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Global Translational Medicine Precision medicine via personalized nutrition

proteomics—using computational biology tools. This
combination has the potential to advance the diagnosis,
prognosis, and treatment of complex diseases. However,
several key challenges remain in interactomics and
network medicine, including the incompleteness of the
molecular interactome, difficulties in recognizing critical
genes within genetic association regions, and the limited
application of these approaches to human diseases.
3. Advances in food analytics and
digitalization in PN and PF
Food analysis is an evolving field that focuses on the
development of more robust, efficient, and sensitive
analytical techniques. To achieve these goals, information
technologies (IT) such as AI and ML, along with advanced
computational resources, are employed to process and
extract data (e.g., gathering dietary information) and
to integrate model features for generating outputs that Figure 12. Big data analytics in personalized nutrition (PN) involves
the genome, metabolome, microbiome, lifestyle, diet, and phenome.
elucidate the complex relationship within large-scale “Big Nutrition plays a key role in our overall well-being, influencing both
Data” datasets, which encompass numerous data points physical and mental health. As understanding of the intricate relationship
and variables (Figure 12). between diet and health advances, PN has emerged as a promising
strategy to optimize individual dietary choices. This approach involves
Recent advances have led to significant developments customizing dietary recommendations based on unique characteristics
in novel techniques in the following areas: such as genetics, metabolism, lifestyle, and health goals. By adjusting the
diet to meet specific needs, PN can aid in managing chronic conditions,
(i). Molecular methods and DNA-based techniques now boosting the immune system, improving energy levels, and lowering
enable faster and more precise detection of bacteria the risk of diet-related diseases. Although the integration of digital
in foods, characterization of microbial communities, technologies has facilitated technical advancements and the broader
and identification of genetically engineered crops, all adoption of PN, challenges and ethical concerns remain, such as data
of which remain critical areas of investigation. privacy, algorithmic accuracy, and potential biases in data analysis. PN
leverages the latest advancements in analytical instrumentation (e.g.,
(ii). Biosensors are analytical devices composed of a omics) and computational tools (e.g., big data and AI) to gain deeper
specific biologically recognized element, such as insights into the connections between foods, individuals, and health.
enzymes, antibodies, or microbes, paired with a This knowledge is then applied to the design of foods tailored to specific
transducer that converts a biochemical response into nutritional needs, ultimately promoting better health and well-being. 9
an electrical signal. These devices are used to detect
food components, including preservatives, colorants, highlights the importance of providing consumer feedback
and sweeteners, as well as contaminants such as toxins, and establishing a continuous support system to monitor
pesticides, antibiotics, hormones, and microbes. progress and encourage behavior changes that promote
(iii). The development of advanced methodologies has positive health outcomes. Meanwhile, digitalization can
led to the application of peptide nucleic acid-based facilitate the adoption of PN and PF through the following
technologies for food authentication and analysis, means:
the refinement of immunoassay techniques to detect (i). Data collection and analysis: Digital tools and
veterinary drug residues in food products, and the platforms allow users to gather and track their health-
enhancement of methods for characterizing plant related data, such as blood sugar levels, cholesterol,
food allergens. Figure 13 provides a comprehensive lipid profiles, and nutritional and dietary biomarkers,
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overview of the components and activities that through wearables, mobile applications, and genetic
constitute a fully integrated and PN service. testing. Advancements in profiling algorithms enable
Figure 13 provides a comprehensive overview of the key the rapid management of vast amounts of data and the
elements and activities that constitute a PN-guided service. identification of patterns and correlations.
Specifically, it illustrates the process from utilizing various (ii). Personalized meal planning: Digital platforms can
technologies for data collection, as previously discussed, generate and recommend customized meal plans
to processing this information through big data analytics, based on an individual’s dietary preferences, genetics,
algorithms, and AI to generate PN advice. In addition, it allergies, nutritional requirements, and health

Volume 4 Issue 3 (2025) 72 doi: 10.36922/GTM025080017