REVIEW article
Front. Aging
Sec. Healthy Longevity
Volume 6 - 2025 | doi: 10.3389/fragi.2025.1703698
Biomarker Integration and Biosensor Technologies Enabling AI-Driven Insights into Biological Aging
Provisionally accepted
- 1Department of Geography, University of Victoria, Victoria, Canada
- 2The University of British Columbia, Vancouver, Canada
- 3McMaster University Michael G DeGroote School of Medicine, Hamilton, Canada
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As the global population continues to age, there is an increasing demand for ways to accurately quantify the biological processes underlying aging. Biological age, unlike chronological age, reflects an individual's physiological state, offering a more accurate measure of health-span and age-related decline. This review focuses on four key biochemical markers - C-Reactive Protein (CRP), Insulin like Growth Factor-1 (IGF-1), Interleukin-6 (IL-6), and Growth Differentiation Factor-15 (GDF-15) – and explores how Artificial Intelligence (AI) and biosensor technologies enhance their measurement and interpretation. AI-driven methods including machine learning, deep learning, and generative models facilitate the interpretation of high dimensional datasets and support the development of widely accessible, data-informed tools for health monitoring and disease risk assessment. This paves the way for a future medical system, enabling more personalized and accessible care, offering deeper, data-driven insights into individual health trajectories, risk profiles, and treatment response. The review additionally highlights the key challenges and future directions for the implementation of AI-driven methods in precision aging frameworks.
Keywords: Longevity, biomarkers, CRP - C-reactive protein, IL-6 (Interleukin 6), IGF-1 (insulin-like growth factor 1), GDF-15, artificial intelligence, machine learning (ML)
Received: 11 Sep 2025; Accepted: 16 Oct 2025.
Copyright: © 2025 Kushner, Pandey and Kohli. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mohit Pandey, mohit@digen.ai
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