Despite initial forays into clinical settings, single-cell technologies do not yet routinely inform medical decision-making. Here, we identify and categorize barriers hindering the clinical deployment of single-cell omics. We articulate a framework to identify patient subpopulations that stand to benefit from such biomarkers and outline the requirements to derive actionable clinical readouts.

Significant progress has been made in recent years in applying large language models and multimodal artificial intelligence to health and medicine, transforming diagnostics, patient interactions, and medical forecasting, although challenges like privacy, regulation, and system integration remain before widespread clinical adoption.

Cell Death Discovery, Published online: 10 July 2025; doi:10.1038/s41420-025-02615-5The transcriptomic fingerprint of cancer response to Tumor Treating Fields (TTFields)