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.”
Can blockchain help solve the Henrietta Lacks problem?
Science has come a long way since Henrietta Lacks, a Black woman from Baltimore, succumbed to cervical cancer at age 31 in 1951 -- only eight months after her diagnosis. Since then, research involving her cancer cells has advanced scientific understanding of the human papilloma virus, polio vaccines, medications for HIV/AIDS and in vitro fertilization.
Today, the World Health Organization reports that those cells are essential in mounting a COVID-19 response. But they were commercialized without the awareness or permission of Lacks or her family, who have filed a lawsuit against a biotech company for profiting from these “HeLa” cells.
While obtaining an individual's informed consent has become standard procedure before the use of tissues in medical research, many patients still don’t know what happens to their samples. Now, a new phone-based app is aiming to change that.
Tissue donors can track what scientists do with their samples while safeguarding privacy, through a pilot program initiated in October by researchers at the Johns Hopkins Berman Institute of Bioethics and the University of Pittsburgh’s Institute for Precision Medicine. The program uses blockchain technology to offer patients this opportunity through the University of Pittsburgh's Breast Disease Research Repository, while assuring that their identities remain anonymous to investigators.
A blockchain is a digital, tamper-proof ledger of transactions duplicated and distributed across a computer system network. Whenever a transaction occurs with a patient’s sample, multiple stakeholders can track it while the owner’s identity remains encrypted. Special certificates called “nonfungible tokens,” or NFTs, represent patients’ unique samples on a trusted and widely used blockchain that reinforces transparency.
Blockchain could be used to notify people if cancer researchers discover that they have certain risk factors.
“Healthcare is very data rich, but control of that data often does not lie with the patient,” said Julius Bogdan, vice president of analytics for North America at the Healthcare Information and Management Systems Society (HIMSS), a Chicago-based global technology nonprofit. “NFTs allow for the encapsulation of a patient’s data in a digital asset controlled by the patient.” He added that this technology enables a more secure and informed method of participating in clinical and research trials.
Without this technology, de-identification of patients’ samples during biomedical research had the unintended consequence of preventing them from discovering what researchers find -- even if that data could benefit their health. A solution was urgently needed, said Marielle Gross, assistant professor of obstetrics, gynecology and reproductive science and bioethics at the University of Pittsburgh School of Medicine.
“A researcher can learn something from your bio samples or medical records that could be life-saving information for you, and they have no way to let you or your doctor know,” said Gross, who is also an affiliate assistant professor at the Berman Institute. “There’s no good reason for that to stay the way that it is.”
For instance, blockchain could be used to notify people if cancer researchers discover that they have certain risk factors. Gross estimated that less than half of breast cancer patients are tested for mutations in BRCA1 and BRCA2 — tumor suppressor genes that are important in combating cancer. With normal function, these genes help prevent breast, ovarian and other cells from proliferating in an uncontrolled manner. If researchers find mutations, it’s relevant for a patient’s and family’s follow-up care — and that’s a prime example of how this newly designed app could play a life-saving role, she said.
Liz Burton was one of the first patients at the University of Pittsburgh to opt for the app -- called de-bi, which is short for decentralized biobank -- before undergoing a mastectomy for early-stage breast cancer in November, after it was diagnosed on a routine mammogram. She often takes part in medical research and looks forward to tracking her tissues.
“Anytime there’s a scientific experiment or study, I’m quick to participate -- to advance my own wellness as well as knowledge in general,” said Burton, 49, a life insurance service representative who lives in Carnegie, Pa. “It’s my way of contributing.”
Liz Burton was one of the first patients at the University of Pittsburgh to opt for the app before undergoing a mastectomy for early-stage breast cancer.
Liz Burton
The pilot program raises the issue of what investigators may owe study participants, especially since certain populations, such as Black and indigenous peoples, historically were not treated in an ethical manner for scientific purposes. “It’s a truly laudable effort,” Tamar Schiff, a postdoctoral fellow in medical ethics at New York University’s Grossman School of Medicine, said of the endeavor. “Research participants are beautifully altruistic.”
Lauren Sankary, a bioethicist and associate director of the neuroethics program at Cleveland Clinic, agrees that the pilot program provides increased transparency for study participants regarding how scientists use their tissues while acknowledging individuals’ contributions to research.
However, she added, “it may require researchers to develop a process for ongoing communication to be responsive to additional input from research participants.”
Peter H. Schwartz, professor of medicine and director of Indiana University’s Center for Bioethics in Indianapolis, said the program is promising, but he wonders what will happen if a patient has concerns about a particular research project involving their tissues.
“I can imagine a situation where a patient objects to their sample being used for some disease they’ve never heard about, or which carries some kind of stigma like a mental illness,” Schwartz said, noting that researchers would have to evaluate how to react. “There’s no simple answer to those questions, but the technology has to be assessed with an eye to the problems it could raise.”
To truly make a difference, blockchain must enable broad consent from patients, not just de-identification.
As a result, researchers may need to factor in how much information to share with patients and how to explain it, Schiff said. There are also concerns that in tracking their samples, patients could tell others what they learned before researchers are ready to publicly release this information. However, Bogdan, the vice president of the HIMSS nonprofit, believes only a minimal study identifier would be stored in an NFT, not patient data, research results or any type of proprietary trial information.
Some patients may be confused by blockchain and reluctant to embrace it. “The complexity of NFTs may prevent the average citizen from capitalizing on their potential or vendors willing to participate in the blockchain network,” Bogdan said. “Blockchain technology is also quite costly in terms of computational power and energy consumption, contributing to greenhouse gas emissions and climate change.”
In addition, this nascent, groundbreaking technology is immature and vulnerable to data security flaws, disputes over intellectual property rights and privacy issues, though it does offer baseline protections to maintain confidentiality. To truly make a difference, blockchain must enable broad consent from patients, not just de-identification, said Robyn Shapiro, a bioethicist and founding attorney at Health Sciences Law Group near Milwaukee.
The Henrietta Lacks story is a prime example, Shapiro noted. During her treatment for cervical cancer at Johns Hopkins, Lacks’s tissue was de-identified (albeit not entirely, because her cell line, HeLa, bore her initials). After her death, those cells were replicated and distributed for important and lucrative research and product development purposes without her knowledge or consent.
Nonetheless, Shapiro thinks that the initiative by the University of Pittsburgh and Johns Hopkins has potential to solve some ethical challenges involved in research use of biospecimens. “Compared to the system that allowed Lacks’s cells to be used without her permission, Shapiro said, “blockchain technology using nonfungible tokens that allow patients to follow their samples may enhance transparency, accountability and respect for persons who contribute their tissue and clinical data for research.”
Read more about laws that have prevented people from the rights to their own cells.
New tech for prison reform spreads to 11 states
A new non-profit called Recidiviz is using data technology to reduce the size of the U.S. criminal justice system. The bi-coastal company (SF and NYC) is currently working with 11 states to improve their systems and, so far, has helped remove nearly 69,000 people — ones left floundering in jail or on parole when they should have been released.
“The root cause is fragmentation,” says Clementine Jacoby, 31, a software engineer who worked at Google before co-founding Recidiviz in 2019. In the 1970s and 80s, the U.S. built a series of disconnected data systems, and this patchwork is still being used by criminal justice authorities today. It requires parole officers to manually calculate release dates, leading to errors in many cases. “[They] have done everything they need to do to earn their release, but they're still stuck in the system,” Jacoby says.
Recidiviz has built a platform that connects the different databases, with the goal of identifying people who are already qualified for release but remain behind bars or on supervision. “Think of Recidiviz like Google Maps,” says Jacoby, who worked on Maps when she was at the tech giant. Google Maps takes in data from different sources – satellite images, street maps, local business data — and organizes it into one easy view. “Recidiviz does something similar with criminal justice data,” Jacoby explains, “making it easy to identify people eligible to come home or to move to less intensive levels of supervision.”
People like Jacoby’s uncle. His experience with incarceration is what inspired her passion for criminal justice reform in the first place.
The problems are vast
The U.S. has the highest incarceration rate in the world — 2 million people according to the watchdog group, Prison Policy Initiative — at a cost of $182 billion a year. The numbers could be a lot lower if not for an array of problems including inaccurate sentencing calculations, flawed algorithms and parole violations laws.
Sentencing miscalculations
To determine eligibility for release, the current system requires corrections officers to check 21 different requirements spread across five different databases for each of the 90 to 100 people under their supervision. These manual calculations are time prohibitive, says Jacoby, and fall victim to human error.
In addition, Recidiviz found that policies aimed at helping to reduce the prison population don’t always work correctly. A key example is time off for good behavior laws that allow inmates to earn one day off for every 30 days of good behavior. Some states' data systems are built to calculate time off as one day per month of good behavior, rather than per day. Over the course of a decade-long sentence, Jacoby says these miscalculations can lead to a huge discrepancy in the calculated release data and the actual release date.
Algorithms
Commercial algorithm-based software systems for risk assessment continue to be widely used in the criminal justice system, even though a 2018 study published in Science Advances exposed their limitations. After the study went viral, it took three years for the Justice Department to issue a report on their own flawed algorithms used to reduce the federal prison population as part of the 2018 First Step Act. The program, it was determined, overestimated the risk of putting inmates of color into early-release programs.
Despite its name, Recidiviz does not build these types of algorithms for predicting recidivism, or whether someone will commit another crime after being released from prison. Rather, Jacoby says the company’s "descriptive analytics” approach is specifically intended to weed out incarceration inequalities and avoid algorithmic pitfalls.
Parole violation laws
Research shows that 350,000 people a year — about a quarter of the total prison population — are sent back not because they’ve committed another crime, but because they’ve broken a specific rule of their probation. “Things that wouldn't send you or I to prison, but would send someone on parole,” such as crossing county lines or being in the presence of alcohol when they shouldn’t be, are inflating the prison population, says Jacoby.
It’s personal for the co-founder and CEO
“I grew up with an uncle who went into the prison system,” Jacoby says. At 19, he was sentenced to ten years in prison for a non-violent crime. A few months after being released from jail, he was sent back for a non-violent parole violation.
“For my family, the fact that one in four prison admissions are driven not by a crime but by someone who's broken a rule on probation and parole was really profound because that happened to my uncle,” Jacoby says. The experience led her to begin studying criminal justice in high school, then college. She continued her dive into how the criminal justice system works as part of her Passion Project while at Google, a program that allows employees to spend 20 percent of their time on pro-bono work. Two colleagues whose family members had also been stuck in the system joined her.
As part of the project, Jacoby interviewed hundreds of people involved in the criminal justice system. “Those on the right, those on the left, agreed that bad data was slowing down reform,” she says. Their research brought them to North Dakota where they began to understand the root of the problem. The corrections department is making “huge, consequential decisions every day [without] … the data,” Jacoby says. In a new video by Recidiviz not yet released, Jacoby recounts her exchange with the state’s director of corrections who told her, “‘It’s not that we have the data and we just don’t know how to make it public; we don’t have the information you think we have.'"
A mock-up (with fake data) of the types of dashboards and insights that Recidiviz provides to state governments.
Recidiviz
As a software engineer, Jacoby says the comment made no sense to her — until she witnessed it first-hand. “We spent a lot of time driving around in cars with corrections directors and parole officers watching them use these incredibly taxing, frankly terrible, old data systems,” Jacoby says.
As they weeded through thousands of files — some computerized, some on paper — they unearthed the consequences of bad data: Hundreds of people in prison well past their release date and thousands more whose release from parole was delayed because of minor paperwork issues. They found individuals stuck in parole because they hadn’t checked one last item off their eligibility list — like simply failing to provide their parole officer with a paystub. And, even when parolees advocated for themselves, the archaic system made it difficult for their parole officers to confirm their eligibility, so they remained in the system. Jacoby and her team also unpacked specific policies that drive racial disparities — such as fines and fees.
The Solution
It’s more than a trivial technical challenge to bring the incomplete, fragmented data onto a 21st century data platform. It takes months for Recidiviz to sift through a state’s information systems to connect databases “with the goal of tracking a person all the way through their journey and find out what’s working for 18- to 25-year-old men, what’s working for new mothers,” explains Jacoby in the video.
TED Talk: How bad data traps people in the U.S. justice system
TED Fellow Clementine Jacoby's TED Talk went live on Jan. 13. It describes how we can fix bad data in the criminal justice system, "bringing thousands of people home, reducing costs and improving public safety along the way."
Clementine Jacoby • TED2022
Ojmarrh Mitchell, an associate professor in the School of Criminology and Criminal Justice at Arizona State University, who is not involved with the company, says what Recidiviz is doing is “remarkable.” His perspective goes beyond academic analysis. In his pre-academic years, Mitchell was a probation officer, working within the framework of the “well known, but invisible” information sharing issues that plague criminal justice departments. The flexibility of Recidiviz’s approach is what makes it especially innovative, he says. “They identify the specific gaps in each jurisdiction and tailor a solution for that jurisdiction.”
On the downside, the process used by Recidiviz is “a bit opaque,” Mitchell says, with few details available on how Recidiviz designs its tools and tracks outcomes. By sharing more information about how its actions lead to progress in a given jurisdiction, Recidiviz could help reformers in other places figure out which programs have the best potential to work well.
The eleven states in which Recidiviz is working include California, Colorado, Maine, Michigan, Missouri, Pennsylvania and Tennessee. And a pilot program launched last year in Idaho, if scaled nationally, with could reduce the number of people in the criminal justice system by a quarter of a million people, Jacoby says. As part of the pilot, rather than relying on manual calculations, Recidiviz is equipping leaders and the probation officers with actionable information with a few clicks of an app that Recidiviz built.
Mitchell is disappointed that there’s even the need for Recidiviz. “This is a problem that government agencies have a responsibility to address,” he says. “But they haven’t.” For one company to come along and fill such a large gap is “remarkable.”