-QIAGEN N.V.  announced new artificial intelligence (AI) capabilities to help researchers analyze complex biological and genomic data faster while keeping the scientific evidence behind the results visible.

The expansion includes IPA Investigator, a new AI research companion for QIAGEN Ingenuity Pathway Analysis (IPA), and the new QIAGEN Discovery Platform, which extends these capabilities into automated drug discovery workflows.

The new offerings build on more than 25 years of biomedical knowledge from QIAGEN Digital Insights (QDI), whose bioinformatics solutions are used by around 150,000 users. The global market for AI in bioinformatics is projected to more than double from about $12 billion in 2026 to more than $25 billion by 2031, according to Mordor Intelligence.

As researchers increasingly use AI to analyze growing volumes of biological and genomic data, speed alone is not enough. QIAGEN combines AI with expert-reviewed biological, genomic and clinical information so scientists can examine the evidence behind the results.

“AI can deliver an answer in seconds, but in science, speed without evidence can create false confidence,” said Dominic John, Vice President and Head of QIAGEN Digital Insights. “Our approach is to combine the speed of AI with expert-curated biomedical knowledge and traceable scientific evidence so researchers can examine the evidence behind the results and evaluate them for themselves.”

IPA Investigator allows scientists to ask questions about their data in natural language. It can identify relevant biological relationships, recommend analyses and carry them out within IPA. Researchers can then connect their own experimental data with existing biological knowledge to better understand disease, identify potential drug targets and decide what to investigate next.

At the University of Bergen in Norway, researchers tested IPA Investigator using complex datasets that deliberately introduced misleading sample comparisons.

“We deliberately introduced misleading comparisons to see how IPA Investigator would respond. It identified the problem, cautioned us against overinterpreting the results and suggested a better experimental design,” said Dr. Simona Chera, Professor at the University of Bergen.

QIAGEN is also introducing the QIAGEN Discovery Platform, which enables the integration of AI with QIAGEN’s biomedical knowledge base and molecular data to support drug discovery. The platform is designed to help researchers identify potential drug targets and biomarkers, generate research hypotheses and automate parts of the discovery process.

The launches are part of a broader rollout of AI across QIAGEN Digital Insights, including AI-powered translation in QIAGEN Clinical Insight (QCI) Interpret and machine learning combined with expert-reviewed information in Franklin by QIAGEN.