Meeting Report National Initiatives: Opportunities for Knowledge Exchange & Collaboration Wednesday, May 24th, 2017 – Wellcome Trust (London, UK) Co-hosted by Genomics England and Australian Genomics

Table of Contents

National Initiatives, International Opportunities 3 ​ Presentations from National Initiatives 4 ​ Current UK Plans 5 ​ Data Breakout Workshop Report 6 ​ Regulatory Breakout Workshop Report 7 ​ Clinical & Education Breakout Workshop Report 9 ​ Data-sharing: Opportunities and Challenges 11 ​ Summary & Next Steps 13 ​ Appendix I: Meeting Agenda 14 ​ Appendix II: Meeting Attendees 15 ​

National Initiatives, International Opportunities

Three years after the launch of the Global Alliance for Genomics and Health (GA4GH) and six months after the first GA4GH-hosted convention of national genomics initiatives, Kathryn North (Australian ​ Genomics) and Mark Caulfield (Genomics England) convened representatives from 13 National ​ Initiatives in genomic data collection to discuss areas of potential collaboration.

North provided an overview of recent GA4GH strategic planning efforts, which aim to identify best standards for implementing genomics in clinical practice. “An important part of GA4GH is how the tools and standards that are being developed get used,” she said, pointing out the important role of National Initiatives in helping define those tools. An important outcome of that work, North said, was a renewed focus on engaging partners—including big genomic sequencing initiatives as well as National Initiatives like those in the room—in order to avoid duplication of efforts across multiple countries or the collection of clinical genomic data that are not shareable or interoperable.

The goal of the meeting was to identify potential areas of collaboration and resource/expertise sharing, as well as common needs across National Initiatives that GA4GH can incorporate into its “toolbox” of data sharing standards and tools. North also promoted the concept of a “TripAdvisor for Genomics,” wherein National Initiatives will be able to learn from one another about positive and negative experiences, suggest best practices to others, and work to iteratively improve the tools they develop and use. For instance, she noted that developing an informed consent that adequately takes into account the needs of indigenous populations and cultural sensitivities is relevant across all National Initiatives. She also noted that diagnostic evidence can be transferable across nations, and need only be customized according to local healthcare costs to be immediately locally relevant.

Going forward, North said that efforts to convene National Initiatives, such as the present meeting and a recent meeting of the Global Genomic Medicine Collaborative (G2MC), will be better aligned and result in at least one annual conference to continue the conversation and work toward aligning National Initiatives to ensure interoperable, shareable clinical and genomic data.

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Presentations from National Initiatives

For more details on each of the following, see the Program Booklet released prior to the meeting. ​ ​

Australia | Slides ​ Kathryn North (Australian Genomics)

Brazil | Slides ​ Benilton Carvalho (UNICAMP – BIPMed)

Canada | Slides ​ Marc LePage (Genome Canada)

Finland | Slides ​ Markus Perola (National Institute for Health and Welfare, Finland)

GenomeAsia 100K | Slides ​ Lakshmi Santhosh (GenomeAsia 100k)

Global Gene Corp (India) | Slides ​ Paul Jones (Global Gene Corp)

Netherlands | Slides | Video ​ ​ ​ Gerrit Meijer (Netherlands Cancer Institute)

Qatar | Slides ​ Said Ismail (Qatar Genome Programme)

South Africa | Slides ​ Nicola Mulder (University of Cape Town)

Switzerland | Slides ​ Torsten Schwede (SIB Swiss Institute of Bioinformatics) ​ Turkey | Slides ​ Osman Ugur Sezerman (Acibadem University)

United States of America | Slides ​ David Glazer (Verily), Teri Manolio (NHGRI/NIH), and Heidi Rehm (Harvard Medical School; The Broad Institute)

United Kingdom | Slides ​ Mark Caulfield (Genomics England; Queen Mary, University of London)

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Current UK Plans

Sir John Chisholm, executive chair of the Genomics England Board, spoke on his vision for genomic ​ ​ research. “We are all engaged in the most significant program of the human race in the 21st century,” he said. “If we’re successful, we’ll change the human experience from what it had been throughout history and evolution—that health is something which gets done to you by some force outside of you—to something you have control over.” This change is possible because we will soon be able to understand the genome, and to use it to predict outcomes. “It’s a fantastic vision, but it’s very hard and it will take most of rest of the century to get there,” said Chisholm. He cited two challenges in particular:

1) Genomic medicine involves “colossal” amounts—millions, tens of millions, or even 100s of millions—of data points. This scale is necessary because of the low probability of making connections between the genome and human health. Additionally, because very few associations are monogenic, combinatorial problems make unpacking the genome a very difficult and complex pursuit. In the past, scientific programs have built individual research cohorts for each study. This will not work with clinical genomic research, because no organization has enough money to fund research cohorts at this scale. The only way to achieve cohorts of the size needed is by aligning fully consented patient data from the healthcare system with genomic data. No one country will be able to do this alone so national programs must collaborate.

2) Given that no one country can do it alone, nations must agree on rigorous standards and protocols, as artifacts of non-harmonized data collection processes will make it impossible to understand outcomes across a combined data set.

Implementing standards and protocols in routine healthcare will be difficult, Chisholm said, “but it’s something where the prize is so great, it’s worth doing.” In the four years since it was launched, Genomics England has spent considerable effort and made progress on the development of standards and protocols for data collection and getting them implemented across the UK’s National Health System. Now, he said, that needs to be taken to the international stage. He invited meeting attendees to “form a club” to work together to agree on standards and protocols for clinical genomic data sharing. This will allow for federated data sharing that is protective of participant confidentiality and privacy and enables “this transformation of the human experience in the 21st century.”

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Data Breakout Workshop Report

Discussion Aim 1: Establish a comprehensive set of use cases/scenarios for a genome-phenome database ​ ● Genome/phenome association databases should allow hypothesis free discovery. Need to map across disparate data models to enable interoperability. ● Other types of databases: ○ Gene/variant databases (e.g., ClinGen, CIViC) that store relationships with particular disorders and various levels of evidence from existing databases. ○ Databases of findings (e.g., DECIPHER, NSIGHT). These vary from a simple spreadsheet to sophisticated softwares. Harmonization would have immediate clinical impact. ■ GA4GH can help scope areas in need of new standards, (i.e., database of findings). National Initiatives can be a user group to guide development of and test standards through implementation. ■ National Initiatives need to come together to form a “club” to discuss many things, one of which is standards. GA4GH and G2MC are obvious partners in that part of the discussion. There needs to be a structure for coming to consensus and then accessing the agreements that have been made.

Aim 2: Establish a list of all large-scale population genomics projects internationally ​ ● How many genomes are accessible? Few relative to the number of genomes sequenced. ​ ​ Aim 3: Survey activity of genome/phenome data sharing and map impediments to sharing ​ ● Philosophical reasons academics and clinicians don’t share, but also technical challenges. E.g., majority of genomes sequenced aren’t in a database at all. Also, no standards for sharing, so people don’t feel empowered to do so responsibly. ● What types of data are we missing in the conversation? ○ Clinical, panels, arrays, and exome data are also relevant for patient. ○ Data that don’t exist in a shareable format (e.g, genomes in hard drive; non-digitized data in clinical records). ● Need to incentivize clinicians to share, possibly by returning details about discoveries as a result. Need epidemiologists to help identify gaps in data that are collected. ● Academic reward system does not incentivize sharing in biomedical disciplines. Demonstrations of clinical impact to reinforce a virtuous cycle will naturally alleviate the problem in time. ● Key insights will come from healthcare and large-cohort research studies.

Actions ● Web-based catalogue of real world genome/phenome database use cases, including underlying technology set and how the databases are used. Goal: to track whether technologies being ​ ​ developed are fit for purpose. Use HQL query for analytics. ● Catalogue of National Initiatives’ challenges, strategies, technologies, and data sharing status. ● Measure regular constructive access to and use of data being produced and shared.

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Regulatory Breakout Workshop Report Discussion ● Data sharing motivated by benefit to human health; no country has enough data. ● GWAS data sharing was generally helpful if imperfect. Must make new processes better by making it easier to share data, reducing bureaucratic and technical barriers to legitimate data access. ● GA4GH has many policy documents/guidelines; RECs, IRBs need to understand principles/ethos. An education programme may be useful. ● Funders of research and health care can and do encourage good data management, including ​ appropriate sharing, via e.g. grant conditions and REC/IRB conditions. ​ ● National Initiatives should share good/bad experiences, successes/failures. ● Need to engage regulators, lab accreditors, etc, ensure data sharing principles built in at start. Crucially, this should begin to include healthcare players as well as research organisations. ● Australian Genomics is developing an evaluation framework to justify genetic testing efficacy/payoff. Standards developed in Australia will be shared. ● Focus on changing culture rather than legislation, former will be more effective. ● Need to bring in the experience of clinicians more familiar with data sharing and sequencing, such as those who work on outbreaks and patterns of disease. ● Social science surveys (e.g., Your DNA Your Say) demonstrate that when public understands the ​ ​ aims of genomic research and the necessity to participate, they become more comfortable about participating and sharing data. ● If decision makers understand what patients and public think, they may be more comfortable allowing/encouraging data sharing; Genomics England patients more keen to see data shared than regulators, want to see process simplified. ● Be transparent in initial conversation with policymakers, see Qatar example. ● National Initiatives have health AND wealth agendas, role of commercial companies needs clarity. ● Cancer, rare disease communities have different attitudes; some more altruistic, engaged. ● Need to be honest with patients, funders, and policymakers: some short term gains, but work in complex disease, cancer, etc, is long term and will require major international effort. ● GA4GH role: setting standards. Requires convening community to share experiences and identify commonalities across contexts in order to create common standards that work for all, otherwise risk duplicative, unnecessary work.

Actions ● National Initiatives to share data access processes, consent forms, and criteria, [GA4GH?] volunteer group to compare for unneeded heterogeneity, common features that represent best practice to allow global data sharing. ● Review local initiatives’ social science research activities assessing public perceptions to identify strategies for engaging/educating public, encouraging adoption.

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● A new Public Engagement initiative in the UK will focus specifically on genomics (funded by WT) with the Wellcome Genome Campus Pub Eng team leading. They can helpfully add to discussions about what activities are underway.

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Clinical & Education Breakout Workshop Report

Phenotype data capture ● Core dataset components for interpretation: minimal optimal clinical dataset needed to interpret genome sequence, demographics, agreed-upon coding systems (HPO for rare disease, others for cancer, etc), pedigree, disease status. ● Need to engage clinicians to ensure initial data capture allows for future research/other use. This requires a better understanding of the clinical questions needed for interpretation. ● Gatekeeping sits at test requisition, sometimes with clinician, need to authorize for other contexts/labs/analyses at start. Action: ​ ● Minimal optimal clinical dataset for a range of rare diseases (Australian Genomics will share current flagship data). ● Share and catalogue data models, to define core elements (data captured, tools used) and identify a standard.

Interpretation ● How do we standardize and inform genomic data interpretation? ● In many cases, initial lab interpretation will not be last; how can we support a best practice of sharing information globally so all can see evolution of their variants over time? Publicly share/crowdsource variant interpretations, compare quality/support knowledge evolution. ● Breakout group noted most of discussion focused on rare disease, and more consideration is needed across all domains. GA4GH is planning future meetings focused on rare disease, common disease, cancer, basic biology, respectively. Actions: ​ ● Define tools supporting best practices (e.g., uses professional standards for variant interpretation [ACMG guidelines], supports common data model for defining variant, allows sharing with minimal resources). ● GA4GH to build/endorse common data model for variant annotation, phenotype data capture (e.g., Variant Modeling Consortium, Variant Annotation Task Team); involves ClinGen and Monarch SEPIO models, to define variants and their annotations, evidence, assertions. ● Define best practices for supporting interpretation by multidisciplinary teams to allow optimal engagement of lab and clinicians to interpret genetic/genomic data, educate workforce. ● National Initiatives to share genetic/genomic report formats to aid in clinician consumption of interpretation. Identify exemplars to allow us to learn from each other and gradually improve.

Education & Workforce Training Actions: ​ ● Catalogue of activities (e.g., award/non-award courses, continuing professional development, webinars, etc.), including details on development approaches/strategies of some. ● Share Australian Genomics workforce training program evaluation framework, tailored for global community.

Health Economics ● Major discrepancies between health systems/payers’ priorities around technology use (incl. sequencing) influence which areas decision makers pay attention to. ● Health economics arguments vary across regions.

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● Difficult to untangle healthcare costs from non-healthcare costs, cost of activity vs. cost reimbursed. ● Which data to include and how to weigh, (e.g., patient outcomes, family empowerment, reproductive, quality of life outcomes, mortality/morbidity, etc.); needs standardization.

Action: ​ ● National Initiatives to share approaches for building health economics arguments to support use of genomic sequencing in health care.

Discussion HPO is a major improvement over past approaches, but is it too early to commit to one coding method? Concern that future approaches will need to be more quantitative and not based on HPO alone in some circumstances. ● Genomics England using HPO in conjunction with SNOMED-CT and bespoke coding system for some, currently unmapped, quantitative features. ● Requires ongoing mapping exercise to ensure continuity between all ontologies (Peter Robinson, Melissa Haendel working on this for cancer, in partnership with NCI Thesaurus). ● Each system developed for a different purpose, requires international effort to map across them to allow for cross-communication and to fill gaps; eventually should land on a hybrid that fits all use cases.

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Data-sharing: Opportunities and Challenges

Peter Goodhand (Ontario Institute for Cancer Research) chaired a panel discussion focused on sharing data across National Initiatives, which invited perspectives from four veterans in the genomic data sharing space. As executive director for the Global Alliance for Genomics and Health (GA4GH), he noted that the organization is undergoing a strategic planning effort that will invite projects like those in the room to help drive its future work to ensure GA4GH standards tightly align with the needs of the community. Each panelist gave a brief introduction, followed by a discussion session with the audience.

GA4GH steering committee chair Ewan Birney (EMBL-EBI) said that the broad collection of health care ​ data means humans are now better studied than any model organism in history, representing an enormous opportunity for learning across basic biology and human health. As genome projects around the world spring up, we need to begin operationalizing the agreement to share data to ensure no cures or discoveries are lost, he said. GA4GH aims to create the global standards needed to make that feasible and to enable health care systems around the world to effectively use genomic data for broader learning.

Paul Flicek (EMBL-EBI) gave a brief history of EMBL-EBI, which began ~30 years ago as a data library ​ managed by one person and has since grown to employ more than 650 people focused on supporting advances in biology through storage and interpretation of biomolecular data. Over the last decade, sharing individual-level genomic data has gone from “impossible to really really hard.” As co-chair of the GA4GH Security Working Group and leader of several data resources at at EMBL-EBI, Flicek’s goal is to “give things away as easily and as quickly as possible.” This requires a systemic focus on security. The details of generating, using, and processing large amounts of data require significant resources, he said. The academic community has recognized the value of sharing data for decades; while the problem is old, the community is beginning to tackle it with new, more effective solutions every day.

Three years ago, Teri Manolio (NHGRI) helped launch the Global Genomic Medicine Collaborative ​ ​ (G2MC) to identify innovative approaches for implementing genomic medicine across the spectrum of ​ healthcare systems, including low- and middle-income countries as well as some of the world’s largest ​ and most complex health care systems. G2MC partners are applying genomic medicine in a diverse ​ global environment and are launching pilot programs to test new approaches to the collection and analysis of genomic data. While many are still reluctant to share data, G2MC partners are sharing models across national boundaries. These include innovative, creative implementation strategies such as the Thai pharmacogenomics card to prevent Stevens Johnson Syndrome. Return of results is a focus for these groups, but current legislation often restricts such activity in the clinical environment.

Heidi Rehm (Broad Institute) leads the Clinical Genome Resource and co-leads two GA4GH ​ demonstration projects, Matchmaker Exchange (MME) and BRCA Exchange. To overcome the most difficult barriers to sharing data—which are mainly social—groups need to focus on demonstrating utility to the broader community. MME demonstrates with mathematical clarity how sharing is necessary to solve rare diseases by connecting just two patients. In the case of sharing variant interpretation data, the community needs to point to improved patient outcomes and diagnoses. The promises of better science and better healthcare alone don’t mean people will share data; it takes enormous resources and widespread agreement on tools and approaches (a focus of GA4GH). In order to bring groups on board who recognize the value of sharing but have not yet prioritized it, incentivization may include withholding

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funding, publication, reimbursement, or accreditation until data are shared. Finally, sharing data does not itself lead to benefit. It must be easy, accessible, and useable before the community participates.

Discussion Describe the disparate needs and priorities across the broad spectrum of data sharing stakeholders, from patients to commercial companies. ● Among those who object to data sharing, the first reluctance is often U.S. government use, second is commercial use. ● Data sharing standards must enable fair and equitable practices that allow many stakeholders to participate. ● It is as important for companies to participate as it is for academics. Best practice should protect against any exploitation of private equity. Commercial entities help power research, and must therefore be empowered themselves to participate. ● Many groups work closely with private companies, and trying to police that activity would be very difficult. In an ideal world, such partnerships would be motivated by the good of the people, not just commercial purposes. ● The two-way contract between individuals and their healthcare system looks different in each country, and we cannot assume that the structures we are familiar with in our own system will exist elsewhere. Patient education and engagement are critical. ● Many institutions believe they cannot share data because they need to protect patient privacy, but it is often in a patient's best interest to help them share their data if it will speed diagnosis and ​ ​ effective treatment. GA4GH has focused on the individual right to participate in data sharing. ​ ​ ​ ● It is important to engage with data sharing skeptics. Most arguments against sharing are focused on losing control, which means different things to different people in different national contexts.

Why don’t people upload to ClinVar? How it can be promoted more? ● Potential uploaders have limited resources and time. We need to make it easy and low resource for labs to upload, and to get reimbursed for doing so. National and commercial entities could set aside resources for doing this. ● Some entities fundamentally object to sharing intellectual property while some don’t want to the public to see potentially poor quality work. When labs share data, they inevitably find things they’ve missed. We all have to be honest and open, no one is perfect. ● Agencies won’t accredit a clinical lab unless they do certain things. Perhaps sharing should be one of those things.

What is GA4GH’s role in sharing clinical interpretation data? ● GA4GH is a standards organization, which means file formats but also best practice, policy harmonization, and implementation standards. ● GA4GH can help promote concrete examples of data sharing successes, which are as important as the philosophical motivation to share (e.g., rare disease, pediatric WES) ● Understanding the somatic cancer genome requires many genomes, more resources. The cancer system is unique in different locations, it is taking longer to share in this domain than in rare disease.

Is there a role for IP and where?

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● This is a very significant hurdle, with an endless series of bilateral agreements (e.g., where is IP designed, who keeps it, how does it mix, etc). Tackling these challenges is expensive and complicated by disparate national laws. ● For specifically defined queries, IP is more clear; for large-scale, open-ended data sharing, where exploration is necessary, we need a widely agreed-upon framework that defines where IP starts, and what is precompetitive (e.g., association data). This framework should be guided by the best interests of the human population. ● Standards require very open IP. A pooled environment of IP solutions would be valuable. In some cases it is important for tools not to be protected, as doing so could limit the ecosystem. ● Myriad’s IP disappeared when gene patents were ruled invalid, now to claim hold on market, they assert they have more data and experience, and are the only organization capable of providing an accurate interpretation. There is a valid argument there: Myriad has spent significant resources, and it is not straightforward to say they must release all of that experience. ● Rehm’s lab used to hold the market’s share of knowledge on EGFR and cardiomyopathy, but due to a belief that patients are worse off unless data are joined together, that knowledge is now in the public domain. ● Many publicly available, free databases used for interpretation have complicated IP associated with them. The process to legally collect all publicly available data is far more complex than we initially realized. Publicly available data collections do violate licenses.

Can we achieve international concordance in the insurance space (particularly life insurance)? How can we bring down barriers to individuals participating in genomic studies due to a fear of life insurance discrimination (aka “underwriting”)? ● Insurance companies are poised to do this the moment they perceive it is to their financial benefit. ● Need to prepare the ground beforehand, define underwriters’ and insurers’ allowed maneuvers. ● Societies will have a strong voice in this, as the debate is wrapped up in cultural understandings of life insurance as either an entitlement or a commercial product. ● In the UK, insurance is tied to mortgage so it is seen as an entitlement. In the US and some Asian countries, it is seen as a commercial product.

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Summary & Next Steps In closing remarks, Mark Caulfield said that the groups present must showcase their achievements to ​ patients and the public in order to promote further involvement from those communities. Doing so, he said will result in “more ‘Denmarks’ and less places where we lock data away.” In that spirit, he noted that an upcoming report will highlight successes of Genomics England. He also cited several high level themes from the meeting:

● In three years, the discussion has moved from a focus on future goals to examples of established infrastructure and large-scale genomic data collection in health care systems around the world ● The next step is to position healthcare against research in order to achieve the needed scale, and to move from cohorts of 1 million individuals to 5 or 10 million thanks to shared data across the globe ● This will require an ethical framework and robust guidelines for follow up ● Initiatives must engage with patient advocacy and support groups since those populations are willing to take on challenges that researchers shirk from ● Industry is vital to this endeavor, as it requires millions (or billions) of dollars ● There is a need for robust IP that allows for freedom to operate, and the ability to account for situations where the responsible act is not to protect IP but to give it away

Kathryn North said that the meeting, as well as the goals set forth at the GA4GH strategic planning meeting, embody the notion that no single country can do it on their own. She said she expects this to be only the second in an ongoing series of meetings to keep National Initiatives engaged and communicating with one another. Finally, she identified a series of immediate and longer term next steps:

● National Initiatives encouraged to implement the tools and standards being developed by GA4GH, particularly code of conduct, ethics, consent standards ● Established initiatives should share their best practices across a range of experiences to assist emerging initiatives in getting started ● Several opportunities exist for easy collaboration, for example: ○ Pooling optimal minimal clinical data set to enable interpretation of the genome for specific disease groups ○ Sharing educational resources, including public engagement tools ○ Sharing experience with ethics and consent for indigenous/culturally sensitive populations ● Reference populations should be made freely available, as they represent an invaluable resource for interpreting data in the increasingly multicultural global setting ● Initiatives should work together on joint advocacy to engage governments and must advocate for inclusion of ‘prevention’ in government health budgets ● A white paper will be drafted to present the high level view of National Initiative activities around the globe

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Appendix I: Meeting Agenda

08:00 Registration (Wellcome Trust, front entrance)

08:30 Welcoming remarks [Mark Caulfield (Genomics England)] ​ ​ 08:40 National Initiatives, International Opportunities [Kathryn North (AGHA)] ​ 08:50 Updates from established National Initiatives [Chairs: Mark Caulfield & Kathryn North] ​ ● UK [Mark Caulfield (Genomics England)] ​ ● Australia [Kathryn North (AGHA)] ​ ● USA [David Glazer (Verily), Teri Manolio (U.S. NHGRI), Heidi Rehm (Harvard Medical School)] ​ ​ ​ ​ ​ ​ 10:15 Break 10:30 Updates from emerging National Initiatives [Chairs: Mark Caulfield & Kathryn North] ​ ● Brazil [Benilton Carvalho (UNICAMP – BIPMed)] ​ ​ ● Canada [Marc LePage (Genome Canada)] ​ ​ ● Finland [Markus Perola (National Institute for Health and Welfare, Finland)] ​ ● GenomeAsia 100K [Lakshmi Santhosh (GenomeAsia 100k)] ​ ​ ● India [Paul Jones (Global Gene Corp)] ​ ​ ● Netherlands [Gerrit Meijer (Netherlands Cancer Institute)] ​ ​ ● Qatar [Said Ismail (Qatar Genome Programme)] ​ ​ ● South Africa [Nicola Mulder (University of Cape Town, H3Africa)] ​ ● Switzerland [Torsten Schwede (SIB Swiss Institute of Bioinformatics)] ​ ● Turkey [Ugur Sezerman (Acibadem University)] ​ ​ 12:25 Current UK Plans [Sir John Chisholm (Genomics England)] ​ 12:35 Lunch 13:30 Breakout Workshops 1. Data Track [Chairs: Marcel Dinger (AGHA) & Augusto Rendon (Genomics England)] ​ ​ 2. Regulatory Track [Chairs: Martin Bobrow (Emeritus Fellow, University of Cambridge) & Anna ​ Middleton (Head of Society and Ethics Research, Wellcome Genome Campus)] 3. Clinical & Education Track [Chairs: Sue Hill (NHS England), Sylvia Metcalfe (AGHA), Heidi ​ Rehm (Harvard Medical School) & Richard Scott (Genomics England)] 15:00 Presentations from Breakout Workshop Groups 16:00 Break 16:15 Data-sharing: Opportunities and Challenges [Chair: Peter Goodhand (GA4GH)] ​ ​ Panelists: Ewan Birney (EMBL-EBI), Paul Flicek (EMBL-EBI), Teri Manolio (U.S. NHGRI), Heidi Rehm (Harvard Medical School) 17:15 CLOSE: Summary & Next Steps [Mark Caulfield & Kathryn North] ​ ​ 17:30 Reception & Mixer (6th Floor, Wellcome Trust) ​

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Appendix II: Meeting Attendees

1. Nahla Afifi, Qatar Biobank, Qatar 2. Mark Bale, Department of Health / Genomics England, UK 3. Cindy Bell, Genome Canada, Canada 4. Ewan Birney, EMBL-EBI, UK 5. Martin Bobrow, Wolfson College, University of Cambridge, UK 6. Tiffany Boughtwood, Australian Genomics Health Alliance, Australia 7. Sarion Bowers, Wellcome Trust Sanger Institute, UK 8. Benilton Carvalho, UNICAMP - BIPMed, Brazil 9. Mark Caulfield, Genomics England, UK 10. John Christodoulou, Murdoch Childrens Research Institute, Australia 11. Miro Cupak, DNAstack, Canada 12. Marcel Dinger, Garvan Institute of Medical Research and Genome.One, Australia 13. Lena Dolman, Ontario Institute for Cancer Research and GA4GH, Canada 14. Audrey Duncanson, Wellcome Trust, UK 15. Marc Fiume, DNAstack, Canada 16. Paul Flicek, EMBL-EBI, UK 17. David Glazer, Verily, USA 18. Peter Goodhand, Ontario Institute for Cancer Research and GA4GH, Canada 19. Ian Green, SNOMED International, UK 20. Robert Green, Harvard Medical School, USA 21. Sean Grimmond, University of Melbourne Centre for Cancer Research, Australia 22. Charles Gutteridge, SNOMED International, UK 23. David Hansen, Australian Genomics Health Alliance, Australia 24. David Haussler, UC Santa Cruz Genomics Institute, University of California, Santa Cruz, USA 25. Sue Hill, NHS England, UK 26. Oliver Hofmann, University of Melbourne, Australia 27. Matt Hurles, Wellcome Trust Sanger Institute, UK 28. Diana Iglesais, Genome Quebec, Canada 29. Said Ismail, Qatar Genome Programme, Qatar 30. Sumit Jamuar, Global Gene Corp, Singapore 31. Paul Jones, Global Gene Corp, Singapore 32. Melissa Konopko, University of Maryland, Baltimore, USA 33. Ilkka Lappalainen, CSC/ELIXIR-FI, Finland 34. Marc Lepage, Genome Canada, Canada 35. Teri Manolio, NHGRI/NIH, USA 36. Gerrit Meijer, Netherlands Cancer Institute, Netherlands 37. Sylvia Metcalfe, Murdoch Childrens Research Institute and the University of Melbourne, Australia 38. Anna Middleton, Society and Ethics Research, Wellcome Genome Campus, UK 39. Nicola Mulder, University of Cape Town, South Africa 40. Kathryn North, Murdoch Children's Research Institute, Australia 41. Angela Page, Broad Institute and GA4GH, USA

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42. Markus Perola, National Institute for Health and Welfare, Finland 43. Gunnar Ratsch, ETH Zürich, Switzerland 44. Heidi Rehm, Harvard Medical School and The Broad Institute, USA 45. Augusto Rendon, Genomics England, UK 46. Lakshmi Santhosh, GenomeAsia 100K, India 47. Torsten Schwede, SIB Swiss Institute of Bioinformatics, Switzerland ​ 48. Serena Scollen, ELIXIR, UK 49. Anneke Seller, Health Education England, UK 50. Zornitza Stark, Victorian Clinical Genetics Services (VCGS), Australia 51. Osman Ugur Sezerman, Acibadem University, Turkey 52. Pascal Spothelfer, Genome BC, Canada 53. Adrian Thorogood, McGill University and GA4GH, Canada 54. Lisenka Vissers, Radboud University, Netherlands 55. Julia Wilson, The Wellcome Trust Sanger Institute, UK 56. Grant Wood, Intermountain Healthcare, USA

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