Work

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

Year: 2025

Type: article

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.

Source: Pharmacological Research

DOI: 10.1016/j.phrs.2025.107952

Authors: Chang Hyung Lee, Sang-Han Lee

Institutions: Harvard University, Seoul National University, Sungkyunkwan University, Kyungpook National University

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $4,130