AI and you: Is the promise of personalized nutrition apps worth the hype?
As a type 2 diabetic, Michael Snyder has long been interested in how blood sugar levels vary from one person to another in response to the same food, and whether a more personalized approach to nutrition could help tackle the rapidly cascading levels of diabetes and obesity in much of the western world.
Eight years ago, Snyder, who directs the Center for Genomics and Personalized Medicine at Stanford University, decided to put his theories to the test. In the 2000s continuous glucose monitoring, or CGM, had begun to revolutionize the lives of diabetics, both type 1 and type 2. Using spherical sensors which sit on the upper arm or abdomen – with tiny wires that pierce the skin – the technology allowed patients to gain real-time updates on their blood sugar levels, transmitted directly to their phone.
It gave Snyder an idea for his research at Stanford. Applying the same technology to a group of apparently healthy people, and looking for ‘spikes’ or sudden surges in blood sugar known as hyperglycemia, could provide a means of observing how their bodies reacted to an array of foods.
“We discovered that different foods spike people differently,” he says. “Some people spike to pasta, others to bread, others to bananas, and so on. It’s very personalized and our feeling was that building programs around these devices could be extremely powerful for better managing people’s glucose.”
Unbeknown to Snyder at the time, thousands of miles away, a group of Israeli scientists at the Weizmann Institute of Science were doing exactly the same experiments. In 2015, they published a landmark paper which used CGM to track the blood sugar levels of 800 people over several days, showing that the biological response to identical foods can vary wildly. Like Snyder, they theorized that giving people a greater understanding of their own glucose responses, so they spend more time in the normal range, may reduce the prevalence of type 2 diabetes.
The commercial potential of such apps is clear, but the underlying science continues to generate intriguing findings.
“At the moment 33 percent of the U.S. population is pre-diabetic, and 70 percent of those pre-diabetics will become diabetic,” says Snyder. “Those numbers are going up, so it’s pretty clear we need to do something about it.”
Fast forward to 2022,and both teams have converted their ideas into subscription-based dietary apps which use artificial intelligence to offer data-informed nutritional and lifestyle recommendations. Snyder’s spinoff, January AI, combines CGM information with heart rate, sleep, and activity data to advise on foods to avoid and the best times to exercise. DayTwo–a start-up which utilizes the findings of Weizmann Institute of Science–obtains microbiome information by sequencing stool samples, and combines this with blood glucose data to rate ‘good’ and ‘bad’ foods for a particular person.
“CGMs can be used to devise personalized diets,” says Eran Elinav, an immunology professor and microbiota researcher at the Weizmann Institute of Science in addition to serving as a scientific consultant for DayTwo. “However, this process can be cumbersome. Therefore, in our lab we created an algorithm, based on data acquired from a big cohort of people, which can accurately predict post-meal glucose responses on a personal basis.”
The commercial potential of such apps is clear. DayTwo, who market their product to corporate employers and health insurers rather than individual consumers, recently raised $37 million in funding. But the underlying science continues to generate intriguing findings.
Last year, Elinav and colleagues published a study on 225 individuals with pre-diabetes which found that they achieved better blood sugar control when they followed a personalized diet based on DayTwo’s recommendations, compared to a Mediterranean diet. The journal Cell just released a new paper from Snyder’s group which shows that different types of fibre benefit people in different ways.
“The idea is you hear different fibres are good for you,” says Snyder. “But if you look at fibres they’re all over the map—it’s like saying all animals are the same. The responses are very individual. For a lot of people [a type of fibre called] arabinoxylan clearly reduced cholesterol while the fibre inulin had no effect. But in some people, it was the complete opposite.”
Eight years ago, Stanford's Michael Snyder began studying how continuous glucose monitors could be used by patients to gain real-time updates on their blood sugar levels, transmitted directly to their phone.
The Snyder Lab, Stanford Medicine
Because of studies like these, interest in precision nutrition approaches has exploded in recent years. In January, the National Institutes of Health announced that they are spending $170 million on a five year, multi-center initiative which aims to develop algorithms based on a whole range of data sources from blood sugar to sleep, exercise, stress, microbiome and even genomic information which can help predict which diets are most suitable for a particular individual.
“There's so many different factors which influence what you put into your mouth but also what happens to different types of nutrients and how that ultimately affects your health, which means you can’t have a one-size-fits-all set of nutritional guidelines for everyone,” says Bruce Y. Lee, professor of health policy and management at the City University of New York Graduate School of Public Health.
With the falling costs of genomic sequencing, other precision nutrition clinical trials are choosing to look at whether our genomes alone can yield key information about what our diets should look like, an emerging field of research known as nutrigenomics.
The ASPIRE-DNA clinical trial at Imperial College London is aiming to see whether particular genetic variants can be used to classify individuals into two groups, those who are more glucose sensitive to fat and those who are more sensitive to carbohydrates. By following a tailored diet based on these sensitivities, the trial aims to see whether it can prevent people with pre-diabetes from developing the disease.
But while much hope is riding on these trials, even precision nutrition advocates caution that the field remains in the very earliest of stages. Lars-Oliver Klotz, professor of nutrigenomics at Friedrich-Schiller-University in Jena, Germany, says that while the overall goal is to identify means of avoiding nutrition-related diseases, genomic data alone is unlikely to be sufficient to prevent obesity and type 2 diabetes.
“Genome data is rather simple to acquire these days as sequencing techniques have dramatically advanced in recent years,” he says. “However, the predictive value of just genome sequencing is too low in the case of obesity and prediabetes.”
Others say that while genomic data can yield useful information in terms of how different people metabolize different types of fat and specific nutrients such as B vitamins, there is a need for more research before it can be utilized in an algorithm for making dietary recommendations.
“I think it’s a little early,” says Eileen Gibney, a professor at University College Dublin. “We’ve identified a limited number of gene-nutrient interactions so far, but we need more randomized control trials of people with different genetic profiles on the same diet, to see whether they respond differently, and if that can be explained by their genetic differences.”
Some start-ups have already come unstuck for promising too much, or pushing recommendations which are not based on scientifically rigorous trials. The world of precision nutrition apps was dubbed a ‘Wild West’ by some commentators after the founders of uBiome – a start-up which offered nutritional recommendations based on information obtained from sequencing stool samples –were charged with fraud last year. The weight-loss app Noom, which was valued at $3.7 billion in May 2021, has been criticized on Twitter by a number of users who claimed that its recommendations have led to them developed eating disorders.
With precision nutrition apps marketing their technology at healthy individuals, question marks have also been raised about the value which can be gained through non-diabetics monitoring their blood sugar through CGM. While some small studies have found that wearing a CGM can make overweight or obese individuals more motivated to exercise, there is still a lack of conclusive evidence showing that this translates to improved health.
However, independent researchers remain intrigued by the technology, and say that the wealth of data generated through such apps could be used to help further stratify the different types of people who become at risk of developing type 2 diabetes.
“CGM not only enables a longer sampling time for capturing glucose levels, but will also capture lifestyle factors,” says Robert Wagner, a diabetes researcher at University Hospital Düsseldorf. “It is probable that it can be used to identify many clusters of prediabetic metabolism and predict the risk of diabetes and its complications, but maybe also specific cardiometabolic risk constellations. However, we still don’t know which forms of diabetes can be prevented by such approaches and how feasible and long-lasting such self-feedback dietary modifications are.”
Snyder himself has now been wearing a CGM for eight years, and he credits the insights it provides with helping him to manage his own diabetes. “My CGM still gives me novel insights into what foods and behaviors affect my glucose levels,” he says.
He is now looking to run clinical trials with his group at Stanford to see whether following a precision nutrition approach based on CGM and microbiome data, combined with other health information, can be used to reverse signs of pre-diabetes. If it proves successful, January AI may look to incorporate microbiome data in future.
“Ultimately, what I want to do is be able take people’s poop samples, maybe a blood draw, and say, ‘Alright, based on these parameters, this is what I think is going to spike you,’ and then have a CGM to test that out,” he says. “Getting very predictive about this, so right from the get go, you can have people better manage their health and then use the glucose monitor to help follow that.”
Podcast: The Friday Five - your health research roundup
The Friday Five is a new podcast series in which Leaps.org covers five breakthroughs in research over the previous week that you may have missed. There are plenty of controversies and ethical issues in science – and we get into many of them in our online magazine – but there’s also plenty to be excited about, and this news roundup is focused on inspiring scientific work to give you some momentum headed into the weekend.
Covered in this week's Friday Five:
- Puffer fish chemical for treating chronic pain
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CandyCodes could provide sweet justice against fake pills
When we swallow a pill, we hope it will work without side effects. Few of us know to worry about a growing issue facing the pharmaceutical industry: counterfeit medications. These pills, patches, and other medical products might look just like the real thing. But they’re often stuffed with fillers that dilute the medication’s potency or they’re simply substituted for lookalikes that contain none of the prescribed medication at all.
Now, bioengineer William Grover at the University of California, Riverside, may have a solution. Inspired by the tiny, multi-colored sprinkles called nonpareils that decorate baked goods and candies, Grover created CandyCodes pill coatings to prevent counterfeits.
The idea was borne out of pandemic boredom. Confined to his home, Grover was struck by the patterns of nonpareils he saw on candies, and found himself counting the number of little balls on each one. “It’s random, how they’re applied,” he says. “I wondered if it ever repeats itself or if each of these candies is unique in the entire world.” He suspected the latter, and some quick math proved his hypothesis: Given dozens of nonpareils per candy in a handful of different colors, it’s highly unlikely that the sprinklings on any two candies would be identical.
He quickly realized his finding could have practical applications: pills or capsules could be coated with similar “sprinkles,” with the manufacturer photographing each pill or capsule before selling its products. Consumers looking to weed out fakes could potentially take a photo with their cell phones and go online to compare images of their own pills to the manufacturer’s database, with the help of an algorithm that would determine their authenticity. Or, a computer could generate another type of unique identifier, such as a text-based code, tracking to the color and location of the sprinkles. This would allow for a speedier validation than a photo-based comparison, Grover says. “It could be done very quickly, in a fraction of a second.”
Researchers and manufacturers have already developed some anti-counterfeit tools, including built-in identifiers like edible papers with scannable QR codes. But such methods, while functional, can be costly to implement, Grover says.
It wouldn’t be paranoid to take such precautions. Counterfeits are a growing problem, according to Young Kim, a biomedical engineer at Purdue University who was not involved in the CandyCodes study. “There are approximately 40,000 online pharmacies that one can access via the Internet,” he says. “Only three to four percent of them are operated legally.” Purchases from online pharmacies rose dramatically during the pandemic, and Kim expects a boom in counterfeit medical products alongside it.
The FDA warns that U.S. consumers can be exposed to counterfeits through online purchases, in particular. The problem is magnified in low- to middle-income nations, where one in 10 medical products are counterfeit, according to a World Health Organization estimate. Cost doesn’t seem to be a factor, either; antimalarials and antibiotics are most often reported as counterfeits or fakes, and generic medications are swapped as often as brand-name drugs, according to the same WHO report.
Counterfeits weren’t tracked globally until 2013; since then, there have been 1,500 reports to the WHO, with actual incidences of counterfeiting likely much higher. Fake medicines have been estimated to result in costs of $200 billion each year, and are blamed for more than 72,000 pneumonia- and 116,000 malaria-related deaths.
Researchers and manufacturers have already developed some anti-counterfeit tools, including built-in identifiers like edible papers with scannable QR codes or barcodes that are stamped onto or otherwise incorporated into pills and other medical products. But such methods, while functional, can be costly to implement, Grover says.
CandyCodes could provide unique identifiers for at least 41 million pills for every person on the planet.
William Grover
“Putting universal codes on each pill and each dosage is attractive,” he says. “The challenge is, how can we do it in a way that requires as little modification to the existing manufacturing process as possible? That's where I hope CandyCodes have an edge. It's not zero modification, but I hope it is as minor a modification of the manufacturing process as possible.”
Kim calls the concept “a clever idea to introduce entropy for high-level security” even if it may not be as close to market as other emerging technologies, including some edible watermarks he’s helped develop. He points out that CandyCodes still needs to be tested for reproducibility and readability.
The possibilities are already intriguing, though. Grover’s recent research, published in Scientific Reports, predicts that unique codes could be used for at least 41 million pills for every person on the planet.
Sadly, CandyCodes’ multicolored bits probably won’t taste like candy. They must be made of non-caloric ingredients to meet the international regulatory standards that govern food dyes and colorants. But Grover hopes CandyCodes represent a simple, accessible solution to a heart-wrenching issue. “This feels like trying to track down and go after bad guys,” he says. “Someone who would pass off a medicine intended for a child or a sick person and pass it off as something effective, I can't imagine anything much more evil than that. It's fun and, and a little fulfilling to try to develop technologies that chip away at that.”