This review explores the transformative potentials of artificial intelligence (AI) in promoting healthspan and longevity. Healthspan focuses on enhancing quality of life free from chronic conditions, while longevity defines current lifespan limits within a particular species and encompasses biological aging at multiple levels. AI methodologies—including machine learning, deep learning, natural language processing, robotics, and data analytics—offer unprecedented tools to analyze complex biological data, accelerate biomarker discovery, optimize therapeutic interventions, and personalize medicine. Notably, AI has facilitated breakthroughs in identifying accurate biomarkers of biological age, developing precision medicine approaches, accelerating drug discovery, and enhancing genomic editing technologies such as CRISPR. Further, AI-based analysis of endogenous cytoprotection, especially the activity of molecules such as heme oxygenase, with particular application to hemolytic diseases. AI-driven robotics and automated monitoring systems significantly improve elderly care, lifestyle interventions, and clinical trials, demonstrating considerable potential to extend both healthspan and lifespan. However, the integration of AI into longevity research poses ethical and societal challenges, including concerns over privacy, equitable access, and broader implications of extended human lifespans. Strategic interdisciplinary collaboration, transparent AI methodologies, standardized data frameworks, and equitable policy approaches are essential to responsibly harness AI’s full potential in transforming longevity science and improving human health.

Chronic non-communicable diseases rarely occur in isolation; cardiovascular, metabolic, neurodegenerative, malignant, and age-associated disorders share upstream drivers including oxidative stress, chronic inflammation, mitochondrial dysfunction, and metabolic imbalance. This narrative review synthesizes epidemiological, interventional, and mechanistic studies identified through targeted literature searches to examine redox biology as a shared mechanistic hub linking these conditions. We evaluate antioxidant-rich dietary patterns, selected nutraceuticals, myocardial ischemia–reperfusion injury as a clinical exemplar, rare redox-imbalance disorders as mechanistic stress models, and emerging gene-based reinforcement of endogenous antioxidant systems. Rather than proposing clinical targets, we present an integrative, hypothesis-generating framework illustrating how coordinated lifestyle-driven modulation of redox balance may simultaneously influence multiple disease trajectories. Collectively, the evidence supports a unified redox framework for multi-disease prevention for multi-disease prevention and future intervention design.

Aging is a multidimensional biological process that is not adequately captured by chronological age alone. Geroscience—the study of biological mechanisms that drive age-related functional decline and disease susceptibility—therefore requires biomarker frameworks that can identify biological aging trajectories and assess whether lifestyle-associated interventions meaningfully influence aging-related pathways. In this review, we propose a practical, mechanism-based framework for studying lifestyle-associated effects on cellular and whole-organism aging in humans. We examine major biomarker domains, including DNA-methylation-based epigenetic aging clocks, cellular senescence-associated measures, senescence-associated secretory phenotype factors, inflammaging mediators, oxidative stress indicators, mitochondrial function, metabolic and nutrient-sensing pathways, proteomic and metabolomic signatures, microbiome-associated markers, and functional measures of frailty, mobility, cognition, and resilience. We also discuss criteria for biomarker selection in exploratory and multicenter trials, emphasizing biological relevance, analytical validity, responsiveness to intervention, feasibility, reproducibility, and clinical interpretability. Finally, we outline a practical study-design roadmap integrating biospecimen collection, repeated assessments, core and exploratory biomarker panels, and functional endpoints. A biomarker-guided geroscience strategy may provide a practical route for connecting mechanistic aging biology with clinically relevant human studies designed to preserve healthspan and functional independence.