Researchers spearhead efforts to establish guidelines for personalized nutrition approaches

Personalized nutrition (PN) has gained popularity in recent years as a customized approach to health outcomes. PN combines biomedical, genetic, and lifestyle data to provide individualized recommendations, and a plethora of companies offer various forms of health screenings, apps, programs, products, and diet advice.

The Personalized Nutrition Initiative at the University of Illinois Urbana-Champaign, together with their external partners, hosted two workshops for PN practitioners and experts, aimed at establishing guidelines and setting up best practices for the field. The workshop findings were recently published in two journal articles.

“One of the biggest challenges is that to do personalized nutrition right, you need a lot of different types of data, and the field is becoming increasingly complex. To provide consistency and continuity, we need to understand all these components and how they fit together,” said Sharon Donovan, professor in the Department of Food Science and Human Nutrition, part of the College of Agricultural, Consumer and Environmental Sciences at Illinois.

Donovan is the director of the Personalized Nutrition Initiative at Illinois, which serves as a hub for research and education on the topic.

“We want the Personalized Nutrition Initiative to be viewed as a trusted place where researchers and companies, and perhaps regulatory agencies, can come together to synthesize current knowledge and identify future directions. We serve as a convener, bringing together experts to have conversations and provide recommendations,” she said.

In the first paper, published in Critical Reviews in Food Science and Nutrition, the authors outlined a set of guiding principles for PN approaches addressing users and beneficiaries, data collection and handling, methodology, and purpose.

In the second paper, published in Advances in Nutrition, they addressed the opportunities and challenges around data and regulatory issues. PN spans a wide variety of areas, from medical devices to food supplements, which are covered by different regulatory requirements that are not always coordinated.

Workshop participants also discussed how to use artificial intelligence to analyze data and combine information into a holistic perspective.

“You have some types of data that are very sparse and others that are extremely rich. For example, consumers or research participants often wear a glucose monitor that records glucose levels every second, providing thousands of measures. We can have comprehensive datasets from genetic sequencing or microbiome analysis. These data are often combined with other measures, such as blood triglycerides and lipids, that are measured once,” Donovan said.

PN also includes social and behavioral data that are typically collected through surveys and interviews. Combining these diverse data types together to gather meaningful insights is a challenge.

“We were laying out our vision for the different types of data that should be components of personalized nutrition and how to put them together to personalize somebody’s nutrition advice. Now is the time to set guidelines to ensure the data are ready for artificial intelligence to make sense of the information,” Donovan noted.

There are also ethical aspects to data collection, added Anna Keck, assistant director of the Personalized Nutrition Initiative.

“Many personalized nutrition products and services are data intensive, and people may not realize how much personal information they give out. How do we safeguard data and establish trust with consumers? We discussed with the experts how to build a better framework for collecting data ethically and to determine what should be shared,” she said.

Personalized nutrition (PN) has gained popularity in recent years as a customized approach to health outcomes. PN combines biomedical, genetic, and lifestyle data to provide individualized recommendations, and a plethora of companies offer various forms of health screenings, apps, programs, products, and diet advice.

The Personalized Nutrition Initiative at the University of Illinois Urbana-Champaign, together with their external partners, hosted two workshops for PN practitioners and experts, aimed at establishing guidelines and setting up best practices for the field. The workshop findings were recently published in two journal articles.

“One of the biggest challenges is that to do personalized nutrition right, you need a lot of different types of data, and the field is becoming increasingly complex. To provide consistency and continuity, we need to understand all these components and how they fit together,” said Sharon Donovan, professor in the Department of Food Science and Human Nutrition, part of the College of Agricultural, Consumer and Environmental Sciences at Illinois.

Donovan is the director of the Personalized Nutrition Initiative at Illinois, which serves as a hub for research and education on the topic.

“We want the Personalized Nutrition Initiative to be viewed as a trusted place where researchers and companies, and perhaps regulatory agencies, can come together to synthesize current knowledge and identify future directions. We serve as a convener, bringing together experts to have conversations and provide recommendations,” she said.

In the first paper, published in Critical Reviews in Food Science and Nutrition, the authors outlined a set of guiding principles for PN approaches addressing users and beneficiaries, data collection and handling, methodology, and purpose.

In the second paper, published in Advances in Nutrition, they addressed the opportunities and challenges around data and regulatory issues. PN spans a wide variety of areas, from medical devices to food supplements, which are covered by different regulatory requirements that are not always coordinated.

Workshop participants also discussed how to use artificial intelligence to analyze data and combine information into a holistic perspective.

“You have some types of data that are very sparse and others that are extremely rich. For example, consumers or research participants often wear a glucose monitor that records glucose levels every second, providing thousands of measures. We can have comprehensive datasets from genetic sequencing or microbiome analysis. These data are often combined with other measures, such as blood triglycerides and lipids, that are measured once,” Donovan said.

PN also includes social and behavioral data that are typically collected through surveys and interviews. Combining these diverse data types together to gather meaningful insights is a challenge.

“We were laying out our vision for the different types of data that should be components of personalized nutrition and how to put them together to personalize somebody’s nutrition advice. Now is the time to set guidelines to ensure the data are ready for artificial intelligence to make sense of the information,” Donovan noted.

There are also ethical aspects to data collection, added Anna Keck, assistant director of the Personalized Nutrition Initiative.

“Many personalized nutrition products and services are data intensive, and people may not realize how much personal information they give out. How do we safeguard data and establish trust with consumers? We discussed with the experts how to build a better framework for collecting data ethically and to determine what should be shared,” she said.