Translational Informatics in the Pre-Competitive Era


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Presentation made during the EISBM workshop, 13-15 June 2012 by Anthony Rowe PhD (Janssen, pharmaceutical companies of Johnson & Johnson).

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Translational Informatics in the Pre-Competitive Era

  1. 1. Supported byProminent international speakers from h"p://workshop.eisbm.eu1
  2. 2. Translational Informatics in the Pre-Competitive EraAnthony Rowe PhDPrincipal Research ScientistResearch and Development IT – External InnovationEISBM Workshop – 13 June 2012
  3. 3. Disclaimer• Presentations are intended for educational purposes only and do not replace independent professional judgment.• Statements of fact and opinions expressed are those of the participants individually and, unless expressly stated to the contrary, are not the opinion or position of the Janssen Pharmaceutical Companies or its affiliates. 29/02/2012 2
  4. 4. Agenda• Pre-competitive Research• Translational Informatics• The TranSMART Project• Examples of ongoing studies
  5. 5. What do we mean by the precompetitive era?
  6. 6. Backdrop: Pharma R&D Productivity Gap R&D IT External Innovation 6/13/2012 5
  7. 7. Janssen’s  Vision R&D IT External Innovation 6
  8. 8. The models of drug discovery are evolving Proprietary content Public provider content provider Big Life CRO Patient Science organization Company Pharma Regulatory authorities Academic group Service provider Software vendor R&D IT External Innovation 6/13/2012 7
  9. 9. Leading to precompetitive collaborative research Proprietary content Big Life Public provider Science content Company provider P Big Life CRO Patient Science P organization Company Regulatory P authorities Academic group Big Life Science Service provider Company Software vendor R&D IT External Innovation 6/13/2012 8
  10. 10. R&D IT External Innovation 9
  11. 11. Some example IMI ProjectsProject Research AreaU-BIOPRED Severe AsthmaPharmaCog AlzheimersE-TOX ToxicologyOncoTrack Colon CancerEHR4CR Electronic Health RecordsBT Cure Rheumatoid ArthritisPredict-TB TuberculosisEMIF Medical InformaticsETRIKS Knowledge Management R&D IT External Innovation 6/13/2012 11
  12. 12. Translational Informatics in pre-competitive research R&D IT External Innovation 12
  13. 13. Goal 1: Enable translational informatics Bio-banks Cohorts Biomarkers Bed Bench Bed Care Stratified Companion EHR Medicine Diagnostics Pathways Evidence Based Personalised Medicine Medicine In-vivo/In-Clinical Omic NGS Imaging vitro PK/PD RegistryCentre 1 Centre 2 Centre 3 Centre 4 Centre 5 Centre n 29/02/2012 13
  14. 14. Goal 2: Enable collaboration in network ofpartners Proprietary content Big Life Public provider Science content Company provider P Big Life CRO Patient Science P organization Company Regulatory P authorities Academic group Big Life Science Service provider Company Software vendor R&D IT External Innovation 6/13/2012 14
  15. 15. We need technology to support Virtual BiotechNetworks...
  16. 16. What collaboration tools do we use• Project Collaboration • Data Collaboration – Base Camp ... – Group Camp – Grant Snap – Project Place – Drop Box – Skype – Webex – Go To Meeting – Internal Platforms – Wikis – Millarium – Sales• Note: heavy use of cloud technologies
  17. 17. Our contribution: TranSMART fromJohnson & Johnson Szalma et al. Journal of Translational Medicine 2010, 8:68 R&D IT External Innovation 6/13/2012 17
  18. 18. Informatics ChallengesCommon Challenges tranSMART approachClinical Data organised and A central system to managemanaged separately across knowledge for the researchdifferent groups organisationResearch Data fragmented Integrate Clinical and Omics inand not linked to the clinical a single repository to supportdata translational researchNo single place to find out A search tool to explorewhat research has already internal and external publishtaken place researchRoutine exploratory analyses A suite of tools to supporttake a long time for common exploratorybiostatistics questions R&D IT External Innovation 18
  19. 19. The TranSMART Platform – 60,000 Ft Query and Analysis Tools Patient Biological Data Data• A data management solution to systematically combine clinical and biological data for translational research• A suite of analytical and informatics tools to use this data in translational questions 29/02/2012 19
  20. 20. The TranSMART Platform• Use Cases – what is the correlation between animal models and human data – what is the best biomarker strategy for a given compound – what is the best indication for a given compound – how can a disease stratified based on clinical data – is there support for a target of interest based on clinical data• Data – Clinical data, clinical and pre-clinical gene expression, protein profiling (ELISA, RBM), SNP, PD markers, metabolomics, proteomics • In-house – immunology (large and small mol), oncology, cardiovascular, psychiatry • Public and commercial – Curated text & Text indexing – Master data, ontologies, vocabularies and metadata – Federated sources• User Interfaces – Search Gene, pathway, disease, compound, trial, and combinations – Hypothesis testing - Cohort selection and comparison/analysis – Hypothesis generation - Gene signatures – Analytics workflows 20 29/02/2012
  21. 21. Open Source: The TranSMART Project• An  initiative  to  make  open  source  Janssen’s  translational   research platform TranSMART• Available today under GPL v3 license• A growing community of academic and industrial involvement – Especially in IMI funded projects 29/02/2012 21
  22. 22. tranSMART for precompetitive research IMI OncoTrack IMI BTCure Predect IMI IMI Safe-T Stembancc UBIOPRED IMI IMI Predict EMIF TB J&J Internal IMI eTRIKS Abirisk Use One Mind RA – MAP Consortium NIH MRC Consortium Sage Bio ASTEROID Networks 6 Other Pharma R&D IT External Innovation 22
  23. 23. Example Projects• IMI UBIOPRED• IMI OncoTrack• Sage Bionetworks• One Mind• eTRIKS
  24. 24. IMI U-BIOPRED: Biomarkers for Severe Asthma• Key Facts• Identification of novel biomarkers of severe asthma• 40 Partners (20 Academic, 10 SME, 10 EFPIA)• Novel Cohort and Biobank of Severe Asthma Patients (n=750)• Profiling of Genomics, Proteomics, Lipidomic, Breathomic• Matching with in-vivo and in-vitro models R&D IT External Innovation 6/13/2012 24
  25. 25. Knowledge Production ProcessProcess:Patient Omics Samples Knowledge Delivery Data DataProcedure: Data Analysis Protocol SOP (SRM) KM Structure PlanData Management: TransMart Governance eCRF LIMS Files Others? 25
  26. 26. UBIOPRED Data Sources Number of Data Class Assay/Data Source Sample Types SamplesClinical ECRF (medical history, N/A 725 adult, 525 lung function, drug use) longitudinal 300 paediatricClinical Patient Reported Up to 100 OutcomesClinical Patient Diaries - Up to 100Transcriptomics Human Genome U133 Blood Up to 600 Plus 2.0 ArrayProteomics NanoMate ESI Sputum, Serum 1500Proteomics MS(E) Sputum, Serum 150Lipidomics Sputum, 1500 NanoMate-ESI PlasmaLipidomics lipidomic screen - LC/QTOF Urine 1000Lipidomics lipidomic screen - LC/QTOF Sputum 1000Breathomics eNose Breath Up to 1000Breathomics GC-MS Breath Up to 100Metagenomics TBC Nasel swabs TBCCT Morphology readouts Chest CT TBCHistology Cell counts readouts Broncoscopy Up to 288 R&D IT External Innovation 26
  27. 27. Recruitment Analysis – Built in less than 5 minutes R&D IT External Innovation 27
  28. 28. R&D IT External Innovation 28
  29. 29. R&D IT External Innovation 29
  30. 30. Analytical Registry – Organisational KnowledgeManagement Manage Document N A L Y T I CA Data Sets & SOPS A L Investigators TranSMART Data Mart and Search Engine for Study Data R Y Manage Collaborate EG R I ST Around Cohort Design Ideas Selections
  31. 31. UBIOPRED Current Status: 13 June 2012• Undertaking an interim analysis of our first 60 patients – Bench Test the UBIOPRED system – Look for early signals in well validated platforms• Clinical, Sputum, Urinine & Serum Lipidomics – Preliminary lipid data analysis performed by Xian Yang – Methods will be posted on the analytical registry• Clinical data being review for quality – Looking for outliers, batch effects – TranSMART projects starting soon• UBIOPRED Scientific Board will reviewed in 2 weeks time IMI Day 2012
  32. 32. OncoTrack Consortium• Key Facts• Methods for systematic next generation oncology biomarker development (Focus on Colon Cancer)• 19 Partners (7 Academic, 4 SME, 8 EFPIA)• Sequencing the genome, transcriptome and methylome of each tumor (primary tumor and metastasis)• Sequencing includes tumor derived material (CTCs, free circulating DNA, CSCs, xenografts)• Driving NGS work in tranSMART project 34
  33. 33. Sage Bionetworks Collaboration• Providing comparator arm of a J&J clinical trial for CTCAP• Provided tranSMART for KM• Universal  “opt-in”  and  “Portable  Informed  Consent” Janssen R&D Information Technology 11/1/2011 35
  34. 34. tranSMART for One Mind For Research Janssen R&D Information Technology 1/27/2012 36
  35. 35. eTRIKS: Summary• Problem: No open KM infrastructure to support pre-competitive (& competitive) cross-institute TR. No public knowledge base of curated TR data. • Proposal: • Consortia to develop & deliver an open TR KM infrastructure & Service • Built around J&J’s  tranSMART open platform • Curation of content (live and historic TR trials) • Support of existing IMI initiatives • UBIOPRED, OncoTrack, Safe-T, etc... • TR KM standards, enabling TR data sharing • Promotion of TR analytics innovation. • Mirror of US tranSMART consortia (tba) • Benefits:• Consortia Model & Costs: • Improved TR project operating efficiencies • $31m / 5 year • Stable legacy: IMI TR data security • 10 Pharma (AZ/J+J Lead) • Access to curated historical content enabling • ~5 AMC/SMEs with experience in TR both: KM service delivery • Analytics/Methodology innovation • Review impact in year 2: with follow • Novel x-study translational discovery on funding - possible  IMI  ‘Big  Idea’ • Enables x-institute TR data sharing • Curation funded by supported IMI • Strengthened TR Ix community projects 37
  36. 36. TranSMART in the Bigger Landscape Commercial Technology Industry (e.g.) RecombinantOpen Source eTRIKS ProjectGalaxyProjectsUS Public Private Consortia EU Public Private Consortia Standards Groups(e.g.) Horizon 2020 CDISC Biopharma Industry (e.g.) Open Information Day – 17 June 2011 - Brussels
  37. 37. Summary• Pre-competitive research is creating new virtual organisations• Precompetitive research requires innovative IT Solutions that break down new organisational barriers• Open Source TranSmart is a part of that puzzle
  38. 38. Questions?Join us R&D IT External Innovation 6/13/2012 40