Posts with «health care industry» label

Research indicates that carbon dioxide removal plans will not be enough to meet Paris treaty goals

New research conducted by the University of East Anglia (UEA) suggests that current carbon removal plans will not be enough to comply with Paris treaty goals to limit global warming to 1.5C, as reported in a study published by Nature. Scientists came to this conclusion by measuring the “emissions gap” between various national climate protection plans and what is actually needed to reach that goal.

This first-of-its-kind study found a gap of up to 3.2 billion tons of carbon dioxide (CO2) between current global plans to remove carbon from the atmosphere and what’s needed by 2050 to avoid the worst impacts of global warming. These impacts include heatwaves, floods, droughts, melting ice and sea level rise.

Since 2010, the United Nations environmental organization UNEP has taken similar measurements of this emissions gap. UEA’s research, which focuses primarily on CO2 removal, indicates that climate policy requires a more ambitious scope if we are to, well, survive as a species.

This means a more nuanced and robust approach that still keeps current carbon removal practices in place, but with a renewed focus on cutting emissions, renewable energy and minimizing deforestation. There are also novel carbon removal options that many nations have been slow to discuss, let alone implement.

These include advanced air filters systems and enhanced rock weathering. The latter is a technique in which carbon is removed from the atmosphere and stored in rocks. These techniques account for the removal of just 0.002 billion tons of C02 per year, compared to 3 billion tons through conventional options. The research indicates that these novel options must become more prevalent in the coming years to help meet that 1.5C threshold.

“The calculation should certainly be refined,” said the study’s lead author, Dr. William Lamb, of the MCC Applied Sustainability Science working group. “This much is clear: without a rapid reduction in emissions towards zero, across all sectors, the 1.5C limit will not be met under any circumstances.”

Co-author Dr. Naomi Vaughan, of the Tyndall Centre for Climate Change Research at UEA, added that “countries need more awareness, ambition and action on scaling up carbon dioxide removal methods together with deep emissions reductions to achieve the aspirations of the Paris Agreement."

To that end, even if every country sticks to promises regarding carbon removal targets, the amount of carbon removed would likely increase by a maximum of 0.5 billion tons by 2030 and 1.9 billion tons by 2050. The latest Intergovernmental Panel on Climate Change (IPCC) reported that it would take a removal increase of 5.1 billion tons to avoid the worst effects of climate change. So, yeah, there’s that gap of 3.2 billion tons.

We aren’t doomed, at least not yet anyways. The IPCC suggests an alternative scenario in which the world’s governments work together to reduce global energy demand, hastened by “politically initiated behavior.” In this scenario, carbon removal would increase by 2.5 billion tons by 2050 and alternative methods would help tighten the emissions gap to just 400 million tons. So we basically have to shift our entire society from one of self interest to one of global cooperation. It never hurts to dream and, hey, maybe AI will swoop in and save us

This article originally appeared on Engadget at

Razer will refund Zephyr mask buyers due to bogus N95 claims

Razer has to pay over $1.1 million to the Federal Trade Commission to settle complaints that it advertised its infamous Zephyr masks as N95-grade when it didn't get them certified at all. The gaming peripheral maker released Zephyr, its high-tech face mask with built-in RGB lighting, during the height of the pandemic. Half a year later, in early 2022, it introduced a "Pro" version that added voice amplification. Razer said back then the Zephyr was as effective as an N95 mask, but it later reneged on its claim and removed all references to "N95-grade" filters from its website and other marketing materials after it came out that the company didn't obtain proper certification. 

According to the FTC, Razer never submitted the Zephyr masks for testing to the FDA or the National Institute for Occupational Safety and Health (NIOSH), which gives out the official certification for masks that filter out 95 percent of airborne particles. Razer certainly isn't in the list of companies that manufacture N95 masks approved by NIOSH on its website. In the FTC's complaint, it accused Razer of only stopping its false advertising after consumer outrage. 

The company has to hand over what it earned from selling Zephyr — that's $1,071,254.33 in revenue — to the FTC, which the agency will then use to refund affected consumers. To note, the Zephyr masks cost customers at least $100. It will pay $100,000 in fine over its unsubstantiated health claims, as well. In addition to ordering Razer refund customers, the FTC also prohibited the company from making any claims that it's selling products that reduce the likelihood of being infected with or transmitting the COVID-19 virus without proper FDA approval. Razer has also been prohibited from claiming health benefits for its products without scientific evidence to support them, as well as from "falsely claiming that any product meets government-established standards when it has not."

This article originally appeared on Engadget at

PUBG will take a nostalgia-infused trip back to its first map in May

PUBG: Battlegrounds is somehow old enough to evoke nostalgia. The pioneering battle royale game, which entered Steam Early Access in 2017, will borrow a page from Fortnite’s playbook and honor its first map. Erangel Classic will recreate the old-school battlefield from the game’s inception for a limited two-week run in May and June.

Developer and publisher Krafton says the Erangel Classic map will reproduce the original’s concepts, graphics, atmosphere and UI. However, it will blend those with “modern tweaks” to deliver “the enjoyable gameplay experiences that players have grown accustomed to.” In other words, much like remasters of other classic games, the goal is to feel as close to the original as possible without chucking out all of its subtle quality-of-life improvements from the game’s evolution.


If the revamped map idea sounds familiar, Fortnite brought back its original 2018 island map late last year, breaking its records for player counts. (It peaked at 44.7 million players, marking its biggest day ever.) It’s easy to see why Krafton would want a piece of that action.

Specific nods to the original map include foggy and rainy weather to add an air of unpredictability. In addition, you’ll find bench weapons on the starting island (get ready to scramble for your favorite), and all weapons will have reduced recoil to match the original. It will also have a Tommy Gun in the care package, a vintage map UI and a “charmingly tacky font and graphics.”

The tiered rollout will arrive on PCs and consoles at different times, extending the playtime for those who own the game on multiple platforms (perhaps helping Krafton sell a few extra in-game items). Erangel Classic will be available in PUBG: Battlegrounds on PC from May 14 to May 28 and on consoles from May 23 to June 6, replacing the modern Erangel map during those periods. Krafton says the May 14 patch notes will go into more detail about all the map’s changes, so keep an eye out.

This article originally appeared on Engadget at

England’s NHS will provide artificial pancreas to thousands of diabetes patients

England’s National Health Service (NHS) said on Tuesday that “tens of thousands of children and adults” with type 1 diabetes will receive an “artificial pancreas” to help manage their insulin levels. The hybrid closed loop system — a sensor under the skin that sends wireless readings to an externally worn pump, which delivers insulin as needed — can help patients avoid the risks of type 1 diabetes without worrying about finger sticks or injections.

This isn’t the first device of its kind. Tandem makes similar insulin pumps in the US after it received FDA authorization in 2019. Gizmodo notes that another company called iLet got FDA approval for a similar device last year. Although the NHS hasn’t said which specific device(s) its program will use, what’s different here is the nation’s publicly funded health care system providing them for free rather than as an exclusive privilege for the well-to-do. (Sigh.)

The hybrid closed loop system starts with a sensor implanted beneath the skin, which continually monitors glucose levels at regular intervals. The sensor sends that data wirelessly to a pump, worn externally, which delivers the proper insulin dosage. The “hybrid” part of its name comes from the fact that some user input, including entering carb intake, is still required in the otherwise self-regulating system.

The government agency gave an ultra-precise figure of 269,095 people in England living with type 1 diabetes, highlighting how many folks could potentially benefit from the rollout. The NHS says local branches will begin identifying patients for the program starting on Tuesday.

“Diabetes is a tough and relentless condition, but these systems make a significant, life-changing difference — improving both the overall health and quality of life for people with diabetes,” Colette Marshall, chief executive of Diabetes UK, wrote in the NHS’s press release announcing the rollout. “This really is a landmark moment and we’ll be working with the NHS and others to ensure a fair rollout that reaches people as quickly as possible.”

This article originally appeared on Engadget at

Fitbit’s health chatbot will arrive later this year

Like most other corners of the tech world, Google sees AI powering the next innovations in health technology. The company’s annual The Check Up event expanded on its plans to add a personal health chatbot to the Fitbit app, expand Google Lens for better skin condition searches and use a version of its Gemini chatbot in the medical field.

One of the more intriguing of Google’s announcements on Tuesday was more detail about an experimental AI feature for Fitbit users, briefly teased last year. Fitbit Labs will let owners draw correlations and “connect the dots” from health data tracked using their wearable devices. A chatbot in the mobile app will let you ask questions in natural language and create personalized charts to learn about your health.

The company hasn’t yet gone into great depth about the Fitbit chatbot, but an example it published Tuesday shows a user asking about potential connections between activity and sleep. The Fitbit assistant answered that the user’s days with higher activity scores correlated with better sleep (while cautioning not to assume that’s the only reason).

The Fitbit generative AI tool will arrive later this year. Google says it will (at least initially) only be available to Fitbit Premium subscribers with Android devices enrolled in the Fitbit Labs program.

Google / Fitbit

The company sees Google Lens as filling some healthcare gaps where text-based searches fall short. It says a feature (introduced last year) that uses Lens to identify “visually similar matches from the web” for skin conditions is now available in over 150 countries. It can work even when you don’t know where to begin when describing a dermatological disorder.

In a similar light, Google has added new images and diagrams to its web results from reputable online sources to help you understand conditions like neck pain. Up next: The company sees the visual results powering its searches for more health conditions, including migraines, kidney stones and pneumonia. The visual search engine updates are expected to roll out over the next few months.

The company also mentioned that Fitbit and Google Research are partnering with health and wellness experts and other medical professionals to create a new AI model for health and wellness. The long-term goal is for the Gemini-powered large language model (LLM) to power its future AI features across Google’s various health offerings.

This article originally appeared on Engadget at

FDA approves the first over-the-counter continuous glucose monitor

The US Food and Drug Administration has approved the first continuous glucose monitor (CGM) people can buy without a prescription. Dexcom's Stelo Glucose Biosensor System has a sensor users are meant to insert into their upper arm, similar to the company's other CGMs that need a doctor's prescription for purchase. It pairs with a smartphone application that can show the user's blood glucose measurements and trends every 15 minutes. 

The company designed the device specifically for adults 18 and up who are not using insulin, such as those managing their diabetes with oral medications and non-diabetics making a conscious effort to control their sugar intake. It could be a great tool for people with insulin resistance, including individuals with PCOS and other metabolic issues that heighten their probability of developing diabetes in the future. In general, it could give users the insight to be able to better understand how the food they eat and the movements they make impact their overall health. 

While CGMs aren't anything new, they've become a wellness trend on social media last year, and even non-diabetics started using them. By clearing Stelo, the FDA is making the monitors more accessible than before. "CGMs can be a powerful tool to help monitor blood glucose," said Jeff Shuren, MD, director of the FDA's Center for Devices and Radiological Health. "Today's clearance expands access to these devices by allowing individuals to purchase a CGM without the involvement of a health care provide. Giving more individuals valuable information about their health, regardless of their access to a doctor or health insurance, is an important step forward in advancing health equity for U.S. patients."

Stelo will be available starting this summer. Each patch is meant to last for 15 days before users will need to replace it. Dexcom has yet to reveal how much it would cost, but it said Stelo will "provide an option for those who do not have insurance coverage for CGM."


This article originally appeared on Engadget at

Dr. Garmin will see you now

There’s a reason smartwatches haven’t replaced clinically-validated gear when you visit the hospital — accuracy and reliability are paramount when the data informs medical procedures. Even so, researchers are looking for ways in which these devices can be meaningfully used in a clinical setting. One project in the UK has explored if a Garmin Venu 2 and dedicated companion app could be used to free up doctors and nurses, six minutes at a time.

The Six Minute Walk Test (6MWT) is used to diagnose and monitor a number of cardiovascular maladies. This includes conditions like Pulmonary Hypertension that, if left untreated, are eventually fatal. “[The test has been] a cornerstone of hospital practice and clinical trials for decades all around the world as [...] a marker of how well the heart and lungs are working,” explained project leader Dr. Joseph Newman. While a change in a blood test marker might be clinically relevant, Newman said “it’s probably more important to someone that they can walk to the shop and back.” The test requires a patient walk on a flat, hard surface for six minutes straight, which stresses the heart enough to measure its capacity. A professional tests the patient’s heart rate and blood oxygen levels at the start and end, and while it’s simple and reliable, "it’s not perfect,” according to Newman. “This is why we’ve looked to change it in two important ways," he said, "can we make it shorter [...] and digitize it for remote use?"

After all, six minutes is a lifetime in a clinical setting, and patients dislike having to schlep all the way to their hospital just to walk up and down a corridor. It’s why Newman and Lucy Robertson — both researchers at the Royal Papworth Hospital in Cambridge — began looking for ways to revolutionize the test. They wanted to see if the test could be shortened to a single minute, and also if it could be carried out by a patient at home using a Venu 2. The watch was connected to a secure and dedicated clinical trial platform built by Aparito – a Wrexham-based developer – for testing. This was then sent out to patients who were instructed to wear the watch and walk outdoors to complete their own tests. “They’re asked to walk on flat, even, dry, relatively straight roads rather than in laps or circuits,” said Dr. Newman, with patients walking at their own natural pace.

“We carried out a product appraisal early on in the research process and were open-minded as to the brand or model,” said Newman. “Garmin came out on top for a few reasons; we can access raw data as well as Garmin’s algorithmically-derived variables,” he said. Because the research was being funded by a charity, the British Heart Foundation, the watch had to offer good value for money. It helped that Garmin, because of its existing health research division, gave the team “confidence in the accuracy of the sensors,” not to mention the fact that Aparito feels that “the Garmin SDK is relatively easy to work with,” he said. But while Garmin is in use right now, there’s no reason this setup couldn’t eventually work with a number of other brands. “As long as the technology works, it’s accurate, reliable and patients accept it, then we’re not tied to any brand.”

There are several benefits in giving patients the ability to run the tests at home: it’s more representative of the demands of their actual life, and patients can retake the test at regular intervals, making it easier to track that person’s health over time. “We can see real value in providing patients with pulmonary hypertension with an app and smartwatch to monitor their progress,”said Dr. Newman. “It’s unlikely to ever fully replace the need for in-person hospital reviews, but it will likely reduce their frequency.”

The results of the study right now suggest cutting the test to one minute has no detrimental effect on its outcome or accuracy,and that patients are far more likely to run the test regularly if they’re able to do so at home. “It’s likely that the upfront costs of wearables [to a hospital] may be offset by the longer term reduction in hospital visits,” said Newman. If that turns out to be right, then it means clinicians can better focus their time and efforts where their expertise is more valuable.

This article originally appeared on Engadget at

HIPAA protects health data privacy, but not in the ways most people think

The “P” in HIPAA doesn’t stand for privacy. It’s one of the first things a lot of experts will say when asked to clear up any misconceptions about the health data law. Instead, it stands for portability — it’s called the Health Insurance Portability and Accountability Act —and describes how information can be transferred between providers. With misinterpretations of HIPAA starting with just its name, misunderstandings of what the law actually does greatly impact our ability to recognize how the kinds of data do and don't fall under its scope. That’s especially true as a growing number of consumer tech devices and services gather troves of information related to our health.

We often consider HIPAA a piece of consumer data privacy legislation because it did direct the Department of Health and Human Services to come up with certain security provisions, like breach notification regulations and a health privacy rule for protecting individually identifiable information. But when HIPAA went into effect in the 1990s, its primary aim was improving how providers worked with insurance companies. Put simply, “people think HIPAA covers more than it actually does,” said Daniel Solove, professor at George Washington University and CEO of privacy training firm TeachPrivacy.

HIPAA has two big restrictions in scope: a limited set of covered entities, and limited set of covered data, according to Cobun Zweifel-Keegan, DC managing director of the International Association of Privacy Professionals. Covered entities include healthcare providers like doctors and health plans like health insurance companies. The covered data refers to medical records and other individually identifiable health information used by those covered entities. Under HIPAA, your general practitioner can't sell data related to your vaccination status to an ad firm, but a fitness app (which wouldn't be a covered entity) that tracks your steps and heart rate (which aren't considered covered data) absolutely can.

“What HIPAA covers, is information that relates to health care or payment for health care, and sort of any piece of identifiable information that’s in that file,” Solove said. It doesn’t cover any health information shared with your employer or school, like if you turn in a sick note, but it does protect your doctor from sharing more details about your diagnosis if they call to verify.

A lot has changed in the nearly 30 years since HIPAA went into effect, though. The legislators behind HIPAA didn’t anticipate how much data we would be sharing about ourselves today, much of which can be considered personally identifiable. So, that information doesn’t fall under its scope. “When HIPAA was designed, nobody really anticipated what the world was going to look like,” Lee Tien, senior staff attorney at the Electronic Frontier Foundation said. It’s not badly designed, HIPAA just can’t keep up with the state we’re in today. “You're sharing data all the time with other people who are not doctors or who are not the insurance company,” said Tien.

Think of all the data collected about us on the daily that could provide insight into our health. Noom tracks your diet. Peloton knows your activity levels. Calm sees you when you’re sleeping. Medisafe knows your pill schedule. Betterhelp knows what mental health conditions you might have, and less than a year ago was banned by the FTC from disclosing that information to advertisers. The list goes on, and much of it can be used to sell dietary supplements or sleep aids or whatever else. “Health data could be almost limitless,” so if HIPAA didn’t have a limited scope of covered entities, the law would be limitless, too, Solove said.

Not to mention the amount of inferences that firms can make about our health based on other data. An infamous 2012 New York Times investigation detailed how just by someone’s online searches and purchases, Target can figure out that they’re pregnant. HIPAA may not protect your medical information from being viewed by law enforcement officers. Even without a warrant, cops can get your records just by saying that you’re a suspect (or victim) of a crime. Police have used pharmacies to gather medical data about suspects, but other types of data like location information can provide sensitive details, too. For example, it can show that you went to a specific clinic to receive care. Because of these inferences, laws like HIPAA won’t necessarily stop law enforcement from prosecuting someone based on their healthcare decision.

Today, state-specific laws crop up across the US to help target some of the health data privacy gaps that HIPAA doesn’t cover. This means going beyond just medical files and healthcare providers to encompass more of people’s health data footprint. It varies between states, like in California which provides options to charge anyone who negligently discloses medical information or some additional breach protections for consumers based in Pennsylvania, but Washington state recently passed a law specifically targeting HIPAA’s gaps.

Washington State’s My Health My Data Act, passed last year, aims to “protect personal health data that falls outside the ambit of the Health Insurance Portability and Accountability Act,” according to a press release from Washington’s Office of the Attorney General. Any entity that conducts business in the state of Washington and deals with personal information that identifies a consumer’s past, present or future physical or mental health status must comply with the act’s privacy protections. Those provisions include the right not to have your health data sold without your permission and having health data deleted via written request. Under this law, unlike HIPAA, an app tracking someone’s drug dosage and schedule or the inferences made by Target about pregnancy would be covered.

My Health My Data is still rolling out, so we’ll have to wait and see how the law impacts national health data privacy protections. Still, it’s already sparking copycat laws in states like Vermont.

This article originally appeared on Engadget at

AI is coming for big pharma

If there’s one thing we can all agree upon, it’s that the 21st century’s captains of industry are trying to shoehorn AI into every corner of our world. But for all of the ways in which AI will be shoved into our faces and not prove very successful, it might actually have at least one useful purpose. For instance, by dramatically speeding up the often decades-long process of designing, finding and testing new drugs.

Risk mitigation isn’t a sexy notion but it’s worth understanding how common it is for a new drug project to fail. To set the scene, consider that each drug project takes between three and five years to form a hypothesis strong enough to start tests in a laboratory. A 2022 study from Professor Duxin Sun found that 90 percent of clinical drug development fails, with each project costing more than $2 billion. And that number doesn’t even include compounds found to be unworkable at the preclinical stage. Put simply, every successful drug has to prop up at least $18 billion waste generated by its unsuccessful siblings, which all but guarantees that less lucrative cures for rarer conditions aren’t given as much focus as they may need.

Dr. Nicola Richmond is VP of AI at Benevolent, a biotech company using AI in its drug discovery process. She explained the classical system tasks researchers to find, for example, a misbehaving protein – the cause of disease – and then find a molecule that could make it behave. Once they've found one, they need to get that molecule into a form a patient can take, and then test if it’s both safe and effective. The journey to clinical trials on a living human patient takes years, and it’s often only then researchers find out that what worked in theory does not work in practice.

The current process takes “more than a decade and multiple billions of dollars of research investment for every drug approved,” said Dr. Chris Gibson, co-founder of Recursion, another company in the AI drug discovery space. He says AI’s great skill may be to dodge the misses and help avoid researchers spending too long running down blind alleys. A software platform that can churn through hundreds of options at a time can, in Gibson’s words, “fail faster and earlier so you can move on to other targets.”

CellProfiler / Carpenter-Singh laboratory at the Broad Institute

Dr. Anne E. Carpenter is the founder of the Carpenter-Singh laboratory at the Broad Institute of MIT and Harvard. She has spent more than a decade developing techniques in Cell Painting, a way to highlight elements in cells, with dyes, to make them readable by a computer. She is also the co-developer of Cell Profiler, a platform enabling researchers to use AI to scrub through vast troves of images of those dyed cells. Combined, this work makes it easy for a machine to see how cells change when they are impacted by the presence of disease or a treatment. And by looking at every part of the cell holistically – a discipline known as “omics” – there are greater opportunities for making the sort of connections that AI systems excel at.

Using pictures as a way of identifying potential cures seems a little left-field, since how things look don’t always represent how things actually are, right? Carpenter said humans have always made subconscious assumptions about medical status from sight alone. She explained most people may conclude someone may have a chromosomal issue just by looking at their face. And professional clinicians can identify a number of disorders by sight alone purely as a consequence of their experience. She added that if you took a picture of everyone’s face in a given population, a computer would be able to identify patterns and sort them based on common features.

This logic applies to the pictures of cells, where it’s possible for a digital pathologist to compare images from healthy and diseased samples. If a human can do it, then it should be faster and easier to employ a computer to spot these differences in scale so long as it’s accurate. “You allow this data to self-assemble into groups and now [you’re] starting to see patterns,” she explained, “when we treat [cells] with 100,000 different compounds, one by one, we can say ‘here’s two chemicals that look really similar to each other.’” And this looking really similar to each other isn’t just coincidence, but seems to be indicative of how they behave.

In one example, Carpenter cited that two different compounds could produce similar effects in a cell, and by extension could be used to treat the same condition. If so, then it may be that one of the two – which may not have been intended for this purpose – has fewer harmful side effects. Then there’s the potential benefit of being able to identify something that we didn’t know was affected by disease. “It allows us to say, ‘hey, there’s this cluster of six genes, five of which are really well known to be part of this pathway, but the sixth one, we didn’t know what it did, but now we have a strong clue it’s involved in the same biological process.” “Maybe those other five genes, for whatever reason, aren’t great direct targets themselves, maybe the chemicals don’t bind,” she said, “but the sixth one [could be] really great for that.”

FatCamera via Getty Images

In this context, the startups using AI in their drug discovery processes are hoping that they can find the diamonds hiding in plain sight. Dr. Richmond said that Benevolent’s approach is for the team to pick a disease of interest and then formulate a biological question around it. So, at the start of one project, the team might wonder if there are ways to treat ALS by enhancing, or fixing, the way a cell’s own housekeeping system works. (To be clear, this is a purely hypothetical example supplied by Dr. Richmond.)

That question is then run through Benevolent’s AI models, which pull together data from a wide variety of sources. They then produce a ranked list of potential answers to the question, which can include novel compounds, or existing drugs that could be adapted to suit. The data then goes to a researcher, who can examine what, if any, weight to give to its findings. Dr. Richmond added that the model has to provide evidence from existing literature or sources to support its findings even if its picks are out of left-field. And that, at all times, a human has the final say on what of its results should be pursued and how vigorously.

It’s a similar situation at Recursion, with Dr. Gibson claiming that its model is now capable of predicting “how any drug will interact with any disease without having to physically test it.” The model has now formed around three trillion predictions connecting potential problems to their potential solutions based on the data it has already absorbed and simulated. Gibson said that the process at the company now resembles a web search: Researchers sit down at a terminal, “type in a gene associated with breast cancer and [the system] populates all the other genes and compounds that [it believes are] related.”

“What gets exciting,” said Dr. Gibson, “is when [we] see a gene nobody has ever heard of in the list, which feels like novel biology because the world has no idea it exists.” Once a target has been identified and the findings checked by a human, the data will be passed to Recursion’s in-house scientific laboratory. Here, researchers will run initial experiments to see if what was found in the simulation can be replicated in the real world. Dr. Gibson said that Recursion’s wet lab, which uses large-scale automation, is capable of running more than two million experiments in a working week.

“About six weeks later, with very little human intervention, we’ll get the results,” said Dr. Gibson and, if successful, it’s then the team will “really start investing.” Because, until this point, the short period of validation work has cost the company “very little money and time to get.” The promise is that, rather than a three-year preclinical phase, that whole process can be crunched down to a few database searches, some oversight and then a few weeks of ex vivo testing to confirm if the system’s hunches are worth making a real effort to interrogate. Dr. Gibson said that it believes it has taken a “year’s worth of animal model work and [compressed] it, in many cases, to two months.”

Of course, there is not yet a concrete success story, no wonder cure that any company in this space can point to as a validation of the approach. But Recursion can cite one real-world example of how close its platform came to matching the success of a critical study. In April 2020, Recursion ran the COVID-19 sequence through its system to look at potential treatments. It examined both FDA-approved drugs and candidates in late-stage clinical trials. The system produced a list of nine potential candidates which would need further analysis, eight of which it would later be proved to be correct. It also said that Hydroxychloroquine and Ivermectin, both much-ballyhooed in the earliest days of the pandemic, would flop.

And there are AI-informed drugs that are currently undergoing real-world clinical trials right now. Recursion is pointing to five projects currently finishing their stage one (tests in healthy patients), or entering stage two (trials in people with the rare diseases in question) clinical testing right now. Benevolent has started a stage one trial of BEN-8744, a treatment for ulcerative colitis that may help with other inflammatory bowel disorders. And BEN-8744 is targeting an inhibitor that has no prior associations in the existing research which, if successful, will add weight to the idea that AIs can spot the connections humans have missed. Of course, we can’t make any conclusions until at least early next year when the results of those initial tests will be released.

Yuichiro Chino via Getty Images

There are plenty of unanswered questions, including how much we should rely upon AI as the sole arbiter of the drug discovery pipeline. There are also questions around the quality of the training data and the biases in the wider sources more generally. Dr. Richmond highlighted the issues around biases in genetic data sources both in terms of the homogeneity of cell cultures and how those tests are carried out. Similarly, Dr. Carpenter said the results of her most recent project, the publicly available JUMP-Cell Painting project, were based on cells from a single participant. “We picked it with good reason, but it’s still one human and one cell type from that one human.” In an ideal world, she’d have a far broader range of participants and cell types, but the issues right now center on funding and time, or more appropriately, their absence.

But, for now, all we can do is await the results of these early trials and hope that they bear fruit. Like every other potential application of AI, its value will rest largely in its ability to improve the quality of the work – or, more likely, improve the bottom line for the business in question. If AI can make the savings attractive enough, however, then maybe those diseases which are not likely to make back the investment demands under the current system may stand a chance. It could all collapse in a puff of hype, or it may offer real hope to families struggling for help while dealing with a rare disorder.

This article originally appeared on Engadget at

Vibrating belt that treats low bone density gets FDA approval

The FDA has provided clearance for a medical device called Osteoboost, a vibrating belt that improves bone density in patients with osteopenia. The device, which was developed by California-based startup Bone Health Technologies and in part with NASA, is the first medical device of its kind to get regulatory approval as a treatment option for postmenopausal women.

One in two older women who have experienced menopause gets osteoporosis (the disease that comes after prolonged and untreated osteopenia), which is characterized by porous bones that can easily fracture. The Osteoboost belt is designed to prevent bone density from reaching that stage through early intervention. It works by mechanically stimulating the strength of the bones in the hips and spine of a wearer and prevents the further progression of bone density disintegration. The blueprint for the technology comes from NASA research that was investigating ways to prevent bone density from weakening in astronauts that work in mostly zero gravity environments where deterioration becomes a concern.

The belt should be worn for 30 minutes every day or at least five times a week for it to fully take effect. It delivers a gentle vibration that makes it easy to be worn pretty much anywhere or at any time, such as during dog walks or while washing dishes. During clinical trials, CT scans showed that following the integration of the belt into a patient’s care plan, bone density visually improved over time. In a study backed by the NIH, women aged 50 to 60 lost 3.4 percent of their bone density by the end of 12 months without any intervention, while patients who wore the belt lost only 0.5 percent of their bone strength.

Current standards of care for preventing osteoporosis during the osteopenia stage are mostly lifestyle suggestions that can be hard to adhere to, such as a well-balanced and calcium-rich diet, frequent weight-bearing exercises and reducing the risk of falls. “Although lifestyle interventions such as exercise and diet are beneficial to bone, the effect is small. The Osteoboost shows promise in slowing the loss of bone density and strength and may fill the treatment gap,” Laura Bilek, a researcher who has studied the belt’s effectiveness said.

Osteoboost is still not yet available for sale, but you can sign up to get notified when the device is released. A company representative said they will begin shipping later this year and will accept pre-orders in the next few months. While the price is also still not disclosed, the representative told Engadget that the belt will be “affordable and accessible to the millions of patients who need it.” To get the device, you will need a prescription from your doctor — so pricing may vary depending on insurers and co-pays. Bone Health Technology said it is currently in talks with insurers regarding coverage for the medical device. While the price projection could have drastically changed, three years ago the CEO Laura Yecies told NS Medical Devices she believed the device could debut for about $800.

This article originally appeared on Engadget at