Will COVID-19 Pave the Way For Home-Based Precision Medicine?
It looks like an ordinary toilet but it is anything but. The "smart toilet" is the diagnostic tool of the future, equipped with cameras that take snapshots of the users and their waste, motion sensors to analyze what's inside the urine and stool samples, and software that automatically sends data to a secure, cloud-based system that can be easily accessed by your family doctor.
"It's a way of doing community surveillance. If there is a second wave of infections in the future, we'll know right away."
Using urine "dipstick tests" similar to the home pregnancy strips, the smart toilet can detect certain proteins, immune system biomarkers and blood cells that indicate the presence of such diseases as infections, bladder cancer, and kidney failure.
The rationale behind this invention is that some of the best ways of detecting what's going on in our bodies is by analyzing the substances we excrete every day, our sweat, urine, saliva and yes, our feces. Instead of getting sporadic snapshots from doctor's visits once or twice a year, the smart toilet provides continuous monitoring of our health 24/7, so we can catch the tell-tale molecular signature of illnesses at their earliest and most treatable stages. A brainchild of Stanford University researchers, they're now working to add a COVID-19 detection component to their suite of technologies—corona virus particles can be spotted in stool samples—and hope to have the system available within the year.
"We can connect the toilet system to cell phones so we'll know the results within 30 minutes," says Seung-min Park, a lead investigator on the research team that devised this technology and a senior research scientist at the Stanford University School of Medicine. "The beauty of this technology is that it can continuously monitor even after this pandemic is over. It's a way of doing community surveillance. If there is a second wave of infections in the future, we'll know right away."
Experts believe that the COVID-19 pandemic will accelerate the widespread acceptance of in-home diagnostic tools such as this. "Shock events" like pandemics can be catalysts for sweeping changes in society, history shows us. The Black Death marked the end of feudalism and ushered in the Renaissance while the aftershocks of the Great Depression and two world wars in the 20th century led to the social safety net of the New Deal and NATO and the European Union. COVID-19 could fundamentally alter the way we deliver healthcare, abandoning the outdated 20th century brick and mortar fee-for-service model in favor of digital medicine. At-home diagnostics may be the leading edge of this seismic shift and the pandemic could accelerate the product innovations that allow for home-based medical screening.
"That's the silver lining to this devastation," says Dr. Leslie Saxon, executive director of the USC Center for Body Computing at the Keck School of Medicine in Los Angeles. As an interventional cardiologist, Saxon has spent her career devising and refining the implantable and wearable wireless devices that are used to treat and diagnose heart conditions and prevent sudden death. "This will open up innovation—research has been stymied by a lack of imagination and marriage to an antiquated model," she adds. "There are already signs this is happening—relaxing state laws about licensure, allowing physicians to deliver health care in non-traditional ways. That's a real sea change and will completely democratize medical information and diagnostic testing."
Ironically, diagnostics have long been a step-child of modern medicine, even though accurate and timely diagnostics play a crucial role in disease prevention, detection and management. "The delivery of health care has proceeded for decades with a blind spot: diagnostic errors—inaccurate or delayed diagnoses—persist throughout all settings of care and continue to harm an unacceptable number of patients," according to a 2015 National Academy of Medicine report. That same report found as many as one out of five adverse events in the hospital result from these errors and they contribute to 10 percent of all patient deaths.
The pandemic should alter the diagnostic landscape. We already have a wealth of wearable and implantable devices, like glucose sensors to monitor blood sugar levels for diabetics, Apple's smart watch, electrocardiogram devices that can detect heart arrythmias, and heart pacemakers.
The Food and Drug Administration is working closely with in-home test developers to make accurate COVID-19 diagnostic tools readily available and has so far greenlighted three at-home collection test kits. Two, LabCorp's and Everlywell's, use nasal swabs to take samples. The third one is a spit test, using saliva samples, that was devised by a Rutgers University laboratory in partnership with Spectrum Solutions and Accurate Diagnostic Labs.
The only way to safely reopen is through large scale testing, but hospitals and doctors' offices are no longer the safest places.
In fact, DIY diagnostic company Everlywell, an Austin, Texas- based digital health company, already offers more than 30 at-home kits for everything from fertility to food sensitivity tests. Typically, consumers collect a saliva or finger-prick blood sample, dispatch it in a pre-paid shipping envelope to a laboratory, and a physician will review the results and send a report to consumers' smartphones.
Thanks to advances in technology, samples taken at home can now be preserved long enough to arrive intact at diagnostic laboratories. The key is showing the agency "transport and shipping don't change or interfere with the integrity of the samples," says Dr. Frank Ong, Everlywell's chief medical and scientific officer.
Ong is keenly aware of the importance of saturation testing because of the lessons learned by colleagues fighting the SARS pandemic in his family's native Taiwan in 2003. "In the beginning, doctors didn't know what they were dealing with and didn't protect themselves adequately," he says. "But over two years, they learned the hard way that there needs to be enough testing, contact tracing of those who have been exposed, and isolation of people who test positive. The value of at-home testing is that it can be done on the kind of broad basis that needs to happen for our country to get back to work."
Because of the pandemic, new policies have removed some of the barriers that impeded the widespread adoption of home-based diagnostics and telemedicine. Physicians can now practice across state lines, get reimbursed for telemedicine visits and use FaceTime to communicate with their patients, which had long been considered taboo because of privacy issues. Doctors and patients are becoming more comfortable and realizing the convenience and benefits of being able to do these things virtually.
Added to this, the only way to safely reopen for business without triggering a second and perhaps even more deadly wave of sickness is through large-scale testing, but hospitals and doctors' offices are no longer the safest places. "We don't want people sitting in a waiting room who later find out they're positive, and potentially infected everyone, including doctors and nurses," says Dr. Kavita Patel, a physician in Washington, DC who served as a policy director in the Obama White House.
In-home testing avoids the risks of direct exposure to the virus for both patients and health care professionals, who can dispense with cumbersome protective gear to take samples, and also enables people without reliable transportation or child-care to learn their status. "At home testing can be a critical component of our country's overall testing strategy," says Dr. Shantanu Nundy, chief medical officer at Accolade Health and on the faculty of the Milken Institute School of Public Health at George Washington University. "Once we're back at work, we need to be much more targeted, and have much more access to data and controlling those outbreaks as tightly as possible. The best way to do that is by leapfrogging clinics and being able to deliver tests at home for people who are disenfranchised by the current system."
In the not-too-distant future, in-home diagnostics could be a key component of precision medicine, which is customized care tailored specifically to each patient's individual needs. Like Stanford's smart toilet prototype, these ongoing surveillance tools will gather health data, ranging from exposures to toxins and pollutions in the environment to biochemical activity, like rising blood pressure, signs of inflammation, failing kidneys or tiny cancerous tumors, and provide continuous real-time information.
"These can be deeply personalized and enabled by smart phones, sensors and artificial intelligence," says USC's Leslie Saxon. "We'll be seeing the floodgates opening to patients accessing medical services through the same devices that they access other things, and leveraging these tools for our health and to fine tune disease management in a model of care that is digitally enabled."
[Editor's Note: This article was originally published on June 8th, 2020 as part of a standalone magazine called GOOD10: The Pandemic Issue. Produced as a partnership among LeapsMag, The Aspen Institute, and GOOD, the magazine is available for free online.]
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.