apart in 2017 because of a lack of data in the proper format. The data existed, just not in a way that the voraciously data-hungry AI could use to train itself.
The hiccup certainly hasn't dampened the enthusiasm for medical AI among other tech giants, including Google and Apple, both of which have invested billions in their own healthcare projects. At this point, the main challenge is the need for algorithms to interpret a huge diversity of data mined from medical records. This can include everything from CT scans, MRIs, electrocardiograms, x-rays, and medical slides, to millions of pages of medical literature, physician's notes, and patient histories. It can even include data from implantables and wearables such as the Apple Watch and blood sugar monitors.
None of this information is in anything resembling a standard format across and even within hospitals, clinics, and diagnostic centers. Once the algorithms are trained, however, they can crunch massive amounts of data at blinding speed, with an accuracy that matches and sometimes even exceeds that of highly experienced doctors.
Genome sequencing, for example, took years to accomplish as recently as the early 2000s. The Human Genome Project, the first sequencing of the human genome, was an international effort that took 13 years to complete. In April of this year, Rady Children's Institute for Genomic Medicine in San Diego used an AI-powered genome sequencing algorithm to diagnose rare genetic diseases in infants in about 20 hours, according to ScienceDaily.
"Patient care will always begin and end with the doctor."
Dr. Stephen Kingsmore, the lead author of an article published in Science Translational Medicine, emphasized that even though the algorithm helped guide the treatment strategies of neonatal intensive care physicians, the doctor was still an indispensable link in the chain. "Some people call this artificial intelligence, we call it augmented intelligence," he says. "Patient care will always begin and end with the doctor."
One existing trend is helping to supply a great amount of valuable data to algorithms—the electronic health record. Initially blamed for exacerbating the already crushing workload of many physicians, the EHR is emerging as a boon for algorithms because it consolidates all of a patient's data in one record.
Examples of AI in Action Around the Globe
If you're a parent who has ever taken a child to the doctor with flulike symptoms, you know the anxiety of wondering if the symptoms signal something serious. Kang Zhang, M.D., Ph.D., the founding director of the Institute for Genomic Medicine at the University of California at San Diego, and colleagues developed an AI natural language processing model that used deep learning to analyze the EHRs of 1.3 million pediatric visits to a clinic in Guanzhou, China.
The AI identified common childhood diseases with about the same accuracy as human doctors, and it was even able to split the diagnoses into two categories—common conditions such as flu, and serious, life-threatening conditions like meningitis. Zhang has emphasized that the algorithm didn't replace the human doctor, but it did streamline the diagnostic process and could be used in a triage capacity when emergency room personnel need to prioritize the seriously ill over those suffering from common, less dangerous ailments.
AI's usefulness in healthcare ranges far and wide. In Uganda and several other African nations, AI is bringing modern diagnostics to remote villages that have no access to traditional technologies such as x-rays. The New York Times recently reported that there, doctors are using a pocket-sized, hand-held ultrasound machine that works in concert with a cell phone to image and diagnose everything from pneumonia (a common killer of children) to cancerous tumors.
The beauty of the highly portable, battery-powered device is that ultrasound images can be uploaded on computers so that physicians anywhere in the world can review them and weigh in with their advice. And the images are instantly incorporated into the patient's EHR.
Jonathan Rothberg, the founder of Butterfly Network, the Connecticut company that makes the device, told The New York Times that "Two thirds of the world's population gets no imaging at all. When you put something on a chip, the price goes down and you democratize it." The Butterfly ultrasound machine, which sells for $2,000, promises to be a game-changer in remote areas of Africa, South America, and Asia, as well as at the bedsides of patients in developed countries.
AI algorithms are rapidly emerging in healthcare across the U.S. and the world. China has become a major international player, set to surpass the U.S. this year in AI capital investment, the translation of AI research into marketable products, and even the number of often-cited research papers on AI. So far the U.S. is still the leader, but some experts describe the relationship between the U.S. and China as an AI cold war.
"The future of machine learning isn't sentient killer robots. It's longer human lives."
The U.S. Food and Drug Administration expanded its approval of medical algorithms from two in all of 2017 to about two per month throughout 2018. One of the first fields to be impacted is ophthalmology.
One algorithm, developed by the British AI company DeepMind (owned by Alphabet, the parent company of Google), instantly scans patients' retinas and is able to diagnose diabetic retinopathy without needing an ophthalmologist to interpret the scans. This means diabetics can get the test every year from their family physician without having to see a specialist. The Financial Times reported in March that the technology is now being used in clinics throughout Europe.
In Copenhagen, emergency service dispatchers are using a new voice-processing AI called Corti to analyze the conversations in emergency phone calls. The algorithm analyzes the verbal cues of callers, searches its huge database of medical information, and provides dispatchers with onscreen diagnostic information. Freddy Lippert, the CEO of EMS Copenhagen, notes that the algorithm has already saved lives by expediting accurate diagnoses in high-pressure situations where time is of the essence.
Researchers at the University of Nottingham in the UK have even developed a deep learning algorithm that predicts death more accurately than human clinicians. The algorithm incorporates data from a huge range of factors in a chronically ill population, including how many fruits and vegetables a patient eats on a daily basis. Dr. Stephen Weng, lead author of the study, published in PLOS ONE, said in a press release, "We found machine learning algorithms were significantly more accurate in predicting death than the standard prediction models developed by a human expert."
New digital technologies are allowing patients to participate in their healthcare as never before. A feature of the new Apple Watch is an app that detects cardiac arrhythmias and even produces an electrocardiogram if an abnormality is detected. The technology, approved by the FDA, is helping cardiologists monitor heart patients and design interventions for those who may be at higher risk of a cardiac event like a stroke.
If having an algorithm predict your death sends a shiver down your spine, consider that algorithms may keep you alive longer. In 2018, technology reporter Tristan Greene wrote for Medium that "…despite the unending deluge of panic-ridden articles declaring AI the path to apocalypse, we're now living in a world where algorithms save lives every day. The future of machine learning isn't sentient killer robots. It's longer human lives."
The Risks of AI Compiling Your Data
To be sure, the advent of AI-infused medical technology is not without its risks. One risk is that the use of AI wearables constantly monitoring our vital signs could turn us into a nation of hypochondriacs, racing to our doctors every time there's a blip in some vital sign. Such a development could stress an already overburdened system that suffers from, among other things, a shortage of doctors and nurses. Another risk has to do with the privacy protections on the massive repository of intimately personal information that AI will have on us.
In an article recently published in the Journal of the American Medical Association, Australian researcher Kit Huckvale and colleagues examined the handling of data by 36 smartphone apps that assisted people with either depression or smoking cessation, two areas that could lend themselves to stigmatization if they fell into the wrong hands.
Out of the 36 apps, 33 shared their data with third parties, despite the fact that just 25 of those apps had a privacy policy at all and out of those, only 23 stated that data would be shared with third parties. The recipients of all that data? It went almost exclusively to Facebook and Google, to be used for advertising and marketing purposes. But there's nothing to stop it from ending up in the hands of insurers, background databases, or any other entity.
Even when data isn't voluntarily shared, any digital information can be hacked. EHRs and even wearable devices share the same vulnerability as any other digital record or device. Still, the promise of AI to radically improve efficiency and accuracy in healthcare is hard to ignore.
AI Can Help Restore Humanity to Medicine
Eric Topol, director of the Scripps Research Translational Institute and author of the new book Deep Medicine, says that AI gives doctors and nurses the most precious gift of all: time.
Topol welcomes his patients' use of the Apple Watch cardiac feature and is optimistic about the ways that AI is revolutionizing medicine. He says that the watch helps doctors monitor how well medications are working and has already helped to prevent strokes. But in addition to that, AI will help bring the humanity back to a profession that has become as cold and hard as a stainless steel dissection table.
"When I graduated from medical school in the 1970s," he says, "you had a really intimate relationship with your doctor." Over the decades, he has seen that relationship steadily erode as medical organizations demanded that doctors see more and more patients within ever-shrinking time windows.
"Doctors have no time to think, to communicate. We need to restore the mission in medicine."
In addition to that, EHRs have meant that doctors and nurses are getting buried in paperwork and administrative tasks. This is no doubt one reason why a recent study by the World Health Organization showed that worldwide, about 50 percent of doctors suffer from burnout. People who are utterly exhausted make more mistakes, and medical clinicians are no different from the rest of us. Only medical mistakes have unacceptably high stakes. According to its website, Johns Hopkins University recently announced that in the U.S. alone, 250,000 people die from medical mistakes each year.
"Doctors have no time to think, to communicate," says Topol. "We need to restore the mission in medicine." AI is giving doctors more time to devote to the thing that attracted them to medicine in the first place—connecting deeply with patients.
There is a real danger at this juncture, though, that administrators aware of the time-saving aspects of AI will simply push doctors to see more patients, read more tests, and embrace an even more crushing workload.
"We can't leave it to the administrators to just make things worse," says Topol. "Now is the time for doctors to advocate for a restoration of the human touch. We need to stand up for patients and for the patient-doctor relationship."
AI could indeed be a game changer, he says, but rather than squander the huge benefits of more time, "We need a new equation going forward."
Questions remain about new drug for hot flashes
In May, a new drug, Fezolinetant, was approved by the FDA to treat hot flashes associated with menopause.
Vascomotor symptoms (VMS) is the medical term for hot flashes associated with menopause. You are going to hear a lot more about it because a company has a new drug to sell. Here is what you need to know.
Menopause marks the end of a woman’s reproductive capacity. Normal hormonal production associated with that monthly cycle becomes erratic and finally ceases. For some women the transition can be relatively brief with only modest symptoms, while for others the body's “thermostat” in the brain is disrupted and they experience hot flashes and other symptoms that can disrupt daily activity. Lifestyle modification and drugs such as hormone therapy can provide some relief, but women at risk for cancer are advised not to use them and other women choose not to do so.
Fezolinetant, sold by Astellas Pharma Inc. under the product name Veozah™, was approved by the Food and Drug Administration (FDA) on May 12 to treat hot flashes associated with menopause. It is the first in a new class of drugs called neurokinin 3 receptor antagonists, which block specific neurons in the brain “thermostat” that trigger VMS. It does not appear to affect other symptoms of menopause. As with many drugs targeting a brain cell receptor, it must be taken continuously for a few days to build up a good therapeutic response, rather than working as a rescue product such as an asthma inhaler to immediately treat that condition.
Hot flashes vary greatly and naturally get better or resolve completely with time. That contributes to a placebo effect and makes it more difficult to judge the outcome of any intervention. Early this year, a meta analysis of 17 studies of drug trials for hot flashes found an unusually large placebo response in those types of studies; the placebo groups had an average of 5.44 fewer hot flashes and a 36 percent reduction in their severity.
In studies of fezolinetant, the drug recently approved by the FDA, the placebo benefit was strong and persistent. The drug group bested the placebo response to a statistically significant degree but, “If people have gone from 11 hot flashes a day to eight or seven in the placebo group and down to a couple fewer ones in the drug groups, how meaningful is that? Having six hot flashes a day is still pretty unpleasant,” says Diana Zuckerman, president of the National Center for Health Research (NCHR), a health oriented think tank.
“Is a reduction compared to placebo of 2-3 hot flashes per day, in a population of women experiencing 10-11 moderate to severe hot flashes daily, enough relief to be clinically meaningful?” Andrea LaCroix asked a commentary published in Nature Medicine. She is an epidemiologist at the University of California San Diego and a leader of the MsFlash network that has conducted a handful of NIH-funded studies on menopause.
Questions Remain
LaCroix and others have raised questions about how Astellas, the company that makes the new drug, handled missing data from patients who dropped out of the clinical trials. “The lack of detailed information about important parameters such as adherence and missing data raises concerns that the reported benefits of fezolinetant very likely overestimate those that will be observed in clinical practice," LaCroix wrote.
In response to this concern, Anna Criddle, director of global portfolio communications at Astellas, wrote in an email to Leaps.org: “…a full analysis of data, including adherence data and any impact of missing data, was submitted for assessment by [the FDA].”
The company ran the studies at more than 300 sites around the world. Curiously, none appear to have been at academic medical centers, which are known for higher quality research. Zuckerman says, "When somebody is paid to do a study, if they want to get paid to do another study by the same company, they will try to make sure that the results are the results that the company wants.”
Criddle said that Astellas picked the sites “that would allow us to reach a diverse population of women, including race and ethnicity.”
A trial of a lower dose of the drug was conducted in Asia. In March 2022, Astellas issued a press release saying it had failed to prove effectiveness. No further data has been released. Astellas still plans to submit the data, according to Criddle. Results from clinical trials funded by the U.S. goverment must be reported on clinicaltrials.gov within one year of the study's completion - a deadline that, in this case, has expired.
The measurement scale for hot flashes used in the studies, mild-moderate-severe, also came in for criticism. “It is really not good scale, there probably isn’t a broad enough range of things going on or descriptors,” says David Rind. He is chief medical officer of the Institute for Clinical and Economic Review (ICER), a nonprofit authority on new drugs. It conducted a thorough review and analysis of fezolinestant using then existing data gathered from conference abstracts, posters and presentations and included a public stakeholder meeting in December. A 252-page report was published in January, finding “considerable uncertainty about the comparative net health benefits of fezolinetant” versus hormone therapy.
Questions surrounding some of these issues might have been answered if the FDA had chosen to hold a public advisory committee meeting on fezolinetant, which it regularly does for first in class medicines. But the agency decided such a meeting was unnecessary.
Cost
There was little surprise when Astellas announced a list price for fezolinetant of $550 a month ($6000 annually) and a program of patient assistance to ease out of pocket expenses. The company had already incurred large expenses.
In 2017 Astellas purchased the company that originally developed fezolinetant for $534 million plus several hundred million in potential royalties. The drug company ran a "disease awareness” ad, Heat on the Street, hat aired during the Super Bowl in February, where 30 second ads cost about $7 million. Industry analysts have projected sales to be $1.9 billion by 2028.
ICER’s pre-approval evaluation said fezolinetant might "be considered cost-effective if priced around $2,000 annually. ... [It]will depend upon its price and whether it is considered an alternative to MHT [menopause hormone treatment] for all women or whether it will primarily be used by women who cannot or will not take MHT."
Criddle wrote that Astellas set the price based on the novelty of the science, the quality of evidence for the drug and its uniqueness compared to the rest of the market. She noted that an individual’s payment will depend on how much their insurance company decides to cover. “[W]e expect insurance coverage to increase over the course of the year and to achieve widespread coverage in the U.S. over time.”
Leaps.org wrote to and followed up with nine of the largest health insurers/providers asking basic questions about their coverage of fezolinetant. Only two responded. Jennifer Martin, the deputy chief consultant for pharmacy benefits management at the Department of Veterans Affairs, said the agency “covers all drugs from the date that they are launched.” Decisions on whether it will be included in the drug formulary and what if any copays might be required are under review.
“[Fezolinetant] will go through our standard P&T Committee [patient and treatment] review process in the next few months, including a review of available efficacy data, safety data, clinical practice guidelines, and comparison with other agents used for vasomotor symptoms of menopause," said Phil Blando, executive director of corporate communications for CVS Health.
Other insurers likely are going through a similar process to decide issues such as limiting coverage to women who are advised not to use hormones, how much copay will be required, and whether women will be required to first try other options or obtain approvals before getting a prescription.
Rind wants to see a few years of use before he prescribes fezolinetant broadly, and believes most doctors share his view. Nor will they be eager to fill out the additional paperwork required for women to participate in the Astellas patient assistance program, he added.
Safety
Astellas is marketing its drug by pointing out risks of hormone therapy, such as a recent paper in The BMJ, which noted that women who took hormones for even a short period of time had a 24 percent increased risk of dementia. While the percentage was scary, the combined number of women both on and off hormones who developed dementia was small. And it is unclear whether hormones are causing dementia or if more severe hot flashes are a marker for higher risk of developing dementia. This information is emerging only after 80 years of hundreds of millions of women using hormones.
In contrast, the label for fezolinetant prohibits “concomitant use with CYP1A2 inhibitors” and requires testing for liver and kidney function prior to initiating the drug and every three months thereafter. There is no human or animal data on use in a geriatric population, defined as 65 or older, a group that is likely to use the drug. Only a few thousand women have ever taken fezolinetant and most have used it for just a few months.
Options
A woman seeking relief from symptoms of menopause would like to see how fezolintant compares with other available treatment options. But Astellas did not conduct such a study and Andrea LaCroix says it is unlikely that anyone ever will.
ICER has come the closest, with a side-by-side analysis of evidence-based treatments and found that fezolinetant performed quite similarly and modestly as the others in providing relief from hot flashes. Some treatments also help with other symptoms of menopause, which fezolinetant does not.
There are many coping strategies that women can adopt to deal with hot flashes; one of the most common is dressing in layers (such as a sleeveless blouse with a sweater) that can be added or subtracted as conditions require. Avoiding caffeine, hot liquids, and spicy foods is another common strategy. “I stopped drinking hot caffeinated drinks…for several years, and you get out of the habit of drinking them,” says Zuckerman.
LaCroix curates those options at My Meno Plan, which includes a search function where you can enter your symptoms and identify which treatments might work best for you. It also links to published research papers. She says the goal is to empower women with information to make informed decisions about menopause.
A company in England has made a test that picks out the compounds from breath that reveal if people have liver disease.
Every year, around two million people worldwide die of liver disease. While some people inherit the disease, it’s most commonly caused by hepatitis, obesity and alcoholism. These underlying conditions kill liver cells, causing scar tissue to form until eventually the liver cannot function properly. Since 1979, deaths due to liver disease have increased by 400 percent.
The sooner the disease is detected, the more effective treatment can be. But once symptoms appear, the liver is already damaged. Around 50 percent of cases are diagnosed only after the disease has reached the final stages, when treatment is largely ineffective.
To address this problem, Owlstone Medical, a biotech company in England, has developed a breath test that can detect liver disease earlier than conventional approaches. Human breath contains volatile organic compounds (VOCs) that change in the first stages of liver disease. Owlstone’s breath test can reliably collect, store and detect VOCs, while picking out the specific compounds that reveal liver disease.
“There’s a need to screen more broadly for people with early-stage liver disease,” says Owlstone’s CEO Billy Boyle. “Equally important is having a test that's non-invasive, cost effective and can be deployed in a primary care setting.”
The standard tool for detection is a biopsy. It is invasive and expensive, making it impractical to use for people who aren't yet symptomatic. Meanwhile, blood tests are less invasive, but they can be inaccurate and can’t discriminate between different stages of the disease.
In the past, breath tests have not been widely used because of the difficulties of reliably collecting and storing breath. But Owlstone’s technology could help change that.
The team is testing patients in the early stages of advanced liver disease, or cirrhosis, to identify and detect these biomarkers. In an initial study, Owlstone’s breathalyzer was able to pick out patients who had early cirrhosis with 83 percent sensitivity.
Boyle’s work is personally motivated. His wife died of colorectal cancer after she was diagnosed with a progressed form of the disease. “That was a big impetus for me to see if this technology could work in early detection,” he says. “As a company, Owlstone is interested in early detection across a range of diseases because we think that's a way to save lives and a way to save costs.”
How it works
In the past, breath tests have not been widely used because of the difficulties of reliably collecting and storing breath. But Owlstone’s technology could help change that.
Study participants breathe into a mouthpiece attached to a breath sampler developed by Owlstone. It has cartridges are designed and optimized to collect gases. The sampler specifically targets VOCs, extracting them from atmospheric gases in breath, to ensure that even low levels of these compounds are captured.
The sampler can store compounds stably before they are assessed through a method called mass spectrometry, in which compounds are converted into charged atoms, before electromagnetic fields filter and identify even the tiniest amounts of charged atoms according to their weight and charge.
The top four compounds in our breath
In an initial study, Owlstone captured VOCs in breath to see which ones could help them tell the difference between people with and without liver disease. They tested the breath of 46 patients with liver disease - most of them in the earlier stages of cirrhosis - and 42 healthy people. Using this data, they were able to create a diagnostic model. Individually, compounds like 2-Pentanone and limonene performed well as markers for liver disease. Owlstone achieved even better performance by examining the levels of the top four compounds together, distinguishing between liver disease cases and controls with 95 percent accuracy.
“It was a good proof of principle since it looks like there are breath biomarkers that can discriminate between diseases,” Boyle says. “That was a bit of a stepping stone for us to say, taking those identified, let’s try and dose with specific concentrations of probes. It's part of building the evidence and steering the clinical trials to get to liver disease sensitivity.”
Sabine Szunerits, a professor of chemistry in Institute of Electronics at the University of Lille, sees the potential of Owlstone’s technology.
“Breath analysis is showing real promise as a clinical diagnostic tool,” says Szunerits, who has no ties with the company. “Owlstone Medical’s technology is extremely effective in collecting small volatile organic biomarkers in the breath. In combination with pattern recognition it can give an answer on liver disease severity. I see it as a very promising way to give patients novel chances to be cured.”
Improving the breath sampling process
Challenges remain. With more than one thousand VOCs found in the breath, it can be difficult to identify markers for liver disease that are consistent across many patients.
Julian Gardner is a professor of electrical engineering at Warwick University who researches electronic sensing devices. “Everyone’s breath has different levels of VOCs and different ones according to gender, diet, age etc,” Gardner says. “It is indeed very challenging to selectively detect the biomarkers in the breath for liver disease.”
So Owlstone is putting chemicals in the body that they know interact differently with patients with liver disease, and then using the breath sampler to measure these specific VOCs. The chemicals they administer are called Exogenous Volatile Organic Compound) probes, or EVOCs.
Most recently, they used limonene as an EVOC probe, testing 29 patients with early cirrhosis and 29 controls. They gave the limonene to subjects at specific doses to measure how its concentrations change in breath. The aim was to try and see what was happening in their livers.
“They are proposing to use drugs to enhance the signal as they are concerned about the sensitivity and selectivity of their method,” Gardner says. “The approach of EVOC probes is probably necessary as you can then eliminate the person-to-person variation that will be considerable in the soup of VOCs in our breath.”
Through these probes, Owlstone could identify patients with liver disease with 83 percent sensitivity. By targeting what they knew was a disease mechanism, they were able to amplify the signal. The company is starting a larger clinical trial, and the plan is to eventually use a panel of EVOC probes to make sure they can see diverging VOCs more clearly.
“I think the approach of using probes to amplify the VOC signal will ultimately increase the specificity of any VOC breath tests, and improve their practical usability,” says Roger Yazbek, who leads the South Australian Breath Analysis Research (SABAR) laboratory in Flinders University. “Whilst the findings are interesting, it still is only a small cohort of patients in one location.”
The future of breath diagnosis
Owlstone wants to partner with pharmaceutical companies looking to learn if their drugs have an effect on liver disease. They’ve also developed a microchip, a miniaturized version of mass spectrometry instruments, that can be used with the breathalyzer. It is less sensitive but will enable faster detection.
Boyle says the company's mission is for their tests to save 100,000 lives. "There are lots of risks and lots of challenges. I think there's an opportunity to really establish breath as a new diagnostic class.”