Real-World Evidence (RWE) is a critical enabler of personalized medicine (PM), offering granular insights into how interventions perform across diverse, real-life populations. This manuscript, grounded in over 30 years of health data science and regulatory experience, explores the evolving role of RWE in transforming healthcare delivery-from regulatory frameworks and policy alignment to artificial intelligence (AI)-enabled patient stratification. Through real-world case examples in oncology, ophthalmology, and dermatology, the article illustrates how digital tools and data integration can enhance patient-centred care. Each vignette concludes with an "adoption path" outlining data requirements, minimal IT changes, training, and payer-relevant endpoints. The discussion critically examines risks-such as bias, opacity in algorithms, and lack of harmonization-and translates them into a pre-deployment audit checklist and an equity checklist for subgroup performance and representativeness audits. To guide global regulatory practice, a "regulatory pragmatics" checklist is proposed, covering data quality, traceability, validation, transparency, and patient voice, including patient-generated health data (PGHD). Building on the Healthcare 5.0 vision, the manuscript aligns RWE with human-centric, sustainable, and resilient pillars, highlighting IoT wearables, environmental sensors, and continuous lifestyle data streams. Policy and implementation recommendations, together with a global convergence roadmap, position RWE as a strategic tool for regulators, payers, and clinicians. The paper concludes with a call for systemic accountability: industry must innovate responsibly, regulators must approve with foresight, payers must assess tools beyond medications, and health systems must bridge infrastructure gaps. Over the next 12-24 months, measurable commitments are required across all stakeholders to ensure that PM becomes everyday care. PM must serve patients-not just science, policy, or business-and that demands leadership grounded in scientific integrity and human empathy.
Keywords: artificial intelligence; dermatology; digital health; health policy; oncology; ophthalmology; personalized medicine; real-world evidence.
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