6 Biotech Breakthroughs of 2021 That Missed the Attention They Deserved
News about COVID-19 continues to relentlessly dominate as Omicron surges around the globe. Yet somehow, during the pandemic’s exhausting twists and turns, progress in other areas of health and biotech has marched on.
In some cases, these innovations have occurred despite a broad reallocation of resources to address the COVID crisis. For other breakthroughs, COVID served as the forcing function, pushing scientists and medical providers to rethink key aspects of healthcare, including how cancer, Alzheimer’s and other diseases are studied, diagnosed and treated. Regardless of why they happened, many of these advances didn’t make the headlines of major media outlets, even when they represented turning points in overcoming our toughest health challenges.
If it bleeds, it leads—and many disturbing stories, such as COVID surges, deserve top billing. Too often, though, mainstream media’s parallel strategy seems to be: if it innovates, it fades to the background. But our breakthroughs are just as critical to understanding the state of the world as our setbacks. I asked six pragmatic yet forward-thinking experts on health and biotech for their perspectives on the most important, but under-appreciated, breakthrough of 2021.
Their descriptions, below, were lightly edited by Leaps.org for style and format.
New Alzheimer's Therapies
Mary Carrillo, Chief Science Officer at the Alzheimer’s Association
Alzheimer's Association
One of the biggest health stories of 2021 was the FDA’s accelerated approval of aducanumab, the first drug that treats the underlying biology of Alzheimer’s, not just the symptoms. But, Alzheimer’s is a complex disease and will likely need multiple treatment strategies that target various aspects of the disease. It’s been exciting to see many of these types of therapies advance in 2021.
Following the FDA action in June, we saw renewed excitement in this class of disease-modifying drugs that target beta-amyloid, a protein that accumulates in the brain and leads to brain cell death. This class includes drugs from Eli Lilly (donanemab), Eisai (lecanemab) and Roche (gantenerumab), all of which received Breakthrough Designation by the FDA in 2021, advancing the drugs more quickly through the approval process.
We’ve also seen treatments advance that target other hallmarks of Alzheimer’s this year. We heard topline results from a phase 2 trial of semorinemab, a drug that targets tau tangles, a toxic protein that destroys neurons in the Alzheimer’s brain. Plus, strategies targeting neuroinflammation, protecting brain cells, and reducing vascular contributions to dementia – all funded through the Alzheimer's Association Part the Cloud program – advanced into clinical trials.
The future of Alzheimer’s treatment will likely be combination therapy, including drug therapies and healthy lifestyle changes, similar to how we treat heart disease. Washington University announced they will be testing a combination of both anti-amyloid and anti-tau drugs in a first-of-its-kind clinical trial, with funding from the Alzheimer’s Association.
AlphaFold
Olivier Elemento, Director of the Caryl and Israel Englander Institute for Precision Medicine at Cornell University
Cornell University
AlphaFold is an artificial intelligence system designed by Google’s DeepMind that opens the door to understanding the three-dimensional structures and functions of proteins, the building blocks that make up almost half of our bodies' dry weight. In 2021, Google made AlphaFold available for free and since then, researchers have used it to drive greater understanding of how proteins interact. This is a foundational event in the field of biotech.
It’s going to take time for the benefits from AlphaFold to transpire, but once we know the 3-D structures of proteins that cause various diseases, it will be much easier to design new drugs that can bind to these proteins and change their activity. Prior to AlphaFold, scientists had identified the 3-D structure of just 17 percent of about 20,000 proteins in the body, partly because mapping the structures was extremely difficult and expensive. Thanks to AlphaFold, we’ve now jumped to knowing – with at least some degree of certainty – the protein structures of 98.5 percent of the proteome.
For example, kinases are a class of proteins that modify other proteins and are often aberrantly active in cancer due to DNA mutations. Some of the earliest targeted therapies for cancer were ones that block kinases but, before AlphaFold, we had only a premature understanding of a few hundred kinases. We can now determine the structures of all 1,500 kinases. This opens up a universe of drug targets we didn’t have before.
Additional progress has been made this year toward potentially using AlphaFold to develop blockers of certain protein receptors that contribute to psychiatric illnesses and other neurological diseases. And in July, scientists used AlphaFold to map the dimensions of a bacterial protein that may be key to countering antibiotic resistance. Another discovery in May could be essential to finding treatments for COVID-19. Ongoing research is using AlphaFold principles to create entirely new proteins from scratch that could have therapeutic uses. The AlphaFold revolution is just beginning.
Virtual First Care
Jennifer Goldsack, CEO of Digital Medicine Society
Digital Medicine Society
Imagine a new paradigm of healthcare defined by how good we are at keeping people healthy and out of the clinic, not how good we are at offering services to a sick person at the clinic. That is the promise of virtual-first care, or V1C, what I consider to be the greatest, and most underappreciated, advance that occurred in medicine this year.
V1C is defined as medical care accessed through digital interactions where possible, guided by a clinician, and integrated into a person’s everyday life. This type of care includes spit kits mailed for laboratory tests and replacing in-person exams with biometric sensors. It’s built around the patient, not the clinic, and provides us with the opportunity to fundamentally reimagine what good healthcare looks like.
V1C flew under the radar in 2021, eclipsed by the ongoing debate about the value of telehealth more broadly as we emerge from the pandemic. However, the growth in the number of specialty and primary care virtual-first providers has been matched only by the number of national health plans offering virtual-first plans. Our own virtual-first community, IMPACT, has tripled in size, mirroring the rapid growth of the field driven by patient demand for care on their terms.
V1C differs from the ‘bolt on’ approach of video visits as an add-on to traditional visit-based, episodic care. V1C takes a much more holistic approach; it allows individuals to initiate care at any time in any place, recognizing that healthcare needs extend beyond 9-5. It matches the care setting with each individual’s clinical needs and personal preferences, advancing a thorough, evidence-based, safe practice while protecting privacy and recognizing that patients’ expectations have changed following the pandemic. V1C puts the promise of digital health into practice. This is the blueprint for what good healthcare looks like in the digital era.
Digital Clinical Trials
Craig Lipset, Founder of Clinical Innovation Partners and former Head of Clinical Innovation at Pfizer
Craig Lipset
In 2021, a number of digital- and data-enabled approaches have sustained decentralized clinical trials around the world for many different disease types. Pharma companies and clinical researchers are enthusiastic about this development for good reason. Throughout the pandemic, these decentralized trials have allowed patients to continue in studies with a reduced need for site visits, without compromising their safety or data quality.
Risk-based monitoring was deployed using data and thoughtful algorithms to identify quality and safety issues without relying entirely on human monitors visiting research sites. Some trials used digital measures to ensure high quality data on target health outcomes that could be captured in ways that made the participants’ physical location irrelevant. More than three-quarters of research organizations, such as pharma and biotech, have accelerated their decentralized clinical trial strategies. Before COVID-19, 72 percent of trial sites “rarely or never” used telemedicine for trial participants; during COVID, 64 percent “sometimes, often or always” do.
While the research community does appreciate the tremendous hope and promise brought by these innovations, perhaps what has been under-appreciated is the culture shift toward thoughtful risk-taking and a willingness to embrace and adopt clinical trial innovations. These solutions existed before COVID, but the pandemic shifted the perception of risks versus benefits involved in these trials. If there is one breakthrough that is perhaps under-appreciated in life sciences clinical research today, it’s the power of this new culture of willingness and receptivity to outlast the pandemic. Perhaps the greatest loss to the research ecosystem would be if we lose the momentum with recent trial innovations and must wait for another global pandemic in order to see it again.
Designing Biology
Sudip Parikh, CEO of the American Association for the Advancement of Science and Executive Publisher of the Science family of journals
American Association for the Advancement of Science
As our understanding of basic biology has grown, we are fast approaching an era where it will be possible to design and direct biological machinery to create treatments, medicine, and materials. 2021 saw many breakthroughs in this area, three of which are listed below.
The understanding of the human microbiome is growing as is our ability to modify it. One example is the movement toward the notion of the “bug as the drug.” In June, scientists at the Brigham and Women’s Hospital published a paper showing that they had genetically engineered yeast – using CRISPR/Cas9 – to sense and treat inflammation in the body to relieve symptoms of irritable bowel syndrome in mice. This approach could potentially be used to address issues with your microbiome to treat other chronic conditions.
Another way in which we saw the application of basic biology discoveries to real world problems in 2021 is through groundbreaking research on synthetic biology. Several institutions and companies are pursuing this path. Ginkgo Bioworks, valued at $15 billion, already claims to engineer cells with assembly-line efficiency. Imagine the possibilities of programming cells and tissue to perform chemistry for the manufacturing process, inspired by the way your body does chemistry. That could mean cleaner, more controllable, and affordable ways to manufacture food, therapeutics, and other materials in a factory-like setting.
A final example: consider the possibility of leveraging the mechanics of your own body to deliver proteins as treatments, vaccines, and more. In 2021, several scientists accelerated research to apply the mRNA technology underlying COVID-19 vaccines to make and replace proteins that, when they’re missing or don’t work, cause rare conditions such as cystic fibrosis and multiple sclerosis.
These applications of basic biology to solve real world problems are exciting on their own, but their convergence with incredible advances in computing, materials, and drug delivery hold the promise of game-changing progress in health care and beyond.
Brain Biomarkers
David R. Walt, Professor of Biologically Inspired Engineering, Harvard Medical School, Brigham and Women’s Hospital, Wyss Institute at Harvard University
David Walt
2021 brought the first real hope for identifying biomarkers that can predict neurodegenerative disease. Multiple biomarkers (which are measurable indicators of the presence or severity of disease) were identified that can diagnose disease and that correlate with disease progression. Some of these biomarkers were detected in cerebrospinal fluid (CSF) but others were measured directly in blood by examining precursors of protein fibers.
The blood-brain barrier prevents many biomolecules from both exiting and entering the brain, so it has been a longstanding challenge to detect and identify biomarkers that signal changes in brain chemistry due to neurodegenerative disease. With the advent of omics-based approaches (an emerging field that encompasses genomics, epigenomics, transcriptomics, proteomics, and metabolomics), coupled with new ultrasensitive analytical methods, researchers are beginning to identify informative brain biomarkers. Such biomarkers portend our ability to detect earlier stages of disease when therapeutic intervention could be effective at halting progression.
In addition, these biomarkers should enable drug developers to monitor the efficacy of candidate drugs in the blood of participants enrolled in clinical trials aimed at slowing neurodegeneration. These biomarkers begin to move us away from relying on cognitive performance indicators and imaging—methods that do not directly measure the underlying biology of neurodegenerative disease. The identity of these biomarkers may also provide researchers with clues about the causes of neurodegenerative disease, which can serve as new targets for drug intervention.
Gene therapy helps restore teen’s vision for first time
Story by Freethink
For the first time, a topical gene therapy — designed to heal the wounds of people with “butterfly skin disease” — has been used to restore a person’s vision, suggesting a new way to treat genetic disorders of the eye.
The challenge: Up to 125,000 people worldwide are living with dystrophic epidermolysis bullosa (DEB), an incurable genetic disorder that prevents the body from making collagen 7, a protein that helps strengthen the skin and other connective tissues.Without collagen 7, the skin is incredibly fragile — the slightest friction can lead to the formation of blisters and scarring, most often in the hands and feet, but in severe cases, also the eyes, mouth, and throat.
This has earned DEB the nickname of “butterfly skin disease,” as people with it are said to have skin as delicate as a butterfly’s wings.
The gene therapy: In May 2023, the FDA approved Vyjuvek, the first gene therapy to treat DEB.
Vyjuvek uses an inactivated herpes simplex virus to deliver working copies of the gene for collagen 7 to the body’s cells. In small trials, 65 percent of DEB-caused wounds sprinkled with it healed completely, compared to just 26 percent of wounds treated with a placebo.
“It was like looking through thick fog.” -- Antonio Vento Carvajal.
The patient: Antonio Vento Carvajal, a 14 year old living in Florida, was one of the trial participants to benefit from Vyjuvek, which was developed by Pittsburgh-based pharmaceutical company Krystal Biotech.
While the topical gene therapy could help his skin, though, it couldn’t do anything to address the severe vision loss Antonio experienced due to his DEB. He’d undergone multiple surgeries to have scar tissue removed from his eyes, but due to his condition, the blisters keep coming back.
“It was like looking through thick fog,” said Antonio, noting how his impaired vision made it hard for him to play his favorite video games. “I had to stand up from my chair, walk over, and get closer to the screen to be able to see.”
The idea: Encouraged by how Antonio’s skin wounds were responding to the gene therapy, Alfonso Sabater, his doctor at the Bascom Palmer Eye Institute, reached out to Krystal Biotech to see if they thought an alternative formula could potentially help treat his patient’s eyes.
The company was eager to help, according to Sabater, and after about two years of safety and efficacy testing, he had permission, under the FDA’s compassionate use protocol, to treat Antonio’s eyes with a version of the topical gene therapy delivered as eye drops.
The results: In August 2022, Sabater once again removed scar tissue from Antonio’s right eye, but this time, he followed up the surgery by immediately applying eye drops containing the gene therapy.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy. Don’t be afraid.” -- Yunielkys “Yuni” Carvajal.
The vision in Antonio’s eye steadily improved. By about eight months after the treatment, it was just slightly below average (20/25) and stayed that way. In March 2023, Sabater performed the same procedure on his young patient’s other eye, and the vision in it has also steadily improved.
“I’ve seen the transformation in Antonio’s life,” said Sabater. “He’s always been a happy kid. Now he’s very happy. He can function pretty much normally. He can read, he can study, he can play video games.”
Looking ahead: The topical gene therapy isn’t a permanent fix — it doesn’t alter Antonio’s own genes, so he has to have the eye drops reapplied every month. Still, that’s far less invasive than having to undergo repeated surgeries.
Sabater is now working with Krystal Biotech to launch trials of the eye drops in other patients, and not just those with DEB. By changing the gene delivered by the therapy, he believes it could be used to treat other eye disorders that are far more common — Fuchs’ dystrophy, for example, affects the vision of an estimated 300 million people over the age of 30.
Antonio’s mother, Yunielkys “Yuni” Carvajal, meanwhile, has said that having her son be the first to receive the eye drops was “very scary,” but she’s hopeful others will take a chance on new gene therapies if given the opportunity.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy,” she said. “Don’t be afraid.”
Can AI chatbots help with eating disorders?
Her name was Tessa and she was there to help. That’s what Sharon Maxwell read, anyway. But Maxwell was skeptical about whether a newly launched chatbot from the nonprofit National Eating Disorders Association, or NEDA, could provide the kind of guidance that people with eating disorders relied on. Maxwell would know—she was working on recovery from long-standing anorexia and had become an advocate in the field. So Maxwell took a deep breath and asked, “Hi Tessa. How do you support folks with eating disorders?”
Tessa’s reply was immediate. “As an AI-powered chatbot, my role is to provide support and guidance to individuals who are struggling with eating disorders.”
So far, so good. Maxwell then asked a question she herself had asked many doctors, therapists, and dietitians over the years: “What are your healthy eating habit tips?” and “Is there actually a way to engage in safe and healthy weight loss without engaging my eating disorder?”
Then everything went off the rails. Tessa told Maxwell an unequivocal yes, and that “it’s important to approach weight loss with a balanced and realistic mindset,” and recommended eating whole foods and lean proteins to create a 500-1000 calorie per day deficit that would lead to a loss of 1-2 pounds per week. To most people, the advice sounds anodyne, but alarm bells sounded in Maxwell’s head.
“This is actively going to feed eating disorders,” Maxwell says. “Having a chatbot be the direct response to someone reaching out for support for an eating disorder instead of the helpline seems careless.”
“The scripts that are being fed into the chatbot are only going to be as good as the person who’s feeding them.” -- Alexis Conason.
According to several decades of research, deliberate weight loss in the form of dieting is a serious risk for people with eating disorders. Maxwell says that following medical advice like what Tessa prescribed was what triggered her eating disorder as a child. And Maxwell wasn’t the only one who got such advice from the bot. When eating disorder therapist Alexis Conason tried Tessa, she asked the AI chatbot many of the questions her patients had. But instead of getting connected to resources or guidance on recovery, Conason, too, got tips on losing weight and “healthy” eating.
“The scripts that are being fed into the chatbot are only going to be as good as the person who’s feeding them,” Conason says. “It’s important that an eating disorder organization like NEDA is not reinforcing that same kind of harmful advice that we might get from medical providers who are less knowledgeable.”
Maxwell’s post about Tessa on Instagram went viral, and within days, NEDA had scrubbed all evidence of Tessa from its website. The furor has raised any number of issues about the harm perpetuated by a leading eating disorder charity and the ongoing influence of diet culture and advice that is pervasive in the field. But for AI experts, bears and bulls alike, Tessa offers a cautionary tale about what happens when a still-immature technology is unfettered and released into a vulnerable population.
Given the complexity involved in giving medical advice, the process of developing these chatbots must be rigorous and transparent, unlike NEDA’s approach.
“We don’t have a full understanding of what’s going on in these models. They’re a black box,” says Stephen Schueller, a clinical psychologist at the University of California, Irvine.
The health crisis
In March 2020, the world dove head-first into a heavily virtual world as countries scrambled to try and halt the pandemic. Even with lockdowns, hospitals were overwhelmed by the virus. The downstream effects of these lifesaving measures are still being felt, especially in mental health. Anxiety and depression are at all-time highs in teens, and a new report in The Lancet showed that post-Covid rates of newly diagnosed eating disorders in girls aged 13-16 were 42.4 percent higher than previous years.
And the crisis isn’t just in mental health.
“People are so desperate for health care advice that they'll actually go online and post pictures of [their intimate areas] and ask what kind of STD they have on public social media,” says John Ayers, an epidemiologist at the University of California, San Diego.
For many people, the choice isn’t chatbot vs. well-trained physician, but chatbot vs. nothing at all.
I know a bit about that desperation. Like Maxwell, I have struggled with a multi-decade eating disorder. I spent my 20s and 30s bouncing from crisis to crisis. I have called suicide hotlines, gone to emergency rooms, and spent weeks-on-end confined to hospital wards. Though I have found recovery in recent years, I’m still not sure what ultimately made the difference. A relapse isn't improbably, given my history. Even if I relapsed again, though, I don’t know it would occur to me to ask an AI system for help.
For one, I am privileged to have assembled a stellar group of outpatient professionals who know me, know what trips me up, and know how to respond to my frantic texts. Ditto for my close friends. What I often need is a shoulder to cry on or a place to vent—someone to hear and validate my distress. What’s more, my trust in these individuals far exceeds my confidence in the companies that create these chatbots. The Internet is full of health advice, much of it bad. Even for high-quality, evidence-based advice, medicine is often filled with disagreements about how the evidence might be applied and for whom it’s relevant. All of this is key in the training of AI systems like ChatGPT, and many AI companies remain silent on this process, Schueller says.
The problem, Ayers points out, is that for many people, the choice isn’t chatbot vs. well-trained physician, but chatbot vs. nothing at all. Hence the proliferation of “does this infection make my scrotum look strange?” questions. Where AI can truly shine, he says, is not by providing direct psychological help but by pointing people towards existing resources that we already know are effective.
“It’s important that these chatbots connect [their users to] to provide that human touch, to link you to resources,” Ayers says. “That’s where AI can actually save a life.”
Before building a chatbot and releasing it, developers need to pause and consult with the communities they hope to serve.
Unfortunately, many systems don’t do this. In a study published last month in the Journal of the American Medical Association, Ayers and colleagues found that although the chatbots did well at providing evidence-based answers, they often didn’t provide referrals to existing resources. Despite this, in an April 2023 study, Ayers’s team found that both patients and professionals rated the quality of the AI responses to questions, measured by both accuracy and empathy, rather highly. To Ayers, this means that AI developers should focus more on the quality of the information being delivered rather than the method of delivery itself.
Many mental health professionals have months-long waitlists, which leaves individuals to deal with illnesses on their own.
Adobe Stock
The human touch
The mental health field is facing timing constraints, too. Even before the pandemic, the U.S. suffered from a shortage of mental health providers. Since then, the rates of anxiety, depression, and eating disorders have spiked even higher, and many mental health professionals report waiting lists that are months long. Without support, individuals are left to try and cope on their own, which often means their condition deteriorates even further.
Nor do mental health crises happen during office hours. I struggled the most late at night, long after everyone else had gone to bed. I needed support during those times when I was most liable to hurt myself, not in the mornings and afternoons when I was at work.
In this sense, a 24/7 chatbot makes lots of sense. “I don't think we should stifle innovation in this space,” Schueller says. “Because if there was any system that needs to be innovated, it's mental health services, because they are sadly insufficient. They’re terrible.”
But before building a chatbot and releasing it, Tina Hernandez-Boussard, a data scientist at Stanford Medicine, says that developers need to pause and consult with the communities they hope to serve. It requires a deep understanding of what their needs are, the language they use to describe their concerns, existing resources, and what kinds of topics and suggestions aren’t helpful. Even asking a simple question at the beginning of a conversation such as “Do you want to talk to an AI or a human?” could allow those individuals to pick the type of interaction that suits their needs, Hernandez-Boussard says.
NEDA did none of these things before deploying Tessa. The researchers who developed the online body positivity self-help program upon which Tessa was initially based created a set of online question-and-answer exercises to improve body image. It didn’t involve generative AI that could write its own answers. The bot deployed by NEDA did use generative AI, something that no one in the eating disorder community was aware of before Tessa was brought online. Consulting those with lived experience would have flagged Tessa’s weight loss and “healthy eating” recommendations, Conason says.
The question for healthcare isn’t whether to use AI, but how.
NEDA did not comment on initial Tessa’s development and deployment, but a spokesperson told Leaps.org that “Tessa will be back online once we are confident that the program will be run with the rule-based approach as it was designed.”
The tech and therapist collaboration
The question for healthcare isn’t whether to use AI, but how. Already, AI can spot anomalies on medical images with greater precision than human eyes and can flag specific areas of an image for a radiologist to review in greater detail. Similarly, in mental health, AI should be an add-on for therapy, not a counselor-in-a-box, says Aniket Bera, an expert on AI and mental health at Purdue University.
“If [AIs] are going to be good helpers, then we need to understand humans better,” Bera says. That means understanding what patients and therapists alike need help with and respond to.
One of the biggest challenges of struggling with chronic illness is the dehumanization that happens. You become a patient number, a set of laboratory values and test scores. Treatment is often dictated by invisible algorithms and rules that you have no control over or access to. It’s frightening and maddening. But this doesn’t mean chatbots don’t have any place in medicine and mental health. An AI system could help provide appointment reminders and answer procedural questions about parking and whether someone should fast before a test or a procedure. They can help manage billing and even provide support between outpatient sessions by offering suggestions for what coping skills to use, the best ways to manage anxiety, and point to local resources. As the bots get better, they may eventually shoulder more and more of the burden of providing mental health care. But as Maxwell learned with Tessa, it’s still no replacement for human interaction.
“I'm not suggesting we should go in and start replacing therapists with technologies,” Schueller says. Instead, he advocates for a therapist-tech collaboration. “The technology side and the human component—these things need to come together.”