Your Prescription Is Ready for Download
You may be familiar with Moore's Law, the prediction made by Intel co-founder Gordon Moore that computer chips would get faster and cheaper with each passing year. That's been borne out by the explosive growth of the tech industry, but you may not know that there is an inverse Moore's Law for drug development.
What if there were a way to apply the fast-moving, low-cost techniques of software development to drug discovery?
Eroom's Law—yes that's "Moore" spelled backward—is the observation that drug discovery has become slower and more expensive over time, despite technological improvements. And just like Moore's Law, it's been borne out by experience—from the 1950s to today, the number of drugs that can be developed per billion dollars in spending has steadily decreased, contributing to the continued growth of health care costs.
But what if there were a way to apply the fast-moving, low-cost techniques of software development to drug discovery? That's what a group of startups in the new field of digital therapeutics are promising. They develop apps that are used—either on their own or in conjunction with conventional drugs—to treat chronic disorders like addiction, diabetes and mental health that have so far resisted a pharmaceutical approach. Unlike the thousands of wellness and health apps that can be downloaded to your phone, digital therapeutics are developed and are meant to be used like drugs, complete with clinical trials, FDA approval and doctor prescriptions.
The field is hot—in 2017 global investment in digital therapeutics jumped to $11.5 billion, a fivefold increase from 2012, and major pharma companies like Novartis are developing their own digital products or partnering with startups. One such startup is the bicoastal Pear Therapeutics. Last month, Pear's reSET-O product became the first digital therapeutic to be approved for use by the millions of Americans who struggle with opioid use disorder, and the company has other products addressing addiction and mental illness in the pipeline.
I spoke with Dr. Corey McCann, Pear's CEO, about the company's efforts to meld software and medicine, designing clinical trials for an entirely new kind of treatment, and the future of digital therapeutics.
The interview has been edited and condensed for clarity and length.
"We're looking at conditions that currently can't be cured with drugs."
BRYAN WALSH: What makes a digital therapeutic different than a wellness app?
COREY MCCANN: What we do is develop therapeutics that are designed to be used under the auspices of a physician, just as a drug developed under good manufacturing would be. We do clinical studies for both safety and efficacy, and then they go through the development process you'd expect for a drug. We look at the commercial side, at the role of doctors. Everything we do is what would be done with a traditional medical product. It's a piece of software developed like a drug.
WALSH: What kind of conditions are you first aiming to treat with digital therapeutics?
MCCANN: We're looking at conditions that currently can't be cured with drugs. A good example is our reSET product, which is designed to treat addiction to alcohol, cannabis, stimulants, cocaine. There really aren't pharmaceutical products that are approved to treat people addicted to these substances. What we're doing is functional therapy, the standard of care for addiction treatment, but delivered via software. But we can also work with medication—our reSET-O product is a great example. It's for patients struggling with opioid addiction, and it's delivered in concert with the drug buprenorphine.
WALSH: Walk me through what the patient experience would be like for someone on a digital therapeutic like reSET.
MCCANN: Imagine you're a patient who has been diagnosed with cocaine addiction by a doctor. You would then receive a prescription for reSET during the same office visit. Instead of a pharmacy, the script is sent to the reSET Connect Patient Service Center, where you are onboarded and given an access code that is used to unlock the product after downloading it onto your device. The product has 60 different modules—each one requiring about a 10 to 15-minute interaction—all derived from a form of cognitive behavioral therapy called community reinforcement approach. The treatment takes place over 90 days.
"The patients receiving the digital therapeutic were more than twice as likely to remain abstinent as those receiving standard care."
Patients report their substance abuse, cravings and triggers, and they are also tested on core proficiencies through the therapy. Physicians have access to all of their data, which helps facilitate their one-on-one meetings. We know from regular urine tests how effective the treatment is.
WALSH: What kind of data did you find when you did clinical studies on reSET?
MCCANN: We had 399 patients in 10 centers taking part in a randomized clinical trial run by the National Institute on Drug Abuse. Every patient enrolled in the study had an active substance abuse disorder. The study was randomized so that patients either received the best current standard of care, which is three hours a week of face-to-face therapy, or they received the digital therapeutic. The primary endpoint was abstinence in weeks 9 to 12—if the patient had a single dirty urine screen in the last month, they counted as a failure.
In the end, the patients receiving the digital therapeutic were more than twice as likely to remain abstinent as those receiving standard care—40 percent versus 17 percent. Those receiving reSET were also much more likely to remain in treatment through the entire trial.
WALSH: Why start by focusing your first digital therapeutics on addiction?
MCCANN: We have tried to build a company that is poised to make a difference in medicine. If you look at addiction, there is little to nothing in the drug pipeline to address this. More than 30 million people in the U.S. suffer from addiction disorders, and not only is efficacy a concern, but so is access. Many patients aren't able to receive anything like the kind of face-to-face therapy our control group received. So we think digital therapeutics can make a difference there as well.
WALSH: reSET was the first digital therapeutic approved by the FDA to treat a specific disorder. What has the approval process been like?
MCCANN: It's been a learning process for all involved, including the FDA. Our philosophy is to work within the clinical trials structure, which has specific disease targets and endpoints, and develop quality software, and bring those two strands together to generate digital therapeutics. We now have two products that have been FDA-approved, and four more in development. The FDA is appropriately cautious about all of this, balancing the tradeoff between patient risk and medical value. As we see it, our company is half tech and half biotech, and we follow regulatory trials that are as rigorous as they would be with any drug company.
"This is a new space, but when you look back in 10 years there will be an entire industry of prescription digital therapeutics."
WALSH: How do you balance those two halves, the tech side and the biology side? Tech companies are known for iterating rapidly and cheaply, while pharma companies develop drugs slowly and expensively.
MCCANN: This is a new space, but when you look back in 10 years there will be an entire industry of prescription digital therapeutics. Right now for us we're combining the rigor of the pharmaceutical model with the speed and agility of a tech company. Our product takes longer to develop than an unverified health app, but less time and with less clinical risk than a new molecular entity. This is still a work in progress and not a day goes by where we don't notice the difference between those disciplines.
WALSH: Who's going to pay for these treatments? Insurers are traditionally slow to accept new innovations in the therapeutic space.
MCCANN: This is just like any drug launch. We need to show medical quality and value, and we need to get clinician demand. We want to focus on demonstrating as many scripts as we can in 2019. And we know we'll need to be persistent—we live in a world where payers will say no to anything three times before they say yes. Demonstrating value is how you get there.
WALSH: Is part of that value the possibility that digital therapeutics could be much cheaper than paying someone for multiple face-to-face therapy sessions?
MCCANN: I believe the cost model is very compelling here, especially when you can treat diseases that were not treatable before. That is something that creates medical value. Then you have the data aspect, which makes our product fundamentally different from a drug. We know everything about every patient that uses our product. We know engagement, we can push patient self-reports to clinicians. We can measure efficiency out in the real world, not just in a measured clinical trial. That is the holy grail in the pharma world—to understand compliance in practice.
WALSH: What's the future of digital therapeutics?
MCCANN: In 10 years, what we think of as digital medicine will just be medicine. This is something that will absolutely become standard of care. We are working on education to help partners and payers figure out where go from here, and to incorporate digital therapeutics into standard care. It will start in 2019 and 2020 with addiction medicine, and then in three to five years you'll see treatments designed to address disorders of the brain. And then past the decade horizon you'll see plenty of products that aim at every facet of medicine.
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.