Pharmacy ontology

Conceptualize a domain of discourse, an area of expertise
– Concepts (drug, patient, gene, clinical trial)
– Properties, or attributes (dosage, age, location)
– Relationships (contra-indications, body parts)

Adhere to a modeling formalism, such as:
– Frame-based representation
– Description logics

1. (Standard) Ontologies in Biomedicine
• Pervasive
– From controlled terminologies to full-blown ontologies
– Across the entire scope from biology to medicine
• Many examplars
– Unified Medical Language System (UMLS)
– Medical terminology and concept description
(GALEN/OpenGALEN)
– Foundational Model of Anatomy
– Guideline models (GLIF, SAGE)
– Gene Ontology (GO)
– Pharmacogenomics ontology (PharmGKB)
– …
7
2. Integrating Data and Semantics
Syntactic differences
versus
Differences are usually explicit,
but may be hard to reconcile.
<sales=“Robitussin”>25</sales>
<sales=“Pepto-Bismol”>100</sales>
Robit. 25
PeptoB. 100
Item Sold
Semantic differences
“Sales” means cases sold per week.
“Robitussin” means all Robitussinbranded
medication.
versus
“Sales” is average number of
bottles sold per hour.
“Robitussin” only refers to
Robitussin DM.
Differences can be subtle and
implicit.
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Integrating Data for Epidemic Detection
• The BioSTORM Project:
– Biological Spatio-TempORal Module
– Within DARPA-funded BioALIRT program for
epidemics surveillance based on non-traditional,
pre-diagnostic data
• Purpose:
– To federate diverse non-traditional data sources
(e.g., ER visits, 911 calls, absenteeism reports,
pharmacy sales)
– To enable space/time analysis of data by
various computational methods, for early
epidemics detection

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