Researchers Are Designing a Biosensor to Detect Viruses in Transit Hubs and Hospitals
The unprecedented scale and impact of the COVID-19 pandemic has caused scientists and engineers around the world to stop whatever they were working on and shift their research toward understanding a novel virus instead.
"We have confidence that we can use our system in the next pandemic."
For Guangyu Qiu, normally an environmental engineer at the Swiss Federal Laboratories for Materials Science and Technology, that means finding a clever way to take his work on detecting pollution in the air and apply it to living pathogens instead. He's developing a new type of biosensor to make disease diagnostics and detection faster and more accurate than what's currently available.
But even though this pandemic was the impetus for designing a new biosensor, Qiu actually has his eye on future disease outbreaks. He admits that it's unlikely his device will play a role in quelling this virus, but says researchers already need to be thinking about how to make better tools to fight the next one — because there will be a next one.
"In the last 20 years, there [have been] three different coronavirus [outbreaks] ... so we have to prepare for the coming one," Qiu says. "We have confidence that we can use our system in the next pandemic."
"A Really, Really Neat Idea"
His main concern is the diagnostic tool that's currently front and center for testing patients for SARS-Cov-2, the virus causing the novel coronavirus disease. The tool, called PCR (short for reverse transcription polymerase chain reaction), is the gold standard because it excels at detecting viruses in even very small samples of mucus. PCR can amplify genetic material in the limited sample and look for a genetic code matching the virus in question. But in many parts of the world, mucus samples have to be sent out to laboratories for that work, and results can take days to return. PCR is also notoriously prone to false positives and negatives.
"I read a lot of newspapers that report[ed] ... a lot of false negative or false positive results at the very beginning of the outbreak," Qiu says. "It's not good for protecting people to prevent further transmission of the disease."
So he set out to build a more sensitive device—one that's less likely to give you a false result. Qiu's biosensor relies on an idea similar to the dual-factor authentication required of anyone trying to access a secure webpage. Instead of verifying that a virus is really present by using one way of detecting genetic code, as with PCR, this biosensor asks for two forms of ID.
SARS-CoV-2 is what's called an RNA virus, which means it has a single strand of genetic code, unlike double-stranded DNA. Inside Qiu's biosensor are receptors with the complementary code for this particular virus' RNA; if the virus is present, its RNA will bind with the receptors, locking together like velcro. The biosensor also contains a prism and a laser that work together to verify that this RNA really belongs to SARS-CoV-2 by looking for a specific wavelength of light and temperature.
If the biosensor doesn't detect either, or only registers a match for one and not the other, then it can't produce a positive result. This multi-step authentication process helps make sure that the RNA binding with the receptors isn't a genetically similar coronavirus like SARS-CoV, known for its 2003 outbreak, or MERS-CoV, which caused an epidemic in 2012.
It could also be fitted to detect future novel viruses once their genomes are sequenced.
The dual-feature design of this biosensor "is a really, really neat idea that I have not seen before with other sensor technology," says Erin Bromage, a professor of infection and immunology at the University of Massachusetts Dartmouth; he was not involved in designing or testing Qiu's biosensor. "It makes you feel more secure that when you have a positive, you've really got a positive."
The light and temperature sensors are not in themselves new inventions, but the combination is a first. The part of the device that uses light to detect particles is actually central to Qiu's normal stream of environmental research, and is a versatile tool he's been working with for a long time to detect aerosols in the atmosphere and heavy metals in drinking water.
Bromage says this is a plus. "It's not high-risk in the sense that how they do this is unique, or not validated. They've taken aspects of really proven technology and sort of combined it together."
This new biosensor is still a prototype that will take at least another 12 months to validate in real world scenarios, though. The device is sound from a biological perspective and is sensitive enough to reliably detect SARS-CoV-2 — and to not be tricked by genetically similar viruses like SARS-CoV — but there is still a lot of engineering work that needs to be done in order for it to work outside the lab. Qiu says it's unlikely that the sensor will help minimize the impact of this pandemic, but the RNA receptors, prism, and laser inside the device can be customized to detect other viruses that may crop up in the future.
"If we choose another sequence—like SARS, like MERS, or like normal seasonal flu—we can detect other viruses, or even bacteria," Qiu says. "This device is very flexible."
It could also be fitted to detect future novel viruses once their genomes are sequenced.
The Long-Term Vision: Hospitals and Transit Hubs
The device has been designed to connect with two other systems: an air sampler and a microprocessor because the goal is to make it portable, and able to pick up samples from the air in hospitals or public areas like train stations or airports. A virus could hopefully be detected before it silently spreads and erupts into another global pandemic. In the case of SARS-CoV-2, there has been conflicting research about whether or not the virus is truly airborne (though it can be spread by droplets that briefly move through the air after a cough or sneeze), whereas the highly contagious RNA virus that causes measles can remain in the air for up to two hours.
"They've got a lot on the front end to work out," Bromage says. "They've got to work out how to capture and concentrate a virus, extract the RNA from the virus, and then get it onto the sensor. That's some pretty big hurdles, and may take some engineering that doesn't exist right now. But, if they can do that, then that works out really quite well."
One of the major obstacles in containing the COVID-19 pandemic has been in deploying accurate, quick tools that can be used for early detection of a virus outbreak and for later tracing its spread. That will still be true the next time a novel virus rears its head, and it's why Qiu feels that even if his biosensor can't help just yet, the research is still worth the effort.
It could also be fitted to detect future novel viruses once their genomes are sequenced.
The dual-feature design of this biosensor "is a really, really neat idea that I have not seen before with other sensor technology," says Erin Bromage, a professor of infection and immunology at the University of Massachusetts Dartmouth; he was not involved in designing or testing Qiu's biosensor. "It makes you feel more secure that when you have a positive, you've really got a positive."
The light and temperature sensors are not in themselves new inventions, but the combination is a first. The part of the device that uses light to detect particles is actually central to Qiu's normal stream of environmental research, and is a versatile tool he's been working with for a long time to detect aerosols in the atmosphere and heavy metals in drinking water.
Bromage says this is a plus. "It's not high-risk in the sense that how they do this is unique, or not validated. They've taken aspects of really proven technology and sort of combined it together."
This new biosensor is still a prototype that will take at least another 12 months to validate in real world scenarios, though. The device is sound from a biological perspective and is sensitive enough to reliably detect SARS-CoV-2 — and to not be tricked by genetically similar viruses like SARS-CoV — but there is still a lot of engineering work that needs to be done in order for it to work outside the lab. Qiu says it's unlikely that the sensor will help minimize the impact of this pandemic, but the RNA receptors, prism, and laser inside the device can be customized to detect other viruses that may crop up in the future.
"If we choose another sequence—like SARS, like MERS, or like normal seasonal flu—we can detect other viruses, or even bacteria," Qiu says. "This device is very flexible."
It could also be fitted to detect future novel viruses once their genomes are sequenced.
The Long-Term Vision: Hospitals and Transit Hubs
The device has been designed to connect with two other systems: an air sampler and a microprocessor because the goal is to make it portable, and able to pick up samples from the air in hospitals or public areas like train stations or airports. A virus could hopefully be detected before it silently spreads and erupts into another global pandemic. In the case of SARS-CoV-2, there has been conflicting research about whether or not the virus is truly airborne (though it can be spread by droplets that briefly move through the air after a cough or sneeze), whereas the highly contagious RNA virus that causes measles can remain in the air for up to two hours.
"They've got a lot on the front end to work out," Bromage says. "They've got to work out how to capture and concentrate a virus, extract the RNA from the virus, and then get it onto the sensor. That's some pretty big hurdles, and may take some engineering that doesn't exist right now. But, if they can do that, then that works out really quite well."
One of the major obstacles in containing the COVID-19 pandemic has been in deploying accurate, quick tools that can be used for early detection of a virus outbreak and for later tracing its spread. That will still be true the next time a novel virus rears its head, and it's why Qiu feels that even if his biosensor can't help just yet, the research is still worth the effort.
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.