The National Institutes of Health launched Linked Discoveries on Thursday, an experimental tool designed to help scientists see how an individual research finding relates to the larger body of biomedical evidence. From a citation in PubMed, users can explore a "neighborhood" of closely related publications, including replication studies. More than 29 million PubMed publications are represented at launch.
Developed by NIH's National Library of Medicine, which oversees PubMed, the tool is an early product of an agency-wide initiative to strengthen replication and reproducibility in NIH-funded research. It aims to address the difficulty of determining how a finding fits within existing evidence, since relevant studies may be dispersed across different resources and traditional literature searches can favor already prominent or frequently cited work.
"With modern science racing forward at incredible speed, we face an ever-growing volume of biomedical literature but lack a way to understand how it relates to one another or contributes to the broader scientific context," said NIH Director Jay Bhattacharya, M.D., Ph.D. "Finding the right information and related publications isn't just about matching keywords, it's about understanding how ideas connect, how findings build on one another, and how research evolves as new evidence emerges. Linked Discoveries was designed to support that level of exploration."
Using an AI-informed approach, Linked Discoveries identifies related publications and lets users examine connections through graph and timeline views. Researchers can narrow a neighborhood by conditions, genes and chemicals and see citation connections, reviews, retractions and NIH-funded publications. The tool does not judge study quality or determine whether a finding has been replicated; it organizes connections and provides context so researchers can evaluate evidence themselves.
"Rather than treating published literature as a static collection of facts, Linked Discoveries enables dynamic and discerning engagement," said NLM Director Peter Embí, M.D. "By allowing users to explore the 'neighborhood' of related articles surrounding a publication, we can give researchers a broader view of the work that came before and after it, helping them explore context and identify questions that may warrant further investigation."
The September 24 launch is the first public version. NLM said it will continue to test and refine the tool using user feedback, which can be submitted within the tool, to inform future features.