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How We Classified 38.6M PubMed Records: Hybrid NLP Pipelines vs LLMs

A comparison of two approaches to large scale biomedical literature classification: LLM based classification and a hybrid architecture combining named entity recognition, ontology embeddings, and disease normalization. Using 38.6 million PubMed records, we evaluated throughput, cost, ontology alignment, and traceability, finding that hybrid pipelines remain the more practical choice for production scale, ontology driven systems.

Understanding ODM in Clinical Trials, and Why It Still Matters

Clinical trials today run across a complex mix of systems. Data moves between Electronic Data Capture systems, Clinical Trial Management Systems, ePRO platforms, safety databases, and analytics environments. Without a shared structure, this exchange becomes slow, expensive, and error-prone. This is where ODM comes in.