The Promise of Pills That Know When You Swallow Them
Dr. Sara Browne, an associate professor of clinical medicine at the University of California, San Diego, is a specialist in infectious diseases and, less formally, "a global health person." She often travels to southern Africa to meet with colleagues working on the twin epidemics of HIV and tuberculosis.
"This technology, in my opinion, is an absolute slam dunk for tuberculosis."
Lately she has asked them to name the most pressing things she can help with as a researcher based in a wealthier country. "Over and over and over again," she says, "the only thing they wanted to know is whether their patients are taking the drugs."
Tuberculosis is one of world's deadliest diseases; every year there are 10 million new infections and more than a million deaths. When a patient with tuberculosis is prescribed medicine to combat the disease, adherence to the regimen is important not just for the individual's health, but also for the health of the community. Poor adherence can lead to lengthier and more costly treatment and, perhaps more importantly, to drug-resistant strains of the disease -- an increasing global threat.
Browne is testing a new method to help healthcare workers track their patients' adherence with greater precision—close to exact precision even. They're called digital pills, and they involve a patient swallowing medicine as they normally would, only the capsule contains a sensor that—when it contacts stomach acid—transmits a signal to a small device worn on or near the body. That device in turn sends a signal to the patient's phone or tablet and into a cloud-based database. The fact that the pill has been swallowed has therefore been recorded almost in real time, and notice is available to whoever has access to the database.
"This technology, in my opinion, is an absolute slam dunk for tuberculosis," Browne says. TB is much more prevalent in poorer regions of the world—in Sub-Saharan Africa, for example—than in richer places like the U.S., where Browne's studies thus far have taken place. But when someone is diagnosed in the U.S., because of the risk to others if it spreads, they will likely have to deal with "directly observed therapy" to ensure that they take their medicines correctly.
DOT, as it's called, requires the patient to meet with a healthcare worker several days a week, or every day, so that the medicine intake can be observed in person -- an expensive and time-consuming process. Still, the Centers for Disease Control and Prevention website says (emphasis theirs), "DOT should be used for ALL patients with TB disease, including children and adolescents. There is no way to accurately predict whether a patient will adhere to treatment without this assistance."
Digital pills can help with both the cost and time involved, and potentially improve adherence in places where DOT is impossibly expensive. With the sensors, you can monitor a patient's adherence without a healthcare worker physically being in the room. Patients can live their normal lives and if they miss a pill, they can receive a reminder by text or a phone call from the clinic or hospital. "They can get on with their lives," said Browne. "They don't need the healthcare system to interrupt them."
A 56-year-old patient who participated in one of Browne's studies when he was undergoing TB treatment says that before he started taking the digital pills, he would go to the clinic at least once every day, except weekends. Once he switched to digital pills, he could go to work and spend time with his wife and children instead of fighting traffic every day to get to the clinic. He just had to wear a small patch on his abdomen, which would send the signal to a tablet provided by Browne's team. When he returned from work, he could see the results—that he'd taken the pill—in a database accessed via the tablet. (He could also see his heart rate and respiratory rate.) "I could do my daily activities without interference," he said.
Dr. Peter Chai, a medical toxicologist and emergency medicine physician at Brigham and Women's Hospital in Boston, is studying digital pills in a slightly different context, to help fight the country's opioid overdose crisis. Doctors like Chai prescribe pain medicine, he says, but then immediately put the onus on the patient to decide when to take it. This lack of guidance can lead to abuse and addiction. Patients are often told to take the meds "as needed." Chai and his colleagues wondered, "What does that mean to patients? And are people taking more than they actually need? Because pain is such a subjective experience."
The patients "liked the fact that somebody was watching them."
They wanted to see what "take as needed" actually led to, so they designed a study with patients who had broken a bone and come to the hospital's emergency department to get it fixed. Those who were prescribed oxycodone—a pharmaceutical opioid for pain relief—got enough digital pills to last one week. They were supposed to take the pills as needed, or as many as three pills per day. When the pills were ingested, the sensor sent a signal to a card worn on a lanyard around the neck.
Chai and his colleagues were able to see exactly when the patients took the pills and how many, and to detect patterns of ingestion more precisely than ever before. They talked to the patients after the seven days were up, and Chai said most were happy to be taking digital pills. The patients saw it as a layer of protection from afar. "They liked the fact that somebody was watching them," Chai said.
Both doctors, Browne and Chai, are in early stages of studies with patients taking pre-exposure prophylaxis, medicines that can protect people with a high-risk of contracting HIV, such as injectable drug users. Without good adherence, patients leave themselves open to getting the virus. If a patient is supposed to take a pill at 2 p.m. but the digital pill sensor isn't triggered, the healthcare provider can have an automatic message sent as a reminder. Or a reminder to one of the patient's friends or loved ones.
"Like Swallowing Your Phone"?
Deven Desai, an associate professor of law and ethics at Georgia Tech, says that digital pills sound like a great idea for helping with patient adherence, a big issue that self-reporting doesn't fully solve. He likes the idea of a physician you trust having better information about whether you're taking your medication on time. "On the surface that's just cool," he says. "That's a good thing." But Desai, who formerly worked as academic research counsel at Google, said that some of the same questions that have come up in recent years with social media and the Internet in general also apply to digital pills.
"Think of it like your phone, but you swallowed it," he says. "At first it could be great, simple, very much about the user—in this case, the patient—and the data is going between you and your doctor and the medical people it ought to be going to. Wonderful. But over time, phones change. They become 'smarter.'" And when phones and other technologies become smarter, he says, the companies behind them tend to expand the type of data they collect, because they can. Desai says it will be crucial that prescribers be completely transparent about who is getting the patients' data and for what purpose.
"We're putting stuff in our body in good faith with our medical providers, and what if it turned out later that all of a sudden someone was data mining or putting in location trackers and we never knew about that?" Desai asks. "What science has to realize is if they don't start thinking about this, what could be a wonderful technology will get killed."
Leigh Turner, an associate professor at the University of Minnesota's Center for Bioethics, agrees with Desai that digital pills have great promise, and also that there are clear reasons to be concerned about their use. Turner compared the pills to credit cards and social media, in that the data from them can potentially be stolen or leaked. One question he would want answered before the pills were normalized: "What kind of protective measures are in place to make sure that personal information isn't spilling out and being acquired by others or used by others in unexpected and unwanted ways?"
If digital pills catch on, some experts worry that they may one day not be a voluntary technology.
Turner also wonders who will have access to the pills themselves. Only those who can afford both the medicine plus the smartphones that are currently required for their use? Or will people from all economic classes have access? If digital pills catch on, he also worries they may one day not be a voluntary technology.
"When it comes to digital pills, it's not something that's really being foisted on individuals. It's more something that people can be informed of and can choose to take or not to take," he says. "But down the road, I can imagine a scenario where we move away from purely voluntary agreements to it becoming more of an expectation."
He says it's easy to picture a scenario in which insurance companies demand that patient medicinal intake data be tracked and collected or else. Refuse to have your adherence tracked and you risk higher rates or even overall coverage. Maybe patients who don't take the digital pills suffer dire consequences financially or medically. "Maybe it becomes beneficial as much to health insurers and payers as it is to individual patients," Turner says.
In November 2017, the FDA approved the first-ever digital pill that includes a sensor, a drug called Abilify MyCite, made by Otsuka Pharmaceutical Company. The drug, which is yet to be released, is used to treat schizophrenia, bipolar disorder, and depression. With a built-in sensor developed by Proteus Digital Health, patients can give their doctors permission to see when exactly they are taking, or not taking, their meds. For patients with mental illness, the ability to help them stick to their prescribed regime can be life-saving.
But Turner wonders if Abilify is the best drug to be a forerunner for digital pills. Some people with schizophrenia might be suffering from paranoia, and perhaps giving them a pill developed by a large corporation that sends data from their body to be tracked by other people might not be the best idea. It could in fact exacerbate their sense of paranoia.
The Bottom Line: Protect the Data
We all have relatives who have pillboxes with separate compartments for each day of the week, or who carry pillboxes that beep when it's time to take the meds. But that's not always good enough for people with dementia, mental illness, drug addiction, or other life situations that make it difficult to remember to take their pills. Digital pills can play an important role in helping these people.
"The absolute principle here is that the data has to belong to the patient."
The one time the patient from Browne's study forgot to take his pills, he got a beeping reminder from his tablet that he'd missed a dose. "Taking a medication on a daily basis, sometimes we just forget, right?" he admits. "With our very accelerated lives nowadays, it helps us to remember that we have to take the medications. So patients are able to be on top of their own treatment."
Browne is convinced that digital pills can help people in developing countries with high rates of TB and HIV, though like Turner and Desai she cautions that patients' data must be protected. "I think it can be a tremendous technology for patient empowerment and I also think if properly used it can help the medical system to support patients that need it," she said. "But the absolute principle here is that the data has to belong to the patient."
Researchers probe extreme gene therapy for severe alcoholism
Story by Freethink
A single shot — a gene therapy injected into the brain — dramatically reduced alcohol consumption in monkeys that previously drank heavily. If the therapy is safe and effective in people, it might one day be a permanent treatment for alcoholism for people with no other options.
The challenge: Alcohol use disorder (AUD) means a person has trouble controlling their alcohol consumption, even when it is negatively affecting their life, job, or health.
In the U.S., more than 10 percent of people over the age of 12 are estimated to have AUD, and while medications, counseling, or sheer willpower can help some stop drinking, staying sober can be a huge struggle — an estimated 40-60 percent of people relapse at least once.
A team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
According to the CDC, more than 140,000 Americans are dying each year from alcohol-related causes, and the rate of deaths has been rising for years, especially during the pandemic.
The idea: For occasional drinkers, alcohol causes the brain to release more dopamine, a chemical that makes you feel good. Chronic alcohol use, however, causes the brain to produce, and process, less dopamine, and this persistent dopamine deficit has been linked to alcohol relapse.
There is currently no way to reverse the changes in the brain brought about by AUD, but a team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
To find out, they tested it in heavy-drinking monkeys — and the animals’ alcohol consumption dropped by 90% over the course of a year.
How it works: The treatment centers on the protein GDNF (“glial cell line-derived neurotrophic factor”), which supports the survival of certain neurons, including ones linked to dopamine.
For the new study, a harmless virus was used to deliver the gene that codes for GDNF into the brains of four monkeys that, when they had the option, drank heavily — the amount of ethanol-infused water they consumed would be equivalent to a person having nine drinks per day.
“We targeted the cell bodies that produce dopamine with this gene to increase dopamine synthesis, thereby replenishing or restoring what chronic drinking has taken away,” said co-lead researcher Kathleen Grant.
To serve as controls, another four heavy-drinking monkeys underwent the same procedure, but with a saline solution delivered instead of the gene therapy.
The results: All of the monkeys had their access to alcohol removed for two months following the surgery. When it was then reintroduced for four weeks, the heavy drinkers consumed 50 percent less compared to the control group.
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
The researchers then took the alcohol away for another four weeks, before giving it back for four. They repeated this cycle for a year, and by the end of it, the treated monkeys’ consumption had fallen by more than 90 percent compared to the controls.
“Drinking went down to almost zero,” said Grant. “For months on end, these animals would choose to drink water and just avoid drinking alcohol altogether. They decreased their drinking to the point that it was so low we didn’t record a blood-alcohol level.”
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
Looking ahead: Dopamine is involved in a lot more than addiction, so more research is needed to not only see if the results translate to people but whether the gene therapy leads to any unwanted changes to mood or behavior.
Because the therapy requires invasive brain surgery and is likely irreversible, it’s unlikely to ever become a common treatment for alcoholism — but it could one day be the only thing standing between people with severe AUD and death.
“[The treatment] would be most appropriate for people who have already shown that all our normal therapeutic approaches do not work for them,” said Grant. “They are likely to create severe harm or kill themselves or others due to their drinking.”
This article originally appeared on Freethink, home of the brightest minds and biggest ideas of all time.
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the book The Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.