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Modeling the pharmacogenomics of depression

Explore the application of pharmacogenomics in studying individual variability in drug response for depression treatment. Develop ontology for precise knowledge representation and facilitate personalized medicine by identifying effective drug treatments based on genetic profiles and therapeutic outcomes.

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Modeling the pharmacogenomics of depression

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  1. Modeling the pharmacogenomics of depression Michel Dumontier, Muhammad Faizan, Joseph Obeng, Natalia Villanueva-Rosales Carleton University HCLS2008 @ WWW2008

  2. “If it were not for the great variability among individuals, medicine might as well be a science and not an art” Sir William Osler, 1892 • Pharmacogenomics: The application of genomics to the study of human variability in drug response HCLS2008 @ WWW2008

  3. The ability to offer The Right Drug To The Right Patient For The Right Disease At The Right Time With The Right Dosage Personalized Medicine HCLS2008 @ WWW2008

  4. PHARMGKB +Role of genes, gene variants , drugs +pharmacokinetics +pharmacodynamics + clinical outcomes. + Links to publications - Natural language descriptions - Variant details in publications HCLS2008 @ WWW2008

  5. SOPHARM Suggested Ontology for Pharmacogenomics + OWL ontology +/- Ontology reuse High complexity 14 ontologies: ChEBI, PATO, Unit Ontology, Disease Ontology, Mammalian Phenotype Ontology, MEO, Sequence Ontology, SNP-Ontology, Amino-Acid Ontology, Family Bond Ontology, Pharmacogenetics Ontology, Relationship Ontology and CTO/OBI (Ontology of Clinical Investigation) SOPHARM: 70 classes, 56 properties OTHER: 84786 classes, 189 properties - Veryexpensive to reason with HCLS2008 @ WWW2008

  6. Pharmacogenomics Ontology: simpler knowledge representation Pharmacogenomics of Depression: explicit knowledge representation HCLS2008 @ WWW2008

  7. METHODOLOGY Define the scope of the ontology from use cases. Derive essential concepts. Construct concept taxonomy. Map to an upper level ontology Assign relations between concepts and attributes. Add complex class descriptions. HCLS2008 @ WWW2008

  8. 1 SCOPE researcher, doctor or patient personalized medicine What is the most effective drug treatment for an individual with a particular genetic profile that suffers from a particular disease? Which gene variants affect therapeutic outcomes? What is the clinical response for treating individuals with a particular drug and having a particular allele? HCLS2008 @ WWW2008

  9. 2a SEVEN ESSENTIAL CONCEPTS (out of 20) HCLS2008 @ WWW2008

  10. 2b N-ARY MODELING HCLS2008 @ WWW2008

  11. 3 ONTOLOGY English name (rdfs:label) Clear and precise definition (rdfs:comment). Concepts that subsumed each other were hierarchically organized and a child term is differentiable from its parent term. In line with general normalization techniques, all ontological terms are asserted to have but a single parent. Refactored and Expanded SOPHARM’s measures - differences in values different from values HCLS2008 @ WWW2008

  12. 5 RELATIONS Basic Relation Ontology (BRO) 50+ domain independent relations • e.g. hasPart Anticipated compatibility with RO huge reuse opportunities • Specialized Relations • enormous number of possible domain dependent relations • isVariantOf • set usage with domain / range restrictions. HCLS2008 @ WWW2008

  13. Ontology Population Queried PharmGKB web services, mapped to ontology Contained generic relationship to other named entities Instance representation Reuse individuals • Drug(nortryptiline) reduces KB size HCLS2008 @ WWW2008

  14. Pharmacogenomics of Depression KNOWLEDGE BASE contains statements from 11/40 relevant publications involving 45 genes / gene variants, 57 drugs annotated with 19 classes of antidepressants, 45 drug treatments, 47 drug-gene interactions, 29 clinical outcomes, 10 drug-induced side-effects, and 8 gene-disease interactions. HCLS2008 @ WWW2008

  15. Querying the PGDKB Recommended nortriptyline dose for postural hypotension for CYP2D6 heterozygous individuals Dose that isParticipantIn some (DoseRecommendation that hasParticipant value CYP2D6_4 and hasParticipant value CYP2D6_6 and hasParticipant value PA450657) Nortriptyline treatments for postural hypotension having drug interactions with the ABCB1 gene DrugTreatment that hasPart some (DrugInducedSideEffect that hasParticipant value PosturalHypotension) and hasParticipant value PA450657 and hasParticipant value ABCB1_3435_C Protégé 4, FaCT++, DL Query Tab HCLS2008 @ WWW2008

  16. Conclusions Simplified pharmacogenomics / pharmacogenetics KR Reasoning-capable knowledge base for pharmacogenomics of depression Further extend for pharmacogenomics of other diseases Work with PharmGKB & SOPHARM HCLS2008 @ WWW2008

  17. michel_dumontier@carleton.ca http://dumontierlab.com Michel Dumontier HCLS2008 @ WWW2008

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