Pharmacological class data representation in the Web Ontology Language (OWL)

Qian Zhu, Cui Tao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Dozens of drug terminologies and resources capture drug and/or drug class information; they range greatly in their coverage and their adequacy of representation. However, there are no transformative ways to link these resources together in a standard and formal fashion, which hinders data integration and data representation for supporting drug-related clinical and translational studies. In this study, we generated a standardized Pharmacological Class Profile Ontology, named PCPO, which integrates multiple drug resources in the Web Ontology Language (OWL). More specifically, we mapped two well-known drug class resources, Anatomical Therapeutic Chemical classification system (ATC) and National Drug File Reference Terminology (NDF-RT), as the pharmacological class backbone. Furthermore we extended the PCPO with individual clinical drug information extracted from RxNorm and Structured Product Labeling. In parallel, we calculated and compared chemical structure similarity for each drug pair from ATC and NDF-RT, and re-grouped drugs with a similar structure into a same drug class. PCPO will not only present big drug data into well-organized formal form, OWL with possible inference capability, but also potentially support computational drug repurposing application development.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages77-84
Number of pages8
ISBN (Print)9781479956654
DOIs
StatePublished - Jan 7 2015
Externally publishedYes
Event2nd IEEE International Conference on Big Data, IEEE Big Data 2014 - Washington, United States
Duration: Oct 27 2014Oct 30 2014

Other

Other2nd IEEE International Conference on Big Data, IEEE Big Data 2014
CountryUnited States
CityWashington
Period10/27/1410/30/14

Fingerprint

Terminology
Ontology
Data integration
Labeling

Keywords

  • ATC
  • NDF-RT
  • Ontology
  • Pharmacological class
  • RxNorm
  • SPL
  • The Web Ontology Language (OWL)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Zhu, Q., & Tao, C. (2015). Pharmacological class data representation in the Web Ontology Language (OWL). In Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014 (pp. 77-84). [7004397] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2014.7004397

Pharmacological class data representation in the Web Ontology Language (OWL). / Zhu, Qian; Tao, Cui.

Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014. Institute of Electrical and Electronics Engineers Inc., 2015. p. 77-84 7004397.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhu, Q & Tao, C 2015, Pharmacological class data representation in the Web Ontology Language (OWL). in Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014., 7004397, Institute of Electrical and Electronics Engineers Inc., pp. 77-84, 2nd IEEE International Conference on Big Data, IEEE Big Data 2014, Washington, United States, 10/27/14. https://doi.org/10.1109/BigData.2014.7004397
Zhu Q, Tao C. Pharmacological class data representation in the Web Ontology Language (OWL). In Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014. Institute of Electrical and Electronics Engineers Inc. 2015. p. 77-84. 7004397 https://doi.org/10.1109/BigData.2014.7004397
Zhu, Qian ; Tao, Cui. / Pharmacological class data representation in the Web Ontology Language (OWL). Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 77-84
@inproceedings{a1ef0eb7f40d42ef8fa1259a515becaa,
title = "Pharmacological class data representation in the Web Ontology Language (OWL)",
abstract = "Dozens of drug terminologies and resources capture drug and/or drug class information; they range greatly in their coverage and their adequacy of representation. However, there are no transformative ways to link these resources together in a standard and formal fashion, which hinders data integration and data representation for supporting drug-related clinical and translational studies. In this study, we generated a standardized Pharmacological Class Profile Ontology, named PCPO, which integrates multiple drug resources in the Web Ontology Language (OWL). More specifically, we mapped two well-known drug class resources, Anatomical Therapeutic Chemical classification system (ATC) and National Drug File Reference Terminology (NDF-RT), as the pharmacological class backbone. Furthermore we extended the PCPO with individual clinical drug information extracted from RxNorm and Structured Product Labeling. In parallel, we calculated and compared chemical structure similarity for each drug pair from ATC and NDF-RT, and re-grouped drugs with a similar structure into a same drug class. PCPO will not only present big drug data into well-organized formal form, OWL with possible inference capability, but also potentially support computational drug repurposing application development.",
keywords = "ATC, NDF-RT, Ontology, Pharmacological class, RxNorm, SPL, The Web Ontology Language (OWL)",
author = "Qian Zhu and Cui Tao",
year = "2015",
month = "1",
day = "7",
doi = "10.1109/BigData.2014.7004397",
language = "English (US)",
isbn = "9781479956654",
pages = "77--84",
booktitle = "Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Pharmacological class data representation in the Web Ontology Language (OWL)

AU - Zhu, Qian

AU - Tao, Cui

PY - 2015/1/7

Y1 - 2015/1/7

N2 - Dozens of drug terminologies and resources capture drug and/or drug class information; they range greatly in their coverage and their adequacy of representation. However, there are no transformative ways to link these resources together in a standard and formal fashion, which hinders data integration and data representation for supporting drug-related clinical and translational studies. In this study, we generated a standardized Pharmacological Class Profile Ontology, named PCPO, which integrates multiple drug resources in the Web Ontology Language (OWL). More specifically, we mapped two well-known drug class resources, Anatomical Therapeutic Chemical classification system (ATC) and National Drug File Reference Terminology (NDF-RT), as the pharmacological class backbone. Furthermore we extended the PCPO with individual clinical drug information extracted from RxNorm and Structured Product Labeling. In parallel, we calculated and compared chemical structure similarity for each drug pair from ATC and NDF-RT, and re-grouped drugs with a similar structure into a same drug class. PCPO will not only present big drug data into well-organized formal form, OWL with possible inference capability, but also potentially support computational drug repurposing application development.

AB - Dozens of drug terminologies and resources capture drug and/or drug class information; they range greatly in their coverage and their adequacy of representation. However, there are no transformative ways to link these resources together in a standard and formal fashion, which hinders data integration and data representation for supporting drug-related clinical and translational studies. In this study, we generated a standardized Pharmacological Class Profile Ontology, named PCPO, which integrates multiple drug resources in the Web Ontology Language (OWL). More specifically, we mapped two well-known drug class resources, Anatomical Therapeutic Chemical classification system (ATC) and National Drug File Reference Terminology (NDF-RT), as the pharmacological class backbone. Furthermore we extended the PCPO with individual clinical drug information extracted from RxNorm and Structured Product Labeling. In parallel, we calculated and compared chemical structure similarity for each drug pair from ATC and NDF-RT, and re-grouped drugs with a similar structure into a same drug class. PCPO will not only present big drug data into well-organized formal form, OWL with possible inference capability, but also potentially support computational drug repurposing application development.

KW - ATC

KW - NDF-RT

KW - Ontology

KW - Pharmacological class

KW - RxNorm

KW - SPL

KW - The Web Ontology Language (OWL)

UR - http://www.scopus.com/inward/record.url?scp=84921762811&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84921762811&partnerID=8YFLogxK

U2 - 10.1109/BigData.2014.7004397

DO - 10.1109/BigData.2014.7004397

M3 - Conference contribution

AN - SCOPUS:84921762811

SN - 9781479956654

SP - 77

EP - 84

BT - Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -