After designating social media as a "public health hazard" in late January, New York City is now suing Meta, Google, Snap and TikTok for "fueling nationwide youth mental health crisis." Specifically, these companies face three counts in the lawsuit: public nuisance, negligence and gross negligence. The Mayor Eric Adams administration accuses TikTok, Instagram, Facebook, Snapchat and YouTube of "endangering our children's mental health, promoting addiction, and encouraging unsafe behavior."

These are allegedly achieved by way of harmful algorithms, gambling-like mechanisms and manipulation through reciprocity — making the user "feel compelled to respond to one positive action with another positive action." The city believes that there is a correlation between the increase in social media usage and the decline in local youth mental health over "more than a decade."

In response, Google and Meta told CNBC that they have always worked with youth safety experts and provided parental control tools. ByteDance's TikTok also highlighted some of its specific tools to Axios, namely age-restricted features, parental controls and an automatic 60-minute time limit for users under 18. However, none of the tech companies acknowledged the problematic features listed by the Adams administration.

This lawsuit follows a recent Senate hearing on online child safety, in which the CEOs of all the aforementioned tech companies (except Google) were present. In his opening remarks, Senator Lindsey Graham told the tech execs that "you have blood on your hands" — a reference to online child exploitations and cyberbullying that unfortunately led to deaths. 

Through this case, the Adams administration wants these tech companies to pay up for the city's youth mental health services, which apparently cost more than $100 million each year. But ultimately, it's about forcing these tech giants to stop manipulating young users into addictive behavior, as well as getting policymakers to place new federal laws that safeguard youth mental health on social platforms.

Before this New York City lawsuit, Meta already faces a similar case from 41 states back in October 2023, in which it was accused of misleading the public about the safety of its platform's "addictive" features. Meta, Snap, TikTok and Google were also sued in a multi-district litigation in 2022 for their addictive features that allegedly cause "emotional and physical harms, including death" to adolescents.

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.

The Food and Drug Administration has given the green light to a sleep apnea detection feature on Galaxy Watch devices in the US, Samsung has revealed. The company notes this is the first approval of its kind in the US — South Korean officials previously rubberstamped the feature for use in that country.

Samsung plans to add the sleep apnea monitoring tool to compatible Galaxy Watch wearables in the third quarter of this year. It will be available via the Samsung Health Monitor app.

The feature allows those aged 22 and older who have not been diagnosed with the condition to check for signs of sleep apnea using their smartwatch and phone. It looks for signs of moderate to severe obstructive sleep apnea (OSA) over a two-night monitoring period. Users will need to track their sleep for more than four hours twice over a ten-day period to use the feature.

OSA is a common, chronic condition that affects around 25 percent of men and a tenth of women in the US, according to the National Sleep Foundation. Those with the condition tend to stop breathing while they sleep, which can reduce their sleep quality, disrupt oxygen supply and lead to more daytime tiredness. Left untreated, "sleep apnea can compound the risk of cardiovascular diseases such as hypertension, coronary artery disease, heart failure, cardiac arrhythmia and stroke," Samsung notes. The company added that the feature should help more people detect moderate and severe forms of the condition, and for them to seek medical advice when they do.

Other versions of the feature, which ties into Samsung's other efforts to help its customers have a good night's sleep, have popped up in devices elsewhere. In 2020, Withings added a sleep apnea detection feature to its sleep tracking mat.

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.

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.

Achieving your fitness goals doesn’t have to be expensive or complicated. Keeping tabs on your daily movement can make you conscious of your activity level and motivate you to stay on top of your gym sessions, or at least hit your steps. That rings especially true if you spend most of your day sitting at a desk like I do. Having a device handy that can keep you accountable can be a game changer. While many smartwatches on the market are decked out with fitness tools, the average affordable tracker might offer just enough to help kickstart your health journey.

You might be surprised by how much a $100 (or less) wearable can do. They go well beyond just counting steps, providing in-depth reports on how you're sleeping at night or giving you a breakdown of your heart rate variability during a workout. But given their price, there are tradeoffs: don’t expect a plethora of features or third-party app integrations. To help you decide which cheap fitness tracker to get, I tested a few of the latest devices that are available for $100 or less to find out which are worth your money.

What to look for in a cheap fitness tracker

Even the most basic tracker should have at least three features: a program to track workouts or movement of some sort, the option to monitor and collect sleep data and the ability to measure health metrics like heart rate and blood oxygen levels (though, the readings might not be super accurate).

Fitness features

A cheap workout tracker can be great for someone looking to keep tabs on small, achievable goals like 10,000 steps before sundown or 30 minutes of a HIIT workout to get your heart rate peaking. An experienced long-distance runner looking to train for a triathlon might opt for a more expensive device that can measure cadence or ground contact time, and can track more customizable workouts or give deeper insights into performance data.

At the very least, a budget workout tracker should be able to track workouts beyond walking and running — otherwise, it would just be a pedometer. The number of activities a device will recognize varies. Some will get funky with it and consider skateboarding a workout, while others won’t be able to track a jumping jack.

At this price, you can expect a device to measure a mix of cardio, machine workouts and strength training. With each, you might get a numerical or visual breakdown of heart rate activity, overall pace, and calories burned per session. Although some cheap trackers can offer a really good overview of heart rate zone activity during a workout, a more technically advanced device might be able to go a step further and explain what your results mean and coach you on how to keep your heart rate in a specific bracket so that you can burn more fat per workout. I found that the more budget-friendly the device, the more likely it is that a tracker will fall short when it comes to smart counseling or offering predictive insights beyond a given workout. If a budget tracker does happen to offer some semblance of a coaching program, you can expect it to sit behind a paywall.

Tracking and planning your recovery is just as essential to any fitness journey. A sub-$100 device should be able to tell you how long you’ve slept and provide a breakdown of deep, light and REM sleep activity. It's not a guarantee that you will get a sleep “score” or insights on how to get better rest — that data is usually found on more expensive wearables. Also, because these trackers aren’t designed for bedtime specifically — be mindful of comfort. The bands and watch face on a budget fitness tracker may not be ideal for getting some good shut-eye.

Connectivity and practicality

Not all activity trackers, budget-friendly or not, are designed to seamlessly integrate with a smartphone. The trackers tested for this roundup can’t directly make calls or send texts to contacts on a paired smartphone. They can, however, display and dismiss incoming calls and notifications. You can forget about checking your email or paying for a coffee from your wrist using these more affordable devices.

Most cheap fitness trackers also won't include a built-in GPS. Instead, they usually depend on a paired smartphone to gather location data. The drawback of using a fitness tracker without GPS is that it might not provide as precise for tracking distance or pace. You also can't use a budget tracker to get turn-by-turn directions during a walk or while running errands. For the more outdoorsy consumers, having GPS could be a key safety feature.

Design

You also might find that an inexpensive fitness tracker is harder to navigate than a more advanced smartwatch. Whether it be a screen size issue or simply not having a smart enough interface, don't expect every feature to be one that you can engage with directly on your wrist. Oftentimes, you will need to pull out your smartphone to log information or access more in-depth health data.

The quality and build of displays and bands will also vary in this category. Don’t expect the highest resolution displays or the fanciest materials in the bands. But you can expect some level of sweat and water resistance.

Other cheap fitness trackers we tested

Wyze Watch 47c

I didn't have high expectations of the Wyze Watch 47c, but I was shocked at how little this tracker can do. The 47c can only track walks and runs. It has a dedicated widget, a small logo of a man running, and when you tap it, it begins measuring your pace, heart rate, calories burned and mileage. It does not auto-detect or auto-pause workouts and it doesn't differentiate between a run and walk. Most importantly, this device can’t track any other exercises. It’s basically a glorified pedometer.

The 47c was also my least favorite to sleep with, mainly because the square watch face is so large and heavy. Even if I did manage to sleep through the night with it on, it only gave me a basic sleep report.

Garmin vivofit 4

The Garmin vivofit 4 has a tiny display that is not a touchscreen and all navigation happens through one button. The watch face is impossible to read outdoors and the exercise widget is also very finicky. To start tracking a run, you have to hold down the main button and flip through some pages until you get to a moving person icon. Once there, you have to press the bottom right corner of the bar and hold down and if you press for too long or in the wrong spot, it’ll switch to another page, like a stopwatch. It’s incredibly frustrating.

Once you start a run though, it will start tracking your steps, your distance — and that's pretty much it. It does not auto-detect or auto-pause workouts. It doesn't alert you of any mileage or calorie milestones.

Researchers at MIT’s CSAIL division, which focuses on computer engineering and AI development, built two machine learning algorithms that can detect pancreatic cancer at a higher threshold than current diagnostic standards. The two models together formed to create the “PRISM” neural network. It is designed to specifically detect pancreatic ductal adenocarcinoma (PDAC), the most prevalent form of pancreatic cancer.

The current standard PDAC screening criteria catches about 10 percent of cases in patients examined by professionals. In comparison, MIT’s PRISM was able to identify PDAC cases 35 percent of the time.

While using AI in the field of diagnostics is not an entirely new feat, MIT’s PRISM stands out because of how it was developed. The neural network was programmed based on access to diverse sets of real electronic health records from health institutions across the US. It was fed the data of over 5 million patient’s electronic health records, which researchers from the team said “surpassed the scale” of information fed to an AI model in this particular area of research. “The model uses routine clinical and lab data to make its predictions, and the diversity of the US population is a significant advancement over other PDAC models, which are usually confined to specific geographic regions like a few healthcare centers in the US,” Kai Jia, MIT CSAIL PhD senior author of the paper said.

MIT’s PRISM project started over six years ago. The motivation behind developing an algorithm that can detect PDAC early has a lot to do with the fact that most patients get diagnosed in the later stages of the cancer’s development — specifically about eighty percent are diagnosed far too late.

The AI works by analyzing patient demographics, previous diagnoses, current and previous medications in care plans and lab results. Collectively, the model works to predict the probability of cancer by analyzing electronic health record data in tandem with things like a patient’s age and certain risk factors evident in their lifestyle. Still, PRISM is still only able to help diagnose as many patients at the rate the AI can reach the masses. At the moment, the technology is bound to MIT labs and select patients in the US. The logistical challenge of scaling the AI will involve feeding the algorithm more diverse data sets and perhaps even global health profiles to increase accessibility.

Nonetheless, this isn't MIT’s first stab at developing an AI model that can predict cancer risk. It notably developed a way to train models how to predict the risk of breast cancer among women using mammogram records. In that line of research, MIT experts confirmed, the more diverse the data sets, the better the AI gets at diagnosing cancers across diverse races and populations. The continued development of AI models that can predict cancer probability will not only improve outcomes for patients if malignancy is identified earlier, it will also lessen the workload of overworked medical professionals. The market for AI in diagnostics is so ripe for change that it is piquing the interest of big tech commercial companies like IBM, which attempted to create an AI program that can detect breast cancer a year in advance.

The US government has reportedly approved AI-based memory loss prediction software for the first time. Darmiyan, a San Francisco-based brain imaging analytics company, says the FDA has granted De Novo approval for its product BrainSee. The software platform assigns “an objective score that predicts the likelihood of progression from aMCI to Alzheimer’s dementia within 5 years,” according to the medical company. Fierce Biotech first reported the announcement.

Darmiyan says BrainSee can predict memory loss progression using clinical brain MRIs and cognitive tests, which are already standard for patients worried about early signs of decline. After the program analyzes the imaging and cognitive assessments, it assigns a predictive score indicating the patient’s odds of memory deterioration within the following five years. At least in theory, that would lead to early treatment for some and peace of mind for others.

“This shifts the patient experience from prolonged anxiety to proactive management, which is crucial in an era of emerging Alzheimer’s treatments where accurate prognosis can help determine suitable treatment candidates,” Darmiyan wrote in a press release announcing the FDA approval. “The economic impact of BrainSee will be significant for all stakeholders in healthcare, promising to reduce the billions of dollars annually spent on Alzheimer’s care, through more effective management and treatment.”

The FDA’s “De Novo” designation means the product has no clear market predecessors but has proven its effectiveness and safety in clinical trials. BrainSee first received FDA “breakthrough” designation in 2021, an earlier stage of the approval path for a first-of-its-kind treatment. 

Darmiyan says BrainSee is fully automated and provides results on the same day the scans and cognitive test scores are entered. The company views the tech as shifting the treatment of mild / early cognitive decline from biomarker-based methods to “non-invasive and actionable forecasts of future improvement or progression.”

Following last year's smart toilet which debuted at CES 2023, Vivoo is at it again for CES 2024 with another urine analysis product. The company has unveiled an at-home digital urinary tract infection (UTI) testing kit that provides what it calls "gold standard accuracy results" via a two-minute test. 

To use it, just pee on the provided UTI test strip and scan it to obtain results via Vivoo's app in "seconds," the company says. If the result is positive, customers can then connect with a doctor to obtain a prescription if required. The company says the product "saves customers time, prevents confusion in readings, and digitalizes the data so customers can share results with healthcare providers via the app, if instant treatment is desired." From the looks of it, the results are obtained via the strip, then deciphered by the app.

Vivoo notes that UTIs are the most common type of outpatient infection, with six in ten women experiencing them in their lifetimes. Normally, you'd send your urine off to a lab for analysis, or use an existing at-home test kit. The company says that the new product spares users the bureaucracy of lab testing while also keeping the relevant data for users who might need that, unlike regular testing kits. 

In fact, many women experience recurrent UTIs, which have become resistant to at least one or even multiple types of antibiotics. By keeping a record of past infections, Vivoo's app could help patients and medical professionals track the problem and treat it appropriately. 

Last year, the company unveiled a smart toilet device that clips onto existing toilets and provides data like your body's water, magnesium, PH, protein and sodium levels. Later on, it released strips for vaginal PH levels. The new home UTI test will come to market in Q2 2024, but pricing isn't yet available. 

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2023 was an important year for patients with sickle cell disease. Prior to CRISPR, the only cure for the life-long ailment was a bone marrow transplant, which is notoriously dangerous and costly. This month, the FDA approved Vertex’s “Casgevy,” a CRISPR-based therapy for the treatment of sickle cell disease in patients 12 and older. The landmark approval made the therapeutic the first genetically edited therapy to reach the general market.

Casgevy, which also received the greenlight from regulators in the UK for another blood disorder called beta thalassemia, works by being administered in a single-infusion of genetically modified stem cells to a patient. Clinical study participants that took Casgevy were free from symptoms associated with sickle cell disease, like periodic episodes of extreme pain due to blocked blood flow through vessels, for up to a year.

CRISPR, which modifies precise regions of a human’s DNA strands, was once thought to be a far off scientific innovation. Human cells were first modified using CRISPR in clinical trials in China back in 2016. Less than a decade later, these landmark approvals have set the stage for future nods by regulators for other CRISPR-based therapies that can treat things like HIV, cancers and high blood pressure. “Gene therapy holds the promise of delivering more targeted and effective treatments,” Nicole Verdun, director of the Office of Therapeutic Products within the FDA’s Center for Biologics Evaluation and Research said in a recent press release.

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CRISPR-based gene editing can be designed as a therapeutic for a number of diseases. A scientist can either delete, disrupt or insert segments of DNA to treat conditions by either targeting specific genes or engineering new cell therapies. The editing process can occur ex vivo (outside the body), in the same way Casgevy does, or in vivo (inside the body). Using CRISPR, sickle cell patients’ blood stem cells are modified in a lab before they are re-infused via a single-dose infusion as part of a hematopoietic transplant.

Neville Sanjana, a core faculty member at the New York Genome Center and associate professor in the Department of Biology at New York University, runs the Sanjana lab, which develops gene therapies for complex diseases like autism and cancer. “One of the really fundamental characteristics of CRISPR is its programmability,” Sanjana told Engadget. While working at the Zhang lab at the Broad Institute of MIT and Harvard, Sanjana says he helped design the “guide RNA” that became the blueprint for Vertex’s Casgevy. “CRISPR screens can be powerful tools for understanding any disease or genetic trait,” Sanjana said. Right now, he said biomedical folks are focused on applying CRISPR-based therapies for really serious inheritable diseases.

While it does “set a precedent” to have these first CRISPR-based gene therapies out there, it could also mean that regulators and the general public will regard future innovations in the space as “less novel,” Katie Hasson, a researcher with the Center for Genetics and Society (CGS) told Engadget. The CGS is a public interest and social justice organization that is focused on making sure gene editing is developed and distributed for good. Hasson explained, it doesn't mean that because one got approved that all other innovative therapies to come after it will not get as much scrutiny.

Beyond therapeutics, gene editing has very broad applications for the discovery and understanding of diseases. Scientists can use CRISPR to explore the origins of things like cancer and pave paths for therapeutics and incurable diagnoses, but that's not all there is to it. Scientists still need to conduct “considerable experimental research” when it comes to bringing an actual therapeutic to fruition, Sanjana said. “When we focus on therapeutic activity at a particular site in the genome, we need to make sure that there will not be any unintended consequences in other parts of the genome.”

Still, the spotlight will always shine a brighter light on the flashy developments of CRISPR from a therapeutic standpoint. Currently, a new gene editing method is being developed to target specific cells in a process called “cancer shredding“ for difficult-to-treat brain cancer. Scientists have even discovered a pathway to engineer bacteria to discover tumorous cells. However, there are barriers to using CRISPR in clinical practice due to the lack of “safe delivery systems to target the tissues and cells.”

“Maybe by curing one disease, you might give them a different disease — especially if you think of cancer. We call that a secondary malignancy,” Sanjana said. While there is strong reason for concern, one cure creating a pathway for other diseases or cancers is not unique to CRISPR. For example, CAR T cell therapy, which uses an entirely different approach to cell-based gene therapy and is not reflective of CRISPR, is a lifesaving cancer treatment that the FDA discovered can, in certain situations, cause cancer.

“We definitely don't want any unintended consequences. There are bits of the genome that if you edit them by mistake, it's probably no big deal but then there are other genes that are vitally important,” Sanjana said. Direct assessment of “off-target effects” or events in which a gene edit incorrectly edits another point on a DNA strand in vivo is challenging.

The FDA recommends that after a clinical trials’ period of investigatory study looking at the efficacy of a gene editing-based therapy, there needs to be a 15-year long term follow up after product administration. Peter Marks, director of the FDA’s Center for Biologics Evaluation and Research, said that the agency’s approval of Casgevy follows “rigorous evaluations of the scientific and clinical data.” Right now, researchers are focused on improving the precision and accuracy of gene editing and having the proper follow up is absolutely well merited, Sanjana explained. “The process right now is a careful one.”

Hasson believes that the 15-year recommendation is a good start. “I know that there is a big problem overall with pharmaceutical companies actually following through and doing those long term post-market studies.”

That’s where new approaches come into play. Base editing, a CRISPR-derived genome editing method that makes targeted changes to DNA sequences, has been around since 2016. Drugs that use base editing have already made headway in the scientific community. Verve Therapeutics developed a gene edited therapy that can lower cholesterol in patients with a single infusion. At higher doses, Verve said the treatment has the potential to reduce proteins associated with bad cholesterol for 2.5 years. Base editing, like CRISPR, has many potential applications for treatment and discovery. For example, base editing could repair a gene mutation that causes childhood blindness. Researchers at Weill Cornell Medicine also found base editing could help understand what genetic changes influence a patient’s response to cancer therapies.

Base editors use CRISPR to bring another functional element to a specific place in the genome. “But it doesn't matter whether it's CRISPR cutting or base editing… any time you're modifying DNA…you would want to know what the off target effects are and you can bet that the FDA wants to know that too. You're going to need to collect data using standard models like cell culture, or animal models to show there are zero or near zero off-target impacts,” Sanjana said.

CRISPR-based therapies already show high therapeutic potential for conditions beyond sickle cell disease. From blood based treatments, to edited allogeneic immune cells for cancers, there are a number of human clinical trials underway or expected to start next year. Trials for gene-edited therapies that target certain cells for cancer and autoimmune diseases are expected to begin in 2024.

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It won't be until 2025 before we get a better understanding of how Excision BioTherapeutics’ CRISPR-based therapy works to treat HIV. The application of gene editing as a therapeutic for Alzhiemer’s is still in the early stages, with mice at the forefront of research. Similarly, University College London researchers proved that CRISPR has promise as a potential therapeutic for treatment-resistant forms of childhood epilepsy. In a recent study, a gene edited therapy developed in the lab was shown to reduce seizures in mice.

But the clinical process of getting CRISPR to safely and effectively work as it's intended isn’t the only hurdle. The pricing of CRISPR and related therapies in general will be a huge barrier to access. The Innovative Genomics Institute (IGI), a research group that hopes to advance ethical use of these gene editing in medicine, estimates that the average CRISPR-based therapy can cost between $500,000 and $2 million per patient. The IGI has built out an “Affordability Task Force” to tackle the issue of expanding access to these novel therapies. Vertex’s sickle cell treatment costs a cool $2.2 million per treatment, before hospital costs. David Altshuler, the chief scientific officer at Vertex, told MIT Tech Review that wants to innovate the delivery of the therapeutic and make it more accessible to patients. “I think the goal will be achieved sooner by finding another modality, like a pill that can be distributed much more effectively,” Altshuler said.

“Access is a huge issue and it's a huge equity issue,” the CGS’ Hasson told Engadget. “I think we would also like to look at equity here even more broadly. It's not just about who gets access to the medication once it comes on the market but really how can we prioritize equity in the research that's leading to these treatments.” The US already does a poor job of providing equitable healthcare access as it is, Hasson explained, which is why it's important for organizations like CGS to pose roundtable discussions about implementing guardrails that value ethical considerations. “If you support people having access to healthcare, it should encompass these cutting edge treatments as well.”