Vyasa canonical
data fabric

Biomedical Literature in Vyasa's Canonical Data Fabric

Gain real-time insights from the latest research and content published by the healthcare and life science industries. Vyasa’s Canonical Data Fabric is a collection of biomedical resources that can be seamlessly searched and analyzed via powerful transformer-based deep learning models.

This unique and proprietary resource allows you to unify valuable healthcare and life science content with your internal data.

Vyasa’s Canonical Data Fabric is available through a simple subscription service. 

Biomedical Data Sources

Vyasa’s Canonical Data Fabric delivers access to the following resources:

  • arXiv – Repository of preprint and postprint scientific literature
  • bioRxiv – Library of preprint biological science literature
  • Biotech News – Collection of biomedical RSS feeds curated by Vyasa
  • ClinicalTrials.gov – Latest information on publicly and privately sponsored clinical trials on diseases, conditions, therapeutics and more
  • medRxiv – Collection of preprint health science literature
  • National Institute of Health and Care Excellence (NICE) – Published guidelines from England’s Department of Health and Social Care
  • PubChem – World’s largest database of chemical and molecular data
  • PubMed – Repository of MEDLINE references and abstracts, as well as additional journals and publications
  • PubMed Central Open Access – Full text archive of healthcare and life science journal publications
  • U.S. Patent Office (USPTO) – Database of U.S. patent filings across industries

Named Entity Recognition (NER)

Vyasa’s named entity recognition (NER) tags and categorizes terms and phrases from content within the Canonical Data Fabric. NER concepts are continuously updated and refined by our deep learning models to reflect the current language of the domain and novel terms not previously mentioned in literature.

With Vyasa’s NER, you can quickly identify insights and terms of interest hidden within your data.

Exploring the

Canonical Data Fabric

Early-Stage Research & Target Discovery

Early-stage research and target discovery requires searching the latest scientific literature which is both time and labor-intensive.

Vyasa brings these insights to your fingertips, enabling you to run queries in natural language and explore results through visual, low-code tools. Vyasa Axon collects query results from across the Canonical Data Fabric. Results are represented in a dynamic knowledge graph, allowing you to uncover novel insights and relationships in their data to identify biological entities and targets. 

Clinical Trial Analysis

When developing a new drug, pharmaceutical firms need to review thousands of PDFs, each hundreds of pages long, from public sources and their own repositories.

Historically, large teams have spent weeks manually processing these documents. Vyasa analyzes content from the Canonical Data Fabric with proprietary deep learning models.

Vyasa Synapse retrieves the answers and automatically compiles them into easy-to-review formats including smart spreadsheets. Collectively, the protocol summaries are produced in minutes, instead of days or weeks.

Medical Writing

Enable comprehensive biomedical literature and clinical trial reviews to identify unmet disease area needs and monitor publishing trends occurring within real-world data and real-world evidence. Identify key authors, organizations and technologies as well as sentiment and publishing focus. Detect relevant insights and emerging trends across all relevant sources. Generate semi-structured data records from vast document repositories in fractions of the time required by manual review and extraction (typically a saving of weeks to months of time per project).

Vyasa features a suite of application interfaces
for exploring your data fabric.