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Reminder: Clinical Pharmacogenomics Telecon (was Re: PK Ontology)

From: Matthias Samwald <matthias.samwald@meduniwien.ac.at>
Date: Tue, 5 Feb 2013 21:14:23 +0100
Message-ID: <4C4BBA1C61F24CF18CF4A0EB482D9DFF@zetsu>
To: "Richard Boyce" <rdb20@pitt.edu>, <public-semweb-lifesci@w3.org>
There is a Clinical Pharmacogenomics telecon scheduled for tomorrow, Wednesday, 10:15 Eastern Time (remember that we decided to have the telecon a bit earlier). I suggest that we use the teleconference to discuss this!
If you have other agenda items to suggest, please add them to the wiki page.

Meeting:      HCLS Pharmacogenomics
Date:         February 06, 2013
Time:         10:15 Eastern Time (16:15 Middle European Time)
Frequency:    1st and 3rd Wednesday of the month
Convener:     Michel Dumontier, Matthias Samwald
Dial-In #:    +1.617.761.6200 (Cambridge, MA)
VoIP address: sip:zakim@voip.w3.org
Participant   Access Code: 4257 ("HCLS")
IRC Channel:  irc.w3.org port 6665 channel #HCLS
Suggested Agenda

  a.. PK Ontology 
  b.. Discussing a potential HCLS IG / task force meetup around CSHALS 2013 in Boston this year 
  c.. (add other agenda items to the wiki page) 

From: Richard Boyce 
Sent: Tuesday, February 05, 2013 8:34 PM
To: public-semweb-lifesci@w3.org 
Subject: Re: PK Ontology

This is relevant, thanks for finding Bob. Lang Li's group has been doing some interesting work. This ontology is a start in the right direction but has some issues (see below). I  would certainly be interested in discussing this and related work on a call. As you know, I would like to lead an effort to build a DDI ontology for the semantic web that meets pharmacist use cases. 

- The ontology uses almost no formal definitions except for those imported. 

- It is inconsistent according to Hermit 1.3.6 and Fact++ (Protege 4.2)

- a quick inspection finds evidence that formal relationships are not being used e.g., why are CYP probe inhibitors and inducers sub-classes of specific CYP families? As it is, Omeprazole is_a CYP1A2-inducer-probe is_a CYP1A2 is_a Metabolism-enzyme!? Seems this should be a relationship between a set of a drug/chemicals as the domain and a CYP family as the range.

- The enzymes themselves are not mapped to anything!

- Its good to see muon's and positrons in there just in case... ;)

- variants come from the Sequence ontology

- the paper refers to a 2006 guidance to industry on drug-drug interaction studies for probe inhibitors, inducers, and substrates (see page 7 URL). This was updated in 2012 (http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm292362.pdf) and its not clear if the ontology has been updated with it (I know that I need to update the Drug Interaction Knowledge Base).

- There are at least two other DDI corpuses out there besides Li's and the SemEval 2011. SemEval 2013 has a new corpus with MedLine and DrugBank annotations that will be publicly released in a couple of months when this years' the SemEval DDI challenge is completed (http://www.cs.york.ac.uk/semeval-2013/task9/). Also, we have made public a corpus of pharmacokinetic PDDIs manually annotated from drug product labeling: <http://dbmi-icode-01.dbmi.pitt.edu/dikb-evidence/package-insert-DDI-NLP-corpus.html>. 


On 02/05/2013 12:04 PM, Freimuth, Robert, Ph.D. wrote:

  URLs to save you time...

  The article abstract and provisional pdf are available at:

  The ontology is at:

  The PK corpuses that were used are at:


    From: public-semweb-lifesci-request@listhub.w3.org [mailto:public-semweb-lifesci-request@listhub.w3.org] On Behalf Of Freimuth, Robert, Ph.D.
    Sent: Tuesday, February 05, 2013 10:20 AM
    To: public-semweb-lifesci@w3.org
    Subject: PK Ontology

    Hi All,

    I haven't read this yet, but thought the abstract sounded interesting.  Perhaps it is a topic for a future meeting?


    BMC Bioinformatics. 2013 Feb 1;14(1):35. [Epub ahead of print]

    An integrated pharmacokinetics ontology and corpus for text mining.

    Wu HY, Karnik S, Subhadarshini A, Wang Z, Philips S, Han X, Chiang C, Liu L, Boustani M, Rocha LM, Quinney SK, Flockhart D, Li L.


    ABSTRACT: BACKGROUND: Drug pharmacokinetics parameters, drug interaction parameters, and pharmacogenetics data have been unevenly collected in different databases and published extensively in the literature. Without appropriate pharmacokinetics ontology and a well annotated pharmacokinetics corpus, it will be difficult to develop text mining tools for pharmacokinetics data collection from the literature and pharmacokinetics data integration from multiple databases.Description: A comprehensive pharmacokinetics ontology was constructed. It can annotate all aspects of in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. It covers all drug metabolism and transportation enzymes. Using our pharmacokinetics ontology, a PK-corpus was constructed to present four classes of pharmacokinetics abstracts: in vivo pharmacokinetics studies, in vivo pharmacogenetic studies, in vivo drug interaction studies, and in vitro drug interaction studies. A novel hierarchical three level annotation scheme was proposed and implemented to tag key terms, drug interaction sentences, and drug interaction pairs. The utility of the pharmacokinetics ontology was demonstrated by annotating three pharmacokinetics studies; and the utility of the PK-corpus was demonstrated by a drug interaction extraction text mining analysis. CONCLUSIONS: The pharmacokinetics ontology annotates both in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. The PK-corpus is a highly valuable resource for the text mining of pharmacokinetics parameters and drug interactions.

Richard D Boyce, PhD
Assistant Professor of Biomedical Informatics
Faculty, Geriatric Pharmaceutical Outcomes and Gero-Informatics Research and Training Program
Scholar, Comparative Effectiveness Research Program
University of Pittsburgh
Office: 412-648-9219
Twitter: @bhaapgh
Received on Tuesday, 5 February 2013 20:14:56 UTC

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