Aarno Palotie, M.D., Ph.D.

Transcription

1 Aarno Palotie, M.D., Ph.D. 1

2 Genetics and big data

3 The technology drives the change

4 Need of large samples EACH GENE VARIANT HAS A SMALL EFFECT

5 The challenge: we can write down genomes, but we don t yet know how to read them 5

6 To learn, we must compare 6 vs vs Cancer vs Normal

7 Large data collections - biobanks 7

8 Need for large data sets Projects become large Data production will be centralized Projects become expensive (needed funds and traditional funding do not meet) The structure of funding changes

9 The structure and tradition of funding changes 9

10 Need for large data sets Projects become large Data production will be centralized Philantropy Industry Projects become expensive The structure of funding changes The structure of academia changes

11 Philantropy Larger sample sizes are needed to uncover the complexity of mental healt Stanley Center invests in large collections globally: Finland ( psychotics in three years) Mexico Japan China Africa

12 12 SUPER Kaisla Joutsenniemi Markku Lähteenvuo Jaana Suvisaari Jouko Lönnqvist

13 Stanley Center supported global collections, present China S. Africa Japan Kenya Psychosis Mexico Finland Uganda Ethiopia Sweden Controls Neurodevelopmental disorders Parents and controls UK Australia

14 SUPER-study Covering the total geographical area of Finland Goal to collect (11 000) cases with diagnosis of psychosis during

15 Current collection 9150 cases collected DNA from all (except about 40, lost in the mail etc) Cells from 4802 cases for ips production, August: December 2016 December 2017 December 2018

16 Regional organization Over 400 permits or contracts needed Regional coordinator: One young psychiatrist in each region Research nurses: 2-4 nurses in each area There is more granularity

17 FinnGen 17

18 + + + POPULATION ISOLATE HEALTH REGISTERS BIOBANKS GENOME DATA INNOVATIVE STUDY DESIGNS YOUR T E S T B E D F O R N E X T G E N E R A T I O N R E S E A R C H & I N N O V A T I O N

19 Moving from single time point case collections to a comprehensive view of health and disease Cross-sectional investigation in a diabetes study: diabetes & short stature Medical Birth Register Register of Prescription Medicines National Health Register diagnoses / procedures (ICD codes) Causes of Death Register Cancer Register Linkage with person numbers to: Clinical Laboratory databases via Biobanks The Nationwide electronic registers provide a unique possibility for data mining Reconstruction of major life-time events instead of a single-point snapshot YOUR T E S T B E D F O R N E X T G E N E R A T I O N R E S E A R C H & I N N O V A T I O N

20 YOUR T E S T B E D F O R N E X T G E N E R A T I O N R E S E A R C H & I N N O V A T I O N

21 Government backing National Genome Strategy The Biobank act Secondary usage of register data National Genome Center 21

22 FinnGenin aims at: better understanding of disease mechanisms 22 This is a prerequisite for next steps

23 FinnGen Academic research Industry +

24 GENOME DATA THE 200K Genome wide genotype data Genome or exome sequences > FINNGEN-PROJECT SISU-PROJECT SEQUENCING INITIATIVE SUOMI (FINLAND) 500K NATIONAL BIOBANK IMPUTATION individuals 4% of the population 10% Population cohorts Extensive health, phenotype, metabolomic data Disease specific collections POPULATION SPECIFIC CHIP/GENOTYPING REFERENCE DATABASE

25 Finns ~1O % of the 25 Legacy collections: population Prospective collections:

26 Prospective collections Hospital biobanks Legacy collections Individuals DNA Health register data Epidemiological cohorts (Finrisk, H2000, Generisk) Disease collections: Diabetes, Botnia Migraine Schizophrenia (SUPER)

27 National registers Hospital discharge Hospital procedure Outpatient visit Outpatient procedure Primary care All data harmonized Primary care procedure Interconnected by the 11 digit person number Cancer register Cause of death Drug purchase Drug reimbursement Register data for administration Register data for administration Register data for administration 27

28 Population samples (THL) 28 GWA genotypes Imputation individuals Combined genotype and register data National register data (HILMO, KELA etc) Hospital biobank samples Blood Service s biobank Association analyses

29 FinnGen partners 29

30 Funding 30 TEKES 20 M PHARMACEUTICAL INDUSTRY 39 M (7 GLOBAL COMPANIES) 59M HOSPITAL DISTRICTS AND THL DONATE DOZENS OF MAN-YEARS OF LABOR INPUT BY COLLECTING SAMPLES THE INPUT OF FINNISH UNIVERSITIES AND THL THE INPUT OF FINNISH COMPANIES

31 Data freezes in increments, every 6 months 31 Strict timelines Strict deliverables and milestones Milestone payments Project tightly controlled by partners

32 Building Finnish National Health Registers Epidemiological studies

33 Why Finland? Unique genetic ancestry Biobanks 33 Comprehensive high-quality health care system National health registers FINLAND Highly educated experts Government support TRANSFORMATION OF PHARMACEUTICALS PERSONALIZED MEDICINE

34 Building Finnish National Health Registers Epidemiological studies SISu project

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36 GENOME DATA THE 200K Genome wide genotype data Genome or exome sequences > FINNGEN-PROJECT SISU-PROJECT SEQUENCING INITIATIVE SUOMI (FINLAND) 500K NATIONAL BIOBANK IMPUTATION individuals 4% of the population 10% Population cohorts Extensive health, phenotype, metabolomic data Disease specific collections POPULATION SPECIFIC CHIP/GENOTYPING REFERENCE DATABASE

37 Building Finnish National Health Registers Epidemiological studies SISu project First TEKES application Biobank act

38 Building the FinnGen case Key aspect was the enthusiasm and trust of the Broad community in case Finland Early meetings with pharma in Boston Many of the key pharma representatives had previously worked at Broad and/or Sanger The key was to build a story why to invest in Finland 38

39 Building Finnish National Health Registers Epidemiological studies SISu project First TEKES application Biobank act IPHG project

40 PHARMA R&D SPEND 40 Modified from: USFDA, PhRMA

41 IPHG poistogeenisiä ihmisiä Luonnon omia malleja

42 The IPHG was an important pilot Provided the industry a use case: What type of research projects can be developed On what terms What data can be provided, what not Gave confidence that in Finland we deliver what we promis 42 It also became evident that the study had a too small sample(about individuals), more is needed.

43 Building Finnish National Health Registers Epidemiological studies SISu project First TEKES application Biobank act IPHG project Industry site-visit to Finland

44 44

45 Initiation of FinnGen preparation Merck/MSD and Biogen were very active in promoting a potential research collaboration: site-visit in June 2015 Pfizer site-visit in August 2015 Merck/MSD (Robert Plenge, now Celgene) contacted 14 key people in 14 companies who could influence their company from inside Numerous discussions with biobanks, THL and other interest parties We set goals: achieve a collection of individuals with a budget around 50 million), duration 4-5 years Initiated a plan that would include four companies 45

46 Towards a FinnGen project plan The model of four industry partners did not fly. Companies were not willing invest so much in one basket. Key decision: the budget needs to be around 1million/year/partner Merck organized a F2F meeting in Boston for potentially interested parties (April 2016) Contract negotiations were intiated with seven pharma partners, biobanks and TEKES in June 2016 A due-diligence organisation was established 46

47 Building Finnish National Health Registers Epidemiological studies SISu project First TEKES application Biobank act IPHG project Industry site-visit to Finland Due-diligence phase

48 Due-diligence phase It was agreed that University of Helsinki will be a coordinator of the project. Other alterantive: THL Organisation, which has a scientific, administration ja BD&L committee All potential parties included (nationally and internationally) UH lawyer drafted the consortium agreement Weekly phone calls, intensive F2F meetings In January contract negotiations were initiated, potential parties have to announce: in or out One pharma stepped out, one new joined 48

49 Finnish public parties: TEKES/Business Finland: Application filed in fall 2016, decision late 2016 TEKES funding started January The project was presented to ministries, the national biobank steering group, the Ombudsman and to the steering group of the health sector growth strategy in several ocassions Approval from the ethical committee in spring 2017 The process with the Ombudsman was initiated in fall 2016, we still have no statement 49

50 Communication A communication strategy was developed with the Finnish Kaufmann 50 Agency and the partners Aiming at transparency and broad coverage Communication challenges: The consent is given for biobank research, not specifically for the FinnGen project Press coverage mostly positive. Unfortunately the critical writing has not represented high degree knowledge about the subject.

51 Data access, security and privacy 51

52 What was most challenging during the preparation Hard to explain what Finnish/Nordic health registers mean What study designs can this support, what not How is personal data handled (all understood the restrictions) Convince that Finns deliver what they promise. As always, formulating the clause how a partner can get out from the contract Liabilities (all companies have their own regulations) Cautiousness of some Finnish biobanks Passivity of data protection and data security experts 52

53 Building Finnish National Health Registers Epidemiological studies SISu project First TEKES application Biobank act IPHG project Industry site-visit to Finland Due-diligence phase Signing and starting the project

54 54 The University has been very helpful But, nothing is perfect

55 Challenges in the current support within the University The legal team is overloaded, they work very, very hard but there are 55 too many small things that load the pipeline -> preparing small subcontracts, MTAs, DPAs and contracts with new parties can take over 6 months Procurements very slow, the development of the IT system had to be stalled for 7 months The YPA system is not an optimal solution from the scientists perspective. We would need administrative support who reports directly to the PI/unit director Strong administrative support is needed on site

56 Accumulation of new biobank samples by end of July 2018 Altogether 92,000+ samples available at Finnish biobanks Genotype and phenotype data from participants available for analysis Oct 2017 Nov 2017 Dec 2017 Jan 2018Feb 2018 Mar 2018 Apr 2018 May 2018 June 2018 July 2018

57 International interest 57 Potential for new industrial partners FinnGen and/or its components have provided templates for emerging large scale genomic health projects

58 However: The administrative flow of authorities is extremely slow (this concerns all projects): The administrative transfer of existing samples to the biobank takes a year Some registers have increased their bureaucracy implementing very ancient procedures Some registers are extremely slow (takes over a year to evaluate the application) We have waited for the Ombudsman s statement for 20 months Different authorities interpret the legal framework differently not optimal 58

59 Potential new legislation 59 Secondary usage of register data Updated biobank law Genome center Implementation has to be clear and uniform Authorities need to have a consensus

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