Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Nov 30, 2021)
Date Submitted: Feb 18, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Leveraging a Pharmacogenomics Knowledgebase to Formulate a Drug Response Phenotype Terminology for Genomic Medicine
ABSTRACT
Background:
Despite the increasing evidence of utility of genomic medicine in clinical practice, systematically integrating genomic medicine information and knowledge into clinical systems with a high-level of consistency, scalability, and computability remains challenging. A comprehensive terminology is required for relevant concepts and the associated knowledge model for representing relationships.
Objective:
Our study aims to propose a drug response phenotype terminology to represent relationships between genetic variants and drugs in existing knowledge models.
Methods:
In this study, we leveraged PharmGKB, a comprehensive pharmacogenomics (PGx) knowledgebase, to formulate a terminology for drug response phenotypes that can represent relationships between genetic mutations and treatments. We evaluated coverage of the terminology through manual review of a randomly selected subset of 200 sentences extracted from genetic reports that contained concepts for “Genes and Gene Products” and “Treatments”.
Results:
Results showed that our proposed drug response phenotype terminology could cover 96% of the drug response phenotypes in genetic reports. Among 18,653 sentences that contained both “Genes and Gene Products” and “Treatments”, 3,011 sentences were able to be mapped to a drug response phenotype in our proposed terminology, among which the most discussed drug response phenotypes were response (994), sensitivity (829), and survival (332). In addition, we were able to re-analyze genetic report context incorporating the proposed terminology and enrich our previously proposed PGx knowledge model to reveal relationships between genetic mutations and treatments.
Conclusions:
In conclusion, we proposed a drug response phenotype terminology that enhanced structured knowledge representation of genomic medicine.
Citation
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