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3. John Wise, Pistoia Alliance

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  • 1. “Will Big Data and Bigger Cuts Cripple Bioinformatics?” ―If we want things to stay as they are, things will have to change. D‘you understand?‖John WiseExecutive Director, Pistoia AllianceProgramme Coordinator, PRISME Forumhttp://pistoiaalliance.org
  • 2. Beyond The Shadow of a Drought: The Need for aNew Mindset in Pharma R&D - Oliver Wyman http://www.oliverwyman.com/4638.htm#.URpXYirKeMo 2
  • 3. 3
  • 4. “…standing on the shoulders of giants” Sir James Whyte Black OM, FRSNobel Prize for Medicine 1988 4 1924 – 2010
  • 5. Challenges in a Changing Landscape • The terms “efficacy” and “effectiveness” have very different meanings. – Efficacy refers to the extent to which a drug does more good than harm in clinical trials where patients are carefully selected and monitored – Effectiveness refers to the extent to which a drug does more good than harm in real life where patients are not so narrowly selected and often not closely monitored.[Today] ―Pharma is developing drugs that bring incremental benefits, but at apremium price. This has given rise to the debate between the providers andpayers—what is the value of the extra benefit?‖Hans-Georg Eichler, M.D., M.Sc.Senior Medical Officer at the European Medicines Agency in London, United KingdomThe Tale of Health Care Reform - DIA Global Forum December 2010 p20
  • 6. P = R&D Productivity WIP = Work in Progress p(TS) = Probability of Technical Success V = Value of Work in Progress CT = Cycle Time C = Cost of Work in ProgressHow to improve R&D productivity: the pharmaceutical industry’s grandchallenge. S. Paul et al – Nature Reviews, Drug Discovery, March 2010
  • 7. Figure 3 | R&D productivity model: parametric sensitivity analysis. This parametric sensitivity analysis is created from an R&D model that calculates the capitalized cost perlaunch based on assumptions for the model‘s parameters (the probability of technical success (p(Ts)), cost and cycle time, all by phase). When baseline values for each of theparameters are applied, the model calculates a capitalized cost per launch of Us$1,778 million. This forms the spine of the sensitivity analysis (tornado diagram). At the top of thegraph are the parameters that have the greatest effect on the cost per launch, with positive effect in blue (for example, reducing cost) and negative effect in red. Parametersshown lower on the graph have a smaller effect on cost per launch.―How to improve R&D productivity: the pharmaceutical industry’s grand challenge‖ - Steven M. Paul et al.MARCH 2010 | VOLUME 9 www.nature.com/reviews/drugdisc
  • 8. 9http://c1776742.cdn.cloudfiles.rackspacecloud.com/downloads/pdfs/GartnerMagicQuadrant.pdf
  • 9. Isambard Kingdom Brunel, (1805-1859) http://www.brunel.ac.uk/about/history/ikb/greateasternThe Great Eastern, or Leviathan, launched 1858. Larger than any previous ship - not equalledin size for another 50 years. Paddle and screw propulsion & designed to carry 4,000 passengers.Made only nine Atlantic crossings before her conversion to a cable-laying ship.Length 692 feet. Displacement 32,000 tons. Total IHP 8,300.The Great Eastern later went on to lay the first cable to India in 1870. 10http://en.wikipedia.org/wiki/Submarine_communications_cable
  • 10. 1858 cable – 0.1 words per minute 1. Polyethylene1866 cable – 8 words per minute 2. "Mylar" tape 3. Stranded metal (steel) wires1900s – 120 words per minute 4. Aluminum water barrier 5. Polycarbonate2001 – VSNL Transatlantic – 5.1 Tbits 6. Copper or aluminum tube ~ 1 * 10^9 words per minute 7. Petroleum jellyhttp://en.wikipedia.org/wiki/Transatlantic_telegraph_cable 8. Optical fibers 11 Wave Division Multiplexing
  • 11. The Information Ecosystem - Dream or Reality? Virtual Pharma Web Interface Standards-based, Scalable, Ecosystem Semantic Interface 12
  • 12. Phenotypic / Genotypic Information The Warfarin Label: PGx information This is a portion of the label for the anticoagulant warfarin. It shows the range of metabolism rates for some common CYP2C9 variants. Notice the emphasis on race- based categorization pagehttp://www.fda.gov/cder/foi/label/2007/009218s105lblv2.pdf 13
  • 13. The Pistoia AllianceJohn WiseExecutive Director, Pistoia AllianceProgramme Coordinator, PRISME Forumhttp://pistoiaalliance.org
  • 14. The Pistoia Mission Lowering the barriers to innovation by improving inter-operability of R&D business processes through pre competitive collaboration 15
  • 15. Q1 2013 Pistoia Alliance MembershipBoardOther Members
  • 16. Cloud-based Sequence Services• 10 Companies or Consortia responded to the Phase 2 RFP• 3 Consortia were selected to implement the Phase 2 Specification 17
  • 17. www.sequencesqueeze.org 18
  • 18. Sequence Squeeze Results & Winner 19
  • 19. Current portfolio of Pistoia Alliance projects• Controlled Substance Compliance Service – to enable pharma to maintain compliance in whatever geography they or their externalised research partners are operating,• HELM (Hierarchical Editing Language for Macromolecules) – a standard approach for a computer-based way of managing large molecules such as Peptides, Antibodies, Therapeutic Proteins and Vaccines.• tranSMART – to enable scientists to mine and analyse translation research data• AppStore – to encourage innovation in the information eco-system through the encouragement, creation and discussion of life science R&D Apps 20
  • 20. Financial Times25-Feb-13 21
  • 21. Pistoia Alliance App Strategy Unmet Need Value Proposition There is no ―App Store‖ specifically designed to support  Encourage innovation beneficial to the Life Sciences eco- life science R&D apps system through creation of a Pistoia Alliance AppStore App developers have not been encouraged to develop  Encourage life science R&D software developers to create life science R&D apps because there is no appropriate apps to solve industry problems forum for the display, testing, usage and feedback for life science R&D apps.  Use the Pistoia Alliance brand to certify relevant apps, which take advantage of data sharing workflows No standard repository for storing large communal datasets, or offloading calculations to hosted services.  Develop an AppStore Governance policy to ensure: • Apps are appropriate and fit for purpose The ubiquitousness of mobile devices will increase the • Feedback on apps can be made available to the developers demand for apps in general and life science R&D apps is • Liaison agreements with relevant external organizations can be no exception. be effected Business Case Projected Shared Project Costs ~$150,000 [Project Analyst, Legal Fees, Implementation, Project Meeting] Estimated value for the industry of implementing this project is ~$209m “Anywhere Anytime”, mobile-device enabled life science R&D – “Science-on-the-Go”  Laboratory apps on mobile devices takes the computer into places computers have so far not been able to go  The PA is the only formally-established, cross-company organisation equipped to co-ordinate this kind of App Store High Level Implementation Timeline Funding Agreed Funding Available Project Start Standard Available Q4 - 2012 Q1 - 2013 Q2 - 2013 Q3 - 2013 Q4 - 2013 22
  • 22. Pistoia App Catalogue : It‟s real!iOS - AvailableDroid – In ProgressWin8 – In Progress 23
  • 23. Pistoia Alliance Project - HELM Unmet Need Value Proposition There is no standard approach for a computer-based  HELM has been developed, tested and used by Pfizer way of managing large molecules such as:  HELM is being published and its supporting software  Peptides, Antibodies, Therapeutic Proteins and tools will be put into the open-source public domain Vaccines Small molecules can be represented by atom bond  Pistoia Alliance to ―sign-post‖ this standard and foster its representation, oligomers require monomer adoption throughout the Pistoia Alliance community representations.  Pistoia Alliance to provide ad interim governance for the Component-level representations are required for big controlled evolution of the standard. proteins and antibodies. Business Case Projected Shared Project Costs ~$125,000 [Project Coordinator, Governance, Promotion, Project Meeting] Estimated value for the industry of implementing this project is ~$437m  Standard reference notation for macromolecules in pharma compound registration systems  The PA is the best-positioned, formally-established, x-company organisation equipped to co-ordinate this kind of pre-competitive collaboration High Level Implementation Timeline Funding Agreed Funding Available Project Start Standard Available Q4 - 2012 Q1 - 2013 Q2 - 2013 Q3 - 2013 Q4 - 2013 24
  • 24. Companies involved Project team members(Abbott) GSK RocheAccelrys (InChi Trust) RSCACDLabs InfoSys ScilligenceBMS Merck Thompson ReutersCertara NIH UCBChemAxon Pfizer Unilever• 18 different companies expressed an interest or came to the kick off meeting.• Most of these companies have at least one person actively working in a subgroup.• 43 people attended the first meeting! 25
  • 25. Controlled Substances Compliance Service Unmet Need Value Proposition Pharmaceutical companies routinely work with controlled  Establish a high-quality, controlled substance substances, so must have adequate controls in place. compliance information service that will enable pharma to maintain compliance in whatever geography they are Legislation is increasingly complex as legislators attempt operating. to keep up with a rapidly changing environment.  Each pharma company only has a small number of The externalisation of pharma means compounds are domain experts able to monitor and interpret the produced, stored and transported across all legislation. Provision of a comprehensive service will geographies. minimize the risk created by the size-limited workforce No single source of global controlled substance and will also eliminate the replication of effort across the knowledge is available; just the legislation itself or pharmaceutical industry. specific country / legislation-type databases/websites It is imperative that pharma has a clear, detailed and accurate understanding of the regulations in all regions. Business Case Projected Shared Project Costs ~$300,000 [Project Analyst, Legal Consultation, Implementation, Project Meeting] Estimated value for the industry of implementing this project is ~$90m  FTE saving on employing/training domain expertise to monitor and interpret the legislation  FTE saving on the transformation of legislation into data that can be used to enforce control• Risk mitigation - fines, damage to reputation , revocation of licences to operate with controlled substances High Level Implementation TimelineProject Start Funding Available Service Available 26 Q2 Q4 - 12 Q2 - 13 Q4 - 13 Funding Agreed
  • 26. Business Challenge The global nature of externalisation - including outsourcing and collaboration - is increasingly prevalent in today’s pharmaceutical industry. Businesses need to know the international, regional and local laws wherever they operate…United Nations Single Convention on Narcotic Drugs 1961 Belgium - Royal Decree of 1930 on narcotic substances and Royal Decree of 1998 on psychotropic substancesUnited Nations Convention on Psychotropic Substances 1971 Czech Republic - Law no. 167/1998, On Narcotic Drugs and Psychotropic SubstancesUnited Nations Convention against the Illicit Traffic in Narcotic Drugs Denmark - Executive Order 698 of 1993 on Euphoric Substancesand Psychotropic Substances 1988 Germany - Narcotics Act (BtMG)United Kingdom Misuse of Drugs Act 1971 Spain - Order of 8th July 1967 and the Royal Decree 2829/1977United States Controlled Substances Act 1970 Ireland - Misuse of Drugs Regulations1988United States CHEMICAL DIVERSION AND TRAFFICKING ACT OF 1988 France – Decree Law of 22 February 1990Canadian Controlled Drugs and Substances Act 1996 Netherlands - Opium ActIndia - Narcotic Drugs and Psychotropic Substances Act, 1985 Portugal - Decree-Law 15/93Singapore – Misuse of Drugs Act Norway - Regulation of 1978New Zealand – Misuse of Drugs Act 1975 Poland - 1997 Act on Counteracting Drug AddictionThailand - Psychotropic Substances Act Greece - Law 3459/2006 (Codification of the DrugPakistan - Narcotic Drugs and Psychotropic Substances Act, 1985 Legislation)Australia - Standard for the Uniform Scheduling of Medicines and Poisons Estonia - Regulation No 39 of the Minister of Social AffairsPhilippines - Comprehensive Dangerous Drugs Act of 2002 of 4 November 1997Russia - Regulations on the State Committee of Russian Federation for the Austria - ‗Narcotic Substances Act‘ (Suchtmittelgesetz, abbr. SMG)control of narcotic drugs and psychotropic substances Italy - Decree 4 March 1992United Arab Emirates - UAE Federal Law 14 of 1995 Sweden - Narcotic Drugs Punishments Act (1968:64).Japan - Narcotics & Psychotropics Control Law, Stimulants Control Law, Portugal - Decree Law 15/93, of 22 January 1993Narcotics Special Law Slovenia - Production and Trade in Illicit Drugs ActSouth Africa - Drugs and Drug Trafficking Act No. 140 of 1992 Slovakia - Act No. 139/1998Iceland - Regulation on habit-forming and narcotic substances and other Romania - Law no. 143/2000controlled substances No. 233/2001 Malta - Medical and Kindred Professions OrdinanceGibraltar - Drugs (Misuse) Act 1973 (Cap. 31), Dangerous Drugs Ordinance (Cap. 101)Indonesia – law on narcotics (Law No. 22/1997), law on psychotropics Luxembourg - Grand Ducal decrees, 4 March 1974,(Law No. 5/1997) 20 March 1974, 26 March 1974, 8 May 1993 and 30 January 2004European Union - Council Decision 2005/387/JHA of 10 May 2005 on the Lithuania - Law on Narcotic and Psychotropic Substances Controlinformation exchange, risk-assessment and control of new psychoactive (No.VIII-602; 1998)substances Bulgaria - Drugs and Precursors Control Act 1999European Union - REGULATION (EC) No 273/2004 OF THE EUROPEAN Croatia - Law on Combating Narcotic Drugs Abuse 2001PARLIAMENT AND OF THE COUNCIL of 11 February 2004 on drug Cyprus - Narcotic Drugs and Psychotropic Substances Law 1977precursors Finland - Narcotics Act (1289/1993)European Union - COUNCIL REGULATION (EC) No 111/2005 of 22 Hungary - 1/1968. (V. 12., Government Decree No. 272/2001.(XII.21.), 4/1980. (VI. 24.)December 2004 laying down rules for the monitoring of trade between the Latvia - Law on Procedures for the Legal Trade of the Narcotic and Psychotropic Substances, Law on PrecursorsCommunity and third countries in drug precursors Lithuania - Law on Narcotic and Psychotropic Substances Control (No.VIII-602; 1998) 27
  • 27. Project TeamCompany Status Contacts3E Project Team Kishore Mamidi, Jeffrey StarrAccelrys Project Team Carmen Nitsche, Keith TaylorAstraZeneca Project Team/Steering Cmte Daniel Taylor, Stuart BowdenBinocular Vision Project Team Tom BlackadarBoehringer-Ingelheim Project Team John Proudfoot Alex Drijver, Douglas Drake, Aurora Costache,ChemAxon Project Team Daniel BonniotGGA Software Project Team James MartinGSK Project Team/Steering Cmte Rob Lifely (Project Lead), Derek Wilson Josef Eiblmaier, Stephanie North, JürgenInfoChem Project Team RochlitzMerck Project Team Ingrid Akerblom, Jim GogginLHASA Project Team Chris Barber, Nicole McSweeneyNovartis Project Team/Steering Cmte Daniel Baeschlin, Marc Andreae, Greg WendelRobert Schwartz Project Team Robert Schwartz Margret Assfalg, Eva-Maria Gutknecht,Roche Project Team/Steering Cmte Reinhard KnorrPistoia Alliance Project Team/Steering Cmte Anne Dunlop (Project Manager), John WiseEBI In-discussions Dominic ClarkRSC In-discussions Richard KiddSanofi In-discussions Manfred HendlichSigma Aldrich On Hold Judy Pruss, Mike Willis 28 28Thomson Reuters In-discussions Andreas Matern
  • 28. Pistoia Alliance - tranSMART Unmet Need Value Proposition Scientists are expending too much time in finding and Building on the tranSMART open-source platform, enable integrating translational science data and too little time and accelerate translational research by: analyzing it.  Creating a not-for-profit tranSMART organization to coordinate There is no universal technology platform for the management, technology development, semantic standards and data curation integration and analysis of translational research data. processes. There is no universal x-organization forum to provide  Enabling, encouraging and empowering life scientists to mine coordination for the configuration and development of such a and analyze translation research data. technology platform.  Fostering an open-source community of scientific users and There is no place to collect public translational research data technology developers with standardized data-curation processes and terminologies.  Establishing a business model for the on-going sustainability of the tranSMART environment Business Case Estimated value for the industry of implementing this project is ~$298m Increased translational scientist productivity and decreased  Costs savings in Information Management Less tangible benefits:  A forum to collect public translational research studies in a standardized environment High Level Implementation Timeline• Project Start tS Foundation operational PPP Funding established Fully established and• Next Release of tS code funded and globally aligned Q4 - 2012 Q1 - 2013 Q2 - 2013 Q3 - 2013 Q4 - 2013 29
  • 29. tranSMART Origins (2007-2010)• Created by J&J/RDC• Extended i2b2 to include „omics‟• Central knowledge management• Open source (2012)• Cloud based• Pre-competitive data sharing 30
  • 30. Translational Challenge:Data Integration & Analysis 31
  • 31. tranSMART Overview tranSMART platform • management • integration • analysis of translational research data 32
  • 32. Pistoia Alliance Publications 1. “The Pistoia Alliance - The Sequence Services Project” - Simon Thornber et al. - G.I.T. Laboratory Journal 1-2/2011 2. “Need for Collaborative Technologies in Drug Discovery” - Chris L. Waller et al. Book Chapter in “Collaborative Computational Technologies for Biomedical Research” – Edited by Sean Ekins et al. Wiley May 2011 3. “What are the obstacles to innovation in the Pharmaceutical Industry? The Pistoia Alliance responds” – The Pistoia Alliance – Drug Discovery World 4. “Empowering Industrial Research With Shared Biomedical Vocabularies” – Lee Harland et al - Drug Discovery Today 5. “ELNs - An Essential Productivity Tool – But Which One to Use” – John Wise - European Pharmaceutical Review - Issue 4, 2011 6. Towards Virtual Knowledge Broker services for Life Science literature and data resources - Ian Harrow et al – Drug Discovery Today – In press 7. “Semantic integration of gene-disease associations for Diabetes Type II from literature and biomedical data resources” - Dietrich Rebholz-Schuhmann et al. – Drug Discovery Today – In press 33

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