Nine experts break down the biggest biotech and health breakthroughs that didn't get the attention they deserved in 2022.
As the world has attempted to move on from COVID-19 in 2022, attention has returned to other areas of health and biotech with major regulatory approvals such as the Alzheimer's drug lecanemab – which can slow the destruction of brain cells in the early stages of the disease – being hailed by some as momentous breakthroughs.
This has been a year where psychedelic medicines have gained the attention of mainstream researchers with a groundbreaking clinical trial showing that psilocybin treatment can help relieve some of the symptoms of major depressive disorder. And with messenger RNA (mRNA) technology still very much capturing the imagination, the readouts of cancer vaccine trials have made headlines around the world.
But at the same time there have been vital advances which will likely go on to change medicine, and yet have slipped beneath the radar. I asked nine forward-thinking experts on health and biotech about the most important, but underappreciated, breakthrough of 2022.
Their descriptions, below, were lightly edited by Leaps.org for style and format.
New drug targets for Alzheimer’s disease
Professor Julie Williams, Director, Dementia Research Institute, Cardiff University
Genetics has changed our view of Alzheimer’s disease in the last five to six years. The beta amyloid hypothesis has dominated Alzheimer’s research for a long time, but there are multiple components to this complex disease, of which getting rid of amyloid plaques is one, but it is not the whole story. In April 2022, Nature published a paper which is the culmination of a decade’s worth of work - groups all over the world working together to identify 75 genes associated with risk of developing Alzheimer’s. This provides us with a roadmap for understanding the disease mechanisms.
For example, it is showing that there is something different about the immune systems of people who develop Alzheimer’s disease. There is something different about the way they process lipids in the brain, and very specific processes of how things travel through cells called endocytosis. When it comes to immunity, it indicates that the complement system is affecting whether synapses, which are the connections between neurons, get eliminated or not. In Alzheimer’s this process is more severe, so patients are losing more synapses, and this is correlated with cognition.
The genetics also implicates very specific tissues like microglia, which are the housekeepers in the brain. One of their functions is to clear away beta amyloid, but they also prune and nibble away at parts of the brain that are indicated to be diseased. If you have these risk genes, it seems that you are likely to prune more tissue, which may be part of the cell death and neurodegeneration that we observe in Alzheimer’s patients.
Genetics is telling us that we need to be looking at multiple causes of this complex disease, and we are doing that now. It is showing us that there are a number of different processes which combine to push patients into a disease state which results in the death of connections between nerve cells. These findings around the complement system and other immune-related mechanisms are very interesting as there are already drugs which are available for other diseases which could be repurposed in clinical trials. So it is really a turning point for us in the Alzheimer’s disease field.
Preventing Pandemics with Organ-Tissue Equivalents
Anthony Atala, Director of the Wake Forest Institute for Regenerative Medicine
COVID-19 has shown us that we need to be better prepared ahead of future pandemics and have systems in place where we can quickly catalogue a new virus and have an idea of which treatment agents would work best against it.
At Wake Forest Institute, our scientists have developed what we call organ-tissue equivalents. These are miniature tissues and organs, created using the same regenerative medicine technologies which we have been using to create tissues for patients. For example, if we are making a miniature liver, we will recreate this structure using the six different cell types you find in the liver, in the right proportions, and then the right extracellular matrix which holds the structure together. You're trying to replicate all the characteristics of the liver, but just in a miniature format.
We can now put these organ-tissue equivalents in a chip-like device, where we can expose them to different types of viral infections, and start to get a realistic idea of how the human body reacts to these viruses. We can use artificial intelligence and machine learning to map the pathways of the body’s response. This will allow us to catalogue known viruses far more effectively, and begin storing information on them.
Powering Deep Brain Stimulators with Breath
Islam Mosa, Co-Founder and CTO of VoltXon
Deep brain stimulation (DBS) devices are becoming increasingly common with 150,000 new devices being implanted every year for people with Parkinson’s disease, but also psychiatric conditions such as treatment-resistant depression and obsessive-compulsive disorders. But one of the biggest limitations is the power source – I call DBS devices energy monsters. While cardiac pacemakers use similar technology, their batteries last seven to ten years, but DBS batteries need changing every two to three years. This is because they are generating between 60-180 pulses per second.
Replacing the batteries requires surgery which costs a lot of money, and with every repeat operation comes a risk of infection, plus there is a lot of anxiety on behalf of the patient that the battery is running out.
My colleagues at the University of Connecticut and I, have developed a new way of charging these devices using the person’s own breathing movements, which would mean that the batteries never need to be changed. As the patient breathes in and out, their chest wall presses on a thin electric generator, which converts that movement into static electricity, charging a supercapacitor. This discharges the electricity required to power the DBS device and send the necessary pulses to the brain.
So far it has only been tested in a simulated pig, using a pig lung connected to a pump, but there are plans now to test it in a real animal, and then progress to clinical trials.
Smartwatches for Disease Detection
Jessilyn Dunn, Assistant Professor in Duke Biomedical Engineering
A group of researchers recently showed that digital biomarkers of infection can reveal when someone is sick, often before they feel sick. The team, which included Duke biomedical engineers, used information from smartwatches to detect Covid-19 cases five to 10 days earlier than diagnostic tests. Smartwatch data included aspects of heart rate, sleep quality and physical activity. Based on this data, we developed an algorithm to decide which people have the most need to take the diagnostic tests. With this approach, the percent of tests that come back positive are about four- to six-times higher, depending on which factors we monitor through the watches.
Our study was one of several showing the value of digital biomarkers, rather than a single blockbuster paper. With so many new ideas and technologies coming out around Covid, it’s hard to be that signal through the noise. More studies are needed, but this line of research is important because, rather than treat everyone as equally likely to have an infectious disease, we can use prior knowledge from smartwatches. With monkeypox, for example, you've got many more people who need to be tested than you have tests available. Information from the smartwatches enables you to improve how you allocate those tests.
Smartwatch data could also be applied to chronic diseases. For viruses, we’re looking for information about anomalies – a big change point in people’s health. For chronic diseases, it’s more like a slow, steady change. Our research lays the groundwork for the signals coming from smartwatches to be useful in a health setting, and now it’s up to us to detect more of these chronic cases. We want to go from the idea that we have this single change point, like a heart attack or stroke, and focus on the part before that, to see if we can detect it.
A Vaccine For RSV
Norbert Pardi, Vaccines Group Lead, Penn Institute for RNA Innovation, University of Pennsylvania
Scientists have long been trying to develop a vaccine for respiratory syncytial virus (RSV), and it looks like Pfizer are closing in on this goal, based on the latest clinical trial data in newborns which they released in November. Pfizer have developed a protein-based vaccine against the F protein of RSV, which they are giving to pregnant women. It turns out that it induces a robust immune response after the administration of a single shot and it seems to be highly protective in newborns. The efficacy was over 80% after 90 days, so it protected very well against severe disease, and even though this dropped a little after six month, it was still pretty high.
I think this has been a very important breakthrough, and very timely at the moment with both COVID-19, influenza and RSV circulating, which just shows the importance of having a vaccine which works well in both the very young and the very old.
The road to an RSV vaccine has also illustrated the importance of teamwork in 21st century vaccine development. You need people with different backgrounds to solve these challenges – microbiologists, immunologists and structural biologists working together to understand how viruses work, and how our immune system induces protective responses against certain viruses. It has been this kind of teamwork which has yielded the findings that targeting the prefusion stabilized form of the F protein in RSV induces much stronger and highly protective immune responses.
Gene therapy shows its potential
Nicole Paulk, Assistant Professor of Gene Therapy at the University of California, San Francisco
The recent US Food and Drug Administration (FDA) approval of Hemgenix, a gene therapy for hemophilia B, is big for a lot of reasons. While hemophilia is absolutely a rare disease, it is astronomically more common than the first two approvals – Luxturna for RPE65-meidated inherited retinal dystrophy and Zolgensma for spinal muscular atrophy - so many more patients will be treated with this. In terms of numbers of patients, we are now starting to creep up into things that are much more common, which is a huge step in terms of our ability to scale the production of an adeno-associated virus (AAV) vector for gene therapy.
Hemophilia is also a really special patient population because this has been the darling indication for AAV gene therapy for the last 20 to 30 years. AAV trafficks to the liver so well, it’s really easy for us to target the tissues that we want. If you look at the numbers, there have been more gene therapy scientists working on hemophilia than any other condition. There have just been thousands and thousands of us working on gene therapy indications for the last 20 or 30 years, so to see the first of these approvals make it, feels really special.
I am sure it is even more special for the patients because now they have a choice – do I want to stay on my recombinant factor drug that I need to take every day for the rest of my life, or right now I could get a one-time infusion of this virus and possibly experience curative levels of expression for the rest of my life. And this is just the first one for hemophilia, there’s going to end up being a dozen gene therapies within the next five years, targeted towards different hemophilias.
Every single approval is momentous for the entire field because it gets investors excited, it gets companies and physicians excited, and that helps speed things up. Right now, it's still a challenge to produce enough for double digit patients. But with more interest comes the experiments and trials that allow us to pick up the knowledge to scale things up, so that we can go after bigger diseases like diabetes, congestive heart failure, cancer, all of these much bigger afflictions.
Treating Thickened Hearts
John Spertus, Professor in Metabolic and Vascular Disease Research, UMKC School of Medicine
Hypertrophic cardiomyopathy (HCM) is a disease that causes your heart muscle to enlarge, and the walls of your heart chambers thicken and reduce in size. Because of this, they cannot hold as much blood and may stiffen, causing some sufferers to experience progressive shortness of breath, fatigue and ultimately heart failure.
So far we have only had very crude ways of treating it, using beta blockers, calcium channel blockers or other medications which cause the heart to beat less strongly. This works for some patients but a lot of time it does not, which means you have to consider removing part of the wall of the heart with surgery.
Earlier this year, a trial of a drug called mavacamten, became the first study to show positive results in treating HCM. What is remarkable about mavacamten is that it is directed at trying to block the overly vigorous contractile proteins in the heart, so it is a highly targeted, focused way of addressing the key problem in these patients. The study demonstrated a really large improvement in patient quality of life where they were on the drug, and when they went off the drug, the quality of life went away.
Some specialists are now hypothesizing that it may work for other cardiovascular diseases where the heart either beats too strongly or it does not relax well enough, but just having a treatment for HCM is a really big deal. For years we have not been very aggressive in identifying and treating these patients because there have not been great treatments available, so this could lead to a new era.
Regenerating Organs
David Andrijevic, Associate Research Scientist in neuroscience at Yale School of Medicine
As soon as the heartbeat stops, a whole chain of biochemical processes resulting from ischemia – the lack of blood flow, oxygen and nutrients – begins to destroy the body’s cells and organs. My colleagues and I at Yale School of Medicine have been investigating whether we can recover organs after prolonged ischemia, with the main goal of expanding the organ donor pool.
Earlier this year we published a paper in which we showed that we could use technology to restore blood circulation, other cellular functions and even heart activity in pigs, one hour after their deaths. This was done using a perfusion technology to substitute heart, lung and kidney function, and deliver an experimental cell protective fluid to these organs which aimed to stop cell death and aid in the recovery.
One of the aims of this technology is that it can be used in future to lengthen the time window for recovering organs for donation after a person has been declared dead, a logistical hurdle which would allow us to substantially increase the donor pool. We might also be able to use this cell protective fluid in studies to see if it can help people who have suffered from strokes and myocardial infarction. In future, if we managed to achieve an adequate brain recovery – and the brain, out of all the organs, is the most susceptible to ischemia – this might also change some paradigms in resuscitation medicine.
Antibody-Drug Conjugates for Cancer
Yosi Shamay, Cancer Nanomedicine and Nanoinformatics researcher at the Technion Israel Institute of Technology
For the past four or five years, antibody-drug conjugates (ADCs) - a cancer drug where you have an antibody conjugated to a toxin - have been used only in patients with specific cancers that display high expression of a target protein, for example HER2-positive breast cancer. But in 2022, there have been clinical trials where ADCs have shown remarkable results in patients with low expression of HER2, which is something we never expected to see.
In July 2022, AstraZeneca published the results of a clinical trial, which showed that an ADC called trastuzumab deruxtecan can offer a very big survival benefit to breast cancer patients with very little expression of HER2, levels so low that they would be borderline undetectable for a pathologist. They got a strong survival signal for patients with very aggressive, metastatic disease.
I think this is very interesting and important because it means that it might pave the way to include more patients in clinical trials looking at ADCs for other cancers, for example lymphoma, colon cancer, lung cancers, even if they have low expression of the protein target. It also holds implications for CAR-T cells - where you genetically engineer a T cell to attack the cancer - because the concept is very similar. If we now know that an ADC can have a survival benefit, even in patients with very low target expression, the same might be true for T cells.
Look back further: Breakthroughs of 2021
https://leaps.org/6-biotech-breakthroughs-of-2021-that-missed-the-attention-they-deserved/
Personalized nutrition apps could provide valuable data to people trying to eat healthier, though more research must be done to show effectiveness.
“We discovered that different foods spike people differently,” he says. “Some people spike to pasta, others to bread, others to bananas, and so on. It’s very personalized and our feeling was that building programs around these devices could be extremely powerful for better managing people’s glucose.”
Unbeknown to Snyder at the time, thousands of miles away, a group of Israeli scientists at the Weizmann Institute of Science were doing exactly the same experiments. In 2015, they published a landmark paper which used CGM to track the blood sugar levels of 800 people over several days, showing that the biological response to identical foods can vary wildly. Like Snyder, they theorized that giving people a greater understanding of their own glucose responses, so they spend more time in the normal range, may reduce the prevalence of type 2 diabetes.
The commercial potential of such apps is clear, but the underlying science continues to generate intriguing findings.
“At the moment 33 percent of the U.S. population is pre-diabetic, and 70 percent of those pre-diabetics will become diabetic,” says Snyder. “Those numbers are going up, so it’s pretty clear we need to do something about it.”
Fast forward to 2022,and both teams have converted their ideas into subscription-based dietary apps which use artificial intelligence to offer data-informed nutritional and lifestyle recommendations. Snyder’s spinoff, January AI, combines CGM information with heart rate, sleep, and activity data to advise on foods to avoid and the best times to exercise. DayTwo–a start-up which utilizes the findings of Weizmann Institute of Science–obtains microbiome information by sequencing stool samples, and combines this with blood glucose data to rate ‘good’ and ‘bad’ foods for a particular person.
“CGMs can be used to devise personalized diets,” says Eran Elinav, an immunology professor and microbiota researcher at the Weizmann Institute of Science in addition to serving as a scientific consultant for DayTwo. “However, this process can be cumbersome. Therefore, in our lab we created an algorithm, based on data acquired from a big cohort of people, which can accurately predict post-meal glucose responses on a personal basis.”
The commercial potential of such apps is clear. DayTwo, who market their product to corporate employers and health insurers rather than individual consumers, recently raised $37 million in funding. But the underlying science continues to generate intriguing findings.
Last year, Elinav and colleagues published a study on 225 individuals with pre-diabetes which found that they achieved better blood sugar control when they followed a personalized diet based on DayTwo’s recommendations, compared to a Mediterranean diet. The journal Cell just released a new paper from Snyder’s group which shows that different types of fibre benefit people in different ways.
“The idea is you hear different fibres are good for you,” says Snyder. “But if you look at fibres they’re all over the map—it’s like saying all animals are the same. The responses are very individual. For a lot of people [a type of fibre called] arabinoxylan clearly reduced cholesterol while the fibre inulin had no effect. But in some people, it was the complete opposite.”
Eight years ago, Stanford's Michael Snyder began studying how continuous glucose monitors could be used by patients to gain real-time updates on their blood sugar levels, transmitted directly to their phone.
The Snyder Lab, Stanford Medicine
Because of studies like these, interest in precision nutrition approaches has exploded in recent years. In January, the National Institutes of Health announced that they are spending $170 million on a five year, multi-center initiative which aims to develop algorithms based on a whole range of data sources from blood sugar to sleep, exercise, stress, microbiome and even genomic information which can help predict which diets are most suitable for a particular individual.
“There's so many different factors which influence what you put into your mouth but also what happens to different types of nutrients and how that ultimately affects your health, which means you can’t have a one-size-fits-all set of nutritional guidelines for everyone,” says Bruce Y. Lee, professor of health policy and management at the City University of New York Graduate School of Public Health.
With the falling costs of genomic sequencing, other precision nutrition clinical trials are choosing to look at whether our genomes alone can yield key information about what our diets should look like, an emerging field of research known as nutrigenomics.
The ASPIRE-DNA clinical trial at Imperial College London is aiming to see whether particular genetic variants can be used to classify individuals into two groups, those who are more glucose sensitive to fat and those who are more sensitive to carbohydrates. By following a tailored diet based on these sensitivities, the trial aims to see whether it can prevent people with pre-diabetes from developing the disease.
But while much hope is riding on these trials, even precision nutrition advocates caution that the field remains in the very earliest of stages. Lars-Oliver Klotz, professor of nutrigenomics at Friedrich-Schiller-University in Jena, Germany, says that while the overall goal is to identify means of avoiding nutrition-related diseases, genomic data alone is unlikely to be sufficient to prevent obesity and type 2 diabetes.
“Genome data is rather simple to acquire these days as sequencing techniques have dramatically advanced in recent years,” he says. “However, the predictive value of just genome sequencing is too low in the case of obesity and prediabetes.”
Others say that while genomic data can yield useful information in terms of how different people metabolize different types of fat and specific nutrients such as B vitamins, there is a need for more research before it can be utilized in an algorithm for making dietary recommendations.
“I think it’s a little early,” says Eileen Gibney, a professor at University College Dublin. “We’ve identified a limited number of gene-nutrient interactions so far, but we need more randomized control trials of people with different genetic profiles on the same diet, to see whether they respond differently, and if that can be explained by their genetic differences.”
Some start-ups have already come unstuck for promising too much, or pushing recommendations which are not based on scientifically rigorous trials. The world of precision nutrition apps was dubbed a ‘Wild West’ by some commentators after the founders of uBiome – a start-up which offered nutritional recommendations based on information obtained from sequencing stool samples –were charged with fraud last year. The weight-loss app Noom, which was valued at $3.7 billion in May 2021, has been criticized on Twitter by a number of users who claimed that its recommendations have led to them developed eating disorders.
With precision nutrition apps marketing their technology at healthy individuals, question marks have also been raised about the value which can be gained through non-diabetics monitoring their blood sugar through CGM. While some small studies have found that wearing a CGM can make overweight or obese individuals more motivated to exercise, there is still a lack of conclusive evidence showing that this translates to improved health.
However, independent researchers remain intrigued by the technology, and say that the wealth of data generated through such apps could be used to help further stratify the different types of people who become at risk of developing type 2 diabetes.
“CGM not only enables a longer sampling time for capturing glucose levels, but will also capture lifestyle factors,” says Robert Wagner, a diabetes researcher at University Hospital Düsseldorf. “It is probable that it can be used to identify many clusters of prediabetic metabolism and predict the risk of diabetes and its complications, but maybe also specific cardiometabolic risk constellations. However, we still don’t know which forms of diabetes can be prevented by such approaches and how feasible and long-lasting such self-feedback dietary modifications are.”
Snyder himself has now been wearing a CGM for eight years, and he credits the insights it provides with helping him to manage his own diabetes. “My CGM still gives me novel insights into what foods and behaviors affect my glucose levels,” he says.
He is now looking to run clinical trials with his group at Stanford to see whether following a precision nutrition approach based on CGM and microbiome data, combined with other health information, can be used to reverse signs of pre-diabetes. If it proves successful, January AI may look to incorporate microbiome data in future.
“Ultimately, what I want to do is be able take people’s poop samples, maybe a blood draw, and say, ‘Alright, based on these parameters, this is what I think is going to spike you,’ and then have a CGM to test that out,” he says. “Getting very predictive about this, so right from the get go, you can have people better manage their health and then use the glucose monitor to help follow that.”