1. MedDRA and Ontology Discussion of Strategy
Barry Smith and Mélanie Courtot

2. Create an ontology directly by correcting MedDRA subsumption hierarchy
Other cases such as
Increased/decreased

3. Create an ontology directly by correcting MedDRA subsumption hierarchy
Other cases such as
Increased/decreased

4. Create an Ontology via Definitions
Create formal definitions for some subset (module) of MedDRA terms using one or more of:
AERO – Adverse Event Reporting Ontology
OAE – Ontology of Adverse Events
SNOMED
Use a reasoner to create a corresponding MedDRA ontology module

5. Strategy for Definitions
Add definitions to PTs
Add relations such as location of the adverse event
Have a reasoner classify the resulting ontology
In each anatomical system group, check and add relations between PTs (e.g. abdominal pain lower is_a abdominal pain)

6. Examples from Adverse Event Reporting Ontology (AERO)
Mélanie Courtot
Simon Fraser University

7. Automate classification of adverse events
Using a MedDRA- based mapping, I successfully encoded existing clinical guidelines for adverse events classification
Anaphylaxis
MedDRA (800 terms) --> Brighton guidelines --> Brighton ontology (32 terms)
This is a strategy to create an ontology counterpart of one portion of MedDRA

13. Benefits of creating a MedDRA ontology
Interoperability with other data resources
drug surveillance
EHR data
Gene Ontology and related ontologies
Currently SMQs built and maintained manually; the proposed ontology would allow us to build inclusion and exclusion criteria to create SMQs automatically, and also to update these SMQs automatically as MedDRA itself is changes -- saving time and effort (which could be quantified)
It would provide also the ability to add multiple SMQs for the same AE, e.g. based on different guidelines
Enhanced quality assurance
Enhanced consistency checking

14. Data quality – ontology promotes assigning as early as possible in the pipeline; promote MedDRA as coding system to be used in the lab or clinic
Secondary use: promotes using MedDRA data for research in the public domain
for FDA different features are important than are important for clinical and translational science

15. Create Ontology to serve as Master MedDRA
Using MedDRA Have MedDRA Ontology as core, with different views / linearizations of this core (ICD 11 model)
for regulatory purposes
for secondary uses
for attaching term IDs
for attaching English terms and terms and synonyms in other languages
one target for maintenance with changes propagated through the whole structure