The U.S. must fund more biotech innovation – or other countries will catch up faster than you think
The U.S. has approximately 58 percent of the market share in the biotech sector, followed by China with 11 percent. However, this market share is the result of several years of previous research and development (R&D) – it is a present picture of what happened in the past. In the future, this market share will decline unless the federal government makes investments to improve the quality and quantity of U.S. research in biotech.
The effectiveness of current R&D can be evaluated in a variety of ways such as monies invested and the number of patents filed. According to the UNESCO Institute for Statistics, the U.S. spends approximately 2.7 percent of GDP on R&D ($476,459.0M), whereas China spends 2 percent ($346,266.3M). However, investment levels do not necessarily translate into goods that end up contributing to innovation.
Patents are a better indication of innovation. The biotech industry relies on patents to protect their investments, making patenting a key tool in the process of translating scientific discoveries that can ultimately benefit patients. In 2020, China filed 1,497,159 patents, a 6.9 percent increase in growth rate. In contrast, the U.S. filed 597,172, a 3.9 percent decline. When it comes to patents filed, China has approximately 45 percent of the world share compared to 18 percent for the U.S.
So how did we get here? The nature of science in academia allows scientists to specialize by dedicating several years to advance discovery research and develop new inventions that can then be licensed by biotech companies. This makes academic science critical to innovation in the U.S. and abroad.
Academic scientists rely on government and foundation grants to pay for R&D, which includes salaries for faculty, investigators and trainees, as well as monies for infrastructure, support personnel and research supplies. Of particular interest to academic scientists to cover these costs is government support such as Research Project Grants, also known as R01 grants, the oldest grant mechanism from the National Institutes of Health. Unfortunately, this funding mechanism is extremely competitive, as applications have a success rate of only about 20 percent. To maximize the chances of getting funded, investigators tend to limit the innovation of their applications, since a project that seems overambitious is discouraged by grant reviewers.
Considering the difficulty in obtaining funding, the limited number of opportunities for scientists to become independent investigators capable of leading their own scientific projects, and the salaries available to pay for scientists with a doctoral degree, it is not surprising that the U.S. is progressively losing its workforce for innovation.
This approach affects the future success of the R&D enterprise in the U.S. Pursuing less innovative work tends to produce scientific results that are more obvious than groundbreaking, and when a discovery is obvious, it cannot be patented, resulting in fewer inventions that go on to benefit patients. Even though there are governmental funding options available for scientists in academia focused on more groundbreaking and translational projects, those options are less coveted by academic scientists who are trying to obtain tenure and long-term funding to cover salaries and other associated laboratory expenses. Therefore, since only a small percent of projects gets funded, the likelihood of scientists interested in pursuing academic science or even research in general keeps declining over time.
Efforts to raise the number of individuals who pursue a scientific education are paying off. However, the number of job openings for those trainees to carry out independent scientific research once they graduate has proved harder to increase. These limitations are not just in the number of faculty openings to pursue academic science, which are in part related to grant funding, but also the low salary available to pay those scientists after they obtain their doctoral degree, which ranges from $53,000 to $65,000, depending on years of experience.
Thus, considering the difficulty in obtaining funding, the limited number of opportunities for scientists to become independent investigators capable of leading their own scientific projects, and the salaries available to pay for scientists with a doctoral degree, it is not surprising that the U.S. is progressively losing its workforce for innovation, which results in fewer patents filed.
Perhaps instead of encouraging scientists to propose less innovative projects in order to increase their chances of getting grants, the U.S. government should give serious consideration to funding investigators for their potential for success -- or the success they have already achieved in contributing to the advancement of science. Such a funding approach should be tiered depending on career stage or years of experience, considering that 42 years old is the median age at which the first R01 is obtained. This suggests that after finishing their training, scientists spend 10 years before they establish themselves as independent academic investigators capable of having the appropriate funds to train the next generation of scientists who will help the U.S. maintain or even expand its market share in the biotech industry for years to come. Patenting should be given more weight as part of the academic endeavor for promotion purposes, or governmental investment in research funding should be increased to support more than just 20 percent of projects.
Remaining at the forefront of biotech innovation will give us the opportunity to not just generate more jobs, but it will also allow us to attract the brightest scientists from all over the world. This talented workforce will go on to train future U.S. scientists and will improve our standard of living by giving us the opportunity to produce the next generation of therapies intended to improve human health.
This problem cannot rely on just one solution, but what is certain is that unless there are more creative changes in funding approaches for scientists in academia, eventually we may be saying “remember when the U.S. was at the forefront of biotech innovation?”
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.