Tag Archives: Biomedical

Quantum Computing Makes Inroads Towards Pharma

Post Syndicated from Charles Q. Choi original https://spectrum.ieee.org/tech-talk/biomedical/diagnostics/quantum-drug

Theoretically, quantum computers theoretically can prove more powerful than any supercomputer. And recent moves from computer giants such as Google and pharmaceutical titans such as Roche now suggest drug discovery might prove to be quantum computing’s first killer app.

Whereas classical computers switch transistors either on or off to symbolize data as ones or zeroes, quantum computers use quantum bits, or qubits, that, because of the surreal nature of quantum physics, can be in a state of superposition where they are both 1 and 0 simultaneously.

Superposition lets one qubit essentially perform two calculations at once, and if two qubits are linked through a quantum effect known as entanglement, they can help perform 22 or four calculations simultaneously; three qubits, 23 or eight calculations; and so on. In theory, a quantum computer with 300 qubits could perform more calculations in an instant than there are atoms in the visible universe.

The Real Lesson of Sweden’s Laissez-Faire COVID-19 Response

Post Syndicated from Afzal S. Siddiqui original https://spectrum.ieee.org/tech-talk/biomedical/ethics/swedens-actual-covid-policy-herd-immunity

This is a guest post. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE.

The COVID-19 pandemic, now in its second year, has prompted a great deal of debate and reflection on the tension between personal civil liberties and the collective good. A surprising amount of this soul searching has offered up Sweden as either a shining example or a cautionary tale, depending on the viewpoint of the onlooker. 

In Europe, America, and elsewhere, politicians ostensibly arguing for individual liberty and economic growth have weighed in against mandates on business restrictions and the wearing of masks. Some scientists have also joined the fray. For example, Scott Atlas (former advisor on the White House Coronavirus Task Force) and Sunetra Gupta (co-author of the Great Barrington Declaration) favor looser measures in order to preserve civil liberties and to attain herd immunity as a byproduct. 

Sweden figures in all this because of its largely voluntary approach to quarantining and social distancing. Indeed, for much of 2020, Sweden’s strategy was spearheaded not by politicians but by a health official, Anders Tegnell, the state epidemiologist at the Public Health Agency of Sweden. In advocating for a light-touch approach, Tegnell noted in September 2020 that controlled spread of the virus over the population should provide Sweden with greater protection in the second wave vis-à-vis its Nordic neighbors, who opted for conventional strategies. Thus, the cost of a high death rate in the first wave would be more than offset by the benefit of a low death rate in the second wave. 

So, has this hypothesis been upheld? Were the voices championing individual liberties correct all along?

No. If they had been correct, then during the second half of 2020, excess mortality in Sweden—from all causes and not just COVID-19—should have ticked lower in comparison to that of the other Nordic countries. In fact, no such thing happened.

During weeks 46 to 52 of 2020, Sweden’s standardized excess mortality rates were persistently above the “normal range” (Figure 1, above). By contrast, all of Sweden’s Nordic neighbors combined had just three instances of excess mortality outside the “normal range” during weeks 36 to 52. In terms of actual COVID-19 deaths per million inhabitants, Sweden has done no better than the U.K. and the U.S. for much of the so-called second wave (Figure 2, below). Hence, the data for the final few months of 2020 contradict the individualists’ case.

Faced with such sobering statistics, champions of a hands-off approach should respond with humility. Yet, instead of adapting their hypothesis to fit the facts, they twist the numbers in order to suit their beliefs.

For example, Tegnell claimed in December 2020 that Sweden’s immigrants have been “driving” its higher death rate. However, on a national TV appearance, Tegnell provided no evidence to back up this statement. Others, too, have misleadingly cited Sweden’s relatively high percentage of foreign-born residents to make a case that Sweden did not fare too badly if you take into account the fact that the country has a higher proportion of more-vulnerable people than its immediate neighbors. In making this argument, though, some cited figures as high as 25 percent for Sweden’s foreign-born population. But, this 25 percent estimate includes not only the foreign born but also people born in Sweden to two foreign-born parents. In fact, just 13.9 percent of the Swedish population is born outside the EU, EEA, and U.K., according to Eurostat. This is a critical distinction because only immigrants from low-and-medium-income countries tend to have the kinds of jobs and lifestyles that make them more vulnerable to infection.

Furthermore, consider the Norrland region in northern Sweden. Immigrants from outside the EU/EEA/U.K. constitute 8.2 percent of its population, not far off the 6.6 percent share seen in the neighboring Nordic countries. Yet as of 29 November, Norrland had a COVID-19 death rate that was 4.8 times higher than the average in those Nordic countries. During the so-called second wave (weeks 45 to 48), the discrepancy was starker still: Norrland’s COVID-19 death rate then was over six times as high as the neighboring Nordic countries’ average. All of which suggests that policy—not demographics—explains the outcome.

Some on the right have long trotted out Sweden as a job-killing, high-tax nanny state. Although there was scant empirical evidence for such a caricature, it conveniently suited a particular worldview. Now, during the COVID-19 pandemic, some civil libertarians and others have serendipitously found Sweden’s laissez-faire public-health strategy amenable to their ideology and rushed to embrace it while again brushing aside other facts.

If these people insist on using Sweden as an exemplar when debating governance, then may I suggest that they take a look at the country’s environmental policy? At €110 per metric ton of COemitted, Sweden’s carbon tax is the highest in the world. More important, there is empirical evidence that the carbon tax has, indeed, reduced CO2 emissions from transportation. In this domain, Swedish authorities have long acknowledged the obvious: that laws and regulations do affect human behavior. They further recognize that polite entreaties to firms and households to curb CO2 emissions would not work. The reason for this ineffectiveness is that the cost that an individual consumer incurs for using fossil fuel is lower than the cost that society bears.

If you want people to behave in a way that reflects the full cost of their actions to society, then you must change incentives. This is true whether you are dealing with environmental policy or with a public-health crisis. In a world where data are widely available, evidence-based best practices and not ideology should inform public policy. Framing the discourse in any other way is disingenuous at best and a willful obfuscation at worst.

The author is a professor in the Department of Computer and Systems Sciences, Stockholm University, Sweden, and an Adjunct Professor in the Department of Mathematics and Systems Analysis, Aalto University, Finland.

This article was edited on 1 March, 2021, to more clearly describe Swedish immigration statistics and competing theories about their effect on COVID-19 infection rates.

Two Health Sensors Unite in One Powerful Gadget

Post Syndicated from Megan Scudellari original https://spectrum.ieee.org/the-human-os/biomedical/devices/two-health-sensors-unite-in-one-powerful-gadget

What’s not to love about a good flexible health sensor? Someday technology based on such bendable electronic tech might well replace some of those chunky wearables in the marketplace today with sleek, golden skin patches.

Now, a team at the UC San Diego Center for Wearable Sensors has created a stretchy skin patch that combines electrochemical sensors for alcohol, caffeine, glucose, and lactate with an ultrasound-based sensor that monitors blood pressure deep inside the body. Described in the journal Nature Biomedical Engineering, it’s the first wearable device that tracks heart signals and biochemical levels at the same time, the authors said.

“Conventionally, those two types of signals are monitored separately by different devices,” said study co-author Sheng Xu, a UCSD nanoengineer. “By bridging the gap between those two, we can get a more comprehensive view of what’s going on in the human body.”

Bionic muscles that are stronger, faster, and more efficient

Post Syndicated from Payal Dhar original https://spectrum.ieee.org/tech-talk/biomedical/bionics/nanotube-bionic-muscles-are-10-times-stronger

Artificial muscles, once a tangle of elaborate servomotors, and hydraulic and pneumatic actuators, is now a thing of shape-memory alloys and hair-thin carbon nanotube (CNT) fibers. Bionics are, in brief, getting smaller—though perhaps not simpler. 

Electrochemical CNT muscles are also energy efficient, and they provide larger muscle strokes as well. Recently, a group of researchers from the U.S., Australia, South Korea and China, working with polymer-coated CNT fibers twisted into yarn, have effectively demonstrated how these muscles can be  faster, more powerful and more energy efficient.

Electrochemically driven CNT muscles actuate when a voltage is passed between the muscle fiber and a counter-electrode, causing a movement of ions to and from the surrounding electrolyte and the muscle. Generally speaking, this results in the muscles either contracting or expanding, until the potential reaches zero charge—after which it changes direction. In other words, a bipolar muscle stroke ensues. The bipolar movement, however, results in a smaller muscle stroke, reducing the muscle’s efficiency. 

The research team devised a way to circumvent this limitation. “When we coated the internal surface of the yarns with about a nanometer thicknesses of special polymers, we could shift the potential of zero charge of the muscle to outside the [stability window of the electrolyte, a voltage range beyond which it breaks down],” says Ray Baughman, director of the Alan G. MacDiarmid NanoTech Institute, University of Texas at Dallas, one of the authors of the paper. 

These polymers are ionically conducting materials with either positively or negatively charged chemical groups. In other words, they can accept either positive (cations) or negative ions (anions). With the potential of zero charge outside the electrolyte’s stability window, only one kind of ion (either cations or anions) infiltrates the muscle, and the muscle actuates in a unipolar direction. 

In the lab, the researchers used a CNT yarn muscle with a counter-electrode that was non-actuating to demonstrate their concept. But Baughman says that this doesn’t have to be the case. They found that by using two different types of their polymer-coated carbon nanotube yarns—one with positive substituents and the other with negative—they could create a dual-electrode unipolar muscle. “You can use the mechanical work being done by each muscle [additively]… [by putting] an unlimited numbers of these muscles together.”

The team were also able to make a dual-electrode CNT yarn muscle with a solid-state electrolyte, eliminating the need for a liquid electrolyte bath. “These dual electrode, unipolar muscles were woven to make actuating textiles that could be used for morphing clothing,” said Zhong Wang, a doctoral student and co-author, in the press release.

The group’s electrochemical unipolar muscles generate an average mechanical power output that is 10 times the average capability of human muscles, and about 2.2 times the weight-normalized power capability of a turbocharged V-8 diesel engine.

As such, it has a wide range of applications—including robotics and adaptable clothing. Of the former example, Baughman says robotic motors can be heavy and difficult to coordinate in a device with broad freedom of movement. By contrast, the artificial muscles could power electric robotic exoskeletons, which, could enable a person to work in a warehouse and move heavy items around with ease. 

Clothing that could adjust according to comfort is another application, allowing wearers to change the porosity of textiles depending on the weather. Medical implants, like a heart assist apparatus, could also use compact and lightweight artificial muscles, as could prosthetics. We are [currently]… writing a proposal for doing studies that will actually involve patients,” Baughman adds. 

Before real-world applications become possible, the challenge is to produce cost-effective, high-quality carbon nanotube yarn at scale. Baughman and his team also hope to adapt the unipolar CNT muscles to make more powerful mechanical energy harvesters.

AI Predicts Asymptomatic Carriers of COVID-19

Post Syndicated from Emily Waltz original https://spectrum.ieee.org/the-human-os/biomedical/devices/ai-predicts-asymptomatic-carriers-of-covid19

One of COVID-19’s nastiest tricks is the way it can infect someone and not cause any symptoms. This allows the virus to proliferate under the radar of contact tracers. But new artificial intelligence could help track down these silent carriers. 

In a paper published Friday in the journal Scientific Reports, researchers at Synergies Intelligent Systems and Universität Hamburg describe a machine learning algorithm that can identify people in a moving crowd who are most likely asymptomatic carriers of the virus that causes COVID-19. The algorithm makes these predictions based on the GPS-tracked movement of people in a city environment, and known cases of infection. 

3D Printing Bone Directly Into the Body

Post Syndicated from Megan Scudellari original https://spectrum.ieee.org/the-human-os/biomedical/devices/3d-printing-bone-directly-into-the-body

3D printing living tissueincluding corneasblood vessels and skinis no easy task. But at least it’s all living tissue. Bone, by contrast, is a mixture of living and inorganic compounds in a highly structured mineral matrix. 

3D printing bone, in other words, is a challenge within a challenge.  

Which is why bioengineers have tried so many different materials for their synthetic bones—including hydrogels, thermoplastics, and bioceramics. Now, a team at the University of New South Wales in Sydney, Australia, has developed a ceramic ink that can be 3D-printed at room temperature with live cells and without harsh chemicals—a notable improvement over earlier technologies. The new technique could eventually be used to print bone directly into a patient’s body, the researchers say.

Brain Implants and Wearables Let Paralyzed People Move Again

Post Syndicated from Chad Bouton original https://spectrum.ieee.org/biomedical/bionics/brain-implants-and-wearables-let-paralyzed-people-move-again

In 2015, a group of neuroscientists and engineers assembled to watch a man play the video game Guitar Hero. He held the simplified guitar interface gingerly, using the fingers of his right hand to press down on the fret buttons and his left hand to hit the strum bar. What made this mundane bit of game play so extraordinary was the fact that the man had been paralyzed from the chest down for more than three years, without any use of his hands. Every time he moved his fingers to play a note, he was playing a song of restored autonomy.

His movements didn’t rely on the damaged spinal cord inside his body. Instead, he used a technology that we call a neural bypass to turn his intentions into actions. First, a brain implant picked up neural signals in his motor cortex, which were then rerouted to a computer running machine-learning algorithms that deciphered those signals; finally, electrodes wrapped around his forearm conveyed the instructions to his muscles. He used, essentially, a type of artificial nervous system.

We did that research at the Battelle Memorial Institute in Columbus, Ohio. I’ve since moved my lab to the Institute of Bioelectronic Medicine at the Feinstein Institutes for Medical Research, in Manhasset, N.Y. Bioelectronic medicine is a relatively new field, in which we use devices to read and modulate the electrical activity within the body’s nervous system, pioneering new treatments for patients. My group’s particular quest is to crack the neural codes related to movement and sensation so we can develop new ways to treat the millions of people around the world who are living with paralysis—5.4 million people in the United States alone. To do this we first need to understand how electrical signals from neurons in the brain relate to actions by the body; then we need to “speak” the language correctly and modulate the appropriate neural pathways to restore movement and the sense of touch. After working on this problem for more than 20 years, I feel that we’ve just begun to understand some key parts of this mysterious code.

My team, which includes electrical engineer Nikunj Bhagat, neuroscientist Santosh Chandrasekaran, and clinical manager Richard Ramdeo, is using that information to build two different kinds of synthetic nervous systems. One approach uses brain implants for high-fidelity control of paralyzed limbs. The other employs noninvasive wearable technology that provides less precise control, but has the benefit of not requiring brain surgery. That wearable technology could also be rolled out to patients relatively soon.

Ian Burkhart, the participant in the Guitar Hero experiment, was paralyzed in 2010 when he dove into an ocean wave and was pushed headfirst into a sandbar. The impact fractured several vertebrae in his neck and damaged his spinal cord, leaving him paralyzed from the middle of his chest down. His injury blocks electrical signals generated by his brain from traveling down his nerves to trigger actions by his muscles. During his participation in our study, technology replaced that lost function. His triumphs—which also included swiping a credit card and pouring water from a bottle into a glass—were among the first times a paralyzed person had successfully controlled his own muscles using a brain implant. And they pointed to two ways forward for our research.

The system Burkhart used was experimental, and when the study ended, so did his new autonomy. We set out to change that. In one thrust of our research, we’re developing noninvasive wearable technology, which doesn’t require a brain implant and could therefore be adopted by the paralyzed community fairly quickly. As I’ll describe later in this article, tetraplegic people are already using this system to reach out and grasp a variety of objects. We are working to commercialize this noninvasive technology and hope to gain clearance from the U.S. Food and Drug Administration within the next year. That’s our short-term goal.

We’re also working toward a long-term vision of a bidirectional neural bypass, which will use brain implants to pick up the signals close to the source and to return feedback from sensors we’ll place on the limb. We hope this two-way system will restore both motion and sensation, and we’ve embarked on a clinical trial to test this approach. We want people like Burkhart to feel the guitar as they make music with their paralyzed hands.

Paralysis used to be considered a permanent condition. But in the past two decades, there’s been remarkable progress in reading neural signals from the brain and using electrical stimulation to power paralyzed muscles.

In the early 2000s, the BrainGate consortium began groundbreaking work with brain implants that picked up signals from the motor region of the brain, using those signals to control various machines. I had the privilege of working with the consortium during the early years and developed machine-learning algorithms to decipher the neural code. In 2007, those algorithms helped a woman who was paralyzed due to a stroke drive a wheelchair with her thoughts. By 2012, the team had enabled a paralyzed woman to use a robotic arm to pick up a bottle. Meanwhile, other researchers were using implanted electrodes to stimulate the spinal cord, enabling people with paralyzed legs to stand up and even walk.

My research group has continued to tackle both sides of the problem: reading the signals from the brain as well as stimulating the muscles, with a focus on the hands. Around the time that I was working with the BrainGate team, I remember seeing a survey that asked people with spinal cord injuries about their top priorities. Tetraplegics—that is, people with paralysis of all four limbs—responded that their highest priority was regaining function in their arms and hands.

Robotics has partially filled that need. One commercially available robotic arm can be operated with wheelchair controls, and studies have explored controlling robotic arms through brain implants or scalp electrodes. But some people still long to use their own arms. When Burkhart spoke to the press in 2016, he said that he’d rather not have a robotic arm mounted on his wheelchair, because he felt it would draw too much attention. Unobtrusive technology to control his own arm would allow him “to function almost as a normal member of society,” he said, “and not be treated as a cyborg.”

Restoring movement in the hands is a daunting challenge. The human hand has more than 20 degrees of freedom, or ways in which it can move and rotate—that’s many more than the leg. That means there are many more muscles to stimulate, which creates a highly complex control-systems problem. And we don’t yet completely understand how all of the hand’s intricate movements are encoded in the brain. Despite these challenges, my group set out to give tetraplegics back their hands.

Burkhart’s implant was in his brain’s motor cortex, in a region that controls hand movements. Researchers have extensively mapped the motor cortex, so there’s plenty of information about how general neuronal activity there correlates with movements of the hand as a whole, and each finger individually. But the amount of data coming off the implant’s 96 electrodes was formidable: Each one measured activity 30,000 times per second. In this torrent of data, we had to find the discrete signals that meant “flex the thumb” or “extend the index finger.”

To decode the signals, we used a combination of artificial intelligence and human perseverance. Our stalwart volunteer attended up to three sessions weekly for 15 weeks to train the system. In each session, Burkhart would watch an animated hand on a computer screen move and flex its fingers, and he’d imagine making the same movements while the implant recorded his neurons’ activity. Over time, a machine-learning algorithm figured out which pattern of activity corresponded to the flexing of a thumb, the extension of an index finger, and so on.

Once our neural-bypass system understood the signals, it could generate a pattern of electrical pulses for the muscles of Burkhart’s forearm, in theory mimicking the pulses that the brain would send down an undamaged spinal cord and through the nerves. But in reality, translating Burkhart’s intentions to muscle movements required another intense round of training and calibration. We spent countless hours stimulating different sets of the 130 electrodes wrapped around his forearm to determine how to control the muscles of his wrist, hand, and each finger. But we couldn’t duplicate all of the movements the hand can make, and we never quite got control of the pinkie! We knew we had to develop something better.

To make a more practical and convenient system, we decided to develop a version that is completely noninvasive, which we call GlidePath. We recruited volunteers who have spinal cord injuries but still have some mobility in their shoulders. We placed a proprietary mix of inertial and biometric sensors on the volunteers’ arms, and asked them to imagine reaching for different objects. The data from the sensors fed into a machine-learning algorithm, enabling us to infer the volunteers’ grasping intentions. Flexible electrodes on their forearms then stimulated their muscles in a particular sequence. In one session, volunteer Casey Ellin used this wearable bypass to pick up a granola bar from a table and bring it to his mouth to take a bite. We published these results in 2020 in the journal Bioelectronic Medicine.

My team is working to integrate the sensors and the stimulators into lightweight and inconspicuous wearables; we’re also developing an app that will be paired with the wearable, so that clinicians can check and adjust the stimulation settings. This setup will allow for remote rehabilitation sessions, because the data from the app will be uploaded to the cloud.

To speed up the process of calibrating the stimulation patterns, we’re building a database of how the patterns map to hand movements, with the help of both able-bodied and paralyzed volunteers. While each person responds differently to stimulation, there are enough similarities to train our system. It’s analogous to Amazon’s Alexa voice assistant, which is trained on thousands of voices and comes out of the box ready to go—but which over time further refines its understanding of its specific users’ speech patterns. Our wearables will likewise be ready to go immediately, offering basic functions like opening and closing the hand. But they’ll continue to learn about their users’ intentions over time, helping with the movements that are most important to each user.

We think this technology can help people with spinal cord injuries as well as people recovering from strokes, and we’re collaborating with Good Shepherd Rehabilitation Hospital and the Barrow Neurological Institute to test our technology. Stroke patients commonly receive neuromuscular electrical stimulation, to assist with voluntary movements and help recover motor function. There’s considerable evidence that such rehab works better when a patient actively tries to make a movement while electrodes stimulate the proper muscles; that connected effort by brain and muscles has been shown to increase “plasticity,” or the ability of the nervous system to adapt to damage. Our system will ensure that the patient is fully engaged, as the stimulation will be triggered by the patient’s intention. We plan to collect data over time, and we hope to see patients eventually regain some function even when the technology is turned off.

As exciting as the wearable applications are, today’s noninvasive technology doesn’t readily control complex finger movements, at least initially. We don’t expect the GlidePath technology to immediately enable people to play Guitar Hero, much less a real guitar. So we’ve continued to work on a neural bypass that involves brain implants.

When Burkhart used the earlier version of the neural bypass, he told us that it offered a huge step toward independence. But there were a lot of practical things we hadn’t considered. He told us, “It is strange to not feel the object I’m holding.” Daily tasks like buttoning a shirt require such sensory feedback. We decided then to work on a two-way neural bypass, which conveyed movement commands from the brain to the hand and sent sensory feedback from the hand to the brain, skipping over the damaged spinal cord in both directions.

To give people sensation from their paralyzed hands, we knew that we’d need both finely tuned sensors on the hand and an implant in the sensory cortex region of the brain. For the sensors, we started by thinking about how human skin sends feedback to the brain. When you pick something up—say, a disposable cup filled with coffee—the pressure compresses the underlying layers of skin. Your skin moves, stretches, and deforms as you lift the cup. The thin-film sensors we developed can detect the pressure of the cup against the skin, as well as the shear (transverse) force exerted on the skin as you lift the cup and gravity pulls it down. This delicate feedback is crucial, because there’s a very narrow range of appropriate movement in that circumstance; if you squeeze the cup too tightly, you’ll end up with hot coffee all over you.

Each of our sensors has different zones that detect the slightest pressure or shear force. By aggregating the measurements, our system determines exactly how the skin is bending or stretching. The processor will send that information to the implants in the sensory cortex, enabling a user to feel the cup in their hand and adjust their grip as needed.

Figuring out exactly where to stimulate the sensory cortex was another challenge. The part of the sensory cortex that receives input from the hand hasn’t been mapped exhaustively via electrodes, in part because the regions dealing with the fingertips are tucked into a groove in the brain called the central sulcus. To fill in this blank spot on the map, we worked with our neurosurgeon colleagues Ashesh Mehta and Stephan Bickel, along with hospitalized epilepsy patients who underwent procedures to map their seizure activity. Depth electrodes were used to stimulate areas within that groove, and patients were asked where they felt sensation. We were able to elicit sensation in very specific parts of the hand, including the crucial fingertips.

That knowledge prepared us for the clinical trial that marks the next step in our research. We’re currently enrolling volunteers with tetraplegia for the study, in which the neurosurgeons on our team will implant three arrays of electrodes in the sensory cortex and two in the motor cortex. Stimulating the sensory cortex will likely bring new challenges for the decoding algorithms that interpret the neural signals in the motor cortex, which is right next door to the sensory cortex—there will certainly be some changes to the electrical signals we pick up, and we’ll have to learn to compensate for them.

In the study, we’ve added one other twist. In addition to stimulating the forearm muscles and the sensory cortex, we’re also going to stimulate the spinal cord. Our reasoning is as follows: In the spinal cord, there are 10 million neurons in complex networks. Earlier research has shown that these neurons have some ability to temporarily direct the body’s movements even in the absence of commands from the brain. We’ll have our volunteers concentrate on an intended movement, to physically make the motion with the help of electrodes on the forearm, and receive feedback from the sensors on the hand. If we stimulate the spinal cord while this process is going on, we believe we can promote plasticity within its networks, strengthening connections between neurons within the spinal cord that are involved in the hand’s movements. It’s possible that we’ll achieve a restorative effect that lasts beyond the duration of the study: Our dream is to give people with damaged spinal cords their hands back.

One day, we hope that brain implants for people with paralysis will be clinically proven and approved for use, enabling them to go well beyond playing Guitar Hero. We’d like to see them making complex movements with their hands, such as tying their shoes, typing on a keyboard, and playing scales on a piano. We aim to let these people reach out to clasp hands with their loved ones and feel their touch in return. We want to restore movement, sensation, and ultimately their independence.

This article appears in the February 2021 print issue as “Bypassing Paralysis.”

About the Author

Chad Bouton is vice president of advanced engineering at the Feinstein Institutes for Medical Research at Northwell Health, a health care network in New York.

Paper Cards and Digital Codes Target Vaccination Chaos

Post Syndicated from Jeremy Hsu original https://spectrum.ieee.org/tech-talk/biomedical/devices/paper-cards-and-digital-codes-target-vaccination-chaos

Other than Israel and the United Arab Emirates, the COVID-19 vaccine rollout around the world has had a rocky start. Some like Canada and the European Union have suffered stumbles so far. Others like the United States have been in a state of chaos since the vaccines were first approved at the end of last year. Many in the U.S. have scrambled online for ephemeral appointment slots, while pharmacies desperately look to use up leftover doses before they expire.

One low-tech solution may help: An MIT-led coalition has unveiled an augmented vaccination card that works with or without user apps to help enable a much smoother vaccination process for everyone.

The simplest form of the vaccination card would include QR codes that can be applied as stickers to existing cards already distributed by the U.S. Centers for Disease Control. Such codes would contain encrypted digital information necessary for each stage of a person’s vaccination process that can be scanned by the relevant authorities to check the person’s status—but would also avoid storing personally identifiable information in central databases in an effort to respect individual privacy.

“We should start sending these unique vaccination cards to everybody right now, like a mail-in ballot or census form,” said Ramesh Raskar, an associate professor of media arts and sciences at the MIT Media Lab.

As COVID-19 Mutates, AI Algorithms Keep Pace

Post Syndicated from Emily Waltz original https://spectrum.ieee.org/the-human-os/biomedical/devices/ai-predicts-most-potent-covid-19-mutations

As new variants of the coronavirus continue to spring up like wildfires across the planet, researchers have been frantically trying to determine which new strains might outwit our brand new vaccines. 

Artificial intelligence (AI) may be able to help. In a paper published Friday in the journal Science, researchers at MIT described a machine learning algorithm that can predict which mutations pose the biggest threat to the world’s fledgling immunity.

The tool could be used to quickly narrow down which mutations are most likely to evade the immune systems of people who have been vaccinated or previously infected. Researchers can then test suspected strains in the lab and update vaccines accordingly. 

“This is a real-time companion to vaccine development,” says Bryan Bryson, a biological engineer at MIT and co-author of the paper. “What we can do with our model right now is a lot faster than what you can do in the lab.” 

Wearables Provide Speedy COVID Screening

Post Syndicated from Megan Scudellari original https://spectrum.ieee.org/the-human-os/biomedical/diagnostics/wearables-provide-speedy-covid-screening

There’s a new player in the effort to quickly and effectively screen populations for COVID-19: This week, a Princeton spin-off company launches a coronavirus-screening app for businesses that takes two minutes and uses data from commercial wearable devices.

In early clinical tests, the tool was 90% accurate in predicting if a person was positive or negative for the virus—even if they had no noticeable symptoms. Current rapid diagnostic tools, such as temperature checks, are not effective at detecting and preventing the spread of COVID, according to federal authorities.

More Genetic Sequencing Needed To Keep Pace With Coronavirus Mutations

Post Syndicated from Emily Waltz original https://spectrum.ieee.org/the-human-os/biomedical/devices/variant-coronavirus-vaccines

IEEE COVID-19 coverage logo, link to landing page

As new, more contagious variants of the coronavirus surge across the planet, public health officials are scrambling to increase genetic sequencing of positive samples. Sequencing is crucial in understanding how the virus is changing, and determining whether our brand new vaccines will remain effective, officials say.

“Imagine if we didn’t have this genetic data,” says Richard Neher, a professor at the University of Basel who studies the genetic evolution of viruses. “We would see a surge in cases without having any idea what might have changed.”

The new variants emerged over the last few months, one out of the United Kingdom and the other out of South Africa. The variant that arose in the UK, dubbed B.1.1.7, correlated with a huge surge in cases there, and has now reportedly been detected in at least 33 countries.  

While the variants are likely more contagious, there is no evidence suggesting that they are more deadly or cause more severe disease. Many experts also say that the COVID-19 vaccines that have already been developed will still be effective against the new variants. Still, global surveillance of the virus’s genetic sequence is needed to stay on top of the virus’s continual adaptations, and plan a vaccine response.

What are viral variants?   

Viruses, including SARS-CoV-2 (the coronavirus that causes COVID-19), are constantly mutating. As they move from person to person, their genetic code changes slightly. Most of these mutations are inconsequential, producing no meaningful changes to the structure or function of the virus. 

As a virus moves through populations of people, it begins to accumulate enough mutations to lead researchers to call it a “variant” and give it a name. Many variants of the coronavirus have already been recognized.

Sometimes multiple mutations occur quickly, as was the case with the B.1.1.7 variant in the UK. Neher, who helps track the genetic changes in viruses using the software tool Nextstrain, estimates that B.1.1.7 is about 30-35 mutations away from the original strain detected in Wuhan, China at the beginning of the pandemic. Between 10 and 17 of those mutations appeared suddenly, compared with the virus’s most recent ancestor. 

Many of B.1.1.7’s mutations occur in areas of the genome that code for elements of the virus’s spike protein. That’s important, because the virus’s spike protein is what it uses to enter human cells. It’s also what our immune systems will recognize when attacking the virus.

Will approved vaccines work against the new variants? 

The more the spike protein changes, the harder it is for the immune systems of people who have been vaccinated to mount a swift attack. The same goes for people who have already had COVID-19—their immune systems know the spike protein of the older variants.

But it takes a lot of genetic changes to the spike protein before it can evade our complex immune systems. “The spike protein is a large protein,” says Neher. “It’s not like a single mutation there would change the virus in a way that it can re-infect everybody on the planet. It’s a more of gradual process where some mutations might reduce efficacy of the immune response in some fraction of the population.”

The section of the genome that codes for the spike protein is about 3,800 nucleotides, or units, long. So even with a dozen mutations, “for all intents and purposes, it’s the same protein,” says Neher.  

Many experts, including those at the U.S. Centers for Disease Control and Prevention (CDC) and the U.S. National institute of Allergy and Infectious Diseases, have stated publicly that our current vaccines will most likely be effective against the latest variants. 

The mutations are “unlikely to have a large impact on vaccine-induced immunity or on existing immunity” from previous infection, said Greg Armstrong, director of the advanced molecular detection program at the CDC, in a media briefing last week

If the variants do start to evade immune systems of vaccinated people, vaccines can be altered to mimic the new variants. mRNA-based vaccines, such as those developed by Moderna and Pfizer/BioNTech, can be adjusted relatively quickly. 

Public health experts push for more genetic sequencing

But to be sure, the public health community will have to keep a close eye on the variants, as well as the virus’s future adaptions, which will undoubtedly occur. To that end, experts are calling for larger, more coordinated genetic sequencing and epidemiological surveillance.  

In a statement posted December 31, the World Health Organization (WHO) advised the world to “increase routine systematic sequencing of SARS-CoV-2 viruses to better understand SARS-CoV-2 transmission and to monitor for the emergence of variants. 

That type of work is not new. Since the earliest weeks of the pandemic, scientists and public health experts globally have been sequencing positive samples and uploading them into public databases such as GISAID. More than 326,000 genomes have been submitted to that database alone—an unprecedented effort, compared with other pathogens. 

Still, more is needed. On December 29, the CDC said that the U.S. had about 51,000 sequences in its public databases, noting that the UK had more than twice that many. The CDC now aims to scale up to 3,500 whole genome sequences per week, according to Armstrong at the CDC. 

To do that, the agency in November launched the National SARS-CoV-2 Strain Surveillance (NS3) program, and asked each U.S. state to send at least ten samples biweekly for sequencing. The agency is also funding and working with national reference labs and local academic centers to increase sequencing.

Armstrong’s division has also been working since 2014 to integrate next-generation sequencing and bioinformatics expertise into state and local health departments. It increased funding for that in December. The effort includes training people to use portable, desktop genetic sequencers such as Oxford Nanopore’s MinION and Illumina’s MiniSeq.

Can AI Lead to Pregnancy?

Post Syndicated from Brian Horowitz original https://spectrum.ieee.org/tech-talk/biomedical/diagnostics/how-ai-is-transforming-assisted-reproductive-technology

Artificial intelligence in healthcare is often a story of percentages. One 2017 study predicted AI could broadly improve patient outcomes by 30 to 40 percent. Which makes a manifold improvement in results particularly noteworthy. 

In this case, according to one Israeli machine learning startup, AI has the potential to boost the success rate of in vitro fertilization (IVF) by as much as 3x compared to traditional methods. In other words, at least according to these results, couples struggling to conceive that use the right AI system could be multiple times more likely to get pregnant.

The Centers for Disease Control and Prevention defines assisted reproductive technology (ART) as the process of removing eggs from a woman’s ovaries, fertilizing it with sperm and then implanting it back in the body.

The overall success rate of traditional ART is less than 30%, according to a recent study in the journal Acta Informatica Medica

But, says Daniella Gilboa, CEO of Tel Aviv, Israel-based AiVF—which provides an automated framework for fertility and IVF treatment—help may be on the way. (However, she also cautions against simply multiplying 3x with the 30% traditional ART success rate quoted above. “Since pregnancy is very much dependent on age and other factors, simple multiplication is not the way to compare the two methods,” Gilboa says.)

In the U.S. alone, 7.3 million women are battling infertility, according to a 2020 report from the American Society for Reproductive Medicine. In the U.S., 2.7 million IVF cycles are performed each year. 

AiVF is using ML and computer vision technology to allow embryologists to discover which embryos have the most potential for success during intrauterine implantation. AiVF is working with eight facilities in clinical trials around the world, including in Israel, Europe and the United States. It plans to launch commercially in 2021.

Ron Maor, head of algorithm research at AiVF, says that AiVF has built its own “bespoke” layer on top of various off-the-shelf AI, ML and deep learning applications. These tools “handle the specific and often unusual aspects of embryo images, which are very different from most AI tasks,” Maor says. 

AiVF’s ML technique involves creating time-lapse videos of developing embryos in an incubator. Over five days, the video shows the milestones of embryo development. Gilboa explains that previous methods yielded just one microscope image per day of the embryo compared with computer vision’s greater image-capturing success.

“By analyzing the video, you could dig out so many milestones and so many features the human eye cannot even detect,” Gilboa says. “Basically you train an algorithm on successful embryos, and you teach the algorithm what are successful embryos.”  

Likely only one embryo out of 10 can be implanted in the uterus. Once a physician implants the embryo, the embryologist will know within 14 days whether the patient is pregnant, Gilboa says. 

“As an embryologist I look at embryos, and I understand what happens to them,” Gilboa says. “If I learn on maybe thousands of embryos, the algorithm would learn on millions of embryos.”

As AiVF’s initial results suggest, computer vision and ML could potentially drive IVF’s prices down—in turn making it less expensive and burdensome for a woman to become pregnant. 

“Once you have a digital embryologist, then you could set up clinics much easier,” Gilboa says. “Or each clinic could be much more scalable. So many more people could enjoy IVF and achieve their dream of having a child.”

Don’t be Too Quick to Judge Sweden’s Covid-19 Policy

Post Syndicated from Vaclav Smil original https://spectrum.ieee.org/biomedical/ethics/dont-be-too-quick-to-judge-swedens-covid19-policy

In 2008, I concluded that the next major pandemic would arrive before 2021. The very year after this forecast saw a minor event—involving the H1N1 influenza virus—but the 2019 pandemic obviously qualifies as a major global outbreak.

This was no remarkable feat of forecasting, just a simple recognition that pandemics reappear rather frequently. A regrettable corollary is that we remain repeatedly unprepared for their spread and that we mismanage our responses on truly grand scales. But this does not prevent people from making simplistic judgments.

Sweden’s response to the COVID-19 virus is a perfect example of this habit. The response has not been decided by politicians, it has not involved major adjustments, and all key decisions have been left to the state epidemiologist, Anders Tegnell, who has relied on appealing to his compatriots to behave responsibly.

Even in Sweden, his approach has not remained unchallenged, but abroad it has elicited two remarkably divergent criticisms. Some say, “They did not resort to any panicky lockdowns, and they are none the worse for it,” while others say, “They did not lock down anything, and the consequences have been catastrophic.” Neither statement is true, but even an interim appraisal, made in November 2020, shows an outcome that is as singular as it is a part of a larger piece.

To begin with, Sweden shut down high schools and universities, but not grade schools and kindergartens; it restricted very large gatherings, allowed restaurants, shops, and services to remain open, while leaving to the individual the responsibility of limiting smaller gatherings. The early consequence of these decisions seemed severe: Excess mortality began to rise steeply in late March, and in April it reached levels far higher than in any of the country’s immediate Nordic neighbors. But by midsummer, cumulative mortalities divided by the size of the population were considerably lower in Sweden than in several populous European nations. By the middle of November, cumulative death rates were twice as high in Belgium, 45 percent higher in Spain, 25 percent higher in the United States, United Kingdom, and Italy (the country with extensive restrictive lockdowns) and 12 percent higher in France. On the other hand, the mortality rate in Finland and ­Norway was only about 10 percent that of Sweden, and Denmark’s rate was about 80 percent lower.

There is no doubt that Sweden’s numbers were inflated, in part, by the relatively high share in its population of the foreign born (who are more vulnerable to infection)—a quarter of the people are immigrants, and nearly a third have at least one parent born abroad. Similarly, comparisons of excess all-cause mortality (a rate that is better able to capture the actual death toll attributable to the pandemic) show that in October 2020 the Swedish rate was marginally lower than in France, 30 percent lower than in the United States, only half as high as in Spain—but 2.5 times higher than in Finland and five times higher than in Germany.

EuroMOMO, which monitors mortality, shows Swedish deaths rising substantially above normal from the 13th to the 21st week of 2020, returning within normal range by the 27th week, and steadily declining afterward to below the normally expected rate by the 40th week of 2020. By the 45th week, Swedish mortality remained well below the expected level and even below the Norwegian rate.

Meanwhile France, Italy, Spain and Belgium had, once again, high excess mortalities, and only the Finnish mortality was well below the Swedish rate. The final verdict about Sweden’s relative success or indefensible failure is still many months in coming.

Obviously, you can use these comparisons to portray Sweden as either a success (vis-à-vis Spain, the U.K., or the United States) or a failure (vis-à-vis Germany or Finland). But we will have to wait until the second wave of the pandemic has fully asserted itself to see how such comparisons will fare.

This article appears in the January 2021 print issue as “Sweden’s COVID Response.”

Data-Free Medicine

Post Syndicated from Steven Cherry original https://spectrum.ieee.org/podcast/biomedical/diagnostics/datafree-medicine

Steven Cherry Hi, this is Steven Cherry for Radio Spectrum.

The saddest fact about the coronavirus pandemic is certainly the deaths it has already caused and the many more deaths to come before the world gets the virus under at least as much control as, say, chicken pox or an ordinary flu.

The second-saddest fact about the pandemic is the economic and educational havoc it has wrought.

Perhaps the third-saddest fact is the unfortunate lack of agreement about the best strategies for living with the virus, which, at least in the U.S., is responsible for many of those deaths, and, arguably much of the havoc as well. It has roiled families as well as the presidential election, by politicizing the wearing of masks, the limits on gatherings, the openings and closings of restaurants and schools.

But yet another sad fact is that, as was said thousands of years ago, “there is nothing new under the sun,” and this too is nothing new; there is a shocking and unfortunate lack of widespread agreement about the best answers when it comes to many medical questions, even among doctors, because there is a shocking and unfortunate lack of evidence—and even respect for evidence—in the medical arena. That’s the contention of the authors of a rather prescient 2017 book, Unhealthy Politics: The Battle Over Evidence-Based Medicine, subtitled, how partisanship, polarization, and medical authority stand in the way of evidence-based medicine.

And so I’ve asked one of those authors to lay out the case that medicine isn’t nearly as evidence-based as we think it is and as it should be, and tell us what role that has played in the severity of the pandemic—and what we might do about it, both in the near pandemic future, and to improve American medicine overall.

Eric Patashnik is a professor of public policy and political science at Brown University and the director of its Master of Public Affairs Program. He joins us via Zoom.

Steven Cherry Eric, welcome to the podcast.

Eric Patashnik Thank you so much for having me. It’s a pleasure to be here.

Steven Cherry Eric, the book starts with a rather surprising fact about how little we know about an operation that’s performed millions of times in the U.S., which you call a sham procedure. What is the sham procedure and how is it possible that a procedure that’s known to be a sham can be performed millions of times?

Eric Patashnik Yeah, so the original motivation for my book, which is coauthored with Alan Gerber at Yale and Conor Dowling at the University of Mississippi, was a remarkable study published in the New England Journal of Medicine in 2002. And what the study found was that a very common surgical procedure, arthroscopy for osteoarthritis of the knee—which is an operation that many older folks who have arthritis get after they try more conservative treatments such as drugs or physical therapy—what it found was that this widely used surgical procedure worked no better at relieving joint pain or improving function than a sham operation—in other words, a placebo intervention in which the surgeon merely pretended to operate.

And this was a groundbreaking study. It received a tremendous amount of media coverage. And the three of us are social scientists were not physicians, but we were startled by the study. And we began asking very basic questions. How is it possible that a widely used surgery wouldn’t work any better than a fake operation? And so what we began to do was investigate the medical literature. And what we found was this surgery had diffused into widespread practice in advance of any rigorous evidence that it really worked. Essentially, a number of surgeons began performing this procedure and they found their patients said that they felt better, but there really wasn’t rigorous data.

And that’s not so surprising because it turns out medical procedures, such as the kinds of things that your internist might do for you when you’re ill, or even surgeries, often become widely used without rigorous trials. We have a Food and Drug Administration that looks at the efficacy of pharmaceuticals, but there’s no FDA for surgery, for example. And so this turns out to be actually a very, very wide problem.

And what we learned as we started digging into the case is that this was really illustrative of a much broader problem in health care. Indeed, some experts believe that less than half of the medical care that Americans receive is based on adequate scientific evidence about what works best. Many treatment options have never been compared head-to-head with alternatives. So, for example, let’s say you have a bad back and you know there are different ways to treat it. You could try a drug, you could try physical therapy, you could get spinal fusion surgery. What patients would like to know is which of these treatments is really going to be best for me. And often the answer is we just don’t know. The studies haven’t been done. We just lack that information.

Steven Cherry You say that people in one part of the country get four times as many hip replacements as those in another and not for any sound medical reason. So why are there these regional variations in treatments?

Eric Patashnik Yeah, so basically there’s no centralized process in the United States to investigate alternative treatments for common medical conditions and determining what works best. And scholars at the Dartmouth Institute have found that there are remarkable variations in practice. In other words, patients with the same medical condition might receive very, very different treatment options and that these variances in how patients with the same condition are treated are not driven by, for example, regional differences in disease or patient preferences or even clinical evidence.

It might just be, for example, that physicians in Cleveland use a particular drug, whereas those in Boston use a different one. And we don’t ever have a system to figure out expeditiously which one is best for patients. And as a result of that, it could be the case that some patients in one part of the country are receiving inferior treatments and we might have no way of discovering that in short order. That’s, I think, a major problem that a lot of patients don’t realize. Even if you see a doctor that you trust, even if you have a very good relationship with your physician, the treatment that you may be receiving might be quite different from other patients in other parts of the country that have the very same condition. There was, I think, a recognition that this was a big problem. As part of the Affordable Care Act, there was an agency created the Patient-Centered Outcomes Research Institute [PCORI], whose mission is to fund and disseminate research findings on the comparative effectiveness of different treatments and diagnostic tests and other options. And I think that’s a very good thing. But we’ve only made a limited amount of progress in generating the information we need to answer those basic questions. 

Steven Cherry So to what extent is the problem that true evidence, especially via a large randomized double-blind controlled trials, is hard to come by? It’s expensive to do. It’s time-consuming. It’s rarely done. And if and when it’s done, it’s hardly ever replicated.

Eric Patashnik It’s true. There are there are major barriers and these studies can be expensive. But the information that comes from these comparative effectiveness studies is really a public good. It benefits all patients and payers and all stakeholders in the political system. So that’s one of the justifications for having a government role in subsidizing the production of these studies, because all of us would be better off if we had reliable information about what treatments work best and for whom and under what conditions. Individual physicians really don’t have a strong incentive to fund these studies or ability to fund the studies themselves. In fact, in the knee surgery case that I mentioned earlier, if it were not for the entrepreneurial initiative of a few physicians out of Texas, we might still not have those groundbreaking studies. It was really just because a few leaders decided that they really wanted to answer the question of whether this knee surgery worked. There was no system in place to ensure that those research holes are filled.

Steven Cherry Under our system, trials and other tests of efficacy are often in the hands of the large drug and medical device manufacturers. To the layperson, that sounds like putting the wolf in charge of determining the best way to build the chicken coop.

Eric Patashnik We do have a Food and Drug Administration that does a lot of tremendous work and they’re very valuable. And that’s also a benefit for the pharmaceutical industry. They, too, have an incentive to make sure that products that are sold to the public are seen as effective and trustworthy. So the industry itself does want a certain level of regulatory scrutiny. But the current FDA process, I think, while extremely valuable, has some limits. It’s often the case that drug companies are not required to study whether a new drug works better than, say, a cheaper alternative way of treating the same disease. If there’s medical and nonmedical options for treating a medical condition, say, for example, a surgery or a pharmaceutical agent, we have no process in place to ensure that those two options are forced to compete head-to-head. And so the FDA process, I think, is extremely valuable. And it does ensure that we find that drugs work better than a placebo, but we often don’t have what we really want to know, what patients want to know, which is which drug is best for me or should I be taking any drug.

We’ve also seen, I think over time, in part under industry pressure, a bit of a lowering of the evidentiary bar and even how we evaluate drugs. So oftentimes what the FDA is looking at is not answering the question that patients most want to know, which is, will this drug help me live longer? Will it help me improve my quality of life? Oftentimes, studies are looking at surrogate endpoints. For example, if I take this drug, will it lower my blood pressure or will it improve my cholesterol? And those surrogate outcomes, we hope, are correlated with the health outcomes that we really care about. But oftentimes the statistical causal relationship between them is much weaker than we would like it to be. And so sometimes we even have studies that are well done. But the questions that they’re answering are really not the ones that patients care most about.

Steven Cherry You would think that insurance companies would refuse to pay for a sham procedure or for a procedure that’s done four times in one region than another.

Eric Patashnik The insurance companies are in a difficult position because, of course, they would like to figure out what works best and conserve resources and not allocate them to low-value medical services. But in the United States, it’s very difficult for private insurers not to cover a medical treatment, for example, that is covered by the Medicare program. And the Medicare program really only looks at whether interventions are reasonable as judged essentially by physicians. The Medicare agency doesn’t really have the authority to examine whether a particular intervention is cost-effective or good value for money. And it’s also the case that individual insurers don’t have the resources to pay for the studies themselves, because, after all, if one insurer would spend hundreds of millions of dollars to answer the question, does this treatment A work better than treatment B? Well, once that study is done, the information would be available to other insurance companies, to their competitors. And so they don’t really have—the first insurance company doesn’t really have—an incentive to make that initial investment.

So, yes, payers would like this information, but individual insurance companies really don’t have a strong economic incentive to fund the studies. And it’s also difficult for them to deny coverage to treatments if the Medicare agency funds it.

The entire Medicare program, which was established in 1965, was, of course very controversial at the start. Many physicians and the AMA [American Medical Association] originally opposed Medicare. They were very concerned that government would be intruding on their clinical autonomy and second-guessing them. In exchange for essentially they’re buy-in, the government essentially said, look, we’re going to pay for health care for senior citizens, but we will defer to your professional judgment about the best way to treat patients. That’s not really government’s role. And, of course, Medicare has changed dramatically over the last decades. And I don’t want to say that Medicare doesn’t scrutinize treatments at all or make coverage decisions. It does. But that basic model of essentially deferring judgment or deferring decisions about coverage to physicians basically has remained the same.

And so we rely on physicians to exercise their best judgment to determine appropriate care. In many cases, that works very well. But if we have, for example, a breakdown of professional authority, if we have physicians in a particular practice area are widely using a surgical intervention, that doesn’t work, we don’t really have a good way of fixing that so quickly. And what we saw in that knee surgery case that I mentioned earlier was after that landmark New England Journal of Medicine study came out—and this is what was so disconcerting—a lot of the orthopedic surgeons that perform that surgery did not embrace it at all. They reacted extremely defensively. They attacked the study authors. They they made all sorts of arguments about what was wrong with the study.

And, of course, any study could have some flaws. And certainly every any study should be replicated. And we might not want to change practices based on a single study. But the overall behavior of the orthopedic community was one of essentially trying to push away evidence as opposed to embracing it as a way of learning what is best to treat their patients. In our research, we found that unfortunately, that practice has repeated itself over and over again.

There was another recent study just a couple of years ago called Orbita, which looked at millions of heart patients who had clogged arteries and they were receiving a stent inserted to reduce their chest pain. And this is another example of a very widely medical procedure. It’s expensive. It carries risks. It’s become the standard of care. And yet it’s diffused widely into practice on the basis of really little hard data. And the Orbita study was like the knee surgery finally done and it was a sham-controlled or a placebo-controlled trial in which some patients were randomized to receive a stent and others received no intervention at all beyond everyone in the trial receiving basic pharmaceutical drugs for cardiac disease. And what it found was that the patients who received a stent experienced no more improvement in chest pain or exercise tolerance—that was the other endpoint of the study—compared to patients who received a placebo procedure. And interventional cardiologists really saw that study as an attack on their specialty. And they lashed out at the trial and at the investigators. And it was another similar reaction of self-protective and defensive behavior of physicians that were not embracing the best available medical evidence.

Steven Cherry The book argues that the widespread disregard for scientific evidence or the lack of it is systematic within the medical community but it’s also political—that there’s little incentive for politicians to step in and demand medicine be more evidence-based. Is this physician pushback one of the reasons?

Eric Patashnik Yeah, I mean, I think what we’re talking about then is, essentially, as a society, we have a social contract. We delegate our authority to physicians and we give them the privilege of licensure and they can control who is a physician. They earn high salaries. They quite rightly are treated with great respect. And I should say, we think physicians are amazing people and we see our work as trying to help physicians for sure. But the way that social contract works is we rely on the medical community to self-regulate, to figure out if physicians are not practicing appropriate care, and to learn what would be best for patients.

And if that social contract is not working well, what we find in the book is it’s extremely difficult for government to do anything about it. Well, why is that? The main reason is when it comes to medical care, the public really trusts physicians. We did a bunch of public opinion surveys to try to understand how the public thinks about health care. And we found the bottom line of really scores of surveys that we did was when it comes to medicine, really the only actors that the American public trust are physicians. They don’t trust pharmaceutical firms. They don’t trust insurance companies, and they certainly don’t trust government.

Steven Cherry I mean, part of that trust is grounded in the fact that medicine is pretty arcane, complex, technical … People go to school for years and years and years and train in various ways. I mean, if my life depended on my having an opinion on which version of string theory was more likely to be true, I’d study up on string theory, but I wouldn’t get very far. And I think neither would most people.

Eric Patashnik Absolutely. It’s completely understandable and rational for ordinary Americans to look to doctors for advice about what works best. I certainly do in my own life and would steer people away from just Googling medical conditions at random. And you can find a lot of misleading information on the Web. But what we really do want at the end of the day is the best available evidence about what treatments work best. And then that is a sort of systematic evidence base, and then ideally physicians would be using that kind of data and then taking into account the specific medical conditions and backgrounds and preferences of individual patients. So we certainly think there’s a major role for clinical judgment in medicine. Medicine is always going to be both an art and a science. What we argue in the book is that the ratio of art to science has gotten out of whack, and we’re relying too little on rigorous evidence and too much on idiosyncratic decision making.

Steven Cherry So I take it your solution would involve an FDA for surgery and other medical procedures.

Eric Patashnik Well we certainly think that there should be much more rigorous scrutiny of procedures.

That’s really a big part of medicine. We would like to see PCORI, the Patient Centered Outcomes Research Institute, begin taking on some of those harder questions in medicine. And then we would also like to see, I think, the Medicare agency begin looking more rigorously at the added value of particular treatments.

And if there’s a treatment that is extraordinarily expensive and there’s no evidence that it works better than a cheaper alternative, we don’t necessarily think that patients shouldn’t get it. They should certainly be free to choose it. But perhaps, for example, the Medicare agency should only pay in reimbursement up to the amount of the cheaper, equally effective treatment. So we really need, I think, more tailored kinds of coverage and reimbursement policies, as well as more rigorous studies. It’s been difficult, however, to move the needle on these kinds of policy solutions. The agency that I mentioned, PCORI, was very, very cautious in its first decade. It was just reauthorized, which I think is terrific, but it was very controversial. When it was first created back in 2010, it was seen as a rationing agency. It got caught up in charges of death panels, along with a lot of controversy, as part of the ACA.

Even in the current crisis, we’ve lacked the kind of rigorous information we need to figure out, for example, what covid therapeutics would be most effective. There’s been a paucity of randomized control trials on those kinds of questions. Of course, we’ve been in the middle of a pandemic. It’s quite understandable that physicians have been trying to do the best they can with available therapies. But other countries like the UK have done better in getting rigorous studies going during the pandemic so we can get quick answers to these life and death questions.

Steven Cherry So fundamentally, these are data questions and data scientists are reinventing that sort of thing. Do you think that with electronic medical records and deep learning studies of procedures and outcomes and so forth, that even without a new federal agency, we could get better data just from the data that we have and don’t use properly?

Eric Patashnik I think that’s a fantastic question. My colleague Alan Gerber and I, the coauthor of the book, as I mentioned, there was that landmark Orbita study about the efficacy of heart stents. And we had a conference a couple of years ago at Yale where we brought the lead author of the study, along with other leading cardiologists and social scientists together to look at what had happened in that case and why we are so often struggling with questions of data. And one of the things that I think was most exciting about the conversation is there really is an opportunity, I believe, to connect medical researchers and data scientists and other kinds of scholars to figure out how we can tease out rigorous causal inferences about what treatments work best from observational data.

Now, there’s a long history in medicine of reaching conclusions on the basis of observational data and non-randomized controlled trials, where it turned out that some of our conclusions were wrong.  For example, beliefs that hormone replacement therapy would reduce heart disease, or that aggressive treatments for breast cancer would be better than standard treatments of breast cancer. And it turned out that in both of those cases, that was incorrect after randomized controlled trials were done.

So for very good reason, I think some of the leading evidence-based medicine … physicians have been skeptical about learning through methods other than RCTs [randomized clinical trials]. But in recent years, I think there really have been some breakthroughs in data science and other kinds of. Techniques that do allow us to learn what kinds of treatments work best. I’m hopeful that that kind of partnership in the coming decades will accelerate our ability to learn. We’re certainly going to need more RCTs; we’re doing too few of them. But I think there are other methods of learning.

The COVID pandemic is going to provide a remarkable opportunity to learn about the efficacy of a wide range of treatments, because we kind of had a national experiment, particularly during the early part of the pandemic during March and April. Basically, Americans and people around the world just stopped going to the doctor for all sorts of conditions. And of course, some of that was problematic. There were people that had serious medical conditions. They were fearful of going to the emergency room. But there were also people who might have had knee pain and they otherwise would have gotten the orthopedic surgery. There were people who had a sore back and they put off a procedure or they didn’t get a colonoscopy or they didn’t get some kind of screening for another medical condition. And what we don’t know is what the health outcomes were of this dramatic change in people’s consumption of medical services during this period. We have a remarkable opportunity now to figure out which of those medical interventions really were necessary and that the fact that people didn’t get them or got them in significantly fewer quantities was actually really bad for people’s health. And that’s going to be crucial to learn. So we can make sure that people do get those vital treatments and which are those services turned out upon reflection, actually weren’t so necessary. And that even though people skip some of those things, they didn’t turn out to have any negative health outcomes at all or perhaps even escaped a cascade of further unnecessary treatments or overutilization. Certainly, nobody wishes that this had happened. But now that it did happen and we had this once in a century kind of dramatic shift in people’s consumption of health care services, we really need to do our best to learn from this experience and figure out what the consequences were.

Steven Cherry Well, Eric, I started this podcast with a Bible verse, and I’m going to switch from the early Christians to the ancient Greeks. You might feel like you’re pushing a rock up a hill like Sisyphus, but like the similarly punished Prometheus, it was in the cause of empathy and imparting knowledge. So I thank you for co-authoring the book and thanks for joining us today.

Eric Patashnik Thank you so much. It’s a real pleasure to be here.

Steven Cherry We’ve been speaking with Brown University professor Eric Patashnik about the thesis of his co-authored book, Unhealthy Politics: The Battle Over Evidence-Based Medicine: How partisanship, polarization, and medical authority stand in the way of evidence-based medicine.

Radio Spectrum is brought to you by IEEE Spectrum, the member magazine of the Institute of Electrical and Electronic Engineers, a professional organization dedicated to advancing technology for the benefit of humanity.

This interview was recorded December 16, 2020 via Zoom using Adobe Audition. Our theme music is by Chad Crouch.

You can subscribe to Radio Spectrum on the Spectrum website, spectrum.ieee.org, or on Spotify, Apple, Google—wherever you get your podcasts. We welcome your feedback on the web or in social media.

For Radio Spectrum, I’m Steven Cherry.

Note: Transcripts are created for the convenience of our readers and listeners. The authoritative record of IEEE Spectrum’s audio programming is the audio version.

We welcome your comments on Twitter (@RadioSpectrum1 and @IEEESpectrum) and Facebook.

See also

Proof and Consequences

A new book explores the deceptive power of numbers
A conversation with Charles Seife (06 October 2010)

Step Aside, PCR: CRISPR-based COVID-19 Tests Are Coming

Post Syndicated from Megan Scudellari original https://spectrum.ieee.org/the-human-os/biomedical/diagnostics/step-aside-pcr-crispr-based-covid-19-tests-are-coming

,As the nasal swab probed higher into my nose, as if straining to pierce my brain, time slowed like molasses. Time stretched even longer as I waited three days for the COVID-19 test results.

That was in early August. Now it’s late December, and I’m currently on day four waiting for COVID-19 results for my three-year-old (who enjoyed the nasal swab even less than I did).

Both of us received a PCR test, the gold-standard for COVID-19 testing with a less-than-golden turnaround time of days to weeks. That’s far too slow to use testing as a method to contain the virus as we each wait our turn for a COVID-19 vaccine. Antigen tests, like the one approved by the FDA this week for at-home use, are fast but have sensitivity issues, so health authorities continue to emphasize the need for rapid, reliable tests.

Now, we may be on the cusp of their arrival.

A new wave of rapid molecular tests—which promise the sensitivity of a PCR test with the speed of an antigen test—have recently been validated and are moving from prototype toward FDA approval. In the last two weeks, studies published in the journals Science Advances and Cell detail ultrasensitive molecular COVID-19 tests based on gene-editing CRISPR technology.

This Is How We’ll Vaccinate the World Against COVID-19

Post Syndicated from W. Wayt Gibbs original https://spectrum.ieee.org/biomedical/devices/this-is-how-well-vaccinate-the-world-against-covid19

In a triumph of science, the first two large-scale trials to report the effectiveness of vaccines against SARS-CoV-2—the deadly, highly contagious virus that causes COVID-19—were both great successes right out of the gate. In November, the pharmaceutical giant Pfizer and the much younger biotech company Moderna both reported that their vaccines were about 95 percent effective in preventing cases of COVID-19. The news came just 10 months after the virus was first isolated and sequenced in a lab in China.

As of early December, 50 other candidate vaccines were making their way through human clinical trials, according to the World Health Organization. Thirteen of those vaccines were already in the final stage before approval, each being tested on tens of thousands of volunteers to check for side effects and measure efficacy: how well the shots protect against the disease. One of those, made by AstraZeneca and the University of Oxford, also showed promising—though less clear—efficacy results in late November.

But even before those vaccines neared the finish line, the heaviest burdens of ending the pandemic and restoring the global economy had shifted from the scientists to the engineers. Our hopes now hinge on the technologists who are challenged with manufacturing and transporting billions of doses of new, highly complex biotech products—and the public health officials figuring out how best to distribute them to a world that can hardly wait.

Throughout 2020, vaccine producers and their suppliers constructed new factories and otherwise increased their capacity while governments, international agencies, and philanthropies signed billion-dollar contracts, preordering doses by the hundreds of millions. In the United States, the federal initiative known as Operation Warp Speed deployed a budget of more than US $12 billion to develop, test, and mass-produce new vaccines along with the vials, syringes, and other materials needed to deliver them to an anxious populace.

Moncef Slaoui, the initiative’s chief scientist, told IEEE Spectrum in October that the U.S. government had already begun stockpiling two vaccines (from Pfizer and Moderna), and that commercial-scale production was beginning on two others. “So if and when they are approved” by regulators at the U.S. Food and Drug Administration (FDA), he said, “those can be used in the [U.S.] population immediately.”

Creation and deployment of a new vaccine against a novel disease normally takes at least a decade. The audacious goal of Operation Warp Speed and like-minded efforts in other nations is to complete this feat in less than two years. The pace is every bit as intense as the space race of the 1960s, but the stakes are far higher.

There are plenty of reasons for skepticism. “When was the last time anybody made a billion of anything safely and reliably?” asks Arthur Caplan, a bioethics professor at NYU Grossman School of Medicine. “Never,” he says. “Plants go offline, crap breaks, you can’t find a part.” Caplan argues that we should expect snafus: “There’s a ton of things that can go wrong just on manufacturing.”

But also consider this: In 2019, brewers in the United States used applied microbiology to ferment, filter, fill, package, and distribute nearly 50 billion bottles and cans of beer—all in copacetic single-dose units, most of it refrigerated.

Will the university, industry, and government teams grappling with the vaccine challenge be able to bring together the interrelated technical systems that must work in concert—including massive bioreactors and purification lines, acres of fast-fill vials, and thousands of planeloads of ultracold shipping containers? Can humanity really pull this off?

Somewhat surprisingly, the answer so far appears to be: Yes, we can.

Not everything will go smoothly. Paul Offit, a member of the COVID-19 vaccine working group at the U.S. National Institutes of Health, sat down in June to talk with the editor of the Journal of the American Medical Association about the steep road ahead. “The hardest thing about making a vaccine is mass-producing it,” Offit said. “You have to have the right buffering agent, the right stabilizing agent. You have to have the right vial. You have to do real-time stability studies to make sure that when the vaccine leaves the manufacturing plant, that the time it takes to get from the tarmac to the person’s arm does not cause any problems. Because, remember, when you’re shipping vaccines, they’re going to be exposed to high temperatures and low temperatures, and you have to make sure that you have a stable product.”

Take, for example, the RNA-based vaccine that Pfizer and its German partner BioNTech developed—the first to be approved by the FDA. This kind of vaccine contains slightly altered pieces of the virus’s genetic material (RNA) encased in nanometer-size fatty blobs, which fuse with human cells and cause them to produce the SARS-CoV-2 spike protein, thus triggering an immune response in the body. None of the vaccine experts interviewed for this article had dared to hope that any COVID-19 vaccine—let alone an RNA-based vaccine, a type that’s never before been commercialized—would achieve a 95 percent efficacy rate.

But that stellar effectiveness can wink out if the vaccine gets too warm for too long. As Offit emphasized, temperature affects all vaccines; most (including AstroZeneca’s) must remain between 2 °C and 8 °C to retain potency. RNA vaccines, however, are especially unstable.

At its assembly plants in Kalamazoo, Mich., and Puurs, Belgium, Pfizer has warehouses full of ultracold freezers to store its vaccine at –70 °C. Workers pack the frozen vials into custom-built containers that each hold about 1,000 of them, along with a layer of dry-ice pellets. Also in the box is a GPS-enabled thermal sensor that transmits the temperature and location of the package as it moves via trucks and planes to distribution centers throughout the world.

Distributors are rapidly scaling up too. UPS has said that it’s building two warehouses full of deep freezers—one in Louisville, Ky., and another in the Netherlands—that are capable of storing enough COVID-19 vaccines to inoculate millions of people. FedEx, which routinely delivers about 500,000 dry-ice-packed shipments a month, is doing the same in Memphis, Indianapolis, and Paris.

Rich Gottwald, president of the Compressed Gas Association, says that a nationwide shortage of carbon dioxide last spring spurred CO2 producers to work closely with vaccine makers, ensuring that dry ice will be there when and where they need it. “There may be some challenges in getting the vaccine distributed, but dry ice is not one of those challenges,” he says.

Most of these trips from factory to pharmacy or clinic should take no more than three days, and Pfizer’s vaccine stays fresh for up to 10 days in its container when unopened. Once thawed, the liquids must be kept in pharmacy-grade refrigerators and used within five days. Moderna claims its RNA vaccine can be transported and stored in deep freezers at –20 °C for up to six months and then refrigerated at distribution points for up to 30 days.

Unfortunately, only technologically advanced nations will be able to manage all these logistical complexities. In September, the shipping company DHL analyzed the transport challenges posed by a global rollout of COVID-19 vaccines. Its report concluded that mass distribution of vaccines requiring dry ice for storage will be feasible in only about two dozen countries, accounting for 2.5 billion people. All of Africa, most of South America, and much of Asia would struggle to put such a vaccine to widespread use.

In contrast, DHL estimates, around 60 countries would find it quite possible to inoculate their combined 5 billion residents with vaccines like AstraZeneca’s, which can be stored and transported at refrigerator temperatures of 2 °C to 8 °C (a typical temperature in pharmaceutical supply chains). Both ease of transport and substantially lower manufacturing costs favor more traditional vaccines, such as those that use harmless viruses to trigger an immune response. AstraZeneca’s vaccine, for example, is expected to sell for about a third the cost of the RNA vaccines.

In the hope of making coronavirus vaccines available to even the poorest nations, the World Health Organization, the Coalition for Epidemic Preparedness Innovations, and Gavi, the Vaccine Alliance have joined together to form the COVAX initiative. The coalition has been raising money to secure 2 billion vaccine doses through 2021 for the 90-plus low- and middle-income countries expected to participate, many of which can’t afford to buy or make vaccines on their own. As of mid-November, COVAX reported about US $2 billion in pledged donations, but it said at least $5 billion more is needed to achieve its goal.

These front-runners are just the opening salvo in what will be a protracted battle against SARS-CoV-2. Reinforcements, in the form of other vaccine options, should arrive in 2021 and will be crucial in bringing this pandemic to an end.

“No one manufacturer is going to be able to scale up and make enough doses for 7 billion people,” says Leonard Friedland, director of scientific affairs and public health at GSK Vaccines. “So I hope they all work.”

Pfizer said in July that it was aiming to produce 100 million doses of its product by the end of 2020, but by November it had halved that estimate. The hardest part for Pfizer has been mixing the synthetic pieces of RNA with fatty acids and cholesterol to form delivery particles of just the right size, says Slaoui of Operation Warp Speed. “These mixing operations are very complex,” he says.

And there is likely to be a shortage of cholesterol needed for the lipid nanoparticles, warns Jake Becraft, CEO of Strand Therapeutics, a biotech company in Massachusetts that is developing RNA vaccines of its own. “The simple fact is that those supply chains were nowhere near ready for the demand of billions of vaccines,” Becraft says. Some capacity can be redirected to support COVID-19 vaccine production, he says, “but it will also come at the cost of a lot of drugs in the pipeline for diseases like cystic fibrosis and cancer” that require the same ingredients.

Nevertheless, Pfizer has projected that it will produce up to 1.3 billion doses of COVID-19 vaccine by the end of 2021. Because each person’s inoculation requires two doses spaced two or three weeks apart, that should be enough to protect roughly 650 million people. The U.S. government has prepurchased 100 million of those doses, with an option to buy 500 million more.

As of press time, Moderna was hoping that its vaccine would be ready for broad release to the public in late December, assuming that all went smoothly with its licensing application to the FDA. The company signed up a manufacturing partner, Lonza Group, which is scaling up global manufacturing to be able to deliver 100 million doses a year from its site in Portsmouth, N.H., and another 300 million doses a year from a larger facility in Visp, Switzerland.

Meanwhile, in China, the companies Sinopharm and Sinovac have late-stage trials underway on three vaccines that contain intact coronavirus, which is harvested from live cell cultures and then chemically treated so that it cannot reproduce inside a person. This technology, used to make the annual flu vaccine and many others, has a long track record of success. And China has lots of manufacturing capacity for making inactivated-virus vaccines, notes John Moore, a professor of immunology at Weill Cornell Medical School in New York. Sinopharm is reportedly gearing up to produce 1 billion doses of its vaccine in 2021, if the product succeeds in trials.

But drugmakers elsewhere have largely steered clear of vaccines made from live cells infected with the SARS-CoV-2 virus, which pose obvious dangers to workers. The need for “biosafety level 3” facilities designed and certified to handle such biohazards makes such products harder to scale up, according to Kate Bingham, who chairs the U.K. government’s Vaccines Taskforce.

Of the remaining five vaccines in final-stage trials, four (including the AstraZeneca vaccine) are made by inserting a key gene from the coronavirus into a largely harmless human or chimpanzee adenovirus. After injection, these viral vector vaccines produce the important SARS-CoV-2 protein fragment inside the body, triggering an immune reaction.

The tricky part is harvesting enough of the engineered adenoviruses from the cell cultures in which they are grown. “The biggest issue as we scale up has been optimizing the infection step,” Slaoui says. Stirring 2,000 liters of living cells well enough to let the virus infect most of them—but gently enough so as not to rupture many of them—has proven difficult.

A similar scale-up challenge comes up in the production of the final kind of vaccine, one made by Novavax in Gaithersburg, Md. The company makes its protein vaccine in a factory in Morrisville, N.C., by growing huge batches of armyworm moth cells, which it has genetically engineered to churn out copies of a subunit of the coronavirus’s spike protein. After breaking up the cells and purifying the slurry, workers mix the desired protein with harmless microscopic particles that will carry the virus fragment into the body to trigger an immune response.

Here, Slaoui says, the big challenge is to bust up the cells in a way that doesn’t completely overwhelm the purification process with unwanted moth proteins. The company has a clinical trial underway in the United Kingdom, but in late November it delayed planned trials in the United States and Mexico because production was not scaling up as quickly as anticipated.

Nevertheless, Novavax has promised the U.S. government 100 million doses as they come off its production lines, and the company claims it has the capacity at a plant it bought in the Czech Republic to make a billion more doses in 2021.

If several vaccines gain approval and begin ramping up production in parallel, could there be what engineers call a “common mode” failure? The vaccines may vary, for example, but so far they’re all packaged the same way—in 5-milliliter vials made of a special kind of glass—and then injected into the arm via syringe.

“Syringes are probably less of a problem than vials and stoppers,” says Georges Benjamin, executive director of the American Public Health Association. “If I was wanting to pay attention to what can go wrong, it’d be that.”

Vaccines are so potent that each vial typically holds enough for five doses. Moderna claims its RNA vaccine is stronger still, so doctors can get 10 doses from every vial. On the one hand, that means that a 1,000-vial container of Moderna vaccine could give 10,000 people one of the two doses they will need. On the other hand, every vial that breaks wastes that many more doses.

The problem with frozen vaccines isn’t that ultracold temperatures make vials brittle, says Robert Schaut, the scientific director of pharmaceutical technologies at the glass-making company Corning. “You’re already below its glass-transition temperature, unlike a plastic or other material. So glass is exactly as strong at –70 °C as it is at room temperature,” he points out. “But when you cool vaccine down to those temperatures, the liquid expands and puts a lot of stress on the glass.”

Two years ago, Corning came out with a stronger, aluminosilicate glass that can be prestressed during vial manufacture by replacing sodium atoms in the materials with potassium atoms. That switch introduces hundreds of megapascals of compressive stress into the material—plenty enough to resist breakage during freezing or transport, Schaut says. He claims that the stronger glass vials also eliminate flaking and dramatically reduce tiny particles dislodged during the filling process, which in the past has led to recalls of conventional glass vials.

More useful still, the new vials are slippery. At the fill-finish stage of vaccine production, when big batches of vials are jostling along through the machinery, the slick coating on the vials lets them glide past each other more easily. Reducing jams on manufacturing lines adds 20 to 50 percent to the throughput, Schaut says, and once lines are moving smoothly, operators can double their speed.

Since the first quarter of 2020, Corning has been shipping millions of vials a month to its Operation Warp Speed partners from its plants outside Corning, N.Y. The company used part of its $204 million government contract to speed construction of a new factory in North Carolina, set to come online next year. Schaut says Corning should now be able to churn out 164 million vials a year—enough to ship at least 820 million doses of vaccine. 

“We set the objective to have enough vaccine to immunize the U.S. population by the first half of 2021,” said Slaoui of Operation Warp Speed, in October. “And that definitely will be the case. We will have 600 million to 700 million doses or more by May or June 2021.”

Thanks to unprecedented government investments, an impressively coordinated scramble by several industries, and some fortuitous technological advances, Slaoui’s boast seems credible. Since April, Stacy Springs and Donovan Guttieres at M.I.T.’s Center for Biomedical Innovation have been collecting data about each step of the supply, production, and distribution chains for COVID-19 vaccines. They have built models to investigate dependencies and identify critical points where shortages could interrupt production.

So far, Springs says, they have seen companies and agencies cooperating to spot problems and fix them: “A lot of the manufacturers are already moving to dual sourcing of materials and putting in other safety nets, so that they’re not going to be in a position where they don’t have what they need.” Although governments have been competing with one another to some extent to preorder vaccine for their own people, “there’s a lot of goodwill and sharing going on within the industry,” she says.

It is indeed encouraging to learn that the immense efforts being mounted now to vaccinate the world against COVID-19 are being undertaken in a cooperative spirit. Perhaps, after a year of divisiveness and social isolation, the realization is dawning that we’re all in this together. 

Brain Stimulation Via Earbuds: Unobtrusive Technology Could Treat a Variety of Diseases

Post Syndicated from Emily Waltz original https://spectrum.ieee.org/the-human-os/biomedical/devices/earbuds-electrically-stimulate-the-nervous-system-to-treat-rheumatoid-arthritis

They look like regular earbuds, but these headphones don’t play music, or produce any kind of sound. Instead, they produce electrical fields designed to treat disease.

By delivering electrical pulses to a nerve in the outer ear, the device hacks into neural circuits in the brain in a way that could regulate inflammation and treat rheumatoid arthritis. 

That’s the hope, anyway, of researchers at the start-up Nēsos, which launched out of stealth mode today. “We’re still at the early stages of development,” says Konstantinos Alataris, co-founder and CEO of the company. “We’re developing this as a prescription product and testing it in clinical trials.” 

And arthritis is just the first application that the startup is pursuing. If Nēsos has found an effective way to hack into the brain, the earbuds could help with a range of neurological and psychiatric diseases.

High Quality Asphere Manufacturing from Edmund Optics

Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/webinar/high-quality-asphere-manufacturing-from-edmund-optics

Edmund Optics’ asphere experts Amy Frantz and Oleg Leonov, and moderator Lars Sandström, Precision Optics Senior Business Line Manager, present the benefits of using aspheres in optical system design and what factors need be taken into account during the design process. These key manufacturability considerations will significantly reduce asphere lead time and cost if considered early enough in the design process.

At the conclusion of this webinar, participants will have a strong understanding around:

  • Benefits of using aspheres in optics system design
  • Challenges of asphere manufacturing
  • Key factors on manufacturable aspheres

Quadriplegic Pilots Race for Gold in Cybathlon Brain Race

Post Syndicated from Emily Waltz original https://spectrum.ieee.org/the-human-os/biomedical/bionics/quadriplegic-pilots-race-for-gold-in-cybathlon-brain-race

The competitors were neck-and-neck going into the final turns of the last heat, and in the end, Italy beat Thailand by four seconds. But unlike the Olympic games, none of the competitors in this race could move their bodies. Instead, they competed using only their thoughts. 

This is Olympic racing, cyborg-style. Using brain-computer interface (BCI) systems, the competitors—all of whom are paralyzed from the neck down—navigated computer avatars through a racetrack using thought-controlled commands. 

The race was part of Cybathlon 2020: The second ever cyborg Olympics, in which people with paralysis or amputated limbs turn themselves into cyborg athletes using robotics and algorithms. Proud competitors raced with their exoskeletons, powered wheelchairs and prosthetic limbs through obstacle courses as their tech teams cheered them on.

Turning the Body into a Wire

Post Syndicated from Shreyas Sen original https://spectrum.ieee.org/biomedical/devices/turning-the-body-into-a-wire

In 2007, U.S. vice president Dick Cheney ordered his doctors to disable all wireless signals to and from his Internet-connected pacemaker. Cheney later said that the decision was motivated by his desire to prevent terrorists from being able to hack his pacemaker and use it to lethally shock his heart. Cheney’s command to his doctors might seem to some to be overly cautious, but wirelessly connected medical devices have a history of exploitable vulnerabilities. At a series of conferences in 2011 and 2012, for example, New Zealand hacker Barnaby Jack showed that connected medical devices could be remotely attacked. Jack used a high-gain antenna to capture the unencrypted electromagnetic signals transmitted by an insulin pump on a mannequin 90 meters away. He then used those signals to hack into the pump and adjust the level of insulin the pump delivered. He also hacked a pacemaker and made it deliver deadly electric shocks.

Eight years after those demonstrations, connected medical devices remain vulnerable. In June 2020, for example, the U.S. Department of Homeland Security recalled a model of connected insulin pumps. The pumps were transmitting sensitive information without encryption, making the data accessible to anyone nearby who might want to listen in.

Medical devices are only the tip of the iceberg when it comes to the wireless devices people are putting in or on their bodies. The list includes wireless earbuds, smartwatches, and virtual-reality headsets. Technologies still in development, such as smart contact lenses that display information and digital pills that transmit sensor data after being swallowed, will also be at risk.

All of these devices need to transmit data securely at low power and over a short range. That’s why researchers have started to think about them as individual components of a single human-size wireless network, referred to as a body-area network. The term “Internet of Bodies” (IoB) is also coming into use, taking a cue from the Internet of Things.

At the moment, IoB devices use established wireless technologies, mainly Bluetooth, to communicate. While these technologies are low power, well understood, and easy to implement, they were never designed for IoB networks. One of Bluetooth’s defining features is the ability for two devices to easily find and connect to one another from meters away. That feature is precisely what allows a hypothetical attacker to snoop on or attack the devices on someone’s body. Wireless technologies have also been designed to travel through air or vacuum, not through the medium of the human body, and therefore they are less efficient than a method of communicating designed to do so from scratch.

Through our research at Purdue University, we have developed a new method of communication that will keep medical devices, wearables, and any other devices on or near the body more secure than they are using low-power wireless signals to communicate with one another. The system capitalizes on the human body’s innate ability to conduct tiny, harmless electrical signals to turn the entire body into a wired communication channel. By turning the body into the network, we will make IoB devices more secure.

Sensitive personal data like medical information should always be encrypted when it’s transmitted, whether wirelessly or in an email or via some other channel. But there are three other especially good reasons to prevent an attacker from gaining access to medical devices locally.

The first is that medical data should be containable. You don’t want a device to be broadcasting information that someone might eavesdrop on. The second reason is that you don’t want the integrity of the device to be compromised. If you have a glucose monitor connected to an insulin pump, for example, you don’t want the pump to release more glucose because the monitor’s data was compromised. Not enough glucose in the blood can cause headaches, weakness, and dizziness, while too much can lead to vision and nerve problems, kidney disease, and strokes. Either situation can eventually lead to death. The third reason is that the device’s information always needs to be available. If an attacker were to jam the signals from an insulin pump or a pacemaker, the device might not even know it needed to respond to a sudden problem in the body.

So if security and privacy are so important, why not use wires? A wire creates a dedicated channel between two devices. Someone can eavesdrop on a wired signal only if they physically tap the wire itself. That’s going to be hard to do if the wire in question is on or inside your body.

Setting aside the benefits of security and privacy, there are some important reasons why you wouldn’t want wires crisscrossing your body. If a wire isn’t properly insulated, the body’s own biochemical processes can corrode the metal in the wire, which could in turn cause heavy-metal poisoning. It’s also a matter of convenience. Imagine needing to repair or replace a pacemaker with wires. Rethreading the wires through the body would be a very delicate task.

Rather than choose between wireless signals, which are easy for eavesdroppers to snoop, and wired signals, which bring risk to the body, why not a third option that combines the best of both? That’s the inspiration behind our work to use the human body as the communication medium for the devices in someone’s body-area network.

We call the method of sending signals directly through the body electro-quasistatic human-body communication. That’s a mouthful, so let’s just think of it as a body channel. The important takeaway is that by exploiting the body’s own conductive properties, we can avoid the pitfalls of both wired and wireless channels.

Metal wires are great conductors of electric charge. It’s a simple matter to transmit data by encoding 1s and 0s as different voltages. You need only define 1s as some voltage, which would cause current to flow through the wire, and 0s as zero voltage, which would mean no current flowing through the wire. By measuring the voltage over time at the other end of the wire, you end up with the original sequence of 1s and 0s. However, given you don’t want metal wires running around or through the body, what can you do instead?

The average adult human is about 60 percent water by weight. And though pure water is a terrible electrical conductor, water filled with conductive particles like electrolytes and salts conducts electricity better. Your body is filled with a watery solution called the interstitial fluid that sits underneath your skin and around the cells of your body. The interstitial fluid is responsible for carrying nutrients from the bloodstream to the body’s cells, and is filled with proteins, salts, sugars, hormones, neurotransmitters, and all sorts of other molecules that help keep the body going. Because inter­stitial fluid is everywhere in the body, it allows us to establish a circuit among two or more communicating devices sitting pretty much anywhere on the body.

Imagine someone with diabetes who uses an insulin pump and a separate monitor on the abdomen to manage blood glucose levels. Suppose they want their smartwatch, among its many other functions, to display current glucose levels and the operational status of the pump. Traditionally, these devices would have to be connected wirelessly, which would make it theoretically possible for anyone to grab a copy of the user’s personal data. Or worse, potentially attack the pump itself. Today, many medical devices still aren’t encrypted, and even for those that are, encryption is not a guarantee of security.

Here’s how it would work with a body channel instead. The pump, the monitor, and the smartwatch would each be outfitted with a small copper electrode on its back, in direct contact with the skin. Each device also has a second electrode not in contact with the skin that functions as a sort of floating ground, which is a local electrical ground that is not directly connected with Earth’s ground. When the monitor takes a blood glucose measurement, it will need to send that data to both the pump, in case the insulin level needs to be adjusted, and to the smartwatch, so that the individual can see the level. The smartwatch can also store data for long-term monitoring, or encrypt it and send it to the user’s computer, or their doctor’s computer, for remote storage and analysis.

The monitor communicates its glucose measurements by encoding the data into a series of voltage values. Then, it transmits these values by applying a voltage between its two copper electrodes—the one touching the human body, and the one acting as a floating ground.

This applied voltage very slightly changes the potential of the entire body with respect to Earth’s ground. This tiny change in potential between the body and Earth’s ground is just a fraction of the potential difference between the monitor’s two electrodes. But it’s enough to be picked up, as an even smaller fraction after crossing the body, by the devices elsewhere. Because both the pump on the waist as well as the smartwatch on the wrist are on the body, they can detect this change in potential across their own two electrodes—both on-body and floating. The pump and the smartwatch then convert these potential measurements back into data. All without the actual signal ever traveling beyond the skin.

One of the biggest challenges for realizing this method of body communication is in selecting the best wavelengths for the electrical signals. Electrical wavelengths like the ones we’re considering here are much longer than the RF wavelengths for wireless communications.

The reason selecting a frequency is a challenge is that there is a range of frequencies at which the human body itself can become an antenna. An ordinary radio antenna creates a signal when an alternating current causes the electrons in its material to oscillate and create electromagnetic waves. The frequency of the transmitted waves depends on the frequency of the alternating current fed into the antenna. Likewise, an alternating current at certain frequencies applied to the human body will cause the body to radiate a signal. This signal, while weak, is still strong enough to be picked up with the right equipment and from some distance away. And if the body is acting as an antenna, it can also pick up unwanted signals from elsewhere that might interfere with wearables’ and implants’ ability to talk with one another.

For the same reason you don’t want to use technologies like Bluetooth, you want to keep electrical signals confined to the body and not accidentally radiating from or to it. So you have to avoid electrical frequencies at which the human body becomes an antenna, which are in the range of 10 to 100 megahertz. Above that are the wireless bands, and we’ve already mentioned the problems there. The upshot is that you need to use frequencies in the range of 0.1 to 10 MHz, in which signals will stay confined to the body.

Earlier attempts to use the human body to communicate have usually shied away from these lower frequencies because the body is typically high loss at low frequencies. In other words, signals at these lower frequencies require more power to guarantee that a signal will make it to its destination. That means a signal from a glucose monitor on the abdomen might not make it to a smartwatch on the wrist before it’s unreadable, without a significant boost in power. These previous efforts were high loss because they focused on sending direct electrical signals, rather than information encoded in potential changes. We’ve found that the parasitic capacitance between a device and the body is key to creating a working channel.

Capacitance refers to the ability of an object to store electrical charge. Parasitic capacitance is unwanted capacitance that occurs unintentionally between any two objects. For example, two charged areas in close proximity on a circuit board, or between a person’s hand and their phone. Typically, parasitic capacitance is a nuisance, although it also enables certain applications like touch screens.

Astute readers may have picked up that we haven’t mentioned one key aspect of circuits before now: A circuit needs to be a closed loop for electrical communication to be possible. Up until now, we’ve restricted our discussion to the forward path, meaning the part of the circuit from the transmitting electrode to the receiving electrode. But we need a path back. We have one thanks to parasitic capacitance between the floating ground electrodes on the devices and Earth’s ground.

Here’s how to picture the circuit we’re using. First, imagine two circuit loops. The first loop begins with the transmitting device, at the electrode touching the skin. The circuit then goes through the body, down through the feet to the actual ground, and then back up through the air to the other (floating) electrode on the transmitting device. We should note here that this is not a loop through which direct current can flow. But because parasitic capacitances exist between any two objects, such as your feet and your shoes, and your shoes and the ground, a small alternating current can exist.

The second loop, in a similar fashion, begins with the receiving device, at its electrode that is touching the skin. It then goes through the body—both loops share this segment—to the ground, and back through the air to the floating-ground electrode on the receiving device.

The key here is to understand that the circuit loops are important not because we have to push a current through them necessarily, but because we need a closed path of capacitors. In a circuit, if the voltage changes across one capacitor—for example, the two electrodes of the transmitting device—it creates a slight alternating current in the loop. The other capacitors, meaning both the body and the air, “see” this current and, because of their impedances, or resistances to the current, their voltages change as well.

Remember that the circuit loop with the transmitting device and the one with the receiving device share the body as a segment of their respective loops. Because they share that segment, the receiving device also responds to the slight change in the body’s voltage. The two electrodes making up the receiving device’s capacitor detect the body’s changing voltage and allow that measurement to be decoded as meaningful information.

We have found that we want any IoB device’s capacitor to have high capacitance. If this is the case, relatively high voltages created by the transmitting device will result in extremely low currents in the body itself. Obviously, this makes sense from a safety perspective: We don’t want to run high current through the body, after all. But it also makes the communications channel low loss. That’s because a high-impedance capacitor will be particularly sensitive to minor changes in current. The upshot is that we can keep the current low (and safe) and still get clear voltage measurements at the receiving device. We’ve found that our technique results in a reduction in loss of two orders of magnitude compared with previous attempts to create a wireless channel in the body, which relied on sending an electrical signal via current directly through the body.

Our method for turning the human body into a communications channel shifts the distance at which signals can be intercepted from the 5- to 10-meter range of ­Bluetooth and similar signals to below 15 centimeters. In other words, we’ve reduced the distance over which an attacker can both intercept and interfere with signals by two orders of magnitude. With our method, an attacker would need to be so close to the target that there’s no way to hide.

Not only does our method offer more privacy and security for anyone with a medical implant or device, but as a bonus, the communications are far more energy efficient as well. Because we’ve developed a system that is low loss at low frequencies, we can send information between devices using far less power. Our method requires less than 10 picojoules per transferred bit. For reference, that’s about 0.01 percent of the energy required by Bluetooth. Using 256-bit encryption, it drew 415 nanowatts of power to transmit 1 kilobit per second, which is more than three orders of magnitude below Bluetooth (which draws between 1 and 10 milliwatts).

Medical devices like pacemakers and insulin pumps have been around for decades. Bluetooth earbuds and smartwatches may be newer, but neither life-saving medical equipment nor consumer tech is leaving our bodies any time soon. It only makes sense to make both categories of devices as secure as possible. Data is always most vulnerable to a malicious attack when it is moving from one point to another, and our IoB communication technique can finally close the loop on keeping personal data from leaving your body.

This article appears in the December 2020 print issue as “To Safeguard Sensitive Data, Turn Flesh and Tissue Into a Secure Wireless Channel.”

About the Author

Shreyas Sen is an associate professor of electrical and computer engineering at Purdue University. He is a Senior Member of the IEEE. Shovan Maity and Debayan Das are graduate students of Sen at Purdue University.