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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