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bioRxiv · 10.64898/2026.01.16.699755

PersonaAI: An Interactive Agentic-AI Framework for Autonomous Hypothesis Generation and Validation in Aging

Cho, B.·Lee, G.-Y.·Jung, J.·Kim, J.·Park, G.·Martin, P. C. N.·Kim, H.·Oh, J.·Kim, J.-S.·Kim, T.-H.·Won, K.-J.
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Abstract

Elucidating the mechanisms of aging is impeded by its stochastic, multi-scale nature and cellular heterogeneity, challenges that are compounded by the overwhelming volume of biomedical literature and the complexity of genome-wide datasets. To overcome these barriers, we present PersonaAI, an interactive agentic-AI framework that acts as a digital co-scientist. By integrating literature-based reasoning with autonomous in silico validation, PersonaAI synthesizes over 560,000 aging-related publications via retrieval-augmented generation (RAG) to propose mechanistic hypotheses. These hypotheses are subsequently validated by autonomous agents utilizing single-cell RNA-seq data. Using a temporal cutoff strategy restricted to pre-2020 literature, we demonstrate that PersonaAI can generate hypotheses effectively validated by post-2021 discoveries, proving its capacity for inference beyond simple information retrieval. In application, the system identified senescent Cirbp+ hepatocytes as a liver-intrinsic aging program and uncovered a middle-aged, male-specific decline in adipose stem and progenitor cells, driven by vascular niche deterioration and disrupted VEGF-VEGFR signaling. These results establish PersonaAI as a scalable platform that augments human intuition with autonomous data-driven validation, providing a generalizable platform for accelerating discovery in aging biology.

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Cho, B., Lee, G.-Y., Jung, J., Kim, J., Park, G., Martin, P. C. N., Kim, H., Oh, J., Kim, J.-S., Kim, T.-H., Won, K.-J.. 2026-01-20. PersonaAI: An Interactive Agentic-AI Framework for Autonomous Hypothesis Generation and Validation in Aging. https://doi.org/10.64898/2026.01.16.699755

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