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INFOBIOMED

INFOBIOMED. NoE. WP 6.1 Pharmainformatics. Exploitation of Biomedical Informatics In Drug Discovery. INFOBIOMED. NoE. WP 6.1 Pharmainformatics. Overall Needs Disease Understanding Biochemical/Genetic Context Drug/Ligand Characterisation Adverse Effect Deconvolution. INFOBIOMED. NoE.

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INFOBIOMED

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  1. INFOBIOMED NoE WP 6.1 Pharmainformatics Exploitation of Biomedical Informatics In Drug Discovery

  2. INFOBIOMED NoE WP 6.1 Pharmainformatics Overall Needs Disease Understanding Biochemical/Genetic Context Drug/Ligand Characterisation Adverse Effect Deconvolution

  3. INFOBIOMED NoE WP 6.1 Pharmainformatics Challenges Pharmaceutical companies are: Flooded with data Secretive Highly Regulated Chemistry-focussed

  4. INFOBIOMED NoE WP 6.1 Pharmainformatics Non-Responders AEs in NonResponders Responders AEs in Responders

  5. INFOBIOMED NoE WP 6.1 Pharmainformatics Ideal

  6. INFOBIOMED NoE WP 6.1 Pharmainformatics AE Related to Target Pathway ?

  7. INFOBIOMED NoE WP 6.1 Pharmainformatics AEs Unrelated to Target Pathway ?

  8. Data Complexity - Bx • AZID (Interaction Database) in support of pathway analysis

  9. INFOBIOMED NoE WP 6.1 Pharmainformatics Information Continuum Pathology Pathway Target Ligand Ontologies Evolution

  10. INFOBIOMED NoE Target Pathway AE-1 Target Pathway AE-2 Target Pathway AE-3 Target Pathway AE-4 Target Target Target Pathway Pathway Pathway AE-5 AE-1 AE-1 Target Pathway AE-6 Adverse Effect Deconvolution ? Pathology Pathway Target Ligand Ontologies

  11. INFOBIOMED NoE WP 6.1 Pharmainformatics – First 6 Months Information Continuum Practical work Pathology Pathway Target Ligand Ontologies Evolution

  12. INFOBIOMED NoE WP 6.1 Pharmainformatics – First 12 Months Information Continuum Definition of synergies Pathology Pathway Target Ligand Clinical Data Standards & Formats Ontologies & Lexicons Knowledege Extraction Technologies Evolution

  13. INFOBIOMED NoE Activity code and title: Indicate the expected involvement of partners in the table below, describing role and estimated effort, expressed in person-months. *: Code as follows: L - Activity Leader. W - Works. I - Provides input. R - Reviews. O - Other (please specify).

  14. INFOBIOMED NoE Activity work plan - first 12 months Activity code and title: WP6.1 ‘Pharmainformatics’ Responsible partner: AstraZeneca Activity objectives: Assess impact of BMI on the Drug Discovery Process Expected results Month 6: Catalogue, acquire and preliminarily evaluate from consortium members: 1) Software and datasets/bases 2) Suggested work processess Month 12: Jointly suggest development directions for the above areas that are: 1) Tangible and tractible 2) Expected to give quantifiable results 3) Represent development opportunities Relationships with other activities (input/output): Input: WP2, WP4 & WP5 Output: WP2, WP3, WP4, WP5

  15. INFOBIOMED NoE Activity work plan schedule • Activity code and title: WP6.1 ‘Pharmainformatics’ • Brief description of work to be done during the full 12 months: • Evaluaton of software, database/format and work processes available within the consortium as they relate to the Drug Discovery process. • Evaluation of functionality within a secure network and between secure networks • Usefulness and compatability of data types, formats and storage technologies • ‘Gap’ analysis of existing functionality, etc. with that available from consortium • Pilot-testing of likely future tools & technologies • Proposal for future work that will be of highest impact • Initiate work on ontologies (!) • Details of work to be done in first 6 months: • Collection of existing techniques/tools that consortium members feel would be useful to DD process. • Detailed communication to interested members on details of data-gaps and process bottlenecks in DD.

  16. INFOBIOMED NoE Partner activity work plan schedule - IMIM • Activity code and title: WP6.1 ‘Pharmainformatics’ • Brief description of work to be done during the full 12 months: • Despite the efforts being put in annotating biological entities, annotation of chemical entities has been largely overlooked. Therefore, chemical terminologies for the systematic annotation and classification of large compound collections will be derived. Once chemical annotations are available, they will be used to identify recurrent structural patterns within (sub)families of proteins. To this aim, databases of molecules annotated with biological entities will be constructed. These activities will set the basis for the design and screening of chemical libraries against multiple targets to be done at a later stage. • Details of work to be done in first 6 months: • Review existing chemical annotation schemes • Propose a chemical annotation scheme • Assess linkage with existing protein, gene, and disease annotation schemes

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