A recent study by researchers at the University of Pennsylvania examined how CAR-T therapy helped Doug Olson beat a cancer death sentence for over a decade - and how it could work for more people.
Doug Olson was 49 when he was diagnosed with chronic lymphocytic leukemia, a blood cancer that strikes 21,000 Americans annually. Although the disease kills most patients within a decade, Olson’s case progressed more slowly, and courses of mild chemotherapy kept him healthy for 13 years. Then, when he was 62, the medication stopped working. The cancer had mutated, his doctor explained, becoming resistant to standard remedies. Harsher forms of chemo might buy him a few months, but their side effects would be debilitating. It was time to consider the treatment of last resort: a bone-marrow transplant.
Olson, a scientist who developed blood-testing instruments, knew the odds. There was only a 50 percent chance that a transplant would cure him. There was a 20 percent chance that the agonizing procedure—which involves destroying the patient’s marrow with chemo and radiation, then infusing his blood with donated stem cells—would kill him. If he survived, he would face the danger of graft-versus-host disease, in which the donor’s cells attack the recipient’s tissues. To prevent it, he would have to take immunosuppressant drugs, increasing the risk of infections. He could end up with pneumonia if one of his three grandchildren caught a sniffle. “I was being pushed into a corner,” Olson recalls, “with very little room to move.”
Soon afterward, however, his doctor revealed a possible escape route. He and some colleagues at the University of Pennsylvania’s Abramson Cancer Center were starting a clinical trial, he said, and Olson—still mostly symptom-free—might be a good candidate. The experimental treatment, known as CAR-T therapy, would use genetic engineering to turn his T lymphocytes (immune cells that guard against viruses and other pathogens) into a weapon against cancer.
In September 2010, technicians took some of Olson’s T cells to a laboratory, where they were programmed with new molecular marching orders and coaxed to multiply into an army of millions. When they were ready, a nurse inserted a catheter into his neck. At the turn of a valve, his soldiers returned home, ready to do battle.
“I felt like I’d won the lottery,” Olson says. But he was only the second person in the world to receive this “living drug,” as the University of Pennsylvania investigators called it. No one knew how long his remission would last.
Three weeks later, Olson was slammed with a 102-degree fever, nausea, and chills. The treatment had triggered two dangerous complications: cytokine release syndrome, in which immune chemicals inflame the patient’s tissues, and tumor lysis syndrome, in which toxins from dying cancer cells overwhelm the kidneys. But the crisis passed quickly, and the CAR-T cells fought on. A month after the infusion, the doctor delivered astounding news: “We can’t find any cancer in your body.”
“I felt like I’d won the lottery,” Olson says. But he was only the second person in the world to receive this “living drug,” as the University of Pennsylvania investigators called it. No one knew how long his remission would last.
An Unexpected Cure
In February 2022, the same cancer researchers reported a remarkable milestone: the trial’s first two patients had survived for more than a decade. Although Olson’s predecessor—a retired corrections officer named Bill Ludwig—died of COVID-19 complications in early 2021, both men had remained cancer-free. And the modified immune cells continued to patrol their territory, ready to kill suspected tumor cells the moment they arose.
“We can now conclude that CAR-T cells can actually cure patients with leukemia,” University of Pennsylvania immunologist Carl June, who spearheaded the development of the technique, told reporters. “We thought the cells would be gone in a month or two. The fact that they’ve survived 10 years is a major surprise.”
Even before the announcement, it was clear that CAR-T therapy could win a lasting reprieve for many patients with cancers that were once a death sentence. Since the Food and Drug Administration approved June’s version (marketed as Kymriah) in 2017, the agency has greenlighted five more such treatments for various types of leukemia, lymphoma, and myeloma. “Every single day, I take care of patients who would previously have been told they had no options,” says Rayne Rouce, a pediatric hematologist/oncologist at Texas Children’s Cancer Center. “Now we not only have a treatment option for those patients, but one that could potentially be the last therapy for their cancer that they’ll ever have to receive.”
Immunologist Carl June, middle, spearheaded development of the CAR-T therapy that gave patients Bill Ludwig, left, and Doug Olson, right, a lengthy reprieve on their terminal cancer diagnoses.
Penn Medicine
Yet the CAR-T approach doesn’t help everyone. So far, it has only shown success for blood cancers—and for those, the overall remission rate is 30 to 40 percent. “When it works, it works extraordinarily well,” says Olson’s former doctor, David Porter, director of Penn’s blood and bone marrow transplant program. “It’s important to know why it works, but it’s equally important to know why it doesn’t—and how we can fix that.”
The team’s study, published in the journal Nature, offers a wealth of data on what worked for these two patients. It may also hold clues for how to make the therapy effective for more people.
Building a Better T Cell
Carl June didn’t set out to cure cancer, but his serendipitous career path—and a personal tragedy—helped him achieve insights that had eluded other researchers. In 1971, hoping to avoid combat in Vietnam, he applied to the U.S. Naval Academy in Annapolis, Maryland. June showed a knack for biology, so the Navy sent him on to Baylor College of Medicine. He fell in love with immunology during a fellowship researching malaria vaccines in Switzerland. Later, the Navy deployed him to the Fred Hutchinson Cancer Research Center in Seattle to study bone marrow transplantation.
There, June became part of the first research team to learn how to culture T cells efficiently in a lab. After moving on to the National Naval Medical Center in the ’80s, he used that knowledge to combat the newly emerging AIDS epidemic. HIV, the virus that causes the disease, invades T cells and eventually destroys them. June and his post-doc Bruce Levine developed a method to restore patients’ depleted cell populations, using tiny magnetic beads to deliver growth-stimulating proteins. Infused into the body, the new T cells effectively boosted immune function.
In 1999, after leaving the Navy, June joined the University of Pennsylvania. His wife, who’d been diagnosed with ovarian cancer, died two years later, leaving three young children. “I had not known what it was like to be on the other side of the bed,” he recalls. Watching her suffer through grueling but futile chemotherapy, followed by an unsuccessful bone-marrow transplant, he resolved to focus on finding better cancer treatments. He started with leukemia—a family of diseases in which mutant white blood cells proliferate in the marrow.
Cancer is highly skilled at slipping through the immune system’s defenses. T cells, for example, detect pathogens by latching onto them with receptors designed to recognize foreign proteins. Leukemia cells evade detection, in part, by masquerading as normal white blood cells—that is, as part of the immune system itself.
June planned to use a viral vector no one had tried before: HIV.
To June, chimeric antigen receptor (CAR) T cells looked like a promising tool for unmasking and destroying the impostors. Developed in the early ’90s, these cells could be programmed to identify a target protein, and to kill any pathogen that displayed it. To do the programming, you spliced together snippets of DNA and inserted them into a disabled virus. Next, you removed some of the patient’s T cells and infected them with the virus, which genetically hijacked its new hosts—instructing them to find and slay the patient’s particular type of cancer cells. When the T cells multiplied, their descendants carried the new genetic code. You then infused those modified cells into the patient, where they went to war against their designated enemy.
Or that’s what happened in theory. Many scientists had tried to develop therapies using CAR-T cells, but none had succeeded. Although the technique worked in lab animals, the cells either died out or lost their potency in humans.
But June had the advantage of his years nurturing T cells for AIDS patients, as well as the technology he’d developed with Levine (who’d followed him to Penn with other team members). He also planned to use a viral vector no one had tried before: HIV, which had evolved to thrive in human T cells and could be altered to avoid causing disease. By the summer of 2010, he was ready to test CAR-T therapy against chronic lymphocytic leukemia (CLL), the most common form of the disease in adults.
Three patients signed up for the trial, including Doug Olson and Bill Ludwig. A portion of each man’s T cells were reprogrammed to detect a protein found only on B lymphocytes, the type of white blood cells affected by CLL. Their genetic instructions ordered them to destroy any cell carrying the protein, known as CD19, and to multiply whenever they encountered one. This meant the patients would forfeit all their B cells, not just cancerous ones—but regular injections of gamma globulins (a cocktail of antibodies) would make up for the loss.
After being infused with the CAR-T cells, all three men suffered high fevers and potentially life-threatening inflammation, but all pulled through without lasting damage. The third patient experienced a partial remission and survived for eight months. Olson and Ludwig were cured.
Learning What Works
Since those first infusions, researchers have developed reliable ways to prevent or treat the side effects of CAR-T therapy, greatly reducing its risks. They’ve also been experimenting with combination therapies—pairing CAR-T with chemo, cancer vaccines, and immunotherapy drugs called checkpoint inhibitors—to improve its success rate. But CAR-T cells are still ineffective for at least 60 percent of blood cancer patients. And they remain in the experimental stage for solid tumors (including pancreatic cancer, mesothelioma, and glioblastoma), whose greater complexity make them harder to attack.
The new Nature study offers clues that could fuel further advances. The Penn team “profiled these cells at a level where we can almost say, ‘These are the characteristics that a T cell would need to survive 10 years,’” says Rouce, the physician at Texas Children’s Cancer Center.
One surprising finding involves how CAR-T cells change in the body over time. At first, those that Olson and Ludwig received showed the hallmarks of “killer” T-cells (also known as CD8 cells)—highly active lymphocytes bent on exterminating every tumor cell in sight. After several months, however, the population shifted toward “helper” T-cells (or CD4s), which aid in forming long-term immune memory but are normally incapable of direct aggression. Over the years, the numbers swung back and forth, until only helper cells remained. Those cells showed markers suggesting they were too exhausted to function—but in the lab, they were able not only to recognize but to destroy cancer cells.
June and his team suspect that those tired-looking helper cells had enough oomph to kill off any B cells Olson and Ludwig made, keeping the pair’s cancers permanently at bay. If so, that could prompt new approaches to selecting cells for CAR-T therapy. Maybe starting with a mix of cell types—not only CD8s, but CD4s and other varieties—would work better than using CD8s alone. Or perhaps inducing changes in cell populations at different times would help.
Another potential avenue for improvement is starting with healthier cells. Evidence from this and other trials hints that patients whose T cells are more robust to begin with respond better when their cells are used in CAR-T therapy. The Penn team recently completed a clinical trial in which CLL patients were treated with ibrutinib—a drug that enhances T-cell function—before their CAR-T cells were manufactured. The response rate, says David Porter, was “very high,” with most patients remaining cancer-free a year after being infused with the souped-up cells.
Such approaches, he adds, are essential to achieving the next phase in CAR-T therapy: “Getting it to work not just in more people, but in everybody.”
Doug Olson enjoys nature - and having a future.
Penn Medicine
To grasp what that could mean, it helps to talk with Doug Olson, who’s now 75. In the years since his infusion, he has watched his four children forge careers, and his grandkids reach their teens. He has built a business and enjoyed the rewards of semi-retirement. He’s done volunteer and advocacy work for cancer patients, run half-marathons, sailed the Caribbean, and ridden his bike along the sun-dappled roads of Silicon Valley, his current home.
And in his spare moments, he has just sat there feeling grateful. “You don’t really appreciate the effect of having a lethal disease until it’s not there anymore,” he says. “The world looks different when you have a future.”
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.”