23andMe Is Using Customers’ Genetic Data to Develop Drugs. Is This Brilliant or Dubious?
Leading direct-to-consumer (DTC) genetic testing companies are continuously unveiling novel ways to leverage their vast stores of genetic data.
"23andMe will tell you what diseases you have and then sell you the drugs to treat them."
As reported last week, 23andMe's latest concept is to develop and license new drugs using the data of consumers who have opted in to let their information be used for research. To date, over 10 million people have used the service and around 80 percent have opted in, making its database one of the largest in the world.
Culture researcher Dr. Julia Creet is one of the foremost experts on the DTC genetic testing industry, and in her forthcoming book, The Genealogical Sublime, she bluntly examines whether such companies' motives and interests are in sync with those of consumers.
Leapsmag caught up with Creet about the latest news and the wider industry's implications for health and privacy.
23andMe has just announced that it plans to license a newly developed anti-inflammatory drug, the first one created using its customers' genetic data, to Almirall, a pharma company in Spain. What's your take?
I think this development is the next step in the evolution of the company and its "double-sided" marketing model. In the past, as it enticed customers to give it their DNA, it sold the results and the medical information divulged by customers to other drug companies. Now it is positioning itself to reap the profits of a new model by developing treatments itself.
Given that there are many anti-inflammatory drugs on the market already, whatever Almirall produces might not have much of an impact. We might see this canny move as a "proof of concept," that 23andMe has learned how to "leverage" its genetic data without having to sell them to a third party. In a way, the privacy provisions will be much less complicated, and the company stands to attract investment as it turns itself into [a pseudo pharmaceutical company], a "pharma-psuedocal" company.
Emily Drabant Conley, the president of business development, has said that 23andMe is pursuing other drug compounds and may conduct their own clinical trials rather than licensing them out to their existing research partners. The end goal, it seems, is to make direct-to-consumer DNA testing to drug production and sales back to that same consumer base a seamless and lucrative circle. You have to admit it's a brilliant business model. 23andMe will tell you what diseases you have and then sell you the drugs to treat them.
In your new book, you describe how DTC genetic testing companies have capitalized on our innate human desire to connect with or ancestors and each other. I quote you: "This industry has taken that potent, spiritual, all-too-human need to belong... and monetized it in a particularly exploitative way." But others argue that DTC genetic testing companies are merely providing a service in exchange for fair-market compensation. So where does exploitation come into the picture?
Yes, the industry provides a fee for service, but that's only part of the story. The rest of the story reveals a pernicious industry that hides its business model behind the larger science project of health and heredity. All of the major testing companies play on the idea of "lack," that we can't know who we are unless we buy information about ourselves. When you really think about it, "Who do you think you are?" is a pernicious question that suggests that we don't or can't know who we or to whom we are related without advanced data searches and testing. This existential question used to be a philosophical question; now the answers are provided by databases that acquire more valuable information than they provide in the exchange.
"It's a brilliant business model that exploits consumer naiveté."
As you've said before, consumers are actually paying to be the product because the companies are likely to profit more from selling their genetic data. Could you elaborate?
The largest databases, AncestryDNA and 23andMe, have signed lucrative agreements with biotech companies that pay them for the de-identified data of their customers. What's so valuable is the DNA combined with the family relationships. Consumers provide the family relationships and the companies link and extrapolate the results to larger and larger family trees. Combined with the genetic markers for certain diseases, or increased susceptibility to certain diseases, these databases are very valuable for biotech research.
None of that value will ever be returned to consumers except in the form of for-profit drugs. Ancestry, in particular, has removed all information about its "research partners" from its website, making it very difficult to see how it is profiting from its third-party sales. 23andMe is more open about its "two-sided business model," but encourages consumers to donate their information to science. It's a brilliant business model that exploits consumer naiveté.
A WIRED journalist wrote that "23andMe has been sharing insights gleaned from consented customer data with GSK and at least six other pharmaceutical and biotechnology firms for the past three and a half years." Is this a consumer privacy risk?
I don't see that 23andMe did anything to which consumers didn't consent, albeit through arguably unreadable terms and conditions. The part that worries me more is the 300 phenotype data points that the company has collected on its consumers through longitudinal surveys designed, as Anne Wojcicki, CEO and Co-founder of 23andMe, put it, "to circumvent medical records and just self-report."
Everyone is focused on the DNA, but it's the combination of genetic samples, genealogical information and health records that is the most potent dataset, and 23andMe has figured out a way to extract all three from consumers.
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.