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  • Good morning to you all. I’m glad that I have the opportunity to present to you our results. I have about 20 minutes to talk you through a whole lot of work that we carried out for WP1/7 of BBMRI in the last year. Our objective was to 1,and 2. Obviously this has to be carried out while BBMRI was developing itself as well. What did we do, to answer the research questions. I will show you some concise data on the activities in red. And actually the validaton by stakeholders is today, so by you as a very well informed audience.
  • These are the ten case studies that we studied. As you may be able to see it is a mixture of population based, and case control biobanks, that show a nice geographical spread over Europe. I won’t go into detail on each of the cases but use them to show a limited set of aspects that turn out to be very relevant in the ecology of biobanking. These topics are shown in the next couple of slides.
  • The first slide shows an overview of the maturity and the orientation. Please only note the numbers (behind the numbers are the cases, as a memory stock for me) The majority started 5-7 years ago, before 2000 only a few biobanks were operational, and we included them becvcaise we wanted to see real developments and not plans. Also, the biobanks are mainly nationally organised. You can see that the more recently started actvities tend to be more internationally organised
  • The second slide shows numbers, both for collection as for distribution. One of the reasons to start with BBMRI is to get access to larger collectiosn of samples in order to study multifactorial diseases and rare diseases in more detail. Surprsingly the size of collections doesn’t relate to maturity or orientati Other than that in collection a truly big spread is shown. Another interesting finding is that in terms of ditribution, 50% of the cases don’t actually know how many samples were distributed. As you vcan see, the patient -run biobanks do exactly know, as they are aware of the cimmunity they serve
  • In terms of the organisation of biobanks: we have looked at the location of the repositories: here it is important to that a network can have a central repository, and the other way round, that a biiobank infrastrcuture can be kept at more than one place. In terms of the lower bottom of the table: all biobanks are involved in research, of course, but the more it develops the more it turns into a infrstructure, and on top of that, an network in which data are shared. As you can see coincide distributed bioabnks with a network structure.
  • Outreach activities refer to activities that biobansk display as part of their exteral strategy.I’d like to stress here that this iis not measured as a result, but as an activity thatmay lead to a result. But the activities are only partly reported, and sometimes only mentioned by interviewees, showing that they often are not seen as an important factir. Given these reserves, there are notable differences between biobanks.
  • Contact people from DeCode. Substitute for DeCode?? Funding is extremely important in the life time of a biobank. The mixed funindg model refers to the fact thet none of the cases has a single funder. The mixed funding has also to do with research, and the fact that biobanking is often not made explicit. Governmental funding is significant for sustainabiity. Networking does resuce cost, but this doesn;t count for the set up of any infrastrcutural facility that undelies the network.
  • The SNA is usewd to show the current status of the BBMRI network. And this first slide is to explain the next slides that I will show you
  • What des this piture show yiu, That there are a fewe ineterconnected networks, of which the onde with the green an red squares and rounds are crucial. Th gree ones rpresent BBMRI memeber or associates. S you can see BBMRI is not in every network, but it is mportant player looking at the size of the nodes. Here the core of BBMRI was established/
  • In FP 6 the network has extended, and mind you these are partticipants that are acting in more than ione projetc. So biobanking is b ooming. But there are still a lot of red squares which are not BBMR.... The network is bigger, but the role of BBMRI members is slightly less strong. Might not be the right model for later evaluation in the context of the ERI concept. In this model. Governments are not included
  • Does show the early connection of the BBMRI core member since FP5. Cancer biobanking is not so well connected
  • Different expectations How do you work in the networks, local auditing of the projects, funding Which have an impact on the indicatiors Focus on the outside, increase awarness of what exist outreach. Have to convince funders to avoid redundance and to save money for other research
  • Different expectations How do you work in the networks, local auditing of the projects, funding Which have an impact on the indicatiors Focus on the outside, increase awarness of what exist outreach. Have to convince funders to avoid redundance and to save money for other research
  • Different expectations How do you work in the networks, local auditing of the projects, funding Which have an impact on the indicatiors Focus on the outside, increase awarness of what exist outreach. Have to convince funders to avoid redundance and to save money for other research
  • As there is
  • Different expectations How do you work in the networks, local auditing of the projects, funding Which have an impact on the indicatiors Focus on the outside, increase awarness of what exist outreach. Have to convince funders to avoid redundance and to save money for other research
  • Technopolis

    1. 1. Evaluation BBMRI - (preliminary) results BBMRI Stakeholder’s Forum: Patient Working Group Paris 15 December 2009
    2. 2. Introduction <ul><li>Project for WP1/WP7... </li></ul><ul><ul><li>to carry out an ex-ante impact assessment of BBMRI </li></ul></ul><ul><ul><li>to set up a coherent monitoring and evaluation strategy for BBMRI </li></ul></ul><ul><li>Approach of the study </li></ul><ul><ul><li>Ad 1: Literature review </li></ul></ul><ul><ul><li>Ad 1: 10 Case studies - combined </li></ul></ul><ul><ul><li>Ad1: Mapping and clustering of biobanks - SNA </li></ul></ul><ul><ul><li>Preliminary conclusions </li></ul></ul><ul><ul><li>Ad 2: Logical Framework analysis </li></ul></ul><ul><ul><li>Ad 2: Indicator development </li></ul></ul><ul><ul><li>Validation by stakeholders </li></ul></ul><ul><li>Timeline: January - December 2009 </li></ul>
    3. 3. Case studies - selection <ul><li>Estonia BioBank - population based </li></ul><ul><li>DeCode - population based </li></ul><ul><li>Biobank Castilla-L é on - case/control oncology </li></ul><ul><li>TransBig - case/control oncology (Mammaprint) </li></ul><ul><li>Telethon - case/control rare disease network </li></ul><ul><li>EuroBioBank - case/control rare disease network </li></ul><ul><li>UDBN - case/control network </li></ul><ul><li>ENGAGE - data network </li></ul><ul><li>Graz Biobank - population based </li></ul><ul><li>Huddinge Brain bank - case/control neurology </li></ul>
    4. 4. Case studies results combined (1) - Time/maturity <ul><li>Majority started 5-7 years ago </li></ul><ul><li>Majority is nationally organised </li></ul>< 2000 >2000<2005 >2005 3 (DeCode, Graz, Huddinge) 4 (EGF, UDBN, EBB, TBCyL) 3 (Telethon, Engage, TransBig) Regional National European/Inter-national 1 (TBCyL) 5 ( DeCode, EGF, UDBN, Graz, Huddinge) 3 (EBB, Engage, TransBig)
    5. 5. Case studies results combined (2) - Numbers <ul><li>Collection - big spread: 1,100 - 4,400,000 </li></ul><ul><li>Distribution - mainly unclear, only when central access is available </li></ul>Collection < 10,000 10,000-100,000 >100,000 3 (Huddinge, TransBig, TBCyL) 3 (UDBN, EGF, Telethon) 4 (Graz, EBB, Engage, DeCode Distribution ? 0-1000 >1000 5 (DeCode, EGF, Graz, Engage, Huddinge) 2 (TransBig, TBCyL) 3 (UDBN, Telethon, EBB)
    6. 6. Case studies results combined (3) - Organisation <ul><li>Centralised repositories vs distributed </li></ul><ul><li>Research - networks - infrastructure </li></ul>Central Distributed Mixed 6 (DeCode, EGF, Huddinge, Graz, Transbig, TBCyL) 3 (Telethon, EBB, Engage) 1 (UDBN) Research Soft - networks Infrastructure 3 (TransBig, TBCyL, Huddinge) 3 (Telethon, EBB, Engage) 4 (EGF, DeCode, Graz, UDBN)
    7. 7. Case studies results combined (4) - Outreach activities <ul><li>Majority not very active towards industry </li></ul><ul><li>To society it is slightly better </li></ul>
    8. 8. Case studies results combined (5) - Funding patterns <ul><li>Mixed funding models </li></ul><ul><li>- personnel/infrastructure: public (institution) </li></ul><ul><li>- research: public (grants) </li></ul><ul><li>Biobanking long-term investment in infrastructure </li></ul><ul><ul><li>The start-up phase most expensive </li></ul></ul><ul><ul><li>Personnel highest costs, both at the start and in maintenance </li></ul></ul><ul><ul><li>Hidden costs that are not made explicit </li></ul></ul><ul><li>Networking reduces costs (Telethon) - saved 2/3 </li></ul><ul><li>Funding from industry doesn't work at the start (objectives diverge), but neither in the long run </li></ul><ul><li>Not until public funding is received the biobank activities are getting sustainable (Graz, Estonia) </li></ul><ul><ul><li>Difficult to find core (sustainable) funding </li></ul></ul><ul><ul><li>Difficult to find public funding since it is time-limited </li></ul></ul>
    9. 9. Social Network analysis – Why and how <ul><li>Interconnectedness crucial element in the development of European biobanking </li></ul><ul><li>How can we identify the nature and evolution of links?: “Social Network Analysis” techniques : Inter-organisational links </li></ul><ul><li>Source: projects identified as biobanking related projects by the &quot;Networking meeting for EU-Funded Biobanking Projects&quot; Report (2008) and the Wellcome Trust report &quot;From Biobanks to biomarkers&quot; (2006); Data collected from CORDIS </li></ul><ul><ul><li>Red square is an institution that is not BBMRI </li></ul></ul><ul><ul><li>Green triangle is BBMRI member </li></ul></ul><ul><ul><li>Round green is BBMRI associate </li></ul></ul><ul><ul><li>Size of node is proportional to number of projects an institution has participated in </li></ul></ul><ul><ul><li>The thickness of the line is proportional to the number of projects they have co-participated </li></ul></ul><ul><ul><li>FP6: only institutions that are participating in more than one project </li></ul></ul>
    10. 10. Social Network analysis - result FP5
    11. 11. Social Network analysis - result FP6
    12. 12. Social Network analysis - organisations
    13. 13. Overall (preliminary) conclusions (1) <ul><li>Time/maturity </li></ul><ul><li>Before 2000, biobanking wasn’t really recognized as a concept </li></ul><ul><li>The time it takes before a biobank becomes fully operational is decreasing (speed increases) </li></ul><ul><li>Networking </li></ul><ul><li>There is a tendency towards bigger, international networks, and therefore bigger collections/number of samples </li></ul><ul><ul><li>From the SNA, you can see that the core BBMRI members already had a central position in FP5 </li></ul></ul><ul><ul><li>In FP6 you can see a boost in biobanking activities by the number of projects and number of institutions involved: periphery is growing </li></ul></ul><ul><ul><li>From FP6 SNA, you can see that there are still a considerable number of institutions involved in biobanking that need to be included in BBMRI </li></ul></ul>
    14. 14. Overall (preliminary) conclusions (2) <ul><li>Organisation </li></ul><ul><li>All biobanks display elements of research, networking and infrastructure; </li></ul><ul><ul><li>Research is an ‘early’ activity, </li></ul></ul><ul><ul><li>Networking and infrastructure need time to establish </li></ul></ul><ul><ul><li>Networks, as a ‘soft’ infrastructure, are designed to connect distributed repositories </li></ul></ul><ul><ul><li>4 of the central repositories have evolved into mature, ‘hard’ infrastructures </li></ul></ul><ul><li>Distribution is related to the issue of access </li></ul><ul><ul><li>The fact that half the cases don’t know how many samples are transferred, can be taken as a sign of internal orientation - are they really opening up? </li></ul></ul><ul><ul><li>When we find carefully managed distribution strategies, we can link it to funding cultures </li></ul></ul>
    15. 15. Overall (preliminary) conclusions (3) <ul><li>Funding </li></ul><ul><li>You need at least one funding period to build a biobank </li></ul><ul><li>In the transition from research to infrastructure, the funders should address the issue of funding maintenance of infrastructure </li></ul><ul><li>Funding mechanisms in Europe are not suitable for maintenance of biobanks </li></ul><ul><li>Outreach </li></ul><ul><li>In general, the external activities are not overwhelming; biobanks are usually more geared towards research or operational affairs, rather than towards socio-economic engagement </li></ul><ul><li>Having said that, outreach activities are particularly noticeable in some types of biobanks </li></ul><ul><ul><li>Population based biobanks > society </li></ul></ul><ul><ul><li>Case control biobanks > industry </li></ul></ul><ul><ul><li>Rare disease oriented biobanks > society </li></ul></ul><ul><ul><li>Immature or young biobanks > little external activities as yet </li></ul></ul>
    16. 16. Indicator development <ul><li>Short term outputs - internal and operational side of biobanks/BBMRI </li></ul><ul><ul><li>Quality management procedures, IT infrastructures, ELSI procedures, User access agreements, Search engines, Common tools and services </li></ul></ul><ul><ul><li>Adoption of ERI concept </li></ul></ul><ul><li>Middle term outcomes - establishment of hard infrastructure/networks, </li></ul><ul><ul><li>Increased availability of samples; increased research collaboration; increased use of biobanks and the payment of fees related to this use; </li></ul></ul><ul><ul><li>ERI contracts </li></ul></ul><ul><ul><li>Start of outreach activities to comply with external strategy </li></ul></ul>
    17. 17. Indicator development <ul><li>Long term impacts - sustainable funding/adequate business model </li></ul><ul><ul><li>Medical applications in diagnostics, biomarkers, drugs, and the economic and health benefits of these applications, including new therapies, new diagnostics, personalized medicine: </li></ul></ul><ul><ul><li>Outreach activities to the appropriate professionals, patients and policy makers </li></ul></ul><ul><ul><li>Long term collaborations with industry; New Life Sciences companies providing biobank related services </li></ul></ul><ul><li>Contextual impacts - not so easy to make them explicit: you only miss them when you don’t do it </li></ul><ul><ul><li>Sustainable savings in the execution of biomedical research - funders </li></ul></ul><ul><ul><li>Increased speed in building networks - USA </li></ul></ul><ul><ul><li>A clear governance structure without which it isn’t possible to comply with future regulatory and technological frameworks </li></ul></ul>
    18. 18. Thank you <ul><li>Pauline Mattsson </li></ul><ul><li>Ingeborg Meijer </li></ul><ul><li>Jordi Molas Gallart </li></ul><ul><li>Anke Nooyen </li></ul>Technopolis Group has offices in Amsterdam, Ankara, Brighton, Brussels, Paris, Stockholm, Tallinn and Vienna.