Questions remain about new drug for hot flashes
Vascomotor symptoms (VMS) is the medical term for hot flashes associated with menopause. You are going to hear a lot more about it because a company has a new drug to sell. Here is what you need to know.
Menopause marks the end of a woman’s reproductive capacity. Normal hormonal production associated with that monthly cycle becomes erratic and finally ceases. For some women the transition can be relatively brief with only modest symptoms, while for others the body's “thermostat” in the brain is disrupted and they experience hot flashes and other symptoms that can disrupt daily activity. Lifestyle modification and drugs such as hormone therapy can provide some relief, but women at risk for cancer are advised not to use them and other women choose not to do so.
Fezolinetant, sold by Astellas Pharma Inc. under the product name Veozah™, was approved by the Food and Drug Administration (FDA) on May 12 to treat hot flashes associated with menopause. It is the first in a new class of drugs called neurokinin 3 receptor antagonists, which block specific neurons in the brain “thermostat” that trigger VMS. It does not appear to affect other symptoms of menopause. As with many drugs targeting a brain cell receptor, it must be taken continuously for a few days to build up a good therapeutic response, rather than working as a rescue product such as an asthma inhaler to immediately treat that condition.
Hot flashes vary greatly and naturally get better or resolve completely with time. That contributes to a placebo effect and makes it more difficult to judge the outcome of any intervention. Early this year, a meta analysis of 17 studies of drug trials for hot flashes found an unusually large placebo response in those types of studies; the placebo groups had an average of 5.44 fewer hot flashes and a 36 percent reduction in their severity.
In studies of fezolinetant, the drug recently approved by the FDA, the placebo benefit was strong and persistent. The drug group bested the placebo response to a statistically significant degree but, “If people have gone from 11 hot flashes a day to eight or seven in the placebo group and down to a couple fewer ones in the drug groups, how meaningful is that? Having six hot flashes a day is still pretty unpleasant,” says Diana Zuckerman, president of the National Center for Health Research (NCHR), a health oriented think tank.
“Is a reduction compared to placebo of 2-3 hot flashes per day, in a population of women experiencing 10-11 moderate to severe hot flashes daily, enough relief to be clinically meaningful?” Andrea LaCroix asked a commentary published in Nature Medicine. She is an epidemiologist at the University of California San Diego and a leader of the MsFlash network that has conducted a handful of NIH-funded studies on menopause.
Questions Remain
LaCroix and others have raised questions about how Astellas, the company that makes the new drug, handled missing data from patients who dropped out of the clinical trials. “The lack of detailed information about important parameters such as adherence and missing data raises concerns that the reported benefits of fezolinetant very likely overestimate those that will be observed in clinical practice," LaCroix wrote.
In response to this concern, Anna Criddle, director of global portfolio communications at Astellas, wrote in an email to Leaps.org: “…a full analysis of data, including adherence data and any impact of missing data, was submitted for assessment by [the FDA].”
The company ran the studies at more than 300 sites around the world. Curiously, none appear to have been at academic medical centers, which are known for higher quality research. Zuckerman says, "When somebody is paid to do a study, if they want to get paid to do another study by the same company, they will try to make sure that the results are the results that the company wants.”
Criddle said that Astellas picked the sites “that would allow us to reach a diverse population of women, including race and ethnicity.”
A trial of a lower dose of the drug was conducted in Asia. In March 2022, Astellas issued a press release saying it had failed to prove effectiveness. No further data has been released. Astellas still plans to submit the data, according to Criddle. Results from clinical trials funded by the U.S. goverment must be reported on clinicaltrials.gov within one year of the study's completion - a deadline that, in this case, has expired.
The measurement scale for hot flashes used in the studies, mild-moderate-severe, also came in for criticism. “It is really not good scale, there probably isn’t a broad enough range of things going on or descriptors,” says David Rind. He is chief medical officer of the Institute for Clinical and Economic Review (ICER), a nonprofit authority on new drugs. It conducted a thorough review and analysis of fezolinestant using then existing data gathered from conference abstracts, posters and presentations and included a public stakeholder meeting in December. A 252-page report was published in January, finding “considerable uncertainty about the comparative net health benefits of fezolinetant” versus hormone therapy.
Questions surrounding some of these issues might have been answered if the FDA had chosen to hold a public advisory committee meeting on fezolinetant, which it regularly does for first in class medicines. But the agency decided such a meeting was unnecessary.
Cost
There was little surprise when Astellas announced a list price for fezolinetant of $550 a month ($6000 annually) and a program of patient assistance to ease out of pocket expenses. The company had already incurred large expenses.
In 2017 Astellas purchased the company that originally developed fezolinetant for $534 million plus several hundred million in potential royalties. The drug company ran a "disease awareness” ad, Heat on the Street, hat aired during the Super Bowl in February, where 30 second ads cost about $7 million. Industry analysts have projected sales to be $1.9 billion by 2028.
ICER’s pre-approval evaluation said fezolinetant might "be considered cost-effective if priced around $2,000 annually. ... [It]will depend upon its price and whether it is considered an alternative to MHT [menopause hormone treatment] for all women or whether it will primarily be used by women who cannot or will not take MHT."
Criddle wrote that Astellas set the price based on the novelty of the science, the quality of evidence for the drug and its uniqueness compared to the rest of the market. She noted that an individual’s payment will depend on how much their insurance company decides to cover. “[W]e expect insurance coverage to increase over the course of the year and to achieve widespread coverage in the U.S. over time.”
Leaps.org wrote to and followed up with nine of the largest health insurers/providers asking basic questions about their coverage of fezolinetant. Only two responded. Jennifer Martin, the deputy chief consultant for pharmacy benefits management at the Department of Veterans Affairs, said the agency “covers all drugs from the date that they are launched.” Decisions on whether it will be included in the drug formulary and what if any copays might be required are under review.
“[Fezolinetant] will go through our standard P&T Committee [patient and treatment] review process in the next few months, including a review of available efficacy data, safety data, clinical practice guidelines, and comparison with other agents used for vasomotor symptoms of menopause," said Phil Blando, executive director of corporate communications for CVS Health.
Other insurers likely are going through a similar process to decide issues such as limiting coverage to women who are advised not to use hormones, how much copay will be required, and whether women will be required to first try other options or obtain approvals before getting a prescription.
Rind wants to see a few years of use before he prescribes fezolinetant broadly, and believes most doctors share his view. Nor will they be eager to fill out the additional paperwork required for women to participate in the Astellas patient assistance program, he added.
Safety
Astellas is marketing its drug by pointing out risks of hormone therapy, such as a recent paper in The BMJ, which noted that women who took hormones for even a short period of time had a 24 percent increased risk of dementia. While the percentage was scary, the combined number of women both on and off hormones who developed dementia was small. And it is unclear whether hormones are causing dementia or if more severe hot flashes are a marker for higher risk of developing dementia. This information is emerging only after 80 years of hundreds of millions of women using hormones.
In contrast, the label for fezolinetant prohibits “concomitant use with CYP1A2 inhibitors” and requires testing for liver and kidney function prior to initiating the drug and every three months thereafter. There is no human or animal data on use in a geriatric population, defined as 65 or older, a group that is likely to use the drug. Only a few thousand women have ever taken fezolinetant and most have used it for just a few months.
Options
A woman seeking relief from symptoms of menopause would like to see how fezolintant compares with other available treatment options. But Astellas did not conduct such a study and Andrea LaCroix says it is unlikely that anyone ever will.
ICER has come the closest, with a side-by-side analysis of evidence-based treatments and found that fezolinetant performed quite similarly and modestly as the others in providing relief from hot flashes. Some treatments also help with other symptoms of menopause, which fezolinetant does not.
There are many coping strategies that women can adopt to deal with hot flashes; one of the most common is dressing in layers (such as a sleeveless blouse with a sweater) that can be added or subtracted as conditions require. Avoiding caffeine, hot liquids, and spicy foods is another common strategy. “I stopped drinking hot caffeinated drinks…for several years, and you get out of the habit of drinking them,” says Zuckerman.
LaCroix curates those options at My Meno Plan, which includes a search function where you can enter your symptoms and identify which treatments might work best for you. It also links to published research papers. She says the goal is to empower women with information to make informed decisions about menopause.
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.
DNA gathered from animal poop helps protect wildlife
On the savannah near the Botswana-Zimbabwe border, elephants grazed contentedly. Nearby, postdoctoral researcher Alida de Flamingh watched and waited. As the herd moved away, she went into action, collecting samples of elephant dung that she and other wildlife conservationists would study in the months to come. She pulled on gloves, took a swab, and ran it all over the still-warm, round blob of elephant poop.
Sequencing DNA from fecal matter is a safe, non-invasive way to track and ultimately help protect over 42,000 species currently threatened by extinction. Scientists are using this DNA to gain insights into wildlife health, genetic diversity and even the broader environment. Applied to elephants, chimpanzees, toucans and other species, it helps scientists determine the genetic diversity of groups and linkages with other groups. Such analysis can show changes in rates of inbreeding. Populations with greater genetic diversity adapt better to changes and environmental stressors than those with less diversity, thus reducing their risks of extinction, explains de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
Analyzing fecal DNA also reveals information about an animal’s diet and health, and even nearby flora that is eaten. That information gives scientists broader insights into the ecosystem, and the findings are informing conservation initiatives. Examples include restoring or maintaining genetic connections among groups, ensuring access to certain foraging areas or increasing diversity in captive breeding programs.
Approximately 27 percent of mammals and 28 percent of all assessed species are close to dying out. The IUCN Red List of threatened species, simply called the Red List, is the world’s most comprehensive record of animals’ risk of extinction status. The more information scientists gather, the better their chances of reducing those risks. In Africa, populations of vertebrates declined 69 percent between 1970 and 2022, according to the World Wildlife Fund (WWF).
“We put on sterile gloves and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says Alida de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
“When people talk about species, they often talk about ecosystems, but they often overlook genetic diversity,” says Christina Hvilsom, senior geneticist at the Copenhagen Zoo. “It’s easy to count (individuals) to assess whether the population size is increasing or decreasing, but diversity isn’t something we can see with our bare eyes. Yet, it’s actually the foundation for the species and populations.” DNA analysis can provide this critical information.
Assessing elephants’ health
“Africa’s elephant populations are facing unprecedented threats,” says de Flamingh, the postdoc, who has studied them since 2009. Challenges include ivory poaching, habitat destruction and smaller, more fragmented habitats that result in smaller mating pools with less genetic diversity. Additionally, de Flamingh studies the microbial communities living on and in elephants – their microbiomes – looking for parasites or dangerous microbes.
Approximately 415,000 elephants inhabit Africa today, but de Flamingh says the number would be four times higher without these challenges. The IUCN Red List reports African savannah elephants are endangered and African forest elephants are critically endangered. Elephants support ecosystem biodiversity by clearing paths that help other species travel. Their very footprints create small puddles that can host smaller organisms such as tadpoles. Elephants are often described as ecosystems’ engineers, so if they disappear, the rest of the ecosystem will suffer too.
There’s a process to collecting elephant feces. “We put on sterile gloves (which we change for each sample) and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says de Flamingh. They rub a sample about the size of a U.S. quarter onto a paper card embedded with DNA preservation technology. Each card is air dried and stored in a packet of desiccant to prevent mold growth. This way, samples can be stored at room temperature indefinitely without the DNA degrading.
Earlier methods required collecting dung in bags, which needed either refrigeration or the addition of preservatives, or the riskier alternative of tranquilizing the animals before approaching them to draw blood samples. The ability to collect and sequence the DNA made things much easier and safer.
“Our research provides a way to assess elephant health without having to physically interact with elephants,” de Flamingh emphasizes. “We also keep track of the GPS coordinates of each sample so that we can create a map of the sampling locations,” she adds. That helps researchers correlate elephants’ health with geographic areas and their conditions.
Although de Flamingh works with elephants in the wild, the contributions of zoos in the United States and collaborations in South Africa (notably the late Professor Rudi van Aarde and the Conservation Ecology Research Unit at the University of Pretoria) were key in studying this method to ensure it worked, she points out.
Protecting chimpanzees
Genetic work with chimpanzees began about a decade ago. Hvilsom and her group at the Copenhagen Zoo analyzed DNA from nearly 1,000 fecal samples collected between 2003 and 2018 by a team of international researchers. The goal was to assess the status of the West African subspecies, which is critically endangered after rapid population declines. Of the four subspecies of chimpanzees, the West African subspecies is considered the most at-risk.
In total, the WWF estimates the numbers of chimpanzees inhabiting Africa’s forests and savannah woodlands at between 173,000 and 300,000. Poaching, disease and human-caused changes to their lands are their major risks.
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes.
“One of the threats is mining near the Nimba Mountains in Guinea,” a stronghold for the West African subspecies, Hvilsom says. The Nimba Mountains are a UNESCO World Heritage Site, but they are rich in iron ore, which is used to make the steel that is vital to the Asian construction boom. As she and colleagues wrote in a recent paper, “Many extractive industries are currently developing projects in chimpanzee habitat.”
Analyzing DNA allows researchers to identify individual chimpanzees more accurately than simply observing them, she says. Normally, field researchers would install cameras and manually inspect each picture to determine how many chimpanzees were in an area. But, Hvilsom says, “That’s very tricky. Chimpanzees move a lot and are fast, so it’s difficult to get clear pictures. Often, they find and destroy the cameras. Also, they live in large areas, so you need a lot of cameras.”
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes based upon DNA comparisons with other chimpanzee groups. The mining companies and builders are using this information to locate future roads where they won’t disrupt migration – a more effective solution than trying to build artificial corridors for wildlife.
“The current route cuts off communities of chimpanzees,” Hvilsom elaborates. That effectively prevents young adult chimps from joining other groups when the time comes, eventually reducing the currently-high levels of genetic diversity.
“The mining company helped pay for the genetics work,” Hvilsom says, “as part of its obligation to assess and monitor biodiversity and the effect of the mining in the area.”
Of 50 toucan subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching.
Identifying toucan families
Feces aren't the only substance researchers draw DNA samples from. Jeffrey Coleman, a Ph.D. candidate at the University of Texas at Austin relies on blood tests for studying the genetic diversity of toucans---birds species native to Central America and nearby regions. They live in the jungles, where they hop among branches, snip fruit from trees, toss it in the air and catch it with their large beaks. “Toucans are beautiful, charismatic birds that are really important to the ecosystem,” says Coleman.
Of their 50 subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching. “When people see these aesthetically pleasing birds, they’re motivated to care about conservation practices,” he points out.
Coleman works with the Dallas World Aquarium and its partner zoos to analyze DNA from blood draws, using it to identify which toucans are related and how closely. His goal is to use science to improve the genetic diversity among toucan offspring.
Specifically, he’s looking at sections of the genome of captive birds in which the nucleotides repeat multiple times, such as AGATAGATAGAT. Called microsatellites, these consecutively-repeating sections can be passed from parents to children, helping scientists identify parent-child and sibling-sibling relationships. “That allows you to make strategic decisions about how to pair (captive) individuals for mating...to avoid inbreeding,” Coleman says.
Jeffrey Coleman is studying the microsatellites inside the toucan genomes.
Courtesy Jeffrey Coleman
The alternative is to use a type of analysis that looks for a single DNA building block – a nucleotide – that differs in a given sequence. Called single nucleotide polymorphisms (SNPs, pronounced “snips”), they are very common and very accurate. Coleman says they are better than microsatellites for some uses. But scientists have already developed a large body of microsatellite data from multiple species, so microsatellites can shed more insights on relations.
Regardless of whether conservation programs use SNPs or microsatellites to guide captive breeding efforts, the goal is to help them build genetically diverse populations that eventually may supplement endangered populations in the wild. “The hope is that the ecosystem will be stable enough and that the populations (once reintroduced into the wild) will be able to survive and thrive,” says Coleman. History knows some good examples of captive breeding success.
The California condor, which had a total population of 27 in 1987, when the last wild birds were captured, is one of them. A captive breeding program boosted their numbers to 561 by the end of 2022. Of those, 347 of those are in the wild, according to the National Park Service.
Conservationists hope that their work on animals’ genetic diversity will help preserve and restore endangered species in captivity and the wild. DNA analysis is crucial to both types of efforts. The ability to apply genome sequencing to wildlife conservation brings a new level of accuracy that helps protect species and gives fresh insights that observation alone can’t provide.
“A lot of species are threatened,” Coleman says. “I hope this research will be a resource people can use to get more information on longer-term genealogies and different populations.”