Integrating cure and care in Alzheimer's disease: a systems perspective for precision medicine

Alzheimer's disease remains a major global health challenge, with limited disease-modifying therapies and a rapidly growing societal burden. Although amyloid and tau remain central to the field, current evidence also implicates neuroinflammation, immune dysregulation, vascular dysfunction, and host-microbe interactions in disease pathogenesis. These developments support a broader systems framework, but simply combining additional disciplines or data modalities does not by itself preserve the dynamic biology or lived experience of disease. Artificial intelligence multi-omics, and digital biomarkers can help identify clinically meaningful patterns only when data and models preserve relevant structure across time, scale, context, and uncertainty. Realizing this potential will require responsible international data sharing, interoperable infrastructure, explicit evidence provenance, and ethical governance grounded in FAIR principles, context-appropriate explainability, and privacy-preserving approaches such as federated learning. Scientific progress should therefore be measured not only by disease modification, but also by patterns of cognition, behavior, function, quality of life, and caregiver burden. This Perspective argues that cure and care are not competing or merely parallel priorities; they are linked outputs of the same continuously learning research and care ecosystem.