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Evaluation ViewAttendees 59
Hot Topic Symposia

Pediatric Nutrition
Session Type: Hot Topic Symposia

Digital Twins Concept for Precision Nutrition in Preterm Infants: Is this the future?

Saturday, May 4, 2024
11:00 AM – 12:30 PM ET
Location: Metro Toronto Convention Centre: 204
CE: Live CME: 1.5

Selected By: MOD
Disclosure(s):
Josef Neu, MD: Arla foods (Ongoing) (Products/Services: Advisory Committee); astarte (Ongoing) (Products/Services: Advisory Committee); glycome (Ongoing) (Products/Services: Consultant); Infant Bacterial Therapeutics (Ongoing) (Products/Services: Research Support including clinical trials & the principal or named investigator); medela (Ongoing) (Products/Services: Advisory Committee); nestle nutrition institute (Ongoing) (Products/Services: Advisory Committee)
Mohan Pammi, MD PHD: I do not have any relevant financial / non-financial relationships with any proprietary interests.

Session

Description: The National Institute of Health (NIH) defines precision medicine as ‘an innovative approach that takes into account individual differences in patients’ genes, environments, and lifestyles’ and has initiated the 2020-2030 Strategic Plan for Nutrition Research that emphasizes precision nutrition for preterm infants. Current nutritional guidelines in preterm infants are based on population statistics, although helpful may marginalize some preterm infants. Optimal nutrition not only enhances lifelong health but also influences transgenerational outcomes by epigenetic mechanisms. Once growth faltering or malnutrition is noticed using a growth curve or existing indicators (retroactive approach), it may already be too late for meaningful interventions. Optimization of nutrition via a personalized proactive approach, where malnutrition or faltering growth curve can be predicted before they occur for timely interventions is urgently needed (precision nutrition).

Recent technological advances have provided access to multiomics data that could be harnessed along with clinical data, utilizing machine learning tools for precision nutrition. Digital twin concept (DTC) is a health model in which deep phenotypic and molecular characteristics of a patient are closely matched to thousands of patients with similar clinical and molecular profiles, allowing better prediction of individualized treatment and health outcomes. The DTC is composed of a physical element (the patient), a cybernetic element (the patient’s DT), and two-way interactions between the two elements. The sensors transform the signals of the patient into the DT of the patient. Artificial intelligence software processes the signals to act through recommendations or automatic adaptations of the patient’s management.

Learning Objectives:

  • Summarize current advances in Precision Nutrition with multi-omics data and machine learning.
  • Discuss the Digital Twin Concept (DTC) for predicting and optimizing nutritional outcomes
  • Strategize interventions based on DTC and predictive models to enhance nutritional outcomes in preterm infants