Natural products, artificial intelligence, and the future of anti-aging pharmacology: A human-centered call to action

Aging is increasingly recognized as a process driven by oxidative stress, chronic inflammation, mitochondrial decline, and impaired autophagy. Natural products provide a rich source of antioxidants and autophagy modulators that can counteract these hallmarks of aging, yet their translation into effective interventions has been slow. Recent advances in artificial intelligence (AI), omics and bioinformatic technologies now enable the systematic identification of active compounds, prediction of their molecular targets, and optimization of synergistic combinations. Within a systems pharmacology framework, these tools can transform fragmented findings into an integrated understanding of how natural products promote healthy aging. This perspective highlights the urgent need for human-centered strategies that combine traditional pharmacology with AI-driven discovery to advance safe, effective, and personalized anti-aging preventions/therapeutics.

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Publication Details

Journal
Pharmacological Research
Published
2025-09-16
DOI
https://doi.org/10.1016/j.phrs.2025.107952
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
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article

Natural products, artificial intelligence, and the future of anti-aging pharmacology: A human-centered call to action

Chang Hyung Lee, Sang‐Han Lee
Pharmacological Research
Computational Drug Discovery Methods
article

Natural products, artificial intelligence, and the future of anti-aging pharmacology: A human-centered call to action

Chang Hyung Lee, Sang‐Han Lee
article en

Abstract

Aging is increasingly recognized as a process driven by oxidative stress, chronic inflammation, mitochondrial decline, and impaired autophagy. Natural products provide a rich source of antioxidants and autophagy modulators that can counteract these hallmarks of aging, yet their translation into effective interventions has been slow. Recent advances in artificial intelligence (AI), omics and bioinformatic technologies now enable the systematic identification of active compounds, prediction of their molecular targets, and optimization of synergistic combinations. Within a systems pharmacology framework, these tools can transform fragmented findings into an integrated understanding of how natural products promote healthy aging. This perspective highlights the urgent need for human-centered strategies that combine traditional pharmacology with AI-driven discovery to advance safe, effective, and personalized anti-aging preventions/therapeutics.

Pharmacological ResearchVol. 221
Kyungpook National University (KR), Sungkyunkwan University (KR)
Openalex Percentile: Top 73%
Computational Drug Discovery Methods
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Natural products, artificial intelligence, and the future of anti-aging pharmacology: A human-centered call to action — Chang Hyung Lee, Sang‐Han Lee · Pharmacological Research (2025) | TGRS Research Map | TGRS