COVID Vaccines Put Anti-Science Activists to Shame
It turns out that, despite the destruction and heartbreak caused by the COVID pandemic, there is a silver lining: Scientists from academia, government, and industry worked together and, using the tools of biotechnology, created multiple vaccines that surely will put an end to the worst of the pandemic sometime in 2021. In short, they proved that science works, particularly that which comes from industry. Though politicians and the public love to hate Big Ag and Big Pharma, everybody comes begging for help when the going gets tough.
The change in public attitude is tangible. A headline in the Financial Times declared, "Covid vaccines offer Big Pharma a chance of rehabilitation." In its analysis, the FT says that the pharmaceutical industry is widely reviled because of the high prices it charges for its drugs, among other things, but the speed with which the industry developed COVID vaccines may allow for its reputation to be refurbished.
The Media's Role in Promoting Anti-Biotech Activism
Of course, the media is partly to blame for the pharmaceutical industry's dismal reputation in the first place because of journalists' penchant for oversimplifying complicated stories and pinning blame on an easy scapegoat. While the pharmaceutical industry is far from angelic and places a hefty price tag on its products in the U.S., often gone unmentioned is the fact that high drug prices are the result of multiple factors, including lack of competition (even among generic drugs), foreign price controls that allow citizens of other countries to "free load" off of American consumers, and a deliberately opaque drug supply chain (that involves not only profit-maximizing pharmaceutical manufacturers but "middlemen" like distributors). But why delve into such nuance when it's easier to point to villains like Martin Shkreli?
Big Ag has been subjected to identical mistreatment by the media, with outlets such as the New York Times among the biggest offenders. One article it published compared pesticides to "Nazi-made sarin gas," and another spread misinformation about a high-profile biotech scientist. The website Undark, whose stated mission is "true journalistic coverage of the sciences," once published an opinion piece written by a person who works for an anti-GMO organization and another criticizing Monsanto for its reasonable efforts to defend itself from disinformation. These aren't cherry-picked examples. Overall, the media clearly has taken sides: Science is great, unless it's science from industry.
If the scientific community can use the powerful techniques of biotechnology to cure a previously unknown infectious disease in less than a year, then why shouldn't it be able to cure genetic diseases in humans?
Now, the very same media – which has portrayed the pharmaceutical and biotech industries in the worst possible light, often for political or ideological reasons – is wondering why so many Americans are reluctant to get a COVID vaccine. Perhaps their reportage has something to do with it.
Tech Strikes Back
For years, the agricultural, pharmaceutical, and biotech industries fought back, but to no avail. GMOs are feared, pharma is hated, and biotech is misunderstood. Regulatory red tape abounds. But that may be all about to change, not because of a clever PR campaign, but thanks to the successful coronavirus vaccines produced by the pharma/biotech industry.
All of the major vaccines were created using biotechnology, broadly defined as the use of living systems and organisms to develop products intended to improve human life or the planet. The Pfizer/BioNTech and Moderna vaccines rely on mRNA (messenger RNA), which is essentially a molecular "photocopy" of the more familiar genetic material DNA. The mRNA molecules were tweaked using biotech and then shown to be 95% effective at preventing COVID in human volunteers. The AstraZeneca/Oxford vaccine is based on an older technology that genetically modifies a harmless virus to resemble an immunological target, in this case, SARS-CoV-2. Their vaccine is 62% to 90% effective.
Even better, the pharma/biotech industry showed that it can work hand-in-hand with the government, for instance the FDA, to produce vaccines in record-breaking time. Operation Warp Speed provided some financing to facilitate this process. History will look back at this endeavor and likely conclude that the unprecedented level of cooperation to develop a vaccine in less than 12 months was one of the greatest triumphs in public health history. (The bungled slow rollout is another story.)
Perhaps the most important lesson that society will learn is that the scientific method works.
The pharma/biotech industry has thus gained tremendous momentum. For the first time it seems, those who are opposed to scientific progress and biotechnology are on the defensive. If the scientific community can use the powerful techniques of biotechnology to cure a previously unknown infectious disease in less than a year, then why shouldn't it be able to cure genetic diseases in humans? Or create genetically modified crops that are resistant to insects and drought? Or use genetically modified mosquitoes to help fight against killer diseases like malaria? The arguments against biotechnology have been made exponentially weaker by the success of the coronavirus vaccine.
Perhaps the most important lesson that society will learn is that the scientific method works. We observed (by collecting samples of an unknown virus and sequencing its genome), hypothesized (by predicting which parts of the virus would trigger an immune response), experimented (by recruiting tens of thousands of volunteers into clinical trials), and concluded (that the vaccines worked). It was a thing of pure beauty.
Thanks to all the players involved – from Big Government to Big Pharma – we are beginning the process of being rescued from a modern-day plague. Let us hope that this scientific success also deals a fatal blow to the forces of ignorance that have held back technological progress for decades.
[Editor's Note: LeapsMag is an editorially independent publication that receives program support from Leaps by Bayer. LeapsMag's founding in 2017 predates Bayer's acquisition of Monsanto in 2018. All content published on LeapsMag is strictly free of influence, censorship, and oversight from its corporate sponsor. Read more about LeapsMag's organizational independence here.]
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.