Edward S. Dove

Data Sharing in the Post-Genomic World: The Experience of the International Cancer Genome Consortium (ICGC) Data Access Compliance Office (DACO)

The scientific community, research funders, and governments have repeatedly recognized the importance of open access to genomic data for scientific research and medical progress [1]–[4]. Open access is becoming a well-established practice for large-scale, publicly funded, data-intensive community science projects, particularly in the field of genomics. Given this consensus, restrictions to open access should be regarded as exceptional and treated with caution. Yet, several developments [5] have led scientists and policymakers to investigate and implement open access restrictions [5]–[9]. Notably, there are privacy concerns within the genomics community and critiques from some researchers that open access, if left completely unregulated, could raise significant scientific, ethical, and legal issues (e.g., quality of the data, appropriate credit to data generators, relevance of the system for small and medium projects, etc.) [1]–[10]. A recent paper by Greenbaum and colleagues in this journal [11] identified protecting the privacy of study participants as the main challenge to open genomic data sharing. n nOne possible way to reconcile open data sharing with privacy concerns is to use a tiered access system to separate access into “open” and “controlled.” Open access remains the norm for data that cannot be linked with other data to generate a dataset that would uniquely identify an individual. A controlled access mechanism, on the other hand, regulates access to certain, more sensitive data (e.g., detailed phenotype and outcome data, genome sequences files, raw genotype calls) by requiring third parties to apply to a body (e.g., custodian, original data collectors, independent body, or data access committee) and complete an access application that contains privacy safeguards. This mechanism, while primarily designed to protect study participants, can also be used to protect investigators, database hosting institutions, and funders from perceptions or acts of favoritism or impropriety. The experience of controlled access bodies to date has been only minimally documented in the literature [9], [12]. To address this lacuna, we present the experience of the Data Access Compliance Office (DACO) of the International Cancer Genome Consortium (ICGC). The goal is to provide information on this increasingly important type of database governance body.

A human rights approach to an international code of conduct for genomic and clinical data sharing

AbstractnFostering data sharing is a scientific and ethical imperative. Health gains can be achieved more comprehensively and quickly by combining large, information-rich datasets from across conventionally siloed disciplines and geographic areas. While collaboration for data sharing is increasingly embraced by policymakers and the international biomedical community, we lack a common ethical and legal framework to connect regulators, funders, consortia, and research projects so as to facilitate genomic and clinical data linkage, global science collaboration, and responsible research conduct. Governance tools can be used to responsibly steer the sharing of data for proper stewardship of research discovery, genomics research resources, and their clinical applications. In this article, we propose that an international code of conduct be designed to enable global genomic and clinical data sharing for biomedical research. To give this proposed code universal application and accountability, however, we propose to position it within a human rights framework. This proposition is not without precedent: international treaties have long recognized that everyone has a right to the benefits of scientific progress and its applications, and a right to the protection of the moral and material interests resulting from scientific productions. It is time to apply these twin rights to internationally collaborative genomic and clinical data sharing.

Genomic cloud computing: legal and ethical points to consider

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key ‘points to consider’ (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers’ Terms of Service. These ‘points to consider’ should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider’s servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure.

Building a data sharing model for global genomic research

Data sharing models designed to facilitate global business provide insights for improving transborder genomic data sharing. We argue that a flexible, externally endorsed, multilateral arrangement, combined with an objective third-party assurance mechanism, can effectively balance privacy with the need to share genomic data globally.

Crowd-Funded Micro-Grants for Genomics and “Big Data”: An Actionable Idea Connecting Small (Artisan) Science, Infrastructure Science, and Citizen Philanthropy

Biomedical science in the 21(st) century is embedded in, and draws from, a digital commons and Big Data created by high-throughput Omics technologies such as genomics. Classic Edisonian metaphors of science and scientists (i.e., the lone genius or other narrow definitions of expertise) are ill equipped to harness the vast promises of the 21(st) century digital commons. Moreover, in medicine and life sciences, experts often under-appreciate the important contributions made by citizen scholars and lead users of innovations to design innovative products and co-create new knowledge. We believe there are a large number of users waiting to be mobilized so as to engage with Big Data as citizen scientists-only if some funding were available. Yet many of these scholars may not meet the meta-criteria used to judge expertise, such as a track record in obtaining large research grants or a traditional academic curriculum vitae. This innovation research article describes a novel idea and action framework: micro-grants, each worth

Power to the people: a wiki-governance model for biobanks.

1000, for genomics and Big Data. Though a relatively small amount at first glance, this far exceeds the annual income of the bottom one billion-the 1.4 billion people living below the extreme poverty level defined by the World Bank (

Designing a post-genomics knowledge ecosystem to translate pharmacogenomics into public health action.

1.25/day). We describe two types of micro-grants. Type 1 micro-grants can be awarded through established funding agencies and philanthropies that create micro-granting programs to fund a broad and highly diverse array of small artisan labs and citizen scholars to connect genomics and Big Data with new models of discovery such as open user innovation. Type 2 micro-grants can be funded by existing or new science observatories and citizen think tanks through crowd-funding mechanisms described herein. Type 2 micro-grants would also facilitate global health diplomacy by co-creating crowd-funded micro-granting programs across nation-states in regions facing political and financial instability, while sharing similar disease burdens, therapeutics, and diagnostic needs. We report the creation of ten Type 2 micro-grants for citizen science and artisan labs to be administered by the nonprofit Data-Enabled Life Sciences Alliance International (DELSA Global, Seattle). Our hope is that these micro-grants will spur novel forms of disruptive innovation and genomics translation by artisan scientists and citizen scholars alike. We conclude with a neglected voice from the global health frontlines, the American University of Iraq in Sulaimani, and suggest that many similar global regions are now poised for micro-grant enabled collective innovation to harness the 21(st) century digital commons.

Towards an Ethics Safe Harbor for Global Biomedical Research

Biobanks are adopting various modes of public engagement to close the agency gap between participants and biobank builders. We propose a wiki-governance model for biobanks that harnesses Web 2.0, and which gives citizens the ability to collaborate in biobank governance and policymaking.

Towards an Ecology of Collective Innovation: Human Variome Project (HVP), Rare Disease Consortium for Autosomal Loci (RaDiCAL) and Data-Enabled Life Sciences Alliance (DELSA).

Translation of pharmacogenomics to public health action is at the epicenter of the life sciences agenda. Post-genomics knowledge is simultaneously co-produced at multiple scales and locales by scientists, crowd-sourcing and biological citizens. The latter are entrepreneurial citizens who are autonomous, self-governing and increasingly conceptualizing themselves in biological terms, ostensibly taking responsibility for their own health, and engaging in patient advocacy and health activism. By studying these heterogeneous scientific cultures, we can locate innovative parameters of collective action to move pharmacogenomics to practice (personalized therapeutics). To this end, we reconceptualize knowledge-based innovation as a complex ecosystem comprising actors and narrators. For robust knowledge translation, we require a nested post-genomics technology governance system composed of first-order narrators (for example, social scientists, philosophers, bioethicists) situated at arms length from innovation actors (for example, pharmacogenomics scientists). Yet, second-order narrators (for example, an independent and possibly crowd-funded think-tank of citizen scholars, marginalized groups and knowledge end-users) are crucial to prevent first-order narrators from gaining excessive power that can be misused in the course of steering innovations. To operate such self-calibrating and nested innovation ecosystems, we introduce the concept of wiki-governance to enable mutual and iterative learning among innovation actors and first- and second-order narrators.[A] scientific expert is someone who knows more and more about less and less, until finally knowing (almost) everything about (almost) nothing. [1]Ubuntu: I am because you are. [2]

An ethics safe harbor for international genomics research

Although increasingly global, data-driven genomics and other ‘omics’-focused research hold great promise for health discoveries, current research ethics review systems around the world challenge potential improvements in human health from such research. To overcome this challenge, we propose a ‘Safe Harbor Framework for International Ethics Equivalency’ that facilitates the harmonization of ethics review of specific types of data-driven international research projects while respecting globally transposable research ethics norms and principles. The Safe Harbor would consist in part of an agency supporting an International Federation for Ethics Review (IFER), formed by a voluntary compact among countries, granting agencies, philanthropies, institutions, and healthcare, patient advocacy, and research organizations. IFER would be both a central ethics review body, and also a forum for review and follow-up of policies concerning ethics norms for international research projects. It would be built on five principle elements: (1) registration, (2) compliance review, (3) recognition, (4) monitoring and enforcement, and (5) public participation. The Safe Harbor would create many benefits for researchers, countries, and the general public, and may eventually have application beyond (gen)omics to other areas of biomedical research that increasingly engage in secondary use of data and present only negligible risks.