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The Pistoia Alliance Information Ecosystem Workshop


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Michael Braxenthaler, president of the Pistoia Alliance, introduces the concept of the information ecosystem in life science research and discusses the role the Pistoia Alliance can play within this ecosystem. The workshop occurred in October 2011.

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The Pistoia Alliance Information Ecosystem Workshop

  1. 1. The Pistoia Alliance Information Ecosystem Workshop10 October 2011Hannover, Germany
  2. 2. Welcome! 2
  3. 3. Why this workshop? 3
  4. 4. Why this workshop? 4
  5. 5. Life Science Information LandscapeA rapidly evolving ecosystem Yesterday Today Tomorrow Big Life Science Company Yesterday Today TomorrowInnovation Innovation inside Searching for Innovation Heterogeneity of collaborations. Part of the wider ecosystemModelIT Internal apps & data Struggling with change Cloud/Services Security and TrustData Mostly inside In and Out DistributedPortfolio Internally driven and owned Partially shared Shared portfolio 5
  6. 6. The Pistoia Mission Lowering the barriers to innovation by improving inter-operability of R&D business processes through pre competitive collaboration 6
  7. 7. The Role of Pistoia: Node or ”Glue”? Proprietary • Pistoia is not a node in content Public provider its own right content provider • Pistoia supports the connections between the nodes CRO • Pistoia‟s strength is its diversity ofRegulatory members, representingauthorities substantial parts of this Academic ecosystem group Service provider Software vendor 7
  8. 8. Sept 2011Pistoia Alliance Membership
  9. 9. Pistoia Project Portfolio Questionnaire – Summary Contribute Users Contribute a ContributeAnalysis out of 22 Question # Interested? to define Project Funding? Requirements? Manager?Chemistry - Collaboration 2 15 8 1 1BackboneChemistry - (Hosted) Ordering 3 9 4 3 1/ Requesting ServicesChemistry - Hosted ELN and 4 12 6 1 1ServicesChemistry - Collaboration 5 9 5 0 1BrokeringChemistry - Analytical Data 6 11 7 1 2StandardsChemistry - Hosted 7 12 4 1 0Registration ServicesLife Sciences - InformationEcosystem Workshop 8 19 13 8 2Projects which are important 9 7 1 1 1to you /your company.
  10. 10. Workshop Agenda and Deliverables OutlineMorning session: Afternoon session:What is the IES? What should it be? How do we get there?Develop common understanding on what Develop a roadmap of projects andthe IES should deliver activities White Paper: IES Roadmap: The Key Concepts Projects and of the Information Ecosystem Follow-up activities More info at
  11. 11. Morning SessionOverarching theme:Develop a shared understanding of the problem space: What does ‘information ecosystem’ mean? What are the current shortcomings? What should it look like to help us solve our problems?• Workgroup 1: The industry/academic collaboration space• Workgroup 2: Information exchange with CROs – discovery/chemistry• Workgroup 3: Information exchange with CROs – biology/NCD• Workgroup 4: Integration of public and proprietary content• Workgroup 5: The Standards Landscape
  12. 12. AM Workgroup 1The industry/academic collaboration space• Increasing number of bi- and multilateral collaborations between life science companies and academic groups.• Need for collaboration space – Not just sharing and exchange of documents and data – Secure, „science-aware‟ collaboration environment – Allows collaborative data analysis and discussion – Easy and fast way to spin up and turn off instancesWhat would such a space ideally look like?What are the minimal and optimal requirements for such a space?
  13. 13. AM Workgroup 2Information exchange with CROs – discovery/chemistry• See use case “Research Externalization on a Collaborative Framework”
  14. 14. Use Case “Research Externalizationon a Collaborative Framework”Introduction:Declining R&D productivity, rising costs of commercialization &shorter exclusivity period have driven up the average cost oflaunching a successful new drug to US $ 1.7 billion. To facilitate drugdevelopment & to lower the cost & risk of launching new drugs ontheir own, pharmaceutical companies have increasingly turned toalliances for outsourcing.Actors:Pharmaceutical Company, Scientist, Regulatory body, DiscoveryCRO, Chemistry service providers, Biology service provider, assaydevelopment, screening, lead optimization & other vendors. 14
  15. 15. Use Case “Research Externalizationon a Collaborative Framework” (cont‟d - 1)Scenario:Target molecule has been discovered & validated by pharmaceuticalcompany‟s internal R&D department. Lead identification requiresexpertise, specialized skills, and heavy investments on resources/technology.There already exist vendors in the market withresources/technology/expertise in dedicated areas. Hence thepharmaceutical company decides to externalize the different components oflead identification process to multiple capable vendors, thereby resulting inreduced cost, time and overcoming lack of in-house expertise/resources.The diagram below depicts a scenario indicating a transition from asiloed/fully internal approach to a collaborative model which enablesmultiple pharma‟s to externalize their research activities to multipleorganizations in a secured manner. 15
  16. 16. Use Case “Research Externalizationon a Collaborative Framework” (cont‟d – 2) Pharma Design synthesize Register Distribute Assay Report Fully Internal Model CRO Pharma 1 Design DistributePharma 1 CRO Chem CRO Synthesize 2Pharma 2 CRO Bio Assay CROPharma 3 3 Data CRO Register Report CRO 4 Selectively Integrated Model 16
  17. 17. Use Case “Research Externalizationon a Collaborative Framework” (cont‟d - 3)The current industry challenges to execute the above scenario ona collaborative framework are:• Secured real time information exchange• IP Protection & infringement• Process & Data harmonization• Lack of standard data formats• Lack of regulatory guidelines around collaboration & networkingSummary:This collaborative model would not only drive seamless researchexternalization, but also enable access to information/experts, real timelearning‟s, reuse/sharing of internal assets, increase researchproductivity, focused approach, effective process tracking, shared workspacefor secured communication and risk mitigation. 17
  18. 18. AM Workgroup 3Information exchange with CROs – biology/NCD• Currently, data exchange between life science companies and CROs requires substantial manual involvement – data formatting issues – meta data and context for interpretation• Many areas in the R&D process affected – Genotyping, NGS, Proteomics, Metabolomics, Preclinical Safety - Animal StudiesWhat would the ideal exchange environment look like?• Are data and meta data standards sufficient?• Or would this environment benefit from a collaboration space allowing collaborative data access for QC and interpretation?
  19. 19. AM Workgroup 4Integration of public and proprietary content• Increasingly large volumes of relevant data for life science R&D are available in the public domain.• Tendency increasing in volume, complexity, and geographic/organizational distribution• Conventional approach to bring all relevant data in-house for integration and analysis will not be feasible in the futureWhat are sustainable models for environments which enableintegrated analysis and interpretation of distributed complex data?See also use case “Disease Explorer”
  20. 20. Use Case “Disease Explorer”There is a need to be able to "peel away" layers of information around adisease. For example:• For a given indication, what are the higher-level pathophysiological processes?• For each process, what are the cells, tissues and events within?• To what elements of the disease does each process contribute (initiation, progression, exacerbation etc.)• How does this then break down into molecular pathways?• Where are current therapies targetted?• Are we all targeting the same few pathways in the same process?• Are there processes that are completely untested?• How does the literature map onto this?• Where are the new emerging areas?• Where are the overlaps between diseases? Aan obvious example being the repurposing of viagra due to the enzyme, PDE5 s control of cyclic GMP, and that cGMP is involved in sleeping, diabetes etc.) 20
  21. 21. Use Case “Disease Explorer” (cont‟d)Conclusion:• We should have information systems able to explore disease through different levels of resolution and map databases accordingly.• This requires a functioning information eco-system, where the data is mapped to standards that facilitate this exploration and there is a wide body of developers producing elements of this "browser". 21
  22. 22. AM Workgroup 5The Standards Landscape• Many standards exist or are being developed in the life science information space• At the same time there are many calls for standards to enable information exchange/sharing/integrationWhat does the current standards landscape look like?What are the key issues with the current standard landscape? Too many? (where?) Missing? (where?) Problems with agreement/adoption?
  23. 23. Pistoia Project Portfolio Questionnaire – Summary Contribute Users Contribute a ContributeAnalysis out of 22 Question # Interested? to define Project Funding? Requirements? Manager?Chemistry - Collaboration 2 15 8 1 1BackboneChemistry - (Hosted) Ordering 3 9 4 3 1/ Requesting ServicesChemistry - Hosted ELN and 4 12 6 1 1ServicesChemistry - Collaboration 5 9 5 0 1BrokeringChemistry - Analytical Data 6 11 7 1 2StandardsChemistry - Hosted 7 12 4 1 0Registration ServicesLife Sciences - InformationEcosystem Workshop 8 19 13 8 2Projects which are important 9 7 1 1 1to you /your company.
  24. 24. Open Question - 9 At GQ we believe that both sequencing and sequencing analysis/data management are pre-competitive. To date, Pistoia has focused only on basic sequence analysis. I know Integration the sequence piece will include NGS. that phase II of of public1 However, I like the way you outlined the chemistry piece above, much more life-cycle centric. I’d argue you should do the same with NGS Sequencing and NGS Informatics. and proprietary content2 Interested in the Semantic Web It’s important that Pistoia picks a few key projects and nails them now, so a general steer would be not to dilute3 efforts or become over ambitious now. Put maximum energy and resource into a small number of projects and ensure success to ‘prove’ Pistoia works. Information Multi-party collaboration, project management, reporting tools including hosted, cloud-based or internal platforms. Multi-vendor integration approaches. Multi-discipline datawith CROs exchange integration.45 Pharma is moving towards externalization and the key to success is a standardized, scalable collaboration backbone.6 Platform for sharing in-house code externally7 Standards SEND (the CDISC standard for non-clinical data) Tox/DMPK area - Archiving8 (Pistoia certification?) Standardisation of clinical data format (by this comment was meant the exchange of information with CROs)9 Standards are important to us, as are projects involving making data more accessible to end users. We are very interested in external collaborative systems. However our current focus is to find a vendor already in Information this space and ensure that the Vendor is driven by open standards (where they exist). I hope that Pistoia will exchange with CROs eventually lead to a standards body for data sharing formats. Perhaps our goal should be to have Vendors proud to10 bear the mark Verified by Pistoia. I wonder where this fits into the various standards coming from W3C? The list above does not yet seem to ask questions regarding data formats for Assay/Protocol transfer. I think this is a critical issue when collaborating with multiple organisations. Is there a project looking into this?11 We focus on services around workflows for data integration/analysis, moving towards self-service workflows.
  25. 25. Afternoon SessionOverarching theme:Develop solution outlines to address the current problems: Proposals for short term projects and mid term activities Looking beyond the scientific-technical horizon: Economic feasibility and viable business models• Workgroups 1 and 2: Low-hanging fruit – What can we tackle right away within a 1-year time frame?• Workgroup 3: Continuing focus areas and mid-term activities – How do we approach more complex problems?• Workgroup 4: The Standards Landscape – What needs to be done?• Workgroup 5: Business Models – Rethinking the game
  26. 26. Let‟s go! Time to break up into groups and get our hands dirty… 26