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."
When the COVID-19 pandemic began invading the world in late 2019, Peter Hotez and Maria Elena Bottazzi set out to create a low-cost vaccine that would help inoculate populations in low- and middle-income countries. The scientists, with their prior experience of developing inexpensive vaccines for the world’s poor, had anticipated that the global rollout of Covid-19 jabs would be marked with several inequities. They wanted to create a patent-free vaccine to bridge this gap, but the U.S. government did not seem impressed, forcing the researchers to turn to private philanthropies for funds.
Hotez and Bottazzi, both scientists at the Texas Children’s Hospital Center for Vaccine Development at Baylor College of Medicine, raised about $9 million in private funds. Meanwhile, the U.S. government’s contribution stood at $400,000.
“That was a very tough time early on in the pandemic, you know, trying to do the work and raise the money for it at the same time,” says Hotez, who was nominated in February for a Nobel Peace Prize with Bottazzi for their COVID-19 vaccine. He adds that at the beginning of the pandemic, governments emphasized speed, innovation and rapidly immunizing populations in North America and Europe with little consideration for poorer countries. “We knew this [vaccine] was going to be the answer to global vaccine inequality, but I just wish the policymakers had felt the same,” says Hotez.
Over the past two years, the world has witnessed 488 million COVID-19 infections and over 61 million deaths. Over 11 billion vaccine doses have been administered worldwide; however, the global rollout of COVID-19 vaccines is marked with alarming socio-economic inequities. For instance, 72 percent of the population in high-income countries has received at least one dose of the vaccine, whereas the number stands at 15 percent in low-income countries.
This inequity is worsening vulnerabilities across the world, says Lawrence Young, a virologist and co-lead of the Warwick Health Global Research Priority at the UK-based University of Warwick. “As long as the virus continues to spread and replicate, particularly in populations who are under-vaccinated, it will throw up new variants and these will remain a continual threat even to those countries with high rates of vaccination,” says Young, “Therefore, it is in all our interests to ensure that vaccines are distributed equitably across the world.”
“When your house is on fire, you don't call the patent attorney,” says Hotez. “We wanted to be the fire department.”
The vaccine developed by Hotez and Bottazzi recently received emergency use authorisation in India, which plans to manufacture 100 million doses every month. Dubbed ‘Corbevax’ by its Indian maker, Biological E Limited, the vaccine is now being administered in India to children aged 12-14. The patent-free arrangement means that other low- and middle-income countries could also produce and distribute the vaccine locally.
“When your house is on fire, you don't call the patent attorney, you call the fire department,” says Hotez, commenting on the intellectual property rights waiver. “We wanted to be the fire department.”
The Inequity
Vaccine equity simply means that all people, irrespective of their location, should have equal access to vaccines. However, data suggests that the global COVID-19 vaccine rollout has favoured those in richer countries. For instance, high-income countries like the UAE, Portugal, Chile, Singapore, Australia, Malta, Hong Kong and Canada have partially vaccinated over 85 percent of their populations. This percentage in poorer countries, meanwhile, is abysmally low – 2.1 percent in Yemen, 4.6 in South Sudan, 5 in Cameroon, 9.9 in Burkina Faso, 10 in Nigeria, 12 in Somalia, 12 in Congo, 13 in Afghanistan and 21 in Ethiopia.
In late 2019, scientists Peter Hotez and Maria Elena Bottazzi set out to create a low-cost vaccine that would help inoculate populations in low- and middle-income countries. In February, they were nominated for a Nobel Peace Prize.
Texas Children's Hospital
The COVID-19 vaccination coverage is particularly low in African countries, and according to Shabir Madhi, a vaccinologist at the University of the Witwatersrand, Johannesburg and co-director of African Local Initiative for Vaccinology Expertise, vaccine access and inequity remains a challenge in Africa. Madhi adds that a lack of vaccine access has affected the pandemic’s trajectory on the continent, but a majority of its people have now developed immunity through natural infection. “This has come at a high cost of loss of lives,” he says.
COVID-19 vaccines mean a significant financial burden for poorer countries, which spend an average of $41 per capita annually on health, while the average cost of every COVID-19 vaccine dose ranges between $2 and $40 in addition to a distribution cost of $3.70 per person for two doses. In December last year, the World Health Organisation (WHO) set a goal of immunizing 70 percent of the population of all countries by mid-2022. This, however, means that low-income countries would have to increase their health expenditure by an average of 56.6 percent to cover the cost, as opposed to 0.8 per cent in high-income countries.
Reflecting on the factors that have driven global inequity in COVID-19 vaccine distribution, Andrea Taylor, assistant director of programs at the Duke Global Health Innovation Center, says that wealthy nations took the risk of investing heavily in the development and scaling up of COVID-19 vaccines – at a time when there was little evidence to show that vaccines would work. This reserved a place for these nations at the front of the queue when doses started rolling off production lines. Lower-income countries, meanwhile, could not afford such investments.
“Now, however, global supply is not the issue,” says Taylor. “We are making plenty of doses to meet global need. The main problem is infrastructure to get the vaccine where it is most needed in a predictable and timely way and to ensure that countries have all the support they need to store, transport, and use the vaccine once it is received.”
Taufique Joarder, vice-chairperson of Bangladesh's Public Health Foundation, sees the need for more trials and data before Corbevax is made available to the general population.
In addition to global inequities in vaccination coverage, there are inequities within nations. Taufique Joarder, vice-chairperson of Bangladesh’s Public Health Foundation, points to the situation in his country, where vaccination coverage in rural and economically disadvantaged communities has suffered owing to weak vaccine-promotion initiatives and the difficulty many people face in registering online for jabs.
Joarder also cites the example of the COVID-19 immunization drive for children aged 12 years and above. “[Children] are given the Pfizer vaccine, which requires an ultralow temperature for storage. This is almost impossible to administer in many parts of the country, especially the rural areas. So, a large proportion of the children are being left out of vaccination,” says Joarder, adding that Corbevax, which is cheaper and requires regular temperature refrigeration “can be an excellent alternative to Pfizer for vaccinating rural children.”
Corbevax vs. mRNA Vaccines
As opposed to most other COVID-19 vaccines, which use the new Messenger RNA (mRNA) vaccine technology, Corbevax is an “old school” vaccine, says Hotez. The vaccine is made through microbial fermentation in yeast, similar to the process used to produce the recombinant hepatitis B vaccine, which has been administered to children in several countries for decades. Hence, says Hotez, the technology to produce Corbevax at large scales is already in place in countries like Vietnam, Bangladesh, India, Indonesia, Brazil, Argentina, among many others.
“So if you want to rapidly develop and produce and empower low- and middle-income countries, this is the technology to do it,” he says.
“Global access to high-quality vaccines will require serious investment in other types of COVID-19 vaccines," says Andrea Taylor.
The COVID-19 vaccines created by Pfizer-BioNTech and Moderna marked the first time that mRNA vaccine technology was approved for use. However, scientists like Young feel that there is “a need to be pragmatic and not seduced by new technologies when older, tried and tested approaches can also be effective.” Taylor, meanwhile, says that although mRNA vaccines have dominated the COVID-19 vaccine market in the U.S., “there is no clear grounding for this preference in the data we have so far.” She adds that there is also growing evidence that the immunity from these shots may not hold up as well over time as that of vaccines using different platforms.
“The mRNA vaccines are well suited to wealthy countries with sufficient ultra-cold storage and transportation infrastructure, but these vaccines are divas and do not travel well in the rest of the world,” says Taylor. “Global access to high-quality vaccines will require serious investment in other types of COVID-19 vaccines, such as the protein subunit platform used by Novavax and Corbevax. These require only standard refrigeration, can be manufactured using existing facilities all over the world, and are easy to transport.”
Joarder adds that Corbevax is cheaper due to the developers’ waived intellectual rights. It could also be used as a booster vaccine in Bangladesh, where only five per cent of the population has currently received booster doses. “If this vaccine is proved effective for heterologous boosting, [meaning] it works well and is well tolerated as a booster with other vaccines that are available in Bangladesh, this can be useful,” says Joarder.
According to Hotez, Corbevax can play several important roles - as a standalone adult or paediatric vaccine, and as a booster for other vaccines. Studies are underway to determine Corbevax’s effectiveness in these regards, he says.
Need for More Data
Biological E conducted two clinical trials involving 3000 subjects in India, and found Corbevax to be “safe and immunogenic,” with 90 percent effectiveness in preventing symptomatic infections from the original strain of COVID-19 and over 80 percent effectiveness against the Delta variant. The vaccine is currently in use in India, and according to Hotez, it’s in the pipeline at different stages in Indonesia, Bangladesh and Botswana.
However, Corbevax is yet to receive emergency use approval from the WHO. Experts such as Joarder see the need for more trials and data before it is made available to the general population. He says that while the WHO’s emergency approval is essential for global scale-up of the vaccine, we need data to determine age-stratified efficacy of the vaccine and whether it can be used for heterologous boosting with other vaccines. “According to the most recent data, the 100 percent circulating variant in Bangladesh is Omicron. We need to know how effective is Corbevax against the Omicron variant,” says Joarder.
Shabir Madhi, a vaccinologist at the University of the Witwatersrand, Johannesburg and co-director of the African Local Initiative for Vaccinology Expertise, says that a majority of people in Africa have now developed immunity through natural infection. “This has come at a high cost of loss of lives."
Shivan Parusnath
Others, meanwhile, believe that availing vaccines to poorer countries is not enough to resolve the inequity. Young, the Warwick virologist, says that the global vaccination rollout has also suffered from a degree of vaccine hesitancy, echoing similar observations by President Biden and Pfizer’s CEO. The problem can be blamed on poor communication about the benefits of vaccination. “The Corbevax vaccine [helps with the issues of] patent protection, vaccine storage and distribution, but governments need to ensure that their people are clearly informed.” Notably, however, some research has found higher vaccine willingness in lower-income countries than in the U.S.
Young also emphasized the importance of establishing local vaccination stations to improve access. For some countries, meanwhile, it may be too late. Speaking about the African continent, Madhi says that Corbevax has arrived following the peak of the crisis and won’t reverse the suffering and death that has transpired because of vaccine hoarding by high-income countries.
“The same goes for all the sudden donations from countries such as France - pretty much of little to no value when the pandemic is at its tail end,” says Madhi. “This, unfortunately, is a repeat of the swine flu pandemic in 2009, when vaccines only became available to Africa after the pandemic had very much subsided.”
One of the Netherlands’ most famous pieces of pop culture is “Soldier of Orange.” It’s the title of the country’s most celebrated war memoir, movie and epic stage musical, all of which detail the exploits of the nation’s resistance fighters during World War II.
Willem Johan Kolff was a member of the Dutch resistance, but he doesn’t rate a mention in the “Solider of Orange” canon. Yet his wartime toils in a rural backwater not only changed medicine, but the world.
Kolff had been a physician less than two years before Germany invaded the Netherlands in May 1940. He had been engaged in post-graduate studies at the University of Gronigen but withdrew because he refused to accommodate the demands of the Nazi occupiers. Kolff’s Jewish supervisor made an even starker choice: He committed suicide.
After his departure from the university, Kolff took a job managing a small hospital in Kampen. Located 50 miles from the heavily populated coastal region, the facility was far enough away from the prying eyes of Germans that not only could Kolff care for patients, he could hide fellow resistance fighters and even Jewish refugees in relative safety. Kolff coached many of them to feign convincing terminal illnesses so the Nazis would allow them to remain in the hospital.
Despite the demands of practicing medicine and resistance work, Kolff still found time to conduct research. He had been haunted and inspired when, not long before the Nazi invasion, one of his patients died in agony from kidney disease. Kolff wanted to find a way to save future patients.
He broke his problem down to a simple task: If he could remove 20 grams of urea from a patient’s blood in 24 hours, they would survive. He began experimenting with ways to filter blood and return it to a patient’s body. Since the war had ground all non-military manufacturing to a halt, he was mostly forced to make do with material he could find at the hospital and around Kampen. Kolff eventually built a device from a washing machine parts, juice cans, sausage casings, a valve from an old Ford automobile radiator, and even scrap from a downed German aircraft.
The world’s first dialysis machine was hardly imposing; it resembled a rotating drum for a bingo game or raffle. Yet it carried on the highly sophisticated task of moving a patient’s blood through a semi-permeable membrane (about a 50-foot length of sausage casings) into a saline solution that drew out urea while leaving the blood cells untouched.
In emigrating to the U.S. to practice medicine, Kolff's intent was twofold: Advocate for a wider adoption of dialysis, and work on new projects. He wildly succeeded at both.
Kolff began using the machine to treat patients in 1943, most of whom had lapsed into comas due to their kidney failure. But like most groundbreaking medical devices, it was not an immediate success. By the end of the war, Kolff had dialyzed more than a dozen patients, but all had died. He briefly suspended use of the device after the Allied invasion of Europe, but he continued to refine its operation and the administration of blood thinners to patients.
In September 1945, Kolff dialyzed another comatose patient, 67-year-old Sofia Maria Schafstadt. She regained consciousness after 11 hours, and would live well into the 1950s with Kolff’s assistance. Yet this triumph contained a dark irony: At the time of her treatment, Schafstadt had been imprisoned for collaborating with the Germans.
With a tattered Europe struggling to overcome the destruction of the war, Kolff and his family emigrated to the U.S. in 1950, where he began working for the Cleveland Clinic while undergoing the naturalization process so he could practice medicine in the U.S. His intent was twofold: Advocate for a wider adoption of dialysis, and work on new projects. He wildly succeeded at both.
By the mid-1950s, dialysis machines had become reliable and life-saving medical devices, and Kolff had become a U.S. citizen. About that time he invented a membrane oxygenator that could be used in heart bypass surgeries. This was a critical component of the heart-lung machine, which would make heart transplants possible and bypass surgeries routine. He also invented among the very first practical artificial hearts, which in 1957 kept a dog alive for 90 minutes.
Kolff moved to the University of Utah in 1967 to become director of its Institute for Biomedical Engineering. It was a promising time for such a move, as the first successful transplant of a donor heart to a human occurred that year. But he was interested in going a step further and creating an artificial heart for human use.
It took more than a decade of tinkering and research, but in 1982, a team of physicians and engineers led by Kolff succeeded in implanting the first artificial heart in dentist Barney Clark, whose failing health disqualified him from a heart transplant. Although Clark died in March 1983 after 112 days tethered to the device, that it kept him alive generated international headlines. While graduate student Robert Jarvik received the named credit for the heart, he was directly supervised by Kolff, whose various endeavors into artificial organ research at the University of Utah were segmented into numerous teams.
Forty years later, several artificial hearts have been approved for use by the Food and Drug Administration, although all are a “bridge” that allow patients to wait for a transplant.
Kolff continued researching and tinkering with biomedical devices – including artificial eyes and ears – until he retired in 1997 at the age of 86. When he died in 2009, the medical community acknowledged that he was not only a pioneer in biotechnology, but the “father” of artificial organs.