New Options Are Emerging in the Search for Better Birth Control
A decade ago, Elizabeth Summers' options for birth control suddenly narrowed. Doctors diagnosed her with Factor V Leiden, a rare genetic disorder, after discovering blood clots in her lungs. The condition increases the risk of clotting, so physicians told Summers to stay away from the pill and other hormone-laden contraceptives. "Modern medicine has generally failed to provide me with an effective and convenient option," she says.
But new birth control options are emerging for women like Summers. These alternatives promise to provide more choices to women who can't ingest hormones or don't want to suffer their unpleasant side effects.
These new products have their own pros and cons. Still, doctors are welcoming new contraceptives following a long drought in innovation. "It's been a long time since we've had something new in the world of contraception," says Heather Irobunda, an obstetrician and gynecologist at NYC Health and Hospitals.
On social media, Irobunda often fields questions about one of these new options, a lubricating gel called Phexxi. San Diego-based Evofem, the company behind Phexxi, has been advertising the product on Hulu and Instagram after the gel was approved by the Food and Drug Administration in May 2020. The company's trendy ads target women who feel like condoms diminish the mood, but who also don't want to mess with an IUD or hormones.
Here's how it works: Phexxi is inserted via a tampon-like device up to an hour before sex. The gel regulates vaginal pH — essentially, the acidity levels — in a range that's inhospitable to sperm. It sounds a lot like spermicide, which is also placed in the vagina prior to sex to prevent pregnancy. But spermicide can damage the vagina's cell walls, which can increase the risk of contracting sexually transmitted diseases.
"Not only is innovation needed, but women want a non-hormonal option."
Phexxi isn't without side effects either. The most common one is vaginal burning, according to a late-stage trial. It's also possible to develop a urinary tract infection while using the product. That same study found that during typical use, Phexxi is about 86 percent effective at preventing pregnancy. The efficacy rate is comparable to condoms but lower than birth control pills (91 percent) and significantly lower than an IUD (99 percent).
Phexxi – which comes in a pack of 12 – represents a tiny but growing part of the birth control market. Pharmacies dispensed more than 14,800 packs from April through June this year, a 65 percent increase over the previous quarter, according to data from Evofem.
"We've been able to demonstrate that not only is innovation needed, but women want a non-hormonal option," says Saundra Pelletier, Evofem's CEO.
Beyond contraception, the company is carrying out late-stage tests to gauge Phexxi's effectiveness at preventing the sexually transmitted infections chlamydia and gonorrhea.
Phexxi is inserted via a tampon-like device up to an hour before sex.
Phexxi
A New Pill
The first birth control pill arrived in 1960, combining the hormones estrogen and progestin to stop sperm from joining with an egg, giving women control over their fertility. Subsequent formulations sought to ease side effects, by way of lower amounts of estrogen. But some women still experience headaches and nausea – or more serious complications like blood clots. On social media, women recently noted that birth control pills are much more likely to cause blood clots than Johnson & Johnson's COVID-19 vaccine that was briefly paused to evaluate the risk of clots in women under age 50. What will it take, they wondered, for safer birth control?
Mithra Pharmaceuticals of Belgium sought to create a gentler pill. In April, the FDA approved Mithra's Nextstellis, which includes a naturally occurring estrogen, the first new estrogen in the U.S. in 50 years. Nextstellis selectively acts on tissues lining the uterus, while other birth control pills have a broader target.
A Phase 3 trial showed a 98 percent efficacy rate. Andrew London, an obstetrician and gynecologist, who practices at several Maryland hospitals, says the results are in line with some other birth control pills. But, he added, early studies indicate that Nextstellis has a lower risk of blood clotting, along with other potential benefits, which additional clinical testing must confirm.
"It's not going to be worse than any other pill. We're hoping it's going to be significantly better," says London.
The estrogen in Nexstellis, called estetrol, was skipped over by the pharmaceutical industry after its discovery in the 1960s. Estetrol circulates between the mother and fetus during pregnancy. Decades later, researchers took a new look, after figuring out how to synthesize estetrol in a lab, as well as produce estetrol from plants.
"That allowed us to really start to investigate the properties and do all this stuff you have to do for any new drug," says Michele Gordon, vice president of marketing in women's health at Mayne Pharma, which licensed Nextstellis.
Bonnie Douglas, who followed the development of Nextstellis as part of a search for better birth control, recently switched to the product. "So far, it's much more tolerable," says Douglas. Previously, the Midwesterner was so desperate to find a contraceptive with fewer side effects that she turned to an online pharmacy to obtain a different birth control pill that had been approved in Canada but not in the U.S.
Contraceptive Access
Even if a contraceptive lands FDA approval, access poses a barrier. Getting insurers to cover new contraceptives can be difficult. For the uninsured, state and federal programs can help, and companies should keep prices in a reasonable range, while offering assistance programs. So says Kelly Blanchard, president of the nonprofit Ibis Reproductive Health. "For innovation to have impact, you want to reach as many folks as possible," she says.
In addition, companies developing new contraceptives have struggled to attract venture capital. That's changing, though.
In 2015, Sabrina Johnson founded DARÉ Bioscience around the idea of women's health. She estimated the company would be fully funded in six months, based on her track record in biotech and the demand for novel products.
But it's been difficult to get male investors interested in backing new contraceptives. It took Johnson two and a half years to raise the needed funds, via a reverse merger that took the company public. "There was so much education that was necessary," Johnson says, adding: "The landscape has changed considerably."
Johnson says she would like to think DARÉ had something to do with the shift, along with companies like Organon, a spinout of pharma company Merck that's focused on reproductive health. In surveying the fertility landscape, DARÉ saw limited non-hormonal options. On-demand options – like condoms – can detract from the moment. Copper IUDs must be inserted by a doctor and removed if a woman wants to return to fertility, and this method can have onerous side effects.
So, DARÉ created Ovaprene, a hormone-free device that's designed to be inserted into the vagina monthly by the user. The mesh product acts as a barrier, while releasing a chemical that immobilizes sperm. In an early study, the company reported that Ovaprene prevented almost all sperm from entering the cervical canal. The results, DARÉ believes, indicate high efficacy.
A late-stage study, slated to kick off next year, will be the true judge. Should Ovaprene eventually win regulatory approval, drug giant Bayer will handle commercializing the device.
Other new forms of birth control in development are further out, and that's assuming they perform well in clinical trials. Among them: a once-a-month birth control pill, along with a male version of the birth control pill. The latter is often brought up among women who say it's high time that men take a more proactive role in birth control.
For Summers, her search for a safe and convenient birth control continues. She tried Phexxi, which caused irritation. Still, she's excited that a non-hormonal option now exists. "I'm sure it will work for others," she says.
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.