PhytoIntelligence Framework: A Comprehensive AI-Driven Approach for Nutraceutical Design

Traditional nutraceutical development often relies on empirical methods, resulting in inconsistent efficacy and safety. This paper presents the PhytoIntelligence framework—an AI-assisted methodology that integrates advanced literature search, clinical validation, pharmacokinetics, synergy analysis, and regulatory compliance to optimize the formulation of certified vegan and organic multi-molecule supplements. Based oninitial observations of current limitations, our research question asks: Can an AI-drivensystematic approach improve the design and efficacy of nutraceutical formulations? Wehypothesize that integrating these processes will enable superior product outcomes. The paper details the mathematical framework and standardized reporting template that underpin the methodology, and demonstrates its application via an example report on Z-16, a novel supplement for Alzheimer’s prevention and cognitive health.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-25
DOI
https://doi.org/10.5281/zenodo.15084581
Primary Topic
Nutrition, Genetics, and Disease
Type
article
Field-Weighted Citation Impact
0.00
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article

PhytoIntelligence Framework: A Comprehensive AI-Driven Approach for Nutraceutical Design

Zenodo (CERN European Organization for Nuclear Research)
Nutrition, Genetics, and Disease
article

PhytoIntelligence Framework: A Comprehensive AI-Driven Approach for Nutraceutical Design

article en

Abstract

Traditional nutraceutical development often relies on empirical methods, resulting in inconsistent efficacy and safety. This paper presents the PhytoIntelligence framework—an AI-assisted methodology that integrates advanced literature search, clinical validation, pharmacokinetics, synergy analysis, and regulatory compliance to optimize the formulation of certified vegan and organic multi-molecule supplements. Based oninitial observations of current limitations, our research question asks: Can an AI-drivensystematic approach improve the design and efficacy of nutraceutical formulations? Wehypothesize that integrating these processes will enable superior product outcomes. The paper details the mathematical framework and standardized reporting template that underpin the methodology, and demonstrates its application via an example report on Z-16, a novel supplement for Alzheimer’s prevention and cognitive health.

Zenodo (CERN European Organization for Nuclear Research)
International Society for Optics and Photonics (US)
Openalex Percentile: Top 41%
Nutrition, Genetics, and Disease
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PhytoIntelligence Framework: A Comprehensive AI-Driven Approach for Nutraceutical Design · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS