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

ADME Optim Tox/Efficacy

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 and patients

array of new information

provided by genomic research must be harnessed and made real for doctors 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 be leveraged to

advance basic biological research

.

clinical care

to

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 D 3 Knowledge-base: Drugability and Safety

Drug Discovery & Development Knowledge

Qualified Targets Lead Generation Lead Optimization Molecular Mechanisms Clinical Trials K D Toxicity & Safety Biomarkers Pharmacogenomics

Drug Discovery & Development Knowledge

Qualified Targets Lead Generation Lead Optimization Molecular Mechanisms Toxicity & Safety 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 Group FOAF Person UMLS OMIM SNP Drug target ontology UniProt BioPAX Patent ontology PubChem Chemical entity Disease Polymorphisms Protein Extant ontologies Under development Bridge concept

Potential Linked Clinical Ontologies Clinical Obs Applications CDISC IRB RCRIM (HL7) SNOMED Disease Descriptions ICD10 Clinical Trials ontology Disease Models Pathways (BioPAX) Tox Genomics Mechanisms Molecules Extant ontologies Under development Bridge concept

Drug Safety Knowledge

•

Genomic Profile Standards set by Regulatory Agencies

• To be part of NDA (New

Drug Applications)

•How will Reviewers be

empowered to handle such large amaount sof new data?

Human Hepato-Toxicity Study Hepato-Toxicity Lens 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

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Developing Standards

Design Exchange 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