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."
Talaris Therapeutics, Inc., a biotech company based in Louisville, Ky., is edging closer to eradicating the need for immunosuppressive drugs for kidney transplant patients.
In a series of research trials, Talaris is infusing patients with immune system stem cells from their kidney donor to create a donor-derived immune system that accepts the organ without the need for anti-rejection medications. That newly generated system does not attack other parts of the recipient’s body and also fights off infections and diseases as a healthy immune system would.
Talaris is now moving into the final clinical trial, phase III, before submitting for FDA approval. Known as Freedom-1, this trial has 17 sites open throughout the U.S., and Talaris will enroll a total of 120 kidney transplant recipients. One day after receiving their donor’s kidney, 80 people will undergo the company’s therapy, involving the donor’s stem cells and other critical cells that are processed at their facility. Forty will have a regular kidney transplant and remain on immunosuppression to provide a control group.
“The beauty of this procedure is that I don’t have to take all of the anti-rejection drugs,” says Robert Waddell, a finance professional. “I forget that I ever had any kidney issues. That’s how impactful it is.”
The procedure was pioneered decades ago by Suzanne Ildstad as a faculty member at the University of Pittsburgh before she became founding CEO of Talaris and then its Chief Scientific Officer. If approved by the FDA, the method could soon become the standard of care for patients in need of a kidney transplant.
“We are working to find a way to reprogram the immune system of transplant recipients so that it sees the donated organ as [belonging to one]self and doesn’t attack it,” explains Scott Requadt, CEO of Talaris. “That obviates the need for lifelong immunosuppression.”
Each year, there are roughly 20,000 kidney transplants, making kidneys the most transplanted organ. About 6,500 of those come from living donors, while deceased donors provide roughly 13,000.
One of the challenges, Requadt points out, is that kidney transplant recipients aren’t always aware of all the implications of immunosuppression. Typically, they will need to take about 20 anti-rejection drugs several times a day to provide immunosuppression as well as treat complications caused by the toxicities of immunosuppression medications. The side effects of chronic immunosuppression include weight gain, high blood pressure, and high cholesterol. These cardiovascular comorbidities, Requadt says, are “often more frequently the cause of death than failure of a transplanted organ.”
Patients who are chronically immunosuppressed generally have much higher rates of infections and cancers that have an immune component to them, such as skin cancers.
For the past couple of years, those patients have experienced heightened anxiety because of the COVID-19 pandemic. Immune-suppressing medicine used to protect their new organ also makes it hard for patients to build immunity to foreign invaders like COVID-19.
A study appearing in the Proceedings of the National Academy of Sciences found the probability of a pandemic with similar impact to COVID-19 is about 2 percent in any year, and estimated that the probability of novel disease outbreaks will grow three-fold in the next few decades. All the more reason to identify an FDA-approved alternative to harsh immunosuppressive drugs.
Of the 18 patients during the phase II research trial who received the Talaris therapy, didn’t take immunosuppression medication and were vaccinated, only two ended up with a COVID infection, according to a review of the data. Among patients who needed to continue taking immunosuppressants or those who didn’t have them but were unvaccinated, the rates of infection were between 40 and 60 percent.
In the earlier phase II study by Talaris with 37 patients, the combined transplantation approach allowed 70 percent of patients to get off all immunosuppression.
“We’ve followed that whole cohort for more than six and a half years and one of them for 12 years from transplant, and every single patient that we got off immunosuppression has been able to stay off,” Requadt says.
That one patient, Robert Waddell, 55, was especially thankful to be weaned off immunosuppressive drugs approximately one year after his transplant procedure. The Louisville resident had long watched his mother, sister and other family members with polycystic kidney disease, or PKD, suffer the effects of chronic immunosuppression. That became his greatest fear when he was diagnosed with end stage renal failure.
Waddell enrolled in the phase II research taking place in Louisville after learning about it in early 2006. He chose to remain in the study when it relocated its clinical headquarters to Northwestern University’s medical center in Chicago a couple years later.
Before surgery, he underwent an enervating regimen of chemotherapy and radiation. It’s required to clear out a patient’s bone marrow cells so that they can be replaced by the donor’s cells. Waddell says the result was worth it: he had his combined kidney and immune system stem cell transplant in May 2009, without any need for chronic immunosuppression.
“I call it ‘short-term pain, long-term gain,’ because it was difficult to go through the conditioning, but after that, it was great,” he says. “I’ve talked to so many kidney recipients who say, ‘I wish I would have done that,’ because most people don’t think about clinical trials, but I was very fortunate.”
Waddell has every reason to support the success of this research, especially given the genetic disorder, PKD, that has plagued his family. One of his four children has PKD. He is anxious for the procedure to become standard of care, if and when his son needs it.
The Talaris procedure was pioneered decades ago by Suzanne Ildstad, founding CEO of Talaris and the company's Chief Scientific Officer, pictured here with the current CEO, Scott Requadt.
Talaris
“The beauty of this procedure is that I don’t have to take all of the anti-rejection drugs,” says Waddell, a finance professional. “I forget that I ever had any kidney issues. That’s how impactful it is.”
Talaris will continue to follow Waddell and the rest of his cohort to track the effectiveness and safety of the procedure. According to Requadt, the average life of a transplanted kidney is 12 to 15 years, partly because the immunosuppressive drugs worsen the functioning of the organ each year.
“We were the first group to show that we could robustly and fairly reproducibly do this in a clinical setting in humans,” Requadt says. “Most important, we’ve been able to show that we can still get a good engraftment of the stem cells from the donor, even if there is a profound…mismatch between the donor and the recipient’s immune systems.”
In kidney transplantation, it’s important to match for human leukocyte antigens (HLA) because there is a better graft survival in HLA-identical kidney transplants compared with HLA mismatched transplants.
About three months after the transplant, Talaris researchers look for evidence that the donated immune cells and stem cells have engrafted, while making a donor immune system for the patient. If more than 50 percent of the T cells contain the donor’s DNA after six months, patients can start taking fewer immunosuppressants.
“We know from phase II that in our patients who were able to tolerize [accept the organ without rejection] to their donated organ, we saw completely preserved and in fact slightly increased kidney function,” Requadt says. “So, it stands to reason that if you eliminate the drugs that are associated with declining kidney function that you would preserve kidney function, so hopefully the patient will have that one kidney for life.”
Matthew Cooper, director of kidney and pancreas transplantation for MedStar Georgetown Transplant Institute in Washington, DC, states that, “Right now, the Achilles’ heel is we have such a long waiting list and few donors that people die every day waiting for a kidney transplant. Eventually, we will eliminate the organ shortage so that people won’t die from organ failure.”
Cooper, a nationally recognized clinical transplant surgeon for 20 years, says when he started his career, finding a way for patients to forgo immunosuppression was considered “the Holy Grail” of modern transplant medicine.
“Now that we’ve got the protocols in place and some personal examples of how that can happen, it’s pretty exciting to see that all coming together,” he adds.
Researchers advance drugs that treat pain without addiction
Opioids are one of the most common ways to treat pain. They can be effective but are also highly addictive, an issue that has fueled the ongoing opioid crisis. In 2020, an estimated 2.3 million Americans were dependent on prescription opioids.
Opioids bind to receptors at the end of nerve cells in the brain and body to prevent pain signals. In the process, they trigger endorphins, so the brain constantly craves more. There is a huge risk of addiction in patients using opioids for chronic long-term pain. Even patients using the drugs for acute short-term pain can become dependent on them.
Scientists have been looking for non-addictive drugs to target pain for over 30 years, but their attempts have been largely ineffective. “We desperately need alternatives for pain management,” says Stephen E. Nadeau, a professor of neurology at the University of Florida.
A “dimmer switch” for pain
Paul Blum is a professor of biological sciences at the University of Nebraska. He and his team at Neurocarrus have created a drug called N-001 for acute short-term pain. N-001 is made up of specially engineered bacterial proteins that target the body’s sensory neurons, which send pain signals to the brain. The proteins in N-001 turn down pain signals, but they’re too large to cross the blood-brain barrier, so they don’t trigger the release of endorphins. There is no chance of addiction.
When sensory neurons detect pain, they become overactive and send pain signals to the brain. “We wanted a way to tone down sensory neurons but not turn them off completely,” Blum reveals. The proteins in N-001 act “like a dimmer switch, and that's key because pain is sensation overstimulated.”
Blum spent six years developing the drug. He finally managed to identify two proteins that form what’s called a C2C complex that changes the structure of a subunit of axons, the parts of neurons that transmit electrical signals of pain. Changing the structure reduces pain signaling.
“It will be a long path to get to a successful clinical trial in humans," says Stephen E. Nadeau, professor of neurology at the University of Florida. "But it presents a very novel approach to pain reduction.”
Blum is currently focusing on pain after knee and ankle surgery. Typically, patients are treated with anesthetics for a short time after surgery. But anesthetics usually only last for 4 to 6 hours, and long-term use is toxic. For some, the pain subsides. Others continue to suffer after the anesthetics have worn off and start taking opioids.
N-001 numbs sensation. It lasts for up to 7 days, much longer than any anesthetic. “Our goal is to prolong the time before patients have to start opioids,” Blum says. “The hope is that they can switch from an anesthetic to our drug and thereby decrease the likelihood they're going to take the opioid in the first place.”
Their latest animal trial showed promising results. In mice, N-001 reduced pain-like behaviour by 90 percent compared to the control group. One dose became effective in two hours and lasted a week. A high dose had pain-relieving effects similar to an opioid.
Professor Stephen P. Cohen, director of pain operations at John Hopkins, believes the Neurocarrus approach has potential but highlights the need to go beyond animal testing. “While I think it's promising, it's an uphill battle,” he says. “They have shown some efficacy comparable to opioids, but animal studies don't translate well to people.”
Nadeau, the University of Florida neurologist, agrees. “It will be a long path to get to a successful clinical trial in humans. But it presents a very novel approach to pain reduction.”
Blum is now awaiting approval for phase I clinical trials for acute pain. He also hopes to start testing the drug's effect on chronic pain.
Learning from people who feel no pain
Like Blum, a pharmaceutical company called Vertex is focusing on treating acute pain after surgery. But they’re doing this in a different way, by targeting a sodium channel that plays a critical role in transmitting pain signals.
In 2004, Stephen Waxman, a neurology professor at Yale, led a search for genetic pain anomalies and found that biologically related people who felt no pain despite fractures, burns and even childbirth had mutations in the Nav1.7 sodium channel. Further studies in other families who experienced no pain showed similar mutations in the Nav1.8 sodium channel.
Scientists set out to modify these channels. Many unsuccessful efforts followed, but Vertex has now developed VX-548, a medicine to inhibit Nav1.8. Typically, sodium ions flow through sodium channels to generate rapid changes in voltage which create electrical pulses. When pain is detected, these pulses in the Nav1.8 channel transmit pain signals. VX-548 uses small molecules to inhibit the channel from opening. This blocks the flow of sodium ions and the pain signal. Because Nav1.8 operates only in peripheral nerves, located outside the brain, VX-548 can relieve pain without any risk of addiction.
"Frankly we need drugs for chronic pain more than acute pain," says Waxman.
The team just finished phase II clinical trials for patients following abdominoplasty surgery and bunionectomy surgery.
After abdominoplasty surgery, 76 patients were treated with a high dose of VX-548. Researchers then measured its effectiveness in reducing pain over 48 hours, using the SPID48 scale, in which higher scores are desirable. The score for Vertex’s drug was 110.5 compared to 72.7 in the placebo group, whereas the score for patients taking an opioid was 85.2. The study involving bunionectomy surgery showed positive results as well.
Waxman, who has been at the forefront of studies into Nav1.7 and Nav1.8, believes that Vertex's results are promising, though he highlights the need for further clinical trials.
“Blocking Nav1.8 is an attractive target,” he says. “[Vertex is] studying pain that is relatively simple and uniform, and that's key to having a drug trial that is informative. But the study needs to be replicated and frankly we need drugs for chronic pain more than acute pain. If this is borne out by additional studies, it's one important step in a journey.”
Vertex will be launching phase III trials later this year.
Finding just the right amount of Nerve Growth Factor
Whereas Neurocarrus and Vertex are targeting short-term pain, a company called Levicept is concentrating on relieving chronic osteoarthritis pain. Around 32.5 million Americans suffer from osteoarthritis. Patients commonly take NSAIDs, or non-steroidal anti-inflammatory drugs, but they cannot be taken long-term. Some take opioids but they aren't very effective.
Levicept’s drug, Levi-04, is designed to modify a signaling pathway associated with pain. Nerve Growth Factor (NGF) is a neurotrophin: it’s involved in nerve growth and function. NGF signals by attaching to receptors. In pain there are excess neurotrophins attaching to receptors and activating pain signals.
“What Levi-04 does is it returns the natural equilibrium of neurotrophins,” says Simon Westbrook, the CEO and founder of Levicept. It stabilizes excess neurotrophins so that the NGF pathway does not signal pain. Levi-04 isn't addictive since it works within joints and in nerves outside the brain.
Westbrook was initially involved in creating an anti-NGF molecule for Pfizer called Tanezumab. At first, Tanezumab seemed effective in clinical trials and other companies even started developing their own versions. However, a problem emerged. Tanezumab caused rapidly progressive osteoarthritis, or RPOA, in some patients because it completely removed NGF from the system. NGF is not just involved in pain signalling, it’s also involved in bone growth and maintenance.
Levicept has found a way to modify the NGF pathway without completely removing NGF. They have now finished a small-scale phase I trial mainly designed to test safety rather than efficacy. “We demonstrated that Levi-04 is safe and that it bound to its target, NGF,” says Westbrook. It has not caused RPOA.
Professor Philip Conaghan, director of the Leeds Institute of Rheumatic and Musculoskeletal Medicine, believes that Levi-04 has potential but urges the need for caution. “At this early stage of development, their molecule looks promising for osteoarthritis pain,” he says. “They will have to watch out for RPOA which is a potential problem.”
Westbrook starts phase II trials with 500 patients this summer to check for potential side effects and test the drug’s efficacy.
There is a real push to find an effective alternative to opioids. “We have a lot of work to do,” says Professor Waxman. “But I am confident that we will be able to develop new, much more effective pain therapies.”