The Problem of Reusability of Biomedical Data OBO Foundry & HL7 RIM Barry Smith

2 DCRI Project Goal to facilitate research in CV and TB by increasing the re-usability of data collected in the healthcare setting.

3 Knowledge Environments for Biomedical Research (KEBR) NIH Conference, December 11-12, 2006 Knowledge environments must be characterized by:  sustainability  adaptability  interoperability  evolvability

4 sustainability biologists have huge amounts of data, which they need to manage and make accessible have worked out a sustainable way of achieving this result

5 adaptability best achieved through modularity, each portion of the knowledge environment controlled by appropriate domain experts

6 interoperability the modules should use a common (simple) logic and a common, thoroughly- tested (simple) ontology - unification with a light touch

7 evolvability = change in light of scientific advance  knowledge environments must be tied to biological and clinical research must be able to evolve incrementally must must ensure backwards compatibility with legacy annotations

8 how do we make different sorts of data combinable in ways useful to the human beings who carry out research?

9 how was this problem solved in the years before computers? how did clinical researchers from different disciplines communicate? how did they learn to communicate?

10 Ontology-based methodology for clinical and translational research

11 through the basic biomedical sciences anatomy, physiology, biochemistry, histology,...

12 what is “metadata” ?? data models (HL7 RIM, BRIDG,...  UML) vs. ontologies How should we represent data? vs. How should we represent reality?

13

14 what cellular component? what molecular function? what biological process?

15 Gene Ontology

16 checking the ontology: everything can be traced back to instances in reality serotonin is_a biogenic amine every instance of serotonin is an instance of biogenic amine

17 Heparin therapy is_a written or spoken designation of a concept mouse is_a common name for the species mus musculus virus is_a environment ontology unclassified Lulworthiales is_a environmental samples

18 Logical power of the ontology Example: Ontologies facilitate grouping of annotations brain 20 hindbrain 15 rhombomere 10 Query brain without ontology 20 Query brain with ontology 45

19 CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Organism-Level Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) Cellular Process (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) OBO Foundry coverage GRANULARITY RELATION TO TIME

20 Biorepository Ontology Chemical Entities of Biological Interest (ChEBI) Clinical Investigation Ontology (CIO) Common Anatomy Reference Ontology (CARO) Disease Ontology (DO) Foundational Model of Anatomy (FMA) Cell Ontology (CL) Gene Ontology (GO) Mosquito Anatomy Ontology (MAO) Ontology for Biomedical Investigations (OBI) Phenotypic Quality Ontology (PaTO) Plant Ontology (PO) Protein Ontology (PRO) Relation Ontology (RO) RNA Ontology (RnaO) Sequence Ontology (SO) Xenopus Anatomy Ontology (XAO) Zebrafish Anatomical Ontology (ZAO)

21 Chemical Entities of Biological Interest (ChEBI) Clinical Investigation Ontology (CIO) Common Anatomy Reference Ontology (CARO) Disease Ontology (DO) Foundational Model of Anatomy (FMA) Cell Ontology (CL) Gene Ontology (GO) Mosquito Anatomy Ontology (MAO) Ontology for Biomedical Investigations (OBI) Phenotypic Quality Ontology (PaTO) Plant Ontology (PO) Protein Ontology (PRO) Relation Ontology (RO) RNA Ontology (RnaO) Sequence Ontology (SO) Xenopus Anatomy Ontology (XAO) Zebrafish Anatomical Ontology (ZAO)

22 Biorepository Ontology Chemical Entities of Biological Interest (ChEBI) Clinical Investigation Ontology (CIO) Common Anatomy Reference Ontology (CARO) Disease Ontology (DO)  interoperation with SNOMED CT Foundational Model of Anatomy (FMA) Cell Ontology (CL) Gene Ontology (GO) Mosquito Anatomy Ontology (MAO) Ontology for Biomedical Investigations (OBI) Phenotypic Quality Ontology (PaTO)  signs and symptoms Plant Ontology (PO) Protein Ontology (PRO) Relation Ontology (RO) RNA Ontology (RnaO) Sequence Ontology (SO) Xenopus Anatomy Ontology (XAO) Zebrafish Anatomical Ontology (ZAO)

23 RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy / placeholder) Anatomical Entity (FMA, CARO) Organ Function (placeholder) Phenotypic Quality (PaTO) Biological Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) Building out from the original GO

24 BFO Top-Level Ontology Continuant Occurrent (always dependent on one or more independent continuants) Independent Continuant Dependent Continuant

25 = A representation of top-level types Continuant Occurrent Independent Continuant Dependent Continuant cell component biological process molecular function biological process

26 Top-Level Ontology Continuant Occurrent Independent Continuant Dependent Continuant QualityFunction instances (in space and time)

27 BFO as organising structure

clinical medicine rooted in the basic biological sciences via high-quality controlled vocabularies

29 INDEPENDENT CONTINUANTS organism system organ organ part tissue cell acellular anatomical structure biological molecule genome DEPENDENT CONTINUANTS physiology (functions) pathology acute stage progressive stage resolution stage next step: create a repertoire of disease ontologies built out of OBO Foundry elements

30 Ontology for Acute Respiratory Distress Syndrome

31 Draft Ontology for Multiple Sclerosis what data do we have? what data do the others have? what data do we not have?

32 HL7

33 Schadow The RIM ‘defines the grammar of a language for information in healthcare’. ‘All data is in a form in which Entities (people, places, things: NOUNS) are related in Roles (RELATORS) to other Entities, and through their participations (PREPOSITIONS) interact in Acts (VERBS).’

34 Problems of scope Act = intentional action No processes (verb items) outside Act How can the RIM deal with disease processes, drug interactions, traffic accidents, adverse events?

35 Problems of scope Entity = persons, places, organizations, material No things (noun items) outside Entity How can the RIM deal with wounds, fractures,? How can the RIM deal with diseases?

36 Mayo on ‘Act’ as “intentional action” Is a snake bite or bee sting an intentional action? Is a knife stabbing an intentional action? Is a car accident an intentional action? When a child swallows the contents of a bottle of poison is that an intentional action? of_Observations

37 Diseases in the RIM... are not Acts... are not Entities... are not Roles, Participations, Role-Links... So what are they?

38 Correct Answer Diseases fall outside the scope of the RIM. The RIM is concerned to standardize the way in which data is represented in messages, etc. It is not concerned to standardize the way in which diseases, alleles, drug interactions, etc., are represented.

39 The RIM’s answer Diseases are Acts of Observation A case of pneumonia is an Act of Observation of a case of pneumonia A diagnosis is an Act of Observation of an Act of Observation

40 HL7’s Clinical Genomics Standard Specifications an individual allele as an Act of Observation a phenotype is an Act of Observation of an Act of Observation

41 Why is Act of Observation used for biomolecules but not for pharmaceutical products? Schadow: because biomolecules ‘are in the process of being discovered.’

42 HL7 Items in reality about which we have information that is known a priori are identified as Entities Items in reality about which we are still discovering information are identified as Acts of Observation. Gunther: ‘ What seems like an arbitrary split... is in fact the practical thing to do’ – it helps us to avoid ‘frequent modifications’

43 A disease is an “Act of concern” Dan Russler. 'In HL7, we assert that Peter has a UML symbol with an object instance identifier assigned to "his disease" that includes an instance identifier assigned to his "type of disease". Once consensus builds around the subject of concern, the patient can be said to "have" a specific disease. It can be said that "over time" the UML symbol instance identifier for the "concern" becomes the UML symbol instance identifier for the "disease."'

44 What should be done? Create a clinical ontology which allows adequate treatment of all the types of entity relevant to information exchange in biomedicine, including: non-intentional processes, diseases, infections, biomolecules, etc.

45 BFO top-Level Ontology Continuant Occurrent Independent Continuant Dependent Continuant Quality Function Act Physical Event...

46 RIM Ontology Continuant Occurrent Entity(Intentional) Act Person Physical Thing Organ- ization Bio- molecule Disease Drug interaction...

47 BFO normalized RIM Continuant Occurrent Independent Continuant Dependent Continuant Condition Act Physical Event Disease Request Observation Everything made of molecules Temperature Drug interaction

48 What is new Continuant Occurrent Independent Continuant Dependent Continuant Condition Act Physical Event Disease Request Observation Everything made of molecules Temperature Drug interaction

49 Coherent interoperation with ChEBI, PATO, SNOMED, MedDRA, etc. Continuant Occurrent Independent Continuant Dependent Continuant Condition Act Physical Event Disease Request Observation Everything made of molecules Temperature Drug interaction

50 ? ? ? ? ? ?

51 Draft Ontology for Multiple Sclerosis what data do we have? what data do the others have? what data do we not have?

52 Methodology of cross-products compound terms and definitions should be built out of constituent terms drawn from ontologies. E.g. PaTO increased concentration’ FMA ‘blood’ CheBI term ‘glucose’  blood glucose phenotypes. Foundry provides rigor for post-coordination Contributions to solving the silo problem

53 Open questions relations to generating forms controlled vocabulary for clinical care common data elements clinical trials treatments signs and symptoms (clinical and pre-clinical manifestations)

54 Open questions role of stakeholders professional society support champions who will test role of rare disease researcher communities mandates