QIAGEN (NYSE: QGEN; Frankfurt Prime Standard: QIA) announced at the 2026 BIO-IT World Conference & Expo in Boston that the QIAGEN Digital Insights bioinformatics business and its curated knowledge bases and bioinformatics expertise will be integrating NVIDIA accelerated computing and the NVIDIA BioNeMo platform to help researchers use AI more effectively in drug discovery.
The integration is designed to help pharmaceutical and biotechnology researchers better understand disease biology, identify promising therapeutic targets and uncover biomarkers that can support faster and more effective development of new medicines.
Drug discovery depends on connecting large amounts of complex biological information, including genes, diseases, pathways, compounds and clinical evidence. For many research teams, the challenge is finding the most relevant connections amid increasing amounts of data to understand why they matter and assess whether an AI-generated insight is supported by credible biology.
QIAGEN and NVIDIA are working to address this challenge through graph-based AI. This approach applies retrieval and reasoning techniques over biomedical knowledge graphs, allowing researchers to explore evidence across biological systems and supporting a path toward agentic, multi-step workflows for drug discovery.
“QIAGEN Digital Insights has spent more than 25 years building the biomedical knowledge foundation that researchers rely on to interpret complex biology,” said Nitin Sood, Senior Vice President and Head of Product Portfolio & Innovation at QIAGEN. “Through this collaboration with NVIDIA, we can accelerate the impact of that knowledge by combining it with advanced AI to help customers improve critical steps in drug discovery, from target identification to biomarker research and hypothesis generation.”
The collaboration is designed to support practical applications across the drug discovery lifecycle, including target identification and validation, drug repurposing, biomarker discovery, pathway analysis and hypothesis generation from multi-omics data. By combining curated biomedical knowledge, graph-based AI and accelerated computing, QIAGEN aims to help research teams move from complex data to better-informed discovery decisions.
Initial pilot programs will be made available to select pharmaceutical and biotechnology partners, with broader availability of these new solutions expected following validation.
QIAGEN Digital Insights is developing a range of new AI-enhanced solutions designed to help life sciences organizations extract more value from complex biological, clinical and molecular data.
These solutions build on more than 25 years of curated biomedical knowledge, including knowledge bases used by more than 150,000 scientists worldwide and supported by more than 70,000 scientific publications. By organizing evidence across genes, diseases, pathways, compounds, clinical insights and more than 30,000 diseases, QIAGEN Digital Insights provides the scientific context needed to help researchers assess whether AI-generated insights are biologically credible, novel and relevant to drug discovery.
QIAGEN’s Discovery Platform integrates curated information across genes, diseases, pathways, compounds and clinical insights. To support AI-driven querying across this knowledge graph, the platform is designed to incorporate graph-based retrieval AI drawing on frameworks such as PyTorch Geometric and GPU accelerated GraphRAG systems, with delivery through the NVIDIA BioNeMo platform. This will enable researchers to ask natural language questions across biomedical knowledge graphs while retaining a clear link to structured scientific evidence.
To learn more about the pilot program or explore how the QIAGEN Discovery Platform can support your drug discovery workflows, visit https://digitalinsights.qiagen.com/qiagen-discovery-platform