At the BIO-IT World Conference & Expo 2026, QIAGEN revealed that its bioinformatics arm, QIAGEN Digital Insights, will be leveraging NVIDIA accelerated computing and the NVIDIA BioNeMo platform. The combination is designed to assist programmers in pharmaceutical and biotechnology who are aiming to optimize the usage of artificial intelligence for drug discovery.
Researchers will soon be able to use this tool for accurate biological data analysis which leads to disease mechanisms comprehension, therapeutic target identification, biomarker discovery, and drug development acceleration.
Yet today drug discovery is considered one of the most difficult processes where researchers are not only using but also integrating large volumes of interconnected biological and clinical data, including genes diseases pathways, compounds, and scientific literature. As datasets grow, research teams are more and more facing the problem of how to identify the most significant biological relationships and how to check the scientific credibility of AI-generated findings.
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To solve this issue, QIAGEN in collaboration with NVIDIA is implementing graph-based AI methods that integrate information retrieval and reasoning techniques through biomedical knowledge graphs. The objective of such systems is to assist researchers not only in figuring out biological evidence more quickly but also in laying the groundwork for agentic, multi-step AI drug discovery workflows down the line.
“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. “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 initiative will support multiple applications across the drug discovery lifecycle, including:
- Target identification and validation
- Drug repurposing research
- Biomarker discovery
- Pathway analysis
- Hypothesis generation from multi-omics datasets
QIAGEN said that their partnership fuses curated biomedical data, graph-format AI modeling, and high-speed computing to make it easier for scientists to turn raw biological data into evidence-based research findings.
The Discovery Platform from the company compiles curated scientific data about genes diseases pathways, compounds, and clinical insights.
The platform is planned to feature graph-based retrieval AI and will be built using such technologies as PyTorch Geometric and GPU-accelerated GraphRAG systems, a part of the NVIDIA BioNeMo platform.
This structure will provide researchers with the ability to use natural language to query biomedical knowledge graphs, and at the same time, keep the links to the verified scientific evidence.
QIAGEN said that its curated biomedical knowledge bases are backed by over 25 years of scientific curation, more than 70,000 scientific publications
