When Biology Meets Medicine: A Perspective on Foundation Models

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Authors: Kunying Niu, Yuxuan Wang, Limin Zou, Jing Huang
Cited by: 1
References: 52

Abstract

Foundation models (FMs) are reshaping artificial intelligence and are now poised to transform life sciences and medicine. Here, we review biological FMs across multiple hierarchical scales, spanning from molecules and sequences to cells and tissues, and medical FMs across diverse data modalities. We analyze the core technical advances enabling these systems, alongside the domain‐specific data challenges that currently limit their practical impact. We argue that progress in biomedical FMs depends not only on architectural innovation but also, critically, on addressing the constraints imposed by biological and medical data. We highlight public health insurance claims as a valuable yet underutilized data resource capable of bridging biological mechanisms with real‐world clinical outcomes. Finally, we outline a paradigm in which insurance‐informed FMs are embedded within agent systems, enabling more robust reasoning, adaptive experimentation, and decision support across biomedical domains.

Fields of Study & Subjects

Gene Regulatory Network Analysis Single-cell and spatial transcriptomics Biomedical Text Mining and Ontologies

Publication details

Journal / source
Advanced Intelligent Discovery
Publisher
Wiley
Publication date
27 March 2026
Language
EN