A company called Second Sight made an implant that partially restored vision to people who'd been blind for decades. But when Second Sight pivoted, it stopped servicing its product, leaving many in the dark.
The Argus II uses the implant and a video camera embedded in a special pair of glasses to provide limited vision to those with retinitis pigmentosa, a genetic disease that causes cells in the retina to deteriorate. The camera feeds information to the implant, which sends electrical impulses into the retina to recapitulate what the camera sees. The impulses appear in the Argus II as a 60-pixel grid of blacks, grays and whites in the user’s eye that can render rough outlines of objects and their motion.
Smartphone and computer manufacturers typically stop issuing software upgrades to their devices after two or three years, eventually rendering them bricks. But is the smartphone approach acceptable for a device that helps restore the most crucial sense a human being possesses?
Ross Doerr, a retired disability rights attorney in Maine who received an Argus II in 2019, describes the field of vision as the equivalent of an index card held at arm’s length. Perk often brings objects close to his face to decipher them. Moreover, users must swivel their heads to take in visual data; moving their eyeballs does not work.
Despite its limitations, the Argus II beats the alternative. Perk no longer relies on his guide dog. Doerr was uplifted when he was able to see the outlines of Christmas trees at a holiday show.
“The fairy godmother department sort of reaches out and taps you on the shoulder once in a while,” Doerr says of his implant, which came about purely by chance. A surgeon treating his cataracts was partnered with the son of another surgeon who was implanting the devices, and he was referred.
Doerr had no reason to believe the shower of fairy dust wouldn’t continue. Second Sight held out promises that the Argus II recipients’ vision would gradually improve through upgrades to much higher pixel densities. The ability to recognize individual faces was even touted as a possibility. In the winter of 2020, Doerr was preparing to travel across the U.S. to Second Sight’s headquarters to receive an upgrade. But then COVID-19 descended, and the trip was canceled.
The pandemic also hit Second Sight’s bottom line. Doerr found out about its tribulations only from one of the company’s vision therapists, who told him the entire department was being laid off. Second Sight cut nearly 80% of its workforce in March 2020 and announced it would wind down operations.
Ross Doerr has mostly stopped using his Argus II, the result of combination of fear of losing its assistance from wear and tear and disdain for the company that brought it to market.
Jan Doerr
Second Sight’s implosion left some 350 Argus recipients in the metaphorical dark about what to do if their implants failed. Skeleton staff seem to have rarely responded to queries from their customers, at least based on the experiences of Perk and Doerr. And some recipients have unfortunately returned to the actual dark as well, as reports have surfaced of Argus II failures due to aging or worn-down parts.
Product support for complex products is remarkably uneven. Although the iconic Ford Mustang ceased production in the late 1960s, its parts market is so robust that it’s theoretically possible to assemble a new vehicle from recently crafted components. Conversely, smartphone and computer manufacturers typically stop issuing software upgrades to their devices after two or three years, eventually rendering them bricks. Consumers have accepted both extremes.
But is the smartphone approach acceptable for a device that helps restore the most crucial sense a human being possesses?
Margaret McLean, a senior fellow at the Markkula Center for Applied Ethics at Santa Clara University in California, notes companies like Second Sight have a greater obligation for product support than other consumer product ventures.
“In this particular case, you have a great deal of risk that is involved in using this device, the implant, and the after care of this device,” she says. “You cannot, like with your car, decide that ‘I don’t like my Mustang anymore,’ and go out and buy a Corvette.”
And, whether the Argus II implant works or not, its physical presence can impact critical medical decisions. Doerr’s doctor wanted him to undergo an MRI to assist in diagnosing attacks of vertigo. But the physician was concerned his implant might interfere. With the latest available manufacturer advisories on his implant nearly a decade old, the procedure was held up. Doerr spent months importuning Second Sight through phone calls, emails and Facebook postings to learn if his implant was contraindicated with MRIs, which he never received. Although the cause of his vertigo was found without an MRI, Doerr was hardly assured.
“Put that into context for a minute. I get into a serious car accident. I end up in the emergency room, and I have a tag saying I have an implanted medical device,” he says. “You can’t do an MRI until you get the proper information from the company. Who’s going to answer the phone?”
Second Sight’s management did answer the call to revamp its business. It netted nearly $78 million through a private stock placement and an initial public offering last year. At the end of 2021, Second Sight had nearly $70 million in cash on hand, according to a recent filing with the Securities and Exchange Commission.
And while the Argus II is still touted at length on Second Sight’s home page, it appears little of its corporate coffers are earmarked toward its support. These days, the company is focused on obtaining federal approvals for Orion, a new implant that would go directly into the recipient’s brain and could be used to remedy blindness from a variety of causes. It obtained a $6.4 million grant from the National Institutes of Health in May 2021 to help develop Orion.
Presented with a list of written questions by email, Second Sight’s spokesperson, Dave Gentry of the investor relations firm Red Chip Companies, copied a subordinate with an abrupt message to “please handle.” That was the only response from a company representative. A call to Second Sight acting chief executive officer Scott Dunbar went unreturned.
Whether or not the Orion succeeds remains to be seen. The company’s SEC filings suggest a viable and FDA-approved device is years away, and that operational losses are expected for the “foreseeable future.” Second Sight reported zero revenue in 2020 or 2021.
Moreover, the experiences of the Argus II recipients could color the reception of future Second Sight products. Doerr notes that his insurer paid nearly $500,000 to implant his device and for training on how to use it.
“What’s the insurance industry going to say the next time this crops up?” Doerr asks, noting that the company’s reputation is “completely shot” with the recipients of its implants.
Perk, who made speeches to praise the Argus II and is still featured in a video on the Second Sight website, says he also no longer supports the company.
Jeroen Perk, an investigator for the Dutch customs service, cried for joy after partially regaining his sight, but he no longer trusts Second Sight, the company that provided his implant.
Nanda Perk
Nevertheless, Perk remains highly reliant on the technology. When he dropped an external component of his device in late 2020 and it broke, Perk briefly debated whether to remain blind or find a way to get his Argus II working again. Three months later, he was able to revive it by crowdsourcing parts, primarily from surgeons with spare components or other Argus II recipients who no longer use their devices. Perk now has several spare parts in reserve in case of future breakdowns.
Despite the frantic efforts to retain what little sight he has, Perk has no regrets about having the device implanted. And while he no longer trusts Second Sight, he is looking forward to possibly obtaining more advanced implants from companies in the Netherlands and Australia working on their own products.
Doerr suggests that biotech firms whose implants are distributed globally be bound to some sort of international treaty requiring them to service their products in perpetuity. Such treaties are still applied to the salvage rights for ships that sunk centuries ago, he notes.
“I think that in a global tech economy, that would be a good thing,” says McLean, the fellow at Santa Clara, “but I am not optimistic about it in the near term. Business incentives push toward return on share to stockholders, not to patients and other stakeholders. We likely need to rely on some combination of corporately responsibility…and [international] government regulation. It’s tough—the Paris Climate Accord implementation at a slow walk comes to mind.”
Unlike Perk, Doerr has mostly stopped using his Argus II, the result of combination of fear of losing its assistance from wear and tear and disdain for the company that brought it to market. At 70, Doerr says he does not have the time or energy to hold the company more accountable. And with Second Sight having gone through a considerable corporate reorganization, Doerr believes a lawsuit to compel it to better serve its Argus recipients would be nothing but an extremely costly longshot.
“It’s corporate America at its best,” he observes.
Basecamp Research is using portable labs like this one to gather samples from ecosystems around the world.
Clark works for Basecamp Research, a biotech company headquartered in London, and his job is to collect samples from ecosystems around the world. By extracting DNA from soil, water, plants, microbes and other organisms, Basecamp is building an extensive database of the Earth’s proteins. While DNA itself isn’t a protein, the information stored in DNA is used to create proteins, so extracting, sequencing, and annotating DNA allows for the discovery of unique protein sequences.
Using what they’re finding in the middle of the Atlantic and beyond, Basecamp’s detailed database is constantly growing. The outputs could be essential for cleaning up the damage done by toxic chemicals and finding alternatives to these chemicals.
Catalysts for change
Proteins provide structure and function in all living organisms. Some of these functional proteins are enzymes, which quite literally make things happen.
“Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development. Biocatalysis is providing advantages, both to make more complex drugs and to be more sustainable, reducing the pollution and toxicity of conventional chemistry," says Ahir Pushpanath, who heads partnerships for Basecamp.
“Enzymes are perfectly evolved catalysts,” says Ahir Pushpanath, a partnerships lead at Basecamp. ”Enzymes are essentially just a polymer, and polymers are made up of amino acids, which are nature’s building blocks.” He suggests thinking about it like Legos — if you have a bunch of Lego pieces and use them to build a structure that performs a function, “that’s basically how an enzyme works. In nature, these monuments have evolved to do life’s chemistry. If we didn’t have enzymes, we wouldn’t be alive.”
In our own bodies, enzymes catalyze everything from vision to digesting food to regrowing muscles, and these same types of enzymes are necessary in the pharmaceutical, agrochemical and fine chemical industries. But industrial conditions differ from those inside our bodies. So, when scientists need certain chemical reactions to create a particular product or substance, they make their own catalysts in their labs — generally through the use of petroleum and heavy metals.
These petrochemicals are effective and cost-efficient, but they’re wasteful and often hazardous. With growing concerns around sustainability and long-term public health, it's essential to find alternative solutions to toxic chemicals. “Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development,” Pushpanath says.
Basecamp is trying to replace lab-created catalysts with enzymes found in the wild. This concept is called biocatalysis, and in theory, all scientists have to do is find the right enzymes for their specific need. Yet, historically, researchers have struggled to find enzymes to replace petrochemicals. When they can’t identify a suitable match, they turn to what Pushpanath describes as “long, iterative, resource-intensive, directed evolution” in the laboratory to coax a protein into industrial adaptation. But the latest scientific advances have enabled these discoveries in nature instead.
Marlon Clark, a research scientist at Basecamp Research, looks for novel biochemistries in the Azores.
Glen Gowers
Enzyme hunters
Whether it’s Clark and a colleague setting off on an expedition, or a local, on-the-ground partner gathering and processing samples, there’s a lot to be learned from each collection. “Microbial genomes contain complete sets of information that define an organism — much like how letters are a code allowing us to form words, sentences, pages, and books that contain complex but digestible knowledge,” Clark says. He thinks of the environmental samples as biological libraries, filled with thousands of species, strains, and sequence variants. “It’s our job to glean genetic information from these samples.”
“We can actually dream up new proteins using generative AI," Pushpanath says.
Basecamp researchers manage this feat by sequencing the DNA and then assembling the information into a comprehensible structure. “We’re building the ‘stories’ of the biota,” Clark says. The more varied the samples, the more valuable insights his team gains into the characteristics of different organisms and their interactions with the environment. Sequencing allows scientists to examine the order of nucleotides — the organic molecules that form DNA — to identify genetic makeups and find changes within genomes. The process used to be too expensive, but the cost of sequencing has dropped from $10,000 a decade ago to as low as $100. Notably, biocatalysis isn’t a new concept — there have been waves of interest in using natural enzymes in catalysis for over a century, Pushpanath says. “But the technology just wasn’t there to make it cost effective,” he explains. “Sequencing has been the biggest boon.”
AI is probably the second biggest boon.
“We can actually dream up new proteins using generative AI,” Pushpanath says, which means that biocataylsis now has real potential to scale.
Glen Gowers, the co-founder of Basecamp, compares the company’s AI approach to that of social networks and streaming services. Consider how these platforms suggest connecting with the friends of your friends, or how watching one comedy film from the 1990s leads to a suggestion of three more.
“They’re thinking about data as networks of relationships as opposed to lists of items,” says Gowers. “By doing the same, we’re able to link the metadata of the proteins — by their relationships to each other, the environments in which they’re found, the way those proteins might look similar in sequence and structure, their surrounding genome context — really, this just comes down to creating a searchable network of proteins.”
On an Azores island, this volcanic opening may harbor organisms that can help scientists identify enzymes for biocatalysis to replace toxic chemicals.
Emma Bolton
Uwe Bornscheuer, professor at the Institute of Biochemistry at the University of Greifswald, and co-founder of Enzymicals, another biocatalysis company, says that the development of machine learning is a critical component of this work. “It’s a very hot topic, because the challenge in protein engineering is to predict which mutation at which position in the protein will make an enzyme suitable for certain applications,” Bornscheuer explains. These predictions are difficult for humans to make at all, let alone quickly. “It is clear that machine learning is a key technology.”
Benefiting from nature’s bounty
Biodiversity commonly refers to plants and animals, but the term extends to all life, including microbial life, and some regions of the world are more biodiverse than others. Building relationships with global partners is another key element to Basecamp’s success. Doing so in accordance with the access and benefit sharing principles set forth by the Nagoya Protocol — an international agreement that seeks to ensure the benefits of using genetic resources are distributed in a fair and equitable way — is part of the company's ethos. “There's a lot of potential for us, and there’s a lot of potential for our partners to have exactly the same impact in building and discovering commercially relevant proteins and biochemistries from nature,” Clark says.
Bornscheuer points out that Basecamp is not the first company of its kind. A former San Diego company called Diversa went public in 2000 with similar work. “At that time, the Nagoya Protocol was not around, but Diversa also wanted to ensure that if a certain enzyme or microorganism from Costa Rica, for example, were used in an industrial process, then people in Costa Rica would somehow profit from this.”
An eventual merger turned Diversa into Verenium Corporation, which is now a part of the chemical producer BASF, but it laid important groundwork for modern companies like Basecamp to continue to scale with today’s technologies.
“To collect natural diversity is the key to identifying new catalysts for use in new applications,” Bornscheuer says. “Natural diversity is immense, and over the past 20 years we have gained the advantages that sequencing is no longer a cost or time factor.”
This has allowed Basecamp to rapidly grow its database, outperforming Universal Protein Resource or UniProt, which is the public repository of protein sequences most commonly used by researchers. Basecamp’s database is three times larger, totaling about 900 million sequences. (UniProt isn’t compliant with the Nagoya Protocol, because, as a public database, it doesn’t provide traceability of protein sequences. Some scientists, however, argue that Nagoya compliance hinders progress.)
“Eventually, this work will reduce chemical processes. We’ll have cleaner processes, more sustainable processes," says Uwe Bornscheuer, a professor at the University of Greifswald.
With so much information available, Basecamp’s AI has been trained on “the true dictionary of protein sequence life,” Pushpanath says, which makes it possible to design sequences for particular applications. “Through deep learning approaches, we’re able to find protein sequences directly from our database, without the need for further laboratory-directed evolution.”
Recently, a major chemical company was searching for a specific transaminase — an enzyme that catalyzes a transfer of amino groups. “They had already spent a year-and-a-half and nearly two million dollars to evolve a public-database enzyme, and still had not reached their goal,” Pushpanath says. “We used our AI approaches on our novel database to yield 10 candidates within a week, which, when validated by the client, achieved the desired target even better than their best-evolved candidate.”
Basecamp’s other huge potential is in bioremediation, where natural enzymes can help to undo the damage caused by toxic chemicals. “Biocatalysis impacts both sides,” says Gowers. “It reduces the usage of chemicals to make products, and at the same time, where contamination sites do exist from chemical spills, enzymes are also there to kind of mop those up.”
So far, Basecamp's round-the-world sampling has covered 50 percent of the 14 major biomes, or regions of the planet that can be distinguished by their flora, fauna, and climate, as defined by the World Wildlife Fund. The other half remains to be catalogued — a key milestone for understanding our planet’s protein diversity, Pushpanath notes.
There’s still a long road ahead to fully replace petrochemicals with natural enzymes, but biocatalysis is on an upward trajectory. "Eventually, this work will reduce chemical processes,” Bornscheuer says. “We’ll have cleaner processes, more sustainable processes.”
In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Arnold was diagnosed sooner than many others. It's important to find out early, when interventions can make the most difference. One promising avenue is looking at how people talk. Research has shown that Alzheimer’s affects a part of the brain that controls speech, resulting in small changes before people show other signs of the disease.
Now, Canary Speech, a company based in Utah, is using AI to examine elements like the pitch of a person’s voice and their pauses. In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Developing the AI model
Canary Speech’s CEO, Henry O’Connell, met cofounder Jeff Adams about 40 years before they started the company. Back when they first crossed paths, they were both living in Bethesda, Maryland; O’Connell was a research fellow at the National Institutes of Health studying rare neurological diseases, while Adams was working to decode spy messages. Later on, Adams would specialize in building mathematical models to analyze speech and sound as a team leader in developing Amazon's Alexa.
It wasn't until 2015 that they decided to make use of the fit between their backgrounds. ““We established Canary Speech in 2017 to build a product that could be used in multiple languages in clinical environments,” O'Connell says.
The need is growing. About 55 million people worldwide currently live with Alzheimer’s, a number that is expected to double by 2050. Some scientists think the disease results from a buildup of plaque in the brain. It causes mild memory loss at first and, over time, this issue get worse while other symptoms, such as disorientation and hallucinations, can develop. Treatment to manage the disease is more effective in the earlier stages, but detection is difficult since mild symptoms are often attributed to the normal aging process.
O’Connell and Adams specialize in the complex ways that Alzheimer’s effects how people speak. Using AI, their mathematical model analyzes 15 million data points every minute, focusing on certain features of speech such as pitch, pauses and elongation of words. It also pays attention to how the vibrations of vocal cords change in different stages of the disease.
To create their model, the team used a type of machine learning called deep neural nets, which looks at multiple layers of data - in this case, the multiple features of a person’s speech patterns.
“Deep neural nets allow us to look at much, much larger data sets built out of millions of elements,” O’Connell explained. “Through machine learning and AI, we’ve identified features that are very sensitive to an Alzheimer’s patient versus [people without the disease] and also very sensitive to mild cognitive impairment, early stage and moderate Alzheimer's.” Based on their learnings, Canary is able to classify the disease stage very quickly, O’Connell said.
“When we’re listening to sublanguage elements, we’re really analyzing the direct result of changes in the brain in the physical body,” O’Connell said. “The brain controls your vocal cords: how fast they vibrate, the expansion of them, the contraction.” These factors, along with where people put their tongues when talking, function subconsciously and result in subtle changes in the sounds of speech.
Further testing is needed
In an initial trial, Canary analyzed speech recordings from phone calls to a large U.S. health insurer. They looked at the audio recordings of 651 policyholders who had early stage Alzheimer’s and 1018 who did not have the condition, aiming for a representative sample of age, gender and race. They used this data to create their first diagnostic model and found that it was 96 percent accurate in identifying Alzheimer’s.
Christian Herff, an assistant professor of neuroscience at Maastricht University in the Netherlands, praised this approach while adding that further testing is needed to assess its effectiveness.
“I think the general idea of identifying increased risk for cognitive impairment based on speech characteristics is very feasible, particularly when change in a user’s voice is monitored, for example, by recording speech every year,” Herff said. He noted that this can only be a first indication, not a full diagnosis. The accuracy still needs to be validated in studies that follows individuals over a period of time, he said.
Toby Walsh, a professor of artificial intelligence at the University of New South Wales, also thinks Canary’s tool has potential but highlights that Canary could diagnose some people who don’t really have the disease. “This is an interesting and promising application of AI,” he said, “but these tools need to be used carefully. Imagine the anxiety of being misdiagnosed with Alzheimer’s.”
As with many other AI tools, privacy and bias are additional issues to monitor closely, Walsh said.
Other languages
A related issue is that not everyone is fluent in English. Mahnaz Arvaneh, a senior lecturer in automatic control and systems engineering at the University of Sheffield, said this could be a blind spot.
“The system may not be very accurate for those who have English as their second language as their speaking patterns would be different, and any issue might be because of language deficiency rather than cognitive issues,” Arvaneh said.
The team is expanding to multiple languages starting with Japanese and Spanish. The elements of the model that make up the algorithm are very similar, but they need to be validated and retrained in a different language, which will require access to more data.
Recently, Canary analyzed the phone calls of 233 Japanese patients who had mild cognitive impairment and 704 healthy people. Using an English model they were able to identify the Japanese patients who had mild cognitive impairment with 78 percent accuracy. They also developed a model in Japanese that was 45 percent accurate, and they’re continuing to train it with more data.
The future
Canary is using their model to look at other diseases like Huntington’s and Parkinson’s. They’re also collaborating with pharmaceuticals to validate potential therapies for Alzheimer’s. By looking at speech patterns over time, Canary can get an indication of how well these drugs are working.
Dave Arnold and his wife dance at his nephew’s wedding in Rochester, New York, ten years ago, before his Alzheimer's diagnosis.
Dave Arnold
Ultimately, they want to integrate their tool into everyday life. “We want it to be used in a smartphone, or a teleconference call so that individuals could be examined in their home,” O’Connell said. “We could follow them over time and work with clinical teams and hospitals to improve the evaluation of patients and contribute towards an accurate diagnosis.”
Arnold, the patient with early stage Alzheimer’s, sees great promise. “The process of getting a diagnosis is already filled with so much anxiety,” he said. “Anything that can be done to make it easier and less stressful would be a good thing, as long as it’s proven accurate.”