I was disappointed to not find the UMLS concepts and related terms mapping for participants in the EU-ADR project.
I did find these workflows at the EU-ADR Web Platform:
MEDLINE ADR
In the filtering process of well known signals, the aim of the “MEDLINE ADR” workflow is to automate the search of publications related to ADRs corresponding to a given drug/adverse event association. To do so, we defined an approach based on the MeSH thesaurus, using the subheadings «chemically induced» and «adverse effects» with the “Pharmacological Action” knowledge. Using a threshold of ≥3 extracted publications, the automated search method, presented a sensitivity of 93% and a specificity of 97% on the true positive and true negative sets (WP 2.2). We then determined a threshold number of extracted publications ≥ 3 to confirm the knowledge of this association in the literature. This approach offers the opportunity to automatically determine if an ADR (association of a drug and an adverse event) has already been described in MEDLINE. However, the causality relationship between the drug and an event may be judged only by an expert reading the full text article and determining if the methodology of this article was correct and if the association is statically significant.
MEDLINE Co-occurrence
The “MEDLINE Co-occurrence” workflow performs a comprehensive data processing operation, searching the given Drug-Event combination in the PubMed database. Final workflow results include a final score, measuring found drugs relevance regarding the initial Drug-Event pair, as well as pointers to web pages for the discovered drugs.
DailyMed
The “DailyMed” workflow performs a comprehensive data processing operation, searching the given Drug-Event combination in the DailyMed database. Final workflow results include a final score, measuring found drugs relevance regarding the initial Drug-Event pair, as well as pointers to web pages for the discovered drugs.
DrugBank
The “DrugBank” workflow performs a comprehensive data processing operation, searching the given Drug-Event combination in the DrugBank database. Final workflow results include a final score, measuring found drugs relevance regarding the initial Drug-Event pair, as well as pointers to web pages for the discovered drugs.
Substantiation
The “Substantiation” workflow tries to establish a connection between the clinical event and the drug through a gene or protein, by identifying the proteins that are targets of the drug and are also associated with the event. In addition it also considers information about drug metabolites in this process. In such cases it can be argued that the binding of the drug to the protein would lead to the observed event phenotype. Associations between the event and proteins are found by querying our integrated gene-disease association database (Bauer-Mehren, et al., 2010). As this database provides annotations of the gene-disease associations to the articles reporting the association and in case of text-mining derived associations even the exact sentence, the article or sentence can be studied in more detail in order to inspect the supporting evidence for each gene-disease association. It has to be mentioned that our gene-disease association database also contains information about genetic variants or SNPs and their association to diseases or adverse drug events. The methodology for providing information about the binding of a drug (or metabolite) to protein targets is reported in deliverable 4.2, and includes extraction from different databases (annotated chemical libraries) and application of prediction methods based on chemical similarity.
A glimpse of what is state of the art today and a basis for building better tools for tomorrow.