From Open Access, to Controlled, to Registered Access? Prof. Bartha M. Knoppers Canada Research Chair in Law and Medicine Chair of the GA4GH Regulatory and Ethics Working Group Dr. Stephanie O.M. Dyke Centre of Genomics and Policy McGill University GA4GH Project Liaison 1
Eric E. Schadt, The Changing Privacy Landscape in the Era of Big Data, Molecular Systems Biology 8, 612 (2012).
The Challenge Unparalleled genera:on of human gene:c data How do we unlock its poten:al? In a way that allows data to be shared on a global level Thus empowering new knowledge, new diagnos:cs and new therapeu:cs for pa:ents and popula:ons 3
The Challenge Data from millions of samples may be needed to achieve results and progress - showing paverns that would otherwise remain obscure. That will take new methods and organizaxonal models. Right now: Data is typically in silos: by type, by disease, by country, by insxtuxon Analysis methods are non- standardized, few at scale Approaches to regulaxon, consent and data sharing limit interoperability If we don t act: risk an overwhelming mass of fragmented data, such as electronic medical records in many countries 4
(GA4GH) Mission To accelerate progress in human health by helping to establish a common framework of harmonized approaches to enable effecxve and responsible sharing of genomic and clinical data, and by catalyzing data sharing projects that drive and demonstrate the value of data sharing 5
The Global Alliance will NOT directly: Generate or store data Perform research or care for paxents Interpret genomes Be exclusive to enxxes that have and share data 6
Organiza:onal Members 360+ 36 Global Alliance members include: 1. UniversiXes and research insxtutes (31%) 2. Academic medical centers and health systems (11%) 3. Disease advocacy organizaxons and paxent groups (5%) 4. ConsorXa and professional sociexes (7%) 5. Funders and agencies (6%) 6. Life science and informaxon technology companies (40%) Last Update: October 17, 2015 7
GA4GH Framework for Responsible Sharing of Genomic and Health- Related Data Current frameworks are founded on the principle of protecxon from harm. In contrast, GA4GH Framework aims to ac:vate the right to science and the right to recognixon for scienxfic producxon by promoxng responsible data sharing. hvp://genomicsandhealth.org/framework 8
Human Rights Founda:on Universal Declara:on of Human Rights, (1948) The Right to The Right to Science Recogni:on 27(1) 27(2) Everyone has the right freely to parxcipate in the cultural life of the community, to enjoy the arts and to share in scienxfic advancement and its benefits. Everyone has the right to the protecxon of the moral and material interests resulxng from any scienxfic, literary or arxsxc producxon of which he is the author. 9
Renewed Interest The right to science has acquired an increased importance in today s globalized world. (UNESCO, Venice Statement, (2009)). The scope, normaxve content and obligaxons of the State under the right to science, remain underdeveloped while scienxfic innovaxons are changing human existence in ways inconceivable a few decades ago. (UN Special Rapporteur, A/HRC/20/26 (2012)). 10
Content of the Right to Science 1. access by everyone without discriminaxon to the benefits of science and its applicaxons; 2. opportunixes for all to contribute to the scienxfic enterprise 3. the freedom indispensable for scienxfic research; 4. parxcipaxon of individuals and communixes in decision- making; 5. conservaxon, development and diffusion of science and technology. (UNESCO, Venice Statement 2009) 11
Right to Science = Access to Data American AssociaXon for the Advancement of Science (AAAS, 2010) 12
Framework for Responsible Sharing of Genomic and Health- Related Data Available in 11 languages on the GA4GH website. Thanks to all who contributed! Arabic Chinese French Greek Japanese Portuguese Spanish German Hindi Italian إطار لتبادل مسؤول للمعلومات اجلینومیة واملتصلة بالصحة 基 因 组 学 与 健 康 相 关 数 据 负 责 任 的 共 享 框 架 Cadre pour un partage responsable des données génomiques et des données de santé Πλαίσιο για την Υπεύθυνη Κοινοχρησία Γονιδιωματικών και άλλων Ιατρικών Δεδομένων ゲノム 及 び 健 康 関 連 データの 責 任 ある 共 有 に 関 する 枠 組 み Framework para ComparXlhamento Responsável de Dados Genômicos e Relacionados à Saúde Marco de actuación para el uso comparxdo responsable de datos genómicos y relaxvos a la salud Rahmenkonzept für die den verantwortungsvollen Datenaustausch genomischer und gesundheitsbezogener Daten Framework per la condivisione responsabile di dax genomici e relaxvi alla salute. 13
Framework for Responsible Sharing of Genomic and Health- Related Data Aims Foster responsible data sharing; Protect and promote the welfare, rights, and interests of groups and individuals who donate their data; Provide benchmarks for accountability; Establish a framework for greater internaxonal data sharing cooperaxon, collaboraxon, and good governance; and, Serve as a dynamic instrument. Founda:onal Principles Respect Individuals, Families and CommuniXes; Advance Research and ScienXfic Knowledge; Promote Health, Wellbeing and the Fair DistribuXon of Benefits; and, Foster Trust, Integrity and Reciprocity. 14
Framework for Responsible Sharing of Genomic and Health- Related Data Core Elements for Responsible Data Sharing Transparency Accountability Engagement Data Quality and Security Privacy, Data ProtecXon and ConfidenXality Risk- Benefit Analysis RecogniXon and AVribuXon Sustainability EducaXon and Training Accessibility and DisseminaXon 15
Strong protec:on in 3 cri:cal areas Contours of responsible access, sharing, and avribuxon delineated by other human rights: 1. privacy; 2. anx- discriminaxon and fair access; and 3. procedural fairness. 16
Consent (Open Data) 1000 Genomes Project [ ] Future researchers may use the samples to study many other quesxons, such as how genes and genexc variants affect the way genes work and the products that genes make (these are called gene expression or proteomic studies). Future researchers may also use both the samples and the scienxfic databases to study such quesxons as: the biology of DNA; how new variaxons arise; how the process of evoluxon works; the composixon and size of human groups; and how people from different parts of the world are related to each other. People who do idenxty tesxng, such as for paternity tesxng or law enforcement, may use the samples and the scienxfic databases to do general research about paverns of human genexc variaxon. [ ] ENCODE Project [ ] In order to take part, you must: [ ] be willing to have many researchers around the world study the data from the sample for a long Xme for any purpose [ ] 17
Consent (Open Data) HapMap Project [ ] The HapMap will show researchers where the haplotypes (paverns of genexc variaxon) are. Then, for a disease, such as diabetes, researchers will study the haplotypes in a group of people who have the disease, and in another group of people who do not. Areas in the DNA where the two groups differ in their haplotypes will be clues that those areas might contain genes that affect the disease. Researchers can then look for those genes and study how they work. This will help them figure out bever ways to prevent, diagnose, and treat the disease. They can also learn how to make drugs that work bever in more people. Some researchers will also use the HapMap to look for genes that affect traits such as baldness, behaviors like addicxon, and long life. Researchers will compare the genexc variaxon and haplotype informaxon for people in the same group and in different groups. In the future, researchers will also use the samples to look for differences in the amount and form of the products that genes make, called RNA and proteins, and will put all this informaxon for each sample in the database. The samples, the database, and the HapMap will also be used to study other quesxons, such as the biology of DNA, how new variaxons arise, the genexc history of human groups, and how people from different parts of the world are related to each other. Because the database will be public, people who do idenxty tesxng, such as for paternity tesxng or law enforcement, may also use the samples, the database, and the HapMap, to do general research. [ ] 18
Controlled Access criteria Applicants are affiliated to a recognized insxtuxon; Main applicant is qualified to undertake the proposed data analyses; CompaXbility of proposed study with the Database s objecxves/consent requirements; JusXficaXon that project requires access to controlled- access datasets listed in the applicaxon; Main applicant cerxfies that required ethical obligaxons have been met; ScienXfic merit of proposed study (clarity, novelty and scienxfic excellence); Applicant s privacy and confidenxality policy and security measures are adequate; The User InsXtuXon has approved and signed the Data Access Agreement. 19
Registered Access Falls between open access and controlled access Light touch approval process? No Data Access Agreement (DAA) though agreements of other kinds may be necessary Triple A approach: AuthenXcaXon, AVestaXon, AuthorizaXon 20
Registered Access criteria General criteria (for Authorization) Competence Applicants are bona fide researchers Information required 1 a The applicant s name, title, position, affiliation, email address, institutional website and mailing address (Authentication) 1 b? Ethics Security/ confidentiality! IRB/REC requirements have been met Adhesion to consent restrictions on the scope of data use Will not re-identify data: respect privacy of participants Will not share data with others Will not retain data longer than is required for the project 1 c Attestation? 2 a Attestation of compliance 2 b Attestation 3 a Attestation 3 b Attestation 3c Attestation 21
Applicability May be suitable for certain data types (e.g., less sensixve, low risk data such as non- sxgmaxzing health- related informaxon about non- vulnerable individuals who expect data will be shared for the purposes envisaged) as well as to provide access to different types of data users (e.g., researchers and clinicians) In addixon to the tradixonal Open access and Controlled access categories, Registered access can be used to account for the different levels of iden:fiability, sensi:vity and consent restric:ons related to the types of data included in a database. Governing Principles: Iden:fiability, Traceability and Accountability 22
Consent in registered access Consent permissions can be included as part of the AVestaXon (e.g. I agree to only use data for biomedical research) Broad consent for a data commons? 23
Example of Access Tiers Nature of data available Open-access Data -Less sensitive data (for example: aggregated, anonymous data, etc.). -Final interpretation. Registered-access Data -Data requiring some access review due to levels of identifiability, sensitivity and/or consent restrictions. -For variant classification. Controlled-access Data -More sensitive information (ex: identifiable, family history, etc.). -Vulnerable populations? (Perhaps) -Rare disease? (No) 24
Example of Access Process User / Researcher Online Application Form Open Access Authorization Registered Access Coordination Center Data Access Compliance Office Approval Controlled Access 25
In case of data misuse? Guidance from Accountability REWG Task Team Explores mechanisms to promote responsible data sharing, as well as to prevent and appropriately sanc:on data misuse. Underuse? 26
Demonstra:on Projects Beacon Project Matchmaker Exchange BRCA Challenge 27
Beacon Project inixaxve to test the willingness of internaxonal sites to share genomic datasets a beacon answers yes or no to the quesxon, have you observed this allele? makes data sharing easy because: it s technically very simple limited, aggregaxve response mixgates risks of paxent idenxficaxon 28
Matchmaker Exchange IniXated in October 2013 at ASHG RecogniXon by group of rare disease researcher and diagnosxc leaders that more data sharing was needed Presented at the first GA4GH plenary in March 2014 and collaboraxon inixated through demonstraxon project approach 29
Genomic Matchmaker Pa:ent #1 Clinical Gene:cist #1 Pa:ent #2 Clinical Gene:cist #2 NoXficaXon of Match Phenotypic Data Feature 1 Feature 2 Feature 3 Feature 4 Feature 5 Genotypic Data Gene A Gene B Gene C Gene D Gene E Gene F Genomic Matchmaker Genotypic Data Gene D Gene G Gene H Phenotypic Data Feature 1 Feature 3 Feature 4 Feature 5 Feature 6 Courtesy of Joel Krier
BRCA1/2 variant diversity across databases ClinVar: 7536 variants LOVD: 3362 variants UMD (France): 3913 variants BUT data are frequently nonoverlapping Last Update: June 4 th 2015
Goals of the Challenge To improve the care of paxents at risk of breast and ovarian cancer using global data sharing and collaboraxon in the analysis of BRCA1 and BRCA2 1. Share BRCA1 and BRCA2 variants publically 2. Create an environment for collaboraxve variant curaxon with access to evidence (e.g. phenotypes, family history, genexc data, and funcxonal studies) 3. Create a curated list of BRCA variants, interpreted by expert consensus, to enable, without dictaxng, accurate clinical care 4. Address the social, ethical, and legal challenges to global data sharing, and engage with paxent advocacy organizaxons 5. Create a model for all genes
Iden:fiability Account must be taken of all the means likely reasonably to be used for idenxficaxon by the controller and third parxes, paying special avenxon to what has lately become, in the current state of technology, likely reasonably (given the increase in computaxonal power and tools available). ARTICLE 29 DATA PROTECTION WORKING PARTY Opinion 05/2014 on AnonymisaXon Techniques 33
Public Popula:on Project in Genomics and Society (P 3 G) www.p3g.org 34
Interna:onal Policy interoperability and data Access Clearinghouse (IPAC) A one- stop service for researchers Data/Sample Collec:on ELSI Interoperability DACO Review of Data and Samples Access Request/ Authoriza:on and Compliance ELSI Clauses/ Agreements Database DataTrust Validate whether studies can work together (e.g. consent; confiden:ality; etc.); If not, create tools. Authorize studies to access controlled databases (e.g. ethics approval/ waiver; ins:tu:onal sign off; etc.). Open access resource allowing users to search and select models of clauses that best suit their needs. Support process of re- contac:ng par:cipants and returning individual- level results in transla:onal research projects. 35
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