Quertle has introduced a data analytics and visualization platform designed to enable researchers to unearth relevant information from the thicket of journal articles, patents and other documents that make up the scientific record.
Henderson, NV-based Quertle has spent years working on making it easier to search the scientific record, in which time it has won the National Library of Medicine’s software development challenge. Now, Quertle has introduced a platform called BioAI to improve its search features, while also adding visualization capabilities.
“BioAI combines the latest advances in AI using neural networks with natural language recognition,” Quertle CEO Jeff Saffer said in a statement. “This will enhance drug discovery, accelerating a return on investment, and improve processes across the industry.”
Saffer cofounded Quertle with long-term collaborator Vicki Burnett in 2009. Prior to setting up the company, Saffer and Burnett worked together at OmniViz and SciWit, both of which were involved in the development of software to analyze scientific data.
This interest in life science data analytics and visualization has now manifested in BioAI and the Qinsight product it underpins. Using Qinsight, researchers can sift through PubMed, patents, grant applications to the National Institutes of Health and other sources in search of information that can inform their programs and understanding of the competitive landscape.
None of this information is proprietary. What Quertle is selling is the ability to dig faster and deeper into the expanding repository of information that is available online to identify relevant information, and only relevant information.
To demonstrate why its platform is better than free alternatives, Quertle cites a handful of use cases, including one detailing what happens when a drug discovery team wants to find information on nitric oxide regulated pathways. As, according to Quertle, one-fifth of the scientific literature about nitric oxide refers to it only as NO, it can be hard to home in on relevant papers. Qinsight, in contrast, knows that in this context NO means nitric oxide and adjusts its search accordingly.