Face-to-Face Meeting

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
• 830am - 900am - 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 Huntingtons
  Disease

11
HCLS Ecosystem
HCPChoices
Insurers
Grants
HMO,PPO
Biomed Research
Publications and Public Databases
BioKB
Gov/Funding
Large Studies
Risks Benefits
Disease Areas
Drug RD
EHR
Mol Path Res
Clin Res
Chem Manuf
Drug Programs
Clin POC
Surveillance
BiomarkerTox
HCP
Public
Preclin
Marketing
Gov/Regulatory
VA System RD
CDC
CROs
Clin Safety
JANUS
SafetyCommons
12
Distributed Nature of RD Information
Registry

• Silos of Data

Tox
Biomarkers
Targets
Libraries
Assays
HCS
Diseases
Genotypes
MolModels
13
Data Integration

• Forcing data to fit a specific application

App 2
App 1
?
14
Data Integration
15
Data Aggregation

• Think Smart Mash-up
• Data aggregated for any application ins
  semantically consistent way.

16
Semantic Web Basics
17
The Current Web
Resources

• What the computer sees Dumb links
• No semantics - lta hrefgt treated just like ltboldgt
• Minimal machine-processable information

Resources
Resources
Resources
Resources
Resources
Resources
Resources
18
The Semantic Web
Clinical Study

• RDF- Resource Description Framework
• Machine-processable semantic information
• Semantic context published making the data more
  informative to both humans and machines

hasSubject
using
Subject
Design
hasFindings
hasAE
treatment
Finding
Adverse Event
Intervention
derived
hasExpression
BiomarkerSample
GeneExpression
19
The Layer Cake
20
Facts as triples
has_associated_disease
PARK1
Parkinson disease
subject
predicate
object
21
From triples to a graph
MAPT
Parkinson disease
MAPT
Pick disease
PARK1
Parkinson disease
TBP
Parkinson disease
TBP
Spinocerebellar ataxia
has_associated_disease
22
Connecting graphs

• Integrate graphs from multiple resources
• Query across resources

23
Recombinant Data

• Graphs can be filtered and pivoted, without
  losing meaning

24
Where does Semantic Web Fit In?
Connecting Legacy Data to SWD2R, MagLev
25
Semantic Web Applied to Disease Mechanism and
Pharmacology
26
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 projects
  Exhibit tools to display information merging
  three points of view
• Demographics
• Treatments
• Adverse Events
• SNP

27
Clinical Observations Interoperability

• Recently formed http//esw.w3.org/topic/HCLS/Ontol
  ogyTaskForce/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.

28
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 Ive seen semantic web
  technology do anything useful
• WWW2007 Thank you from the semantic web
• Some problems solved, many remain, ongoing work.

29
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.

30
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

31
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.

32
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 technologys 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.

33
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 RD
• Sponsors Pfizer, Merck,

34
(No Transcript)