How Can We Decide If a Biomedical Advance Is Ethical?
"All fixed, fast-frozen relations, with their train of ancient and venerable prejudices and opinions, are swept away, all new-formed ones become antiquated before they can ossify. All that is solid melts into air, all that is holy is profaned…"
On July 25, 1978, Louise Brown was born in Oldham, England, the first human born through in vitro fertilization, through the work of Patrick Steptoe, a gynecologist, and Robert Edwards, a physiologist. Her birth was greeted with strong (though not universal) expressions of ethical dismay. Yet in 2016, the latest year for which we have data, nearly two percent of the babies born in the United States – and around the same percentage throughout the developed world – were the result of IVF. Few, if any, think of these children as unnatural, monsters, or freaks or of their parents as anything other than fortunate.
How should we view Dr. He today, knowing that the world's eventual verdict on the ethics of biomedical technologies often changes?
On November 25, 2018, news broke that Chinese scientist, Dr. He Jiankui, claimed to have edited the genomes of embryos, two of whom had recently become the new babies, Lulu and Nana. The response was immediate and overwhelmingly negative.
Times change. So do views. How will Dr. He be viewed in 40 years? And, more importantly, how should we view him today, knowing that the world's eventual verdict on the ethics of biomedical technologies often changes? And when what biomedicine can do changes with vertiginous frequency?
How to determine what is and isn't ethical is above my pay grade. I'm a simple law professor – I can't claim any deeper insight into how to live a moral life than the millennia of religious leaders, philosophers, ethicists, and ordinary people trying to do the right thing. But I can point out some ways to think about these questions that may be helpful.
First, consider two different kinds of ethical commands. Some are quite specific – "thou shalt not kill," for example. Others are more general – two of them are "do unto others as you would have done to you" or "seek the greatest good for the greatest number."
Biomedicine in the last two centuries has often surprised us with new possibilities, situations that cultures, religions, and bodies of ethical thought had not previously had to consider, from vaccination to anesthesia for women in labor to genome editing. Sometimes these possibilities will violate important and deeply accepted precepts for a group or a person. The rise of blood transfusions around World War I created new problems for Jehovah's Witnesses, who believe that the Bible prohibits ingesting blood. The 20th century developments of artificial insemination and IVF both ran afoul of Catholic doctrine prohibiting methods other than "traditional" marital intercourse for conceiving children. If you subscribe to an ethical or moral code that contains prohibitions that modern biomedicine violates, the issue for you is stark – adhere to those beliefs or renounce them.
If the harms seem to outweigh the benefits, it's easy to conclude "this is worrisome."
But many biomedical changes violate no clear moral teachings. Is it ethical or not to edit the DNA of embryos? Not surprisingly, the sacred texts of various religions – few of which were created after, at the latest, the early 19th century, say nothing specific about this. There may be hints, precedents, leanings that could argue one way or another, but no "commandments." In that case, I recommend, at least as a starting point, asking "what are the likely consequences of these actions?"
Will people be, on balance, harmed or helped by them? "Consequentialist" approaches, of various types, are a vast branch of ethical theories. Personally I find a completely consequentialist approach unacceptable – I could not accept, for example, torturing an innocent child even in order to save many lives. But, in the absence of a clear rule, looking at the consequences is a great place to start. If the harms seem to outweigh the benefits, it's easy to conclude "this is worrisome."
Let's use that starting place to look at a few bioethical issues. IVF, for example, once proven (relatively) safe seems to harm no one and to help many, notably the more than 8 million children worldwide born through IVF since 1978 – and their 16 million parents. On the other hand, giving unknowing, and unconsenting, intellectually disabled children hepatitis A harmed them, for an uncertain gain for science. And freezing the heads of the dead seems unlikely to harm anyone alive (except financially) but it also seems almost certain not to benefit anyone. (Those frozen dead heads are not coming back to life.)
Now let's look at two different kinds of biomedical advances. Some are controversial just because they are new; others are controversial because they cut close to the bone – whether or not they violate pre-established ethical or moral norms, they clearly relate to them.
Consider anesthesia during childbirth. When first used, it was controversial. After all, said critics, in Genesis, the Bible says God told Eve, "I will greatly multiply Your pain in childbirth, In pain you will bring forth children." But it did not clearly prohibit pain relief and from the advent of ether on, anesthesia has been common, though not universal, in childbirth in western societies. The pre-existing ethical precepts were not clear and the consequences weighed heavily in favor of anesthesia. Similarly, vaccination seems to violate no deep moral principle. It was, and for some people, still is just strange, and unnatural. The same was true of IVF initially. Opposition to all of these has faded with time and familiarity. It has not disappeared – some people continue to find moral or philosophical problems with "unnatural" childbirth, vaccination, and IVF – but far fewer.
On the other hand, human embryonic stem cell research touches deeper issues. Human embryos are destroyed to make those stem cells. Reasonable people disagree on the moral status of the human embryo, and the moral weight of its destruction, but it does at least bring into play clear and broadly accepted moral precepts, such as "Thou shalt not kill." So, at the far side of an individual's time, does euthanasia. More exposure to, and familiarity with, these practices will not necessarily lead to broad acceptance as the objections involve more than novelty.
The first is "what would I do?" The second – what should my government, culture, religion allow or forbid?
Finally, all this ethical analysis must work at two levels. The first is "what would I do?" The second – what should my government, culture, religion allow or forbid? There are many things I would not do that I don't think should be banned – because I think other people may reasonably have different views from mine. I would not get cosmetic surgery, but I would not ban it – and will try not to think ill of those who choose it
So, how should we assess the ethics of new biomedical procedures when we know that society's views may change? More specifically, what should we think of He Jiankui's experiment with human babies?
First, look to see whether the procedure in question violates, at least fairly clearly, some rule in your ethical or moral code. If so, your choice may not be difficult. But if the procedure is unmentioned in your moral code, probably because it was inconceivable to the code's creators, examine the consequences of the act.
If the procedure is just novel, and not something that touches on important moral concerns, looking at the likely consequences may be enough for your ethical analysis –though it is always worth remembering that predicting consequences perfectly is impossible and predicting them well is never certain. If it does touch on morally significant issues, you need to think those issues through. The consequences may be important to your conclusions but they may not be determinative.
And, then, if you conclude that it is not ethical from your perspective, you need to take yet another step and consider whether it should be banned for people who do not share your perspective. Sometimes the answer will be yes – that psychopaths may not view murder as immoral does not mean we have to let them kill – but sometimes it will be no.
What does this say about He Jiankui's experiment? I have no qualms in condemning it, unequivocally. The potential risks to the babies grossly outweighed any benefits to them, and to science. And his secret work, against a near universal scientific consensus, privileged his own ethical conclusions without giving anyone else a vote, or even a voice.
But if, in ten or twenty years, genome editing of human embryos is shown to be safe (enough) and it is proposed to be used for good reasons – say, to relieve human suffering that could not be treated in other good ways – and with good consents from those directly involved as well as from the relevant society and government – my answer might well change. Yours may not. Bioethics is a process for approaching questions; it is not a set of universal answers.
This article opened with a quotation from the 1848 Communist Manifesto, referring to the dizzying pace of change from industrialization and modernity. You don't need to be a Marxist to appreciate that sentiment. Change – especially in the biosciences – keeps accelerating. How should we assess the ethics of new biotechnologies? The best we can, with what we know, at the time we inhabit. And, in the face of vast uncertainty, with humility.
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.