Neo4j can connect fragmented patient data into a unified view of the patient journey across providers, diagnoses, treatments, and other key touchpoints. We'll showcase how graph technology helps reveal care pathways, treatment gaps, and coordination issues that are difficult to capture in traditional systems, and attendees will learn how graph databases support richer patient journey analysis, more personalized care, and better clinical and operational decision-making.
Pete Aven, Sr. Solutions Engineer, Neo4j
Dr. Alexander Jarasch, Global Head of Pharmaceuticals & Life Sciences, Neo4j
From a single gene to a ranked map of disease drivers, drug candidates, and causal evidence — in one click. The Neo4j + QIAGEN solution turns Discovery KB Plus, QIAGEN's causal biomedical knowledge platform, into an interactive discovery surface. Researchers can query any biomarker of interest, traverse causal networks with graph data science, and surface drug repositioning candidates with full literature provenance and natural language summaries.
Yizhi Yin, PhD, Sr. Solutions Engineer, Neo4j
Kyle Nilson, PhD, Field Software Trainer, QIAGEN
