A central theme was the increasing use of AI‑enhanced real‑world data pipelines in drug development, including hypothesis‑free drug‑wide association studies and multimethod validation frameworks combining disproportionality analyses, new‑user cohorts, SCCS designs, and machine‑learning models such as random forests and XGBoost. These approaches illustrate maturing analytical standards directly aligned with our group’s work on causal inference and robust pharmacoepidemiologic study design.
Of particular interest to Norwegian registry research was the session on transportability and external validity, where Medaffcon presented a project using Norwegian data to evaluate how RWE generalizes across populations. The discussion highlighted how alignment of eligibility criteria, index dates, endpoints, covariates, and follow‑up windows is essential when constructing external control arms—a topic increasingly relevant as we expand registry‑based comparative effectiveness work.
The conference also underscored the strategic role of Nordic collaboration between data access bodies, an important development as cross‑border methods become more feasible and expectations for federated analytics grow. For our group, this trend strengthens the case for building methods and workflows that are interoperable across countries and registries.
Together, the sessions confirmed that the Nordic region is moving rapidly toward more sophisticated, AI‑supported, registry‑based evidence generation—directly reinforcing the methodological direction and scientific priorities of our research group.