Linguamatics provides access to a range of content options, all accessible via I2E OnDemand or via our Connected Data Technology for those with an Enterprise installation. All documents are enhanced by including matches against a broad range of ontologies and the generation of document sections, such as title, abstract and author, in order to improve accuracy of extraction. Each source is refreshed weekly by Linguamatics, providing you with up-to-date information and access to the latest documents.
In additional to the following sources hosted by Linguamatics, we partner with Copyright Clearance Center to provide access to full-text journal articles via RightFind for XML Mining. Articles obtained in this way can then be accessed via I2E OnDemand.
ClinicalTrials.gov is a registry of federally and privately supported clinical trials conducted in the United States and around the world. ClinicalTrials.gov contains information about medical studies in human volunteers. Most of the records in ClinicalTrials.gov describe clinical trials (also called interventional studies). ClinicalTrials.gov also includes records describing observational studies and programs providing access to investigational drugs outside of clinical trial (expanded access). Studies listed in the database are conducted in all 50 US States as well as over 200 other countries.
As well as the standard ontologies, the Linguamatics ClinicalTrials.gov index includes its own domain specific ontology providing concepts specific to clinical trials e.g. Recruitment Status, Study Phase/Type/Design. Access to Linguamatics ClinicalTrials.gov for text mining enables researchers to assess clinical trial inclusion/exclusion criteria for patient selection, trial site evaluation and study design as well as to discover competitive intelligence around companies, diseases, targets and novel drugs.
Learn how I2E users can benefit from access to Clinicaltrials.gov
FAERS is a rich source of ready to use safety surveillance data to extract information about safety concerns reported by users and clinicians.
It is typically used to monitor and discover safety issues of a marketed drug product. The data is managed and maintained by FDA and made available for public download. Linguamatics processes this XML to make it searchable as an I2E index.
As well as the standard ontologies, the FAERS index includes its own domain-specific ontologies containing classes which can be used to filter or display FAERS documents by the contents of their structured fields (sections within the documents).
The data is sourced from the DailyMed site hosted by the US National Library of Medicine. It contains high quality information about marketed drugs. This information includes up-to-date and accurate FDA drug labels (package inserts) that describe the composition, form, packaging, and other properties of the drug products in detail. As well as the standard ontologies, FDA Drug Labels index includes its own domain specific ontologies providing concepts specific to drug types and document classifications as defined by FDA.
FDA Drug Labels provide a rich source of detailed intelligence on marketed drug products, including mechanism of action, pharmacology, safety/toxicity data, adverse events, contra-indications, and information on preclinical and clinical study outcomes.
MEDLINE® contains journal citations and abstracts for biomedical literature from around the world.
MEDLINE is the U.S. National Library of Medicine (NLM) premier bibliographic database that contains over 29 million references to journal articles in life sciences with a concentration on biomedicine. Each year there is a new release of the base distribution, usually in mid-December; thenthrough the rest of the year, approximately 2,000-4,000 references are added each day.
MEDLINE is an excellent source of biomedical research knowledge, covering decades of published articles from academic journals covering biochemistry, medicine, nursing, pharmacy, dentistry, veterinary medicine, and health care.
NIH Grants provides data on research projects funded by the National Institutes of Health (NIH), the Centers for Disease Control (CDC), the Food and Drug Administration (FDA), and the Department of Veterans Affairs (VA), their abstracts, and publications and patents citing support from these projects. The data are separated into four major categories of files: Projects, Project Abstracts, Publications, and Patents. The data is sourced from ExPORTER site (owned by NIH).
As well as the standard ontologies, NIH grants includes its own domain specific ontology providing concepts classifying the types of grants awarded. Access to NIH grants can facilitate the development of new collaborations, and provide information on most recent research challenges, through the rapid discovery and recommendation of researchers, key opinion leaders, current expertise, and resources.
Online Mendelian Inheritance in Man® (OMIM) is a comprehensive catalogue of human genes and genetic conditions and traits, with particular focus on the molecular relationship between genetic variation and phenotypic expression.
Curated at John Hopkins University, OMIM has data on over 12000 genes and 5000 phenotypes, and provides a powerful resource for mining genotype-phenotype relationships, for target identification, personalized medicine and pharmacogenomics. Use cases for OMIM data include early discovery projects, to search for novel mechanisms and protein targets for disease areas; and in clinical projects to look at patient stratification, or diagnostic gene variant annotations.
This includes a complete set of full text patents from USPTO, EPO and WIPO. The documents are provided with a uniform structure to allow consistent searching across all sources regardless of their origin. The indexes are organized as a complete set, individual authority or subdivided into era (last year, last 5 years, last 20 years etc).
As well as the standard ontologies, the Patents index includes its own domain specific ontologies providing concepts specific to patent classification using Cooperative Patent Classification (CPC). The I2E Patent Solution allows users to generate powerful and bespoke queries for patent search and analysis, for patent landscapes, white space analyses, freedom-to-operate searches, research methodologies, competitive intelligence and state-of-the-art reviews for confident decision making.
This includes a complete set of patent abstracts (and additional citation information) from all patent agencies. The data is provided with a uniform structure to allow consistent searching across all sources regardless of their origin. The indexes are organized as a complete set or subdivided into era (last year, last 5 years, last 20 years etc).
As well as the standard ontologies, the Patents index includes its own domain specific ontologies providing concepts specific to patent classification using Cooperative Patent Classification (CPC).
This is part of the total collection of articles in PubMed Central (PMC), which is an archive of biomedical and life sciences journal literature at the U.S. National Institutes of Health’s National Library of Medicine (NIH NLM).
PMC Open Subset is an electronic archive of full-text journal articles under the Creative Commons License, offering more liberal redistribution and re-use of the content than traditional copyrighted work. As with MEDLINE abstracts, PubMed Central provides a valuable source of biomedical research knowledge; in particular, access to the full text papers can facilitate extraction of specific methods, assays, or details of healthcare costs, patient outcomes, and other in-depth information.