Face-to-Face Meeting Semantic Web for Healthcare and Life Sciences Interest Group

1. Face-to-Face Meeting Semantic Web for Healthcare and Life Sciences Interest Group http://www.w3.org/2001/sw/hcls/ W3C HCLS chairs, Eric Neumann - Clinical Semantics Group Tonya Hongsermeier -Partners Healthcare

2. F2F Agenda Thursday November 8, 2007 • 1.30pm - 2.00pm - F2F Kickoff, Welcome and Introductions (EricN & Tonya) • 2.00pm - 2.30pm - Clinical Observations Interoperability: How can Semantic Technologies Help? (Vipul) • 2.30pm - 3.00pm - Clincal Observations Interoperability (COI) Use Case (Rachel) • 3.00pm - 3.30pm - Tea/Coffee • 3.30pm - 4.00pm - Detailed Clinical Models and the COI Use Case (Tom) • 4.00pm - 4.15pm - Demo: Semantic DB System at Cleveland Clinic (Chimezie) • 4.15pm - 4.30pm - Demo: SHER System by IBM and Columbia University (Chintan) • 4.30pm - 5.30pm - Round Table and Feedback on Next Steps for COI (Moderator: Vipul) • 5.30pm - 6.00pm - Wrap Up (EricN & Tonya) • 6.30pm - Dinner with COI participants to work on functional requirements spreadsheet, etc.

3. F2F Agenda Friday November 9, 2007 • 8:30am - 9:00am - Welcome and Introductions (EricN & Tonya) • 9.00am - 10.30am - Group Reviews: BioRDF, ACPP, DSE, & BIONT/Clinical Trials + EMR • 10.30am - 11.00am - Break • 11.00am - 12.00pm - HCLS questionnaire results and charter discussion (EricP et al) • 12.00pm - 1.00pm - Lunch • 1.00pm - 2.30pm - BioRDF: Understanding and enhancing the knowledgebase (Alan, et al.) • 2.30pm - 3.00pm - Break • 3.00pm - 4.00pm - BioRDF: URI note discussion (Jonathan) • 4.00pm - 5.00pm - Next Steps / Wrap up

4. What is HCLS? “The Semantic Web Health Care and Life Sciences Interest Group is chartered to develop and support the use of Semantic Web technologies and practices to improve collaboration, research and development, and innovation adoption in the health care and life science domains. Success in these domains will ultimately depend on a foundation of semantically rich systems, processes and information interoperability.” The scope of HCLSIG includes: • Core vocabularies and ontologies to support cross-community data integration and collaborative efforts • Guidelines and Best Practices for Resource Identification to support integrity and version control • Better integration of Scientific Publication with people, data, software, publications, and clinical trials

5. HCLS Themes Principle activities have centered around: • Building a broad and strong community • Exploring and documenting Use Cases • Converting resources to RDF-OWL • Learning to work with semantic web query/inference technology such as SPARQL, OWL, and rule engines.

6. Organization • Chairs: Eric Neumann, Tonya Hongsermeier • Group divided in to task forces (coordinator) • BioRDF. Established initially to convert biomedical data to RDF (Susie Stephens) • BIONT. Established initially to be resource for ontology needs for other groups (Vipul Kashyap) • DSE (Drug Safety and Efficacy). Established initially to work on SW technology to support monitoring drug safety, pharmacovigilance (Eric Neumann) • ACPP (Adaptable Clinical Protocols and Pathways) Established initially to work on method of representing and computing applicability of protocols to dynamically changing patient status (Helen Chen) • COI (Clinical Observations Interoperability). Established recently with two goals 1) Establish new collaboration with health care industry players 2) Work on issues at the intersection of electronic medical records and health care organization needs. (Vipul Kashyap)

7. Membership • 64 participants from 38 organizations • 3 Invited Experts • Many more non-member participants on-line

8. Meetings to-date • Formal F2F, January 2006, Cambridge • Formal F2F, October 2006, Amsterdam • Workshop, ISWC November 2006, Banff • Informal F2F (Demo) 3 x March/April, 2007, Cambridge • Workshop, WWW 2007, May 2007, Banff • Informal F2F (URI), July 2007, Cambridge • Formal F2F, November 2007, Cambridge

9. Demonstrations and Examples • HCLS NeuroScience Demo - WWW2007 Banff • http://esw.w3.org/topic/HCLS/Banff2007Demo • Clinical Trials Data Management and Viewing • http://eneumann.org/exhibit/clinicaldemo/ • Taverna, AIDA • http://taverna.sourceforge.net, http://myexperiment.org/ • Mining Disease Relations from Semantically Integrated Genome - Phenome Maps • http://www2007.org/workshops/paper_146.pdf

10. Presentations • WWW2007 Demo • ISMB 2007 Demo • ISMB BioOntology SIG Poster 2007 • Society for Neuroscience Poster Nov 2007 • Selection of presentation venues of members showing HCLS work • Bridging Pharma and IT • Drug Discovery Technology of Innovative Therapeutics • 1st European Semantic Web Conference • Bio-IT World • Norwegian Semantic Web Day • InfoTech Pharma • Modern Drug Discovery and Development Summit • Massachusetts Biotechnology Panel • eScience Institute; RDF, Ontologies and Meta-Data Workshop • Virginia Biotechnology Summit • Systems Biology • Semantic Web Gathering • Allen Institute for Brain Sciences • Informatics and Interactomes in Huntington’s Disease • Ontology for Biomedical Informatics Workshop • Clinical Trial Ontology Workshop • Jackson Laboratories • Pubmed Plus • NIH Blueprint NIF Workshop

11. HCLS Ecosystem HCPChoices Insurers Grants HMO,PPO Biomed Research Publications and Public Databases BioKB Large Studies Gov/Funding Risks & Benefits Disease Areas Drug R&D EHR Mol Path Res Clin Res Chem Manuf Drug Programs Clin POC Surveillance BiomarkerTox HCP Public Preclin Marketing CDC VA System R&D Gov/Regulatory CROs Clin Safety JANUS SafetyCommons

12. Distributed Nature of R&D Information Registry Tox Silos of Data… Biomarkers Targets Libraries Assays HCS Diseases Genotypes MolModels

13. Data Integration Forcing data to fit a specific application App 2 App 1 ?

14. ? App ? App ? Data Aggregation Think: Smart Mash-up Data aggregated for any application ins semantically consistent way.

15. The Current Web • What the computer sees: “Dumb” links • No semantics - <a href> treated just like <bold> • Minimal machine-processable information Resources Resources Resources Resources Resources Resources Resources Resources

16. The Semantic Web • RDF- Resource Description Framework • Machine-processable semantic information • Semantic context published – making the data more informative to both humans and machines Clinical Study hasSubject using Subject Design hasFindings hasAE treatment Finding Intervention Adverse Event hasExpression derived GeneExpression BiomarkerSample

17. The Layer Cake

18. Facts as triples has_associated_disease PARK1 Parkinson disease subject predicate object

19. Parkinson disease MAPT Pick disease PARK1 Parkinson disease Parkinson disease TBP Spinocerebellar ataxia MAPT Pick disease PARK1 Parkinson disease TBP Spinocerebellar ataxia From triples to a graph MAPT Parkinson disease MAPT Pick disease PARK1 Parkinson disease TBP Parkinson disease TBP Spinocerebellar ataxia has_associated_disease

20. Neurodegenerative diseases isa Alzheimer disease Parkinson disease APP Alzheimer disease has_associated_disease PARK1 Parkinson disease Connecting graphs • Integrate graphs from multiple resources • Query across resources

21. Recombinant Data Graphs can be filtered and pivoted, without losing meaning

22. Where does Semantic Web Fit In? Connecting Legacy Data to SW:D2R, MagLev

23. Semantic Web Applied to Disease Mechanism and Pharmacology

24. Drug Safety and Efficacy • Group focuses on: • Draft an approach for clinical trial data that is in line with the Clinical Data Interchange Standards(CDISC) Study Data Tabulation Model (SDTM) • Can SW standards help with EDC? • Work on aggregating patient data with pharmacogenomic information. • Use Case around Pharmacovigilance • Emphasis on display/visualization of clinical trial data, rather than query • They have a demo that uses the Simile project’s Exhibit tools to display information merging three points of view • Demographics • Treatments • Adverse Events • SNP

25. Clinical Observations Interoperability • Recently formed http://esw.w3.org/topic/HCLS/OntologyTaskForce/BIONTDSEDCM • Focusing on problem of identifying clinical trial candidates based on constraints of participation and information in medical records. • Clinical trial recruitment is an everybody-wins situation • Patients want new cures and development of them is dependent on trials • Pharma want new drugs to bring huge profits • Running clinical trials is profitable for CROs • Doctors and hospitals get money for identifying, treating, and recording information about patients. • Technical problems (evaluation of constraints) are very similar to those identified and somewhat addressed in ACPP. Driver of rule and OWL technology. • Has brought in new industry and academic participants. • DSE, ACPP, and BioONT participants are joining this effort.

26. BioRDF Demo: Neurocommons Triple Store • Challenge: Go beyond toy size examples of Semantic Web • Strategy: 1) Work on translating a dozen existing databases using OBO methodology and OWL, focused on neuroscience research questions • Pubmed/Mesh mappings • OBO ontologies, including Gene functions, molecular processes, cellular components • Neuroscience ontologies: Senselab, BAMS, Allen Brain Atlas • Strategy: 2) Develop capability to run interesting SPARQL queries at scale • 300 Million triples • Open source, reproducible • Queries that could only be done previously with a lot of effort • Demonstrate “Practice” a useful prelude to developing “Best Practice” • Enthusiastic response from community. We often hear • “ This is the first time I’ve seen semantic web technology do anything useful” • WWW2007: “Thank you from the semantic web” • Some problems solved, many remain, ongoing work.

27. Adaptable Clinical Protocols and Pathways • This group was active mostly in the first year • Worked on Guideline Reference Ontology • Prototyped three instances of guidelines based on the ontology • Worked on reasoning with inclusion/exclusion criteria • Developed clear use cases that need temporal concepts reasoning • Two rule engines used. Helen Chen: Euler, Chimezie Ogbuji: Fuxi (his own work!) • This work is great arena for exploring the difference between using OWL versus rules • Although research is finished, need more manpower to write up results • AGFA benefited significantly from the work and it has influenced their internal models. • SW is a strong focus in AGFA health care for evidence based patient care, and they expect to invest in it for years to come. • Helen, Chimezie are now bringing their experiences to the new Clinical Observations Interoperability group.

28. URI recommendations project • Jonathan Rees leading work in BioRDF on upcoming note • Problem is stable identifiers for knowledge resources of import, and for entities in the world • Proteins, Organs, Symptoms etc. • Motivated by complaints about inadequate instruction • From providers not knowing good practices for minting URIs • From users not knowing how to name or make statements about resources that can be effectively integrated • Community finds current AWWW and TAG documentation and recommendations inadequate • Problem is not easily separable from issues of providing good practices for making use of the URIs, such as having mechanisms for figuring out what they mean

29. New charter process • Goal is to design one or two charters for working group and/or interest group. • Initial step was drafting of questionnaire circulated to wide swath of life sciences and health care community. We listed possible activities and asked which would be of interest for participation. Currently almost 50 responses • http://www.w3.org/2007/06/HCLSForm • Next step: analyze and draft a charter that is responsive to the feedback gained from the questionnaire. Target is for new charter to circulate early November.

30. Looking Forward • Work with TAG over architectural needs for Semantic Web for science. Important to get time with them at Tech Plenary meeting in November. • Find and recruit more members like AGFA, who feel they got value from group participation. Current membership has no shortage of other organizations with some tie to health care/life sciences, either as vendors (e.g. IBM) or primary, such as pharma (Merck, Pfizer) • Targeting pharma, health care, vendors, not currently SW-ready standards groups (e.g. CDISC), FDA, NIH sponsored projects, and academic research leaders. • Further recruitment should be based on listening to needs, addressing them with focused projects within the next HCLS. Focus on increasing credibility. • Acceptance of SW technology’s role in pharma/ health care is growing, hopefully to soon match enthusiasm from life sciences community. They are looking for guidance, and we need to provide it.

31. Upcoming Event: C-SHALS • Conference on Semantics in Health and Life Sciences • March 5-7 2008, Cambridge, MA • Industry Presentations on the State of the Art for intelligent semantic applications in Drug R&D • Sponsors: Pfizer, Merck, …