Lexigram raises $2M VC to process healthcare-specific natural language
Natural language processing for health tech start-up Lexigram has closed its first venture capital seed round at $2m. Led by Storm Ventures, the round also included investments from RTA Ventures and Stanford-StartX Fund. Lexigram has only been in operation for a year, but it aims to position itself as an on-demand software-as-a-service (SaaS) provider of natural language processing for the health sector. Its technology gives structure to clinical data to apply analytics and provide results to healthcare provides. The full offering of a data-processing pipeline will be available online from 2017, and will also include machine learning.
Lexigram, a Silicon Valley startup that applies on-demand natural language processing to health data in the cloud, has closed on its first venture capital, a $2 million seed round.

Storm Ventures is the lead investor; other participants include RTA Ventures and the Stanford-StartX Fund. The Stanford connection makes sense, as Redwood City, California-based Lexigram grew out of the Stanford Center for Biomedical Informatics Research.

Year-old Lexigram is positioning itself as an “on-demand” software-as-a-service provider of natural language processing and machine learning, though it is launching with just the NLP enabled.

“It’s something that’s sorely needed,” CEO Paul Alexander said.

Lexigram said that the popularity of free-text progress notes, PDF files and electronic faxes means that as much as 80 percent of information in electronic health records is unstructured. Such unstructured data is fairly useless to clinical decision support systems and other analytics engines.

Adding structure and context allows healthcare organizations to apply analytics to all that information. The SaaS model is intended to bring this technology to smaller healthcare providers that don’t have data scientists on staff, Alexander explained.

The company supplies its technology through application programming interfaces.

The first API, introduced about a month ago, pulls in unstructured data from multiple sources offers access to a knowledge graph that ties to BioPortal, a massive repository of medical ontologies. Alexander and his two other cofounders, Manuel Salvadores and Paea LePendu, worked on BioPortal while at Stanford.

“The full data-processing pipeline will be online next year,” Alexander said. That part will include machine learning.

As an introductory offer, Lexigram is offering three months of free access to the technology to the first 100 customers to sign up, Alexander said. After that, users will pay a monthly subscription fee.

Photo: Lexigram