Engineering Epistemic Resilience: Overcoming Ontological Fragmentation in Pharmaceutical AI

Pharmaceutical quality regulatory oversight remains constrained by legacy ontologies that collapse complex engineered drug products and manufacturing processes into static legal descriptors. This ontological fragmentation generates persistent epistemic vulnerabilities, as demonstrated by recurring therapeutic equivalence failures and the inability of current systems to detect clinically meaningful divergence between regulatory assertions and real-world performance. This Perspective proposes Forced-Contradiction Retrieval (FCR) embedded within a five-layer CMC-GraphRAG architecture as a conceptual mechanism to address these limitations. FCR introduces an antithesis pathway that systematically juxtaposes regulatory assertions with structured mechanistic priors and patient-reported outcomes, quantifying divergence through Semantic Friction (ΔSF), a continuous conceptual measure of ontological misalignment. The framework integrates foundational pharmaceutical ontologies (POPE and COPE), the NIPTE-FDA Excipients Knowledge Base, and New Prior Knowledge (NPK) to enable proactive detection of ontological drift and reverse-causal mapping from real-world evidence to critical quality attribute failures. By transforming retrieval from confirmatory to contradiction-seeking, the proposed architecture aims to support more resilient, evidence-aligned regulatory decision-making that reflects the human-centric aspirations of Pharma 5.0. Implementation challenges and a research agenda for formalizing ΔSF and related metrics are outlined. The work invites the JAIKE community to advance epistemically robust, contradiction-aware AI systems for pharmaceutical regulation.