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Updated: Jul 14, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Medical Affairs in the Age of Complexity: From Scientific Support to Strategic Enterprise Integrator
1MAestro Medical Solutions, Cologne, Germany. connect@maestroms.net.
Abstract:
Regulatory acceleration, expanded reliance on real-world evidence (RWE), and increasing integration of artificial intelligence (AI) into healthcare systems have substantially reshaped expectations placed on Medical Affairs. Accelerated and conditional approval pathways are progressively shifting confirmatory evidence generation into the post-marketing phase, while regulatory agencies have formalized frameworks for incorporating RWE into benefit-risk evaluation and lifecycle decision making. In parallel, healthcare systems are increasingly conceptualized as learning health systems in which routine-care data inform iterative improvement. This Leading Article proposes a conceptual but operationally applicable framework that positions Medical Affairs as a Strategic Enterprise Integrator, responsible for coordinating lifecycle evidence architecture, scientific exchange, insight translation, and governance across development and real-world settings. The framework is structured around four interdependent capability domains: lifecycle evidence architecture; scientific translation and insight management; cross-functional governance; and AI/data governance, including oversight of large language model (LLM)-supported workflows in medical information and analytics. The proposed model explicitly delineates interfaces with Clinical Development, Pharmacovigilance, Market Access/Health Economics and Outcomes Research, and Commercial functions to reduce redundancy while preserving functional accountability. Methodological considerations for RWE are anchored in principles of fit-for-purpose data, study design discipline, and transparent interpretation, while AI-enabled processes are addressed through a scientific governance lens emphasizing validation, auditability, and context-of-use. Illustrative operational examples and a staged maturity model with measurable indicators are introduced to support practical implementation. The framework positions Medical Affairs as a scientifically accountable integrator of lifecycle evidence within evolving regulatory science. As a conceptual model this framework requires further empirical validation to assess its applicability and generalizability across organizational contexts.
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