A Precision Medicine Framework for Individualized Migraine Management: A Data-Driven Clinical Approach

Abstract

Migraine is a highly prevalent neurological disorder characterized by substantial inter-individual variability in symptom presentation, triggers, and treatment response. Despite advances in pharmacological and non-pharmacological therapies, clinical practice largely relies on standardized protocols that fail to address this heterogeneity. This study proposes and evaluates a precision medicine framework designed to deliver individualized migraine management through accurate diagnosis and adaptive, patient-specific treatment strategies.The framework employs a mixed-methods approach integrating comprehensive clinical assessments, validated patient-reported outcome measures, and longitudinal symptom tracking via digital health technologies. Key findings demonstrate that personalized interventions—tailored to unique trigger profiles, comorbidities, and behavioral patterns—significantly enhance treatment efficacy. Compared with patients receiving guideline-based care, those managed under the individualized framework exhibited improved therapeutic response, reduced migraine frequency and severity, and better quality-of-life outcomes. Moreover, the approach facilitates early detection of adverse symptom trajectories, enabling proactive adjustments that may prevent progression to chronic migraine.In the context of rising global migraine prevalence, the shift toward precision medicine, and widespread adoption of digital health ecosystems, this framework offers a timely, evidence-based contribution to modern neurological care. It provides a scalable, patient-centered model that supports the transition to flexible, data-driven healthcare delivery.