The Algorithm Will See You Now
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."
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here are the promising studies covered in this week's Friday Five, featuring interviews with Dr. Christopher Martens, director of the Delaware Center for Cogntiive Aging Research and professor of kinesiology and applied physiology at the University of Delaware, and Dr. Ilona Matysiak, visiting scholar at Iowa State University and associate professor of sociology at Maria Grzegorzewska University.
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As a child, Wendy Borsari participated in a health study at Boston Children’s Hospital. She was involved because heart disease and sudden cardiac arrest ran in her family as far back as seven generations. When she was 18, however, the study’s doctors told her that she had a perfectly healthy heart and didn’t have to worry.
A couple of years after graduating from college, though, the Boston native began to experience episodes of near fainting. During any sort of strenuous exercise, my blood pressure would drop instead of increasing, she recalls.
She was diagnosed at 24 with hypertrophic cardiomyopathy. Although HCM is a commonly inherited heart disease, Borsari’s case resulted from a rare gene mutation, the MYH7 gene. Her mother had been diagnosed at 27, and Borsari had already lost her grandmother and two maternal uncles to the condition. After her own diagnosis, Borsari spent most of her free time researching the disease and “figuring out how to have this condition and still be the person I wanted to be,” she says.
Then, her son was found to have the genetic mutation at birth and diagnosed with HCM at 15. Her daughter, also diagnosed at birth, later suffered five cardiac arrests.
That changed Borsari’s perspective. She decided to become a patient advocate. “I didn’t want to just be a patient with the condition,” she says. “I wanted to be more involved with the science and the biopharmaceutical industry so I could be active in helping to make it better for other patients.”
She consulted on patient advocacy for a pharmaceutical and two foundations before coming to a company called Tenaya in 2021.
“One of our core values as a company is putting patients first,” says Tenaya's CEO, Faraz Ali. “We thought of no better way to put our money where our mouth is than by bringing in somebody who is affected and whose family is affected by a genetic form of cardiomyopathy to have them make sure we’re incorporating the voice of the patient.”
Biomedical corporations and government research agencies are now incorporating patient advocacy more than ever, says Alice Lara, president and CEO of the Sudden Arrhythmia Death Syndromes Foundation in Salt Lake City, Utah. These organizations have seen the effectiveness of including patient voices to communicate and exemplify the benefits that key academic research institutions have shown in their medical studies.
“From our side of the aisle,” Lara says, “what we know as patient advocacy organizations is that educated patients do a lot better. They have a better course in their therapy and their condition, and understanding the genetics is important because all of our conditions are genetic.”
Founded in 2016, Tenaya is advancing gene therapies and small molecule drugs in clinical trials for both prevalent and rare forms of heart disease, says Ali, the CEO.
The firm's first small molecule, now in a Phase 1 clinical trial, is intended to treat heart failure with preserved ejection fraction, where the amount of blood pumped by the heart is reduced due to the heart chambers becoming weak or stiff. The condition accounts for half or more of all heart failure in the U.S., according to Ali, and is growing quickly because it's closely associated with diabetes. It’s also linked with metabolic syndrome, or a cluster of conditions including high blood pressure, high blood sugar, excess body fat around the waist, and abnormal cholesterol levels.
“We have a novel molecule that is first in class and, to our knowledge, best in class to tackle that, so we’re very excited about the clinical trial,” Ali says.
The first phase of the trial is being performed with healthy participants, rather than people with the disease, to establish safety and tolerability. The researchers can also look for the drug in blood samples, which could tell them whether it's reaching its target. Ali estimates that, if the company can establish safety and that it engages the right parts of the body, it will likely begin dosing patients with the disease in 2024.
Tenaya’s therapy delivers a healthy copy of the gene so that it makes a copy of the protein missing from the patients' hearts because of their mutation. The study will start with adult patients, then pivot potentially to children and even newborns, Ali says, “where there is an even greater unmet need because the disease progresses so fast that they have no options.”
Although this work still has a long way to go, Ali is excited about the potential because the gene therapy achieved positive results in the preclinical mouse trial. This animal trial demonstrated that the treatment reduced enlarged hearts, reversed electrophysiological abnormalities, and improved the functioning of the heart by increasing the ejection fraction after the single-dose of gene therapy. That measurement remained stable to the end of the animals’ lives, roughly 18 months, Ali says.
He’s also energized by the fact that heart disease has “taken a page out of the oncology playbook” by leveraging genetic research to develop more precise and targeted drugs and gene therapies.
“Now we are talking about a potential cure of a disease for which there was no cure and using a very novel concept,” says Melind Desai of the Cleveland Clinic.
Tenaya’s second program focuses on developing a gene therapy to mitigate the leading cause of hypertrophic cardiomyopathy through a specific gene called MYPBC3. The disease affects approximately 600,000 patients in the U.S. This particular genetic form, Ali explains, affects about 115,000 in the U.S. alone, so it is considered a rare disease.
“There are infants who are dying within the first weeks to months of life as a result of this mutation,” he says. “There are also adults who start having symptoms in their 20s, 30s and 40s with early morbidity and mortality.” Tenaya plans to apply before the end of this year to get the FDA’s approval to administer an investigational drug for this disease humans. If approved, the company will begin to dose patients in 2023.
“We now understand the genetics of the heart much better,” he says. “We now understand the leading genetic causes of hypertrophic myopathy, dilated cardiomyopathy and others, so that gives us the ability to take these large populations and stratify them rationally into subpopulations.”
Melind Desai, MD, who directs Cleveland Clinic’s Hypertrophic Cardiomyopathy Center, says that the goal of Tenaya’s second clinical study is to help improve the basic cardiac structure in patients with hypertrophic cardiomyopathy related to the MYPBC3 mutation.
“Now we are talking about a potential cure of a disease for which there was no cure and using a very novel concept,” he says. “So this is an exciting new frontier of therapeutic investigation for MYPBC3 gene-positive patients with a chance for a cure.
Neither of Tenaya’s two therapies address the gene mutation that has affected Borsari and her family. But Ali sees opportunity down the road to develop a gene therapy for her particular gene mutation, since it is the second leading cause of cardiomyopathy. Treating the MYH7 gene is especially challenging because it requires gene editing or silencing, instead of just replacing the gene.
Wendy Borsari was diagnosed at age 24 with a commonly inherited heart disease. She joined Tenaya as a patient advocate in 2021.
Wendy Borsari
“If you add a healthy gene it will produce healthy copies,” Ali explains, “but it won’t stop the bad effects of the mutant protein the gene produces. You can only do that by silencing the gene or editing it out, which is a different, more complicated approach.”
Euan Ashley, professor of medicine and genetics at Stanford University and founding director of its Center for Inherited Cardiovascular Disease, is confident that we will see genetic therapies for heart disease within the next decade.
“We are at this really exciting moment in time where we have diseases that have been under-recognized and undervalued now being attacked by multiple companies with really modern tools,” says Ashley, author of The Genome Odyssey. “Gene therapies are unusual in the sense that they can reverse the cause of the disease, so we have the enticing possibility of actually reversing or maybe even curing these diseases.”
Although no one is doing extensive research into a gene therapy for her particular mutation yet, Borsari remains hopeful, knowing that companies such as Tenaya are moving in that direction.
“I know that’s now on the horizon,” she says. “It’s not just some pipe dream, but will happen hopefully in my lifetime or my kids’ lifetime to help them.”