Toward precision music medicine in oncology care: reproducible, scalable and biomarker-driven interventions.

A powerful modulator of the human stress response, music can substantially affect neurophysiological activities and target dysfunctional circuits implicated in various disorders including cancer. However, its clinical application has only recently garnered scientific attention. Cancer functions as both a disease and chronic stressor, triggering an inflammatory response and cascade of symptoms-including pain, fatigue, and cognitive dysfunction-prompting interest in supportive therapies that are non-invasive, low-cost, and scalable. Among these strategies, music-based interventions (MBIs) have shown promise. Whereas music therapy involves active guidance from a certified therapist, music medicine is a passive but immersive musical exposure without facilitation or active patient engagement. However, many studies conflate these modalities, limiting clarity and clinical translation. We focus distinctly on music medicine and discuss potential for application in oncology settings as a scalable and emerging empirically supported intervention capable of eliciting reproducible and measurable outcomes. We identify gaps in previous music medicine research, particularly its reliance on subjective endpoints, and recommend complementing these outcomes within a neurophysiological framework supported by objective assays incorporated into ongoing multidisciplinary, multimodal trials. We also propose integration of artificial intelligence and computational modelling to systematise outcome-specific music selection and validate music medicine's ability to modulate neurophysiological pathways involved in cancer-related symptoms.