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."
Meet Dr. Renee Wegrzyn, the first Director of President Biden's new health agency, ARPA-H
In today’s podcast episode, I talk with Renee Wegrzyn, appointed by President Biden as the first director of a health agency created last year, the Advanced Research Projects Agency for Health, or ARPA-H. It’s inspired by DARPA, the agency that develops innovations for the Defense department and has been credited with hatching world-changing technologies such as ARPANET, which became the internet.
Time will tell if ARPA-H will lead to similar achievements in the realm of health. That’s what President Biden and Congress expect in return for funding ARPA-H at 2.5 billion dollars over three years.
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How will the agency figure out which projects to take on, especially with so many patient advocates for different diseases demanding moonshot funding for rapid progress?
I talked with Dr. Wegrzyn about the opportunities and challenges, what lessons ARPA-H is borrowing from Operation Warp Speed, how she decided on the first ARPA-H project that was announced recently, why a separate agency was needed instead of reforming HHS and the National Institutes of Health to be better at innovation, and how ARPA-H will make progress on disease prevention in addition to treatments for cancer, Alzheimer’s and diabetes, among many other health priorities.
Dr. Wegrzyn’s resume leaves no doubt of her suitability for this role. She was a program manager at DARPA where she focused on applying gene editing and synthetic biology to the goal of improving biosecurity. For her work there, she received the Superior Public Service Medal and, in case that wasn’t enough ARPA experience, she also worked at another ARPA that leads advanced projects in intelligence, called I-ARPA. Before that, she ran technical teams in the private sector working on gene therapies and disease diagnostics, among other areas. She has been a vice president of business development at Gingko Bioworks and headed innovation at Concentric by Gingko. Her training and education includes a PhD and undergraduate degree in applied biology from the Georgia Institute of Technology and she did her postdoc as an Alexander von Humboldt Fellow in Heidelberg, Germany.
Dr. Wegrzyn told me that she’s “in the hot seat.” The pressure is on for ARPA-H especially after the need and potential for health innovation was spot lit by the pandemic and the unprecedented speed of vaccine development. We'll soon find out if ARPA-H can produce gamechangers in health that are equivalent to DARPA’s creation of the internet.
Show links:
ARPA-H - https://arpa-h.gov/
Dr. Wegrzyn profile - https://arpa-h.gov/people/renee-wegrzyn/
Dr. Wegrzyn Twitter - https://twitter.com/rwegrzyn?lang=en
President Biden Announces Dr. Wegrzyn's appointment - https://www.whitehouse.gov/briefing-room/statement...
Leaps.org coverage of ARPA-H - https://leaps.org/arpa/
ARPA-H program for joints to heal themselves - https://arpa-h.gov/news/nitro/ -
ARPA-H virtual talent search - https://arpa-h.gov/news/aco-talent-search/
Dr. Renee Wegrzyn was appointed director of ARPA-H last October.
Tiny, tough “water bears” may help bring new vaccines and medicines to sub-Saharan Africa
Microscopic tardigrades, widely considered to be some of the toughest animals on earth, can survive for decades without oxygen or water and are thought to have lived through a crash-landing on the moon. Also known as water bears, they survive by fully dehydrating and later rehydrating themselves – a feat only a few animals can accomplish. Now scientists are harnessing tardigrades’ talents to make medicines that can be dried and stored at ambient temperatures and later rehydrated for use—instead of being kept refrigerated or frozen.
Many biologics—pharmaceutical products made by using living cells or synthesized from biological sources—require refrigeration, which isn’t always available in many remote locales or places with unreliable electricity. These products include mRNA and other vaccines, monoclonal antibodies and immuno-therapies for cancer, rheumatoid arthritis and other conditions. Cooling is also needed for medicines for blood clotting disorders like hemophilia and for trauma patients.
Formulating biologics to withstand drying and hot temperatures has been the holy grail for pharmaceutical researchers for decades. It’s a hard feat to manage. “Biologic pharmaceuticals are highly efficacious, but many are inherently unstable,” says Thomas Boothby, assistant professor of molecular biology at University of Wyoming. Therefore, during storage and shipping, they must be refrigerated at 2 to 8 degrees Celsius (35 to 46 degrees Fahrenheit). Some must be frozen, typically at -20 degrees Celsius, but sometimes as low -90 degrees Celsius as was the case with the Pfizer Covid vaccine.
For Covid, fewer than 73 percent of the global population received even one dose. The need for refrigerated or frozen handling was partially to blame.
The costly cold chain
The logistics network that ensures those temperature requirements are met from production to administration is called the cold chain. This cold chain network is often unreliable or entirely lacking in remote, rural areas in developing nations that have malfunctioning electrical grids. “Almost all routine vaccines require a cold chain,” says Christopher Fox, senior vice president of formulations at the Access to Advanced Health Institute. But when the power goes out, so does refrigeration, putting refrigerated or frozen medical products at risk. Consequently, the mRNA vaccines developed for Covid-19 and other conditions, as well as more traditional vaccines for cholera, tetanus and other diseases, often can’t be delivered to the most remote parts of the world.
To understand the scope of the challenge, consider this: In the U.S., more than 984 million doses of Covid-19 vaccine have been distributed so far. Each one needed refrigeration that, even in the U.S., proved challenging. Now extrapolate to all vaccines and the entire world. For Covid, fewer than 73 percent of the global population received even one dose. The need for refrigerated or frozen handling was partially to blame.
Globally, the cold chain packaging market is valued at over $15 billion and is expected to exceed $60 billion by 2033.
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Freeze-drying, also called lyophilization, which is common for many vaccines, isn’t always an option. Many freeze-dried vaccines still need refrigeration, and even medicines approved for storage at ambient temperatures break down in the heat of sub-Saharan Africa. “Even in a freeze-dried state, biologics often will undergo partial rehydration and dehydration, which can be extremely damaging,” Boothby explains.
The cold chain is also very expensive to maintain. The global pharmaceutical cold chain packaging market is valued at more than $15 billion, and is expected to exceed $60 billion by 2033, according to a report by Future Market Insights. This cost is only expected to grow. According to the consulting company Accenture, the number of medicines that require the cold chain are expected to grow by 48 percent, compared to only 21 percent for non-cold-chain therapies.
Tardigrades to the rescue
Tardigrades are only about a millimeter long – with four legs and claws, and they lumber around like bears, thus their nickname – but could provide a big solution. “Tardigrades are unique in the animal kingdom, in that they’re able to survive a vast array of environmental insults,” says Boothby, the Wyoming professor. “They can be dried out, frozen, heated past the boiling point of water and irradiated at levels that are thousands of times more than you or I could survive.” So, his team is gradually unlocking tardigrades’ survival secrets and applying them to biologic pharmaceuticals to make them withstand both extreme heat and desiccation without losing efficacy.
Boothby’s team is focusing on blood clotting factor VIII, which, as the name implies, causes blood to clot. Currently, Boothby is concentrating on the so-called cytoplasmic abundant heat soluble (CAHS) protein family, which is found only in tardigrades, protecting them when they dry out. “We showed we can desiccate a biologic (blood clotting factor VIII, a key clotting component) in the presence of tardigrade proteins,” he says—without losing any of its effectiveness.
The researchers mixed the tardigrade protein with the blood clotting factor and then dried and rehydrated that substance six times without damaging the latter. This suggests that biologics protected with tardigrade proteins can withstand real-world fluctuations in humidity.
Furthermore, Boothby’s team found that when the blood clotting factor was dried and stabilized with tardigrade proteins, it retained its efficacy at temperatures as high as 95 degrees Celsius. That’s over 200 degrees Fahrenheit, much hotter than the 58 degrees Celsius that the World Meteorological Organization lists as the hottest recorded air temperature on earth. In contrast, without the protein, the blood clotting factor degraded significantly. The team published their findings in the journal Nature in March.
Although tardigrades rarely live more than 2.5 years, they have survived in a desiccated state for up to two decades, according to Animal Diversity Web. This suggests that tardigrades’ CAHS protein can protect biologic pharmaceuticals nearly indefinitely without refrigeration or freezing, which makes it significantly easier to deliver them in locations where refrigeration is unreliable or doesn’t exist.
The tricks of the tardigrades
Besides the CAHS proteins, tardigrades rely on a type of sugar called trehalose and some other protectants. So, rather than drying up, their cells solidify into rigid, glass-like structures. As that happens, viscosity between cells increases, thereby slowing their biological functions so much that they all but stop.
Now Boothby is combining CAHS D, one of the proteins in the CAHS family, with trehalose. He found that CAHS D and trehalose each protected proteins through repeated drying and rehydrating cycles. They also work synergistically, which means that together they might stabilize biologics under a variety of dry storage conditions.
“We’re finding the protective effect is not just additive but actually is synergistic,” he says. “We’re keen to see if something like that also holds true with different protein combinations.” If so, combinations could possibly protect against a variety of conditions.
Commercialization outlook
Before any stabilization technology for biologics can be commercialized, it first must be approved by the appropriate regulators. In the U.S., that’s the U.S. Food and Drug Administration. Developing a new formulation would require clinical testing and vast numbers of participants. So existing vaccines and biologics likely won’t be re-formulated for dry storage. “Many were developed decades ago,” says Fox. “They‘re not going to be reformulated into thermo-stable vaccines overnight,” if ever, he predicts.
Extending stability outside the cold chain, even for a few days, can have profound health, environmental and economic benefits.
Instead, this technology is most likely to be used for the new products and formulations that are just being created. New and improved vaccines will be the first to benefit. Good candidates include the plethora of mRNA vaccines, as well as biologic pharmaceuticals for neglected diseases that affect parts of the world where reliable cold chain is difficult to maintain, Boothby says. Some examples include new, more effective vaccines for malaria and for pathogenic Escherichia coli, which causes diarrhea.
Tallying up the benefits
Extending stability outside the cold chain, even for a few days, can have profound health, environmental and economic benefits. For instance, MenAfriVac, a meningitis vaccine (without tardigrade proteins) developed for sub-Saharan Africa, can be stored at up to 40 degrees Celsius for four days before administration. “If you have a few days where you don’t need to maintain the cold chain, it’s easier to transport vaccines to remote areas,” Fox says, where refrigeration does not exist or is not reliable.
Better health is an obvious benefit. MenAfriVac reduced suspected meningitis cases by 57 percent in the overall population and more than 99 percent among vaccinated individuals.
Lower healthcare costs are another benefit. One study done in Togo found that the cold chain-related costs increased the per dose vaccine price up to 11-fold. The ability to ship the vaccines using the usual cold chain, but transporting them at ambient temperatures for the final few days cut the cost in half.
There are environmental benefits, too, such as reducing fuel consumption and greenhouse gas emissions. Cold chain transports consume 20 percent more fuel than non-cold chain shipping, due to refrigeration equipment, according to the International Trade Administration.
A study by researchers at Johns Hopkins University compared the greenhouse gas emissions of the new, oral Vaxart COVID-19 vaccine (which doesn’t require refrigeration) with four intramuscular vaccines (which require refrigeration or freezing). While the Vaxart vaccine is still in clinical trials, the study found that “up to 82.25 million kilograms of CO2 could be averted by using oral vaccines in the U.S. alone.” That is akin to taking 17,700 vehicles out of service for one year.
Although tardigrades’ protective proteins won’t be a component of biologic pharmaceutics for several years, scientists are proving that this approach is viable. They are hopeful that a day will come when vaccines and biologics can be delivered anywhere in the world without needing refrigerators or freezers en route.