The white paper explains how AI‑driven predictive analytics can identify undiagnosed patients, predict disease progression and guide treatment decisions by analysing large, anonymised datasets from prescriptions, EHRs and wearables. Real‑world case studies show algorithms detecting under‑diagnosed conditions like idiopathic pulmonary fibrosis and non‑alcoholic steatohepatitis, enabling earlier intervention, and models that predict therapy changes in rheumatoid arthritis more accurately than traditional rules. Predictive analytics also supports patient‑centred physician targeting: instead of focusing on high prescribers, algorithms identify doctors with many eligible patients for new therapies. “Behind‑the‑firewall” deployment protects data privacy while offering decision support. The paper

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