Transcript Semantic Web for Life Sciences

From Bench to Bedside:
Applications to Drug Discovery and
Development
Eric Neumann
W3C HCLSIG co-chair
Teranode Corporation
HCLSIG F2F
Cambridge MA
Knowledge
“--is the human capacity (both potential
and actual) to take effective action in
varied and uncertain situations.”
Drug Innovation and the Technology Gap
Need to utilize
Knowledge more
effectively
Drug R&D Trends
from Innovation or Stagnation, FDA Report March 2004
from Innovation or Stagnation, FDA Report March 2004
New Regulatory Issues
Confronting Pharmaceuticals
Tox/Efficacy
ADME Optim
from Innovation or Stagnation, FDA Report March 2004
Translational Medicine
Enable physicians to more effectively translate
relevant findings and hypotheses into therapies
for human health
 Support the blending of huge volumes of clinical
research and phenotypic data with genomic
research data
 Apply that knowledge to patients and finally make
individualized, preventative medicine a reality for
diseases that have a genetic basis

Role of Informatics
John Glaser, CIO Partners Healthcare
 Providing high quality and efficient health care isn't possible
anymore without a sophisticated marriage of information
technology and state-of-the-art science.
 Bringing these together to inform patient care is a tremendous
undertaking… the full array of new information provided by
genomic research must be harnessed and made real for doctors
and patients
 A Framework for conducting clinical research in and across
large multidisciplinary academic medical centers is designed to
establish a "new" biomedicine to "fully exploits the fruit of the
genomic revolution for clinical practice and allows clinical care to
be leveraged to advance basic biological research.
Challenges for Drug D&D
Counteracting the legacy of “Silos”
 How to break away from the DD “conveyor belt
model” to the “Translation model”

– gaining and sharing insights throughout the
process

The Benefit of New Targets for New Diseases
 How to best identify safety and efficacy issues
early on, so that cost and failure are reduced
 A D3 Knowledge-base: Drugability and Safety
Drug Discovery & Development Knowledge
Qualified
Targets
Lead
Generation
Lead
Optimization
Toxicity &
Safety
KD
Molecular
Mechanisms
Clinical
Trials
Biomarkers
Pharmacogenomics
Drug Discovery & Development Knowledge
Qualified
Targets
Molecular
Mechanisms
Lead
Generation
Toxicity &
Safety
Lead
Optimization
Pharmacogenomics
Biomarkers
Clinical
Trials
Launch
Communities and Interoperability
Semantic interoperability is directly tied to CoP:
“Within
a community or domain, relative homogeneity reduces
interoperability challenges. Heterogeneity increases as one moves
outside of a focal community/domain, and interoperability is likely
[to be] more costly and difficult to achieve” Moen, 2001


Meanings encoded in a schema are usually useful for only
one (original) community - difficult to extend to others!
Database utility more difficult if group is heterogeneous
Multiple Ontologies Used Together
Disease
OMIM
UMLS
Group
FOAF
Disease
Polymorphisms
SNP
Drug target
ontology
UniProt
Protein
BioPAX
Person
PubChem
Patent
ontology
Extant ontologies
Chemical
entity
Under development
Bridge concept
Potential Linked Clinical Ontologies
Clinical Obs
Disease
Descriptions
SNOMED
Applications CDISC
ICD10
RCRIM
(HL7)
Clinical Trials Disease
Models
ontology
Mechanisms
Pathways
(BioPAX)
IRB
Tox
Extant ontologies
Genomics
Molecules
Under development
Bridge concept
Drug Safety Knowledge
• Genomic Profile Standards
set by Regulatory Agencies
Human Hepato-Toxicity Study
Hepato-Toxicity Lens
• To be part of NDA (New
Drug Applications)
•How will Reviewers be
empowered to handle such
large amaount sof new data?
Toxicity Indication
CDISC and the Semantic Web?





Reduce the need to
write data parsers to
any CDISC XML
Schema
Make use of
ontologies and
terminologies directly
using RDF
Easier inclusion of
Genomic data
Use Semantic Lenses
for Reviewers
Easier acceptance by
industry with their
current technologies
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Developing Standards
Exchange
Design
Implementation
Developing Standards
Semantic Web-based
Specifications
Design
Implementation
Exchange
Support Full Information Integration



Integration: integrate and manage data from
sources, EDC systems, Clinical Data Management
Systems , labs and CROs
Analysis and reporting: Accurately and timely
analytical reports from study data, for use in decision
making; easier results sharing with researchers and
reviewers
Discovery: Use expanding research information as a
knowledge base for rapid investigations into critical
drug safety issues, new marketing claims, and
identify product-line extensions.
Thank You