Discussion Framework for Clinical Trial Data Sharing

CONTEXT OF STUDY

Clinical trials are crucial to determining the safety of medical interventions and their ability to achieve particular health outcomes. Clinical trials are required by regulatory authorities around the world before a new medical product can be brought to market, or before a new indication, formulation, or target population can be approved for an intervention already on the market (ICH, 1995). After a product’s introduction, additional clinical trials are commonly conducted by industry, government, and academia to further define the relative safety and efficacy (or effectiveness) of the product. Clinical trials are also used to study interventions that do not involve regulated medical products, for example, surgical techniques, behavioral interventions, or studies designed to improve disease management practice (Califf, 2013).

Vast amounts of data are generated over the course of a clinical trial. These data are held by the sponsors conducting the clinical trial, and in some instances, by participants or their advocates (Drazen, 2002; Terry and Terry, 2011). Depending on the regulatory jurisdiction, data might or might not be shared or made available to the public for secondary uses. Shared data might include both summary data and individual patient data. In the United States, if a sponsor is seeking regulatory approval, data are shared in confidence with regulators.1 Select study data might also be made available to individual researchers on a case by case basis upon request, or could be made publicly available, usually at the

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1 However, in the European Union, the European Medicines Agency (EMA) has undertaken regulatory action to share anonymized clinical trial data with external requestors. The EMA’s data sharing initiative is described on p. 32.



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Discussion Framework for Clinical Trial Data Sharing CONTEXT OF STUDY Clinical trials are crucial to determining the safety of medical inter- ventions and their ability to achieve particular health outcomes. Clinical trials are required by regulatory authorities around the world before a new medical product can be brought to market, or before a new indica- tion, formulation, or target population can be approved for an interven- tion already on the market (ICH, 1995). After a product’s introduction, additional clinical trials are commonly conducted by industry, govern- ment, and academia to further define the relative safety and efficacy (or effectiveness) of the product. Clinical trials are also used to study inter- ventions that do not involve regulated medical products, for example, surgical techniques, behavioral interventions, or studies designed to im- prove disease management practice (Califf, 2013). Vast amounts of data are generated over the course of a clinical trial. These data are held by the sponsors conducting the clinical trial, and in some instances, by participants or their advocates (Drazen, 2002; Terry and Terry, 2011). Depending on the regulatory jurisdiction, data might or might not be shared or made available to the public for secondary uses. Shared data might include both summary data and individual patient data. In the United States, if a sponsor is seeking regulatory approval, data are shared in confidence with regulators.1 Select study data might also be made available to individual researchers on a case by case basis upon request, or could be made publicly available, usually at the 1 However, in the European Union, the European Medicines Agency (EMA) has under- taken regulatory action to share anonymized clinical trial data with external requestors. The EMA’s data sharing initiative is described on p. 32. 1

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2 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING summary level, for example, through publication in a peer-reviewed journal or through publicly accessible clinical trial registration sites (e.g., ClinicalTrials.gov). Other data, however, remain largely unavailable to outside researchers and the public, including data found in analyzable data sets, clinical study reports (CSRs), and individual participant data (IPD) that, if accessible, could facilitate new analyses and a deeper un- derstanding of a particular therapy or condition (Doshi et al., 2013; Goldacre, 2012; Gordon et al., 2013; Rawlins, 2012). Increased sharing of IPD, in particular, could facilitate activities such as independent rea- nalysis of trial results, addressing concerns about publication bias,2 char- acterizing trial outcomes by subgroups, considering additional questions beyond the original trial hypotheses, carrying out meta-analysis for sys- tematic reviews, and facilitating hypothesis generation and additional research to develop new therapies (Doshi et al., 2012; IOM, 2013; McGauran et al., 2010; Ross et al., 2012). The data sharing movement has gained substantial momentum dur- ing the last decade, in both the clinical trial and larger scientific commu- nities (Boulton et al., 2011; Royal Society, 2012). A cultural change has occurred in which the conversation around data sharing has moved from whether it should happen to how it can be carried out (IOM, 2013). To that end, a large number of people and organizations involved in clinical trials have endorsed principles promoting, in their view, responsible sharing of clinical trial data (Loder, 2013). Prominent examples include the joint statement from funders of health research data, the AllTrials campaign, and the Pharmaceutical Research and Manufacturers of America (PhRMA) and European Federation of Pharmaceutical Indus- tries and Associations (EFPIA) principles (AllTrials, 2013; PhRMA and EFPIA, 2013; Wellcome Trust, 2011). Some organizations have gone beyond general statements and principles and begun to adopt data sharing policies as well. The U.S. National Institutes of Health (NIH), as well as international groups of researchers and nonprofit funders, has been involved in data sharing activities for years (e.g., BioLINCC, MalariaGen). More recently, European regulators and some pharmaceu- tical and device companies (e.g., GlaxoSmithKline [GSK], Medtronic) have begun to plan and implement their own data sharing policies (EMA, 2013; Nisen and Rockhold, 2013; YODA, 2013). In addition, medical journals have begun to require authors to include data sharing statements 2 The tendency for positive results of trials of health care interventions to be reported or published, with corresponding underreporting/non-publication of negative or inconclu- sive results (Cochrane Collaboration, 2002).

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 3 and, in the case of the British Medical Journal (BMJ), to agree to make de-identified patient-level data available upon “reasonable request” as a condition for publication (Godlee and Groves, 2012, p. 1). In October 2012, the Institute of Medicine (IOM) convened individ- uals with a broad range of expertise and perspectives to discuss sharing of clinical research data in a public workshop. As highlighted by work- shop participants, data sharing can provide important potential benefits to industry, nonprofit and government funders of research, academic inves- tigators, patient advocacy groups, and, ultimately, patients and the pub- lic, including, for example, speeding medical innovation by reducing redundancies, facilitating the identification and validation of new drug targets, identifying new indications for use, and improving the under- standing of the safety and efficacy of therapies (IOM, 2013). In follow- up to the 2012 IOM workshop, the IOM was asked by a group of federal, industry, and U.S. and international foundation sponsors3 to conduct a consensus study to recommend guiding principles and a framework for the responsible sharing of clinical trial data. Charge to the Committee and Scope of the Study As described in the committee’s charge from the sponsors (see Ap- pendix A), over a 17-month period of deliberations, the committee will release two documents: 1. This document, which is a framework for discussion (“frame- work”), to be released in January 2014 for public comment. The framework will summarize the committee’s initial thoughts on guiding principles that underpin responsible sharing of clinical trial data, define key elements of clinical trial data and data shar- ing, and describe a selected set of clinical trial data sharing activ- ities. The charge to the committee excludes evidence-based findings and conclusions and recommendations from this document. 2. A final report with findings and recommendations related to the committee’s full charge. 3 U.S. National Institutes of Health, U.S. Food and Drug Administration, AbbVie Inc., Amgen Inc., AstraZeneca Pharmaceuticals, Bayer, Biogen Idec, Bristol-Myers Squibb, Burroughs Wellcome Fund, Doris Duke Charitable Foundation, Eli Lilly and Company, EMD Serono, Genentech, GlaxoSmithKline, Johnson & Johnson, Medical Research Council (UK), Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk, Pfizer Inc., Sanofi-Aventis, Takeda, and Wellcome Trust.

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4 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING To respond to the charge, the IOM convened a committee composed of persons with expertise in key scientific and research-related areas, in- cluding academia, industry, funding bodies, regulatory activities, scien- tific publications, clinicians, and patients. Individual committee member expertise spans academic clinical trial design, performance and dissemi- nation; pharmaceutical product development; statistics, informatics, and data security; ethics of human subjects research; and law and regulatory requirements (including privacy, security, and intellectual property). Committee members also have insight into the global context of data sharing; the concerns of research participants, patients, and their fami- lies; and other relevant issues. As charged in its statement of task, in the next phase of the study the committee will identify the key benefits, challenges, and risks of sharing, as well as key risks of not sharing. This analysis will take into considera- tion the full range of perspectives of research sponsors and investigators, study participants, regulatory agencies, patient groups, and the public. The committee is also charged, in the final report, with suggesting strate- gies and practical approaches for responsible data sharing. As part of its recommendations, the committee will offer guiding principles for and characteristics of the optimal infrastructure and governance for data shar- ing. In particular, the committee has been called to consider, among other issues, resource constraints, implementation, disincentives in the aca- demic research model, changing norms, protection of human subjects and patient privacy, intellectual property and other legal issues, and preservation of scientific standards and data quality. As outlined in the statement of task (Appendix A), many terms are defined for the purposes of this study. “Data sharing” is defined as the responsible entity (“data generator”) making the data available via open or restricted access, or exchanged among parties. For the purposes of this study, data generator may include industry sponsors, data repositories, and researchers conducting clinical trials. The committee has adopted a working definition of “data holder” to mean the entity or entities that have access to data, including regulatory agencies, journals to which manuscripts are submitted, and other repositories such as ClinicalTrials.gov in the United States. Data holders—for example, persons who collect source data, develop an analyzable data set, or carry out statistical analyses—may or may not have legal authority to provide third-party access to the data. The scope of the study is limited to interventional clin- ical trials. For the purposes of this study, “interventional clinical trials” are defined as “research in which participants are assigned to receive one

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 5 or more interventions (or no intervention) so that the effects of the inter- ventions on biomedical or health-related outcomes can be evaluated. As- signments to [intervention]4 groups are determined by the study protocol” (ClinicalTrials.gov, 2012). Assignments could be at the indi- vidual or group level. An intervention is a “process or action that is the focus of a clinical trial. This can include giving participants drugs, medi- cal devices, procedures, vaccines, and other products that are either in- vestigational or already available” (ClinicalTrials.gov, 2012). For the purposes of this study, intervention types are limited to drugs, devices, biologics, other treatments or therapies (such as radiation), surgical proce- dures, behavioral interventions, and changes in the administration or deliv- ery of clinical care. A FRAMEWORK FOR DISCUSSION AND CALL FOR COMMENTS This framework for discussion articulates the committee’s prelimi- nary thoughts on guiding principles that underpin the responsible sharing of clinical trial data, defines key elements of data and data sharing activi- ties, and describes a selected set of data sharing activities. One goal of this framework is to set the stage for identification of the numerous com- plicated issues that recommended strategies and practical approaches to sharing of clinical trial data might need to take into account. As with any complex policy problem, there are advantages and disadvantages to be weighed and potential for competing interests and incentives among and within various stakeholder groups. The guiding principles as defined be- low potentially could be in conflict or might be interpreted or prioritized differently, depending on one’s perspective. As a first step in fulfilling the committee’s charge, the framework identifies key issues so that the public can point out omissions and begin to suggest benefits, interests, risks, and burdens of options that should be considered. The framework also identifies issues about which the com- mittee will gather additional information through public meetings and the submission of written materials by interested parties (see Box 1 and the section below). Comparing the various public responses to the frame- work will help clarify the countervailing interests and values the commit- 4 To maintain consistency in its terminology the committee has substituted the term “in- tervention” here for the term “treatment,” which is used in the ClinicalTrials.gov definition.

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6 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING tee will take into account in making its recommendations to enhance re- sponsible sharing of clinical trial data. BOX 1 Specific Topics for Public Feedback Global Implementation and Practical Consideration x Because most large clinical trials are global in nature, how can clin- ical trial data be shared in that global context? How can different national regulations for research participants’ privacy protections, approval of drugs and devices, data exclusivity and intellectual property laws, resources, and health priorities be taken into account? x How might strategies and approaches regarding data sharing take into account clinical trials conducted in resource-poor settings; trials designed by citizen-scientists using data they contribute directly; and trials designed through participatory research? Timing and Prioritization x How might different types of clinical trial data, and different uses of shared data, be prioritized for sharing? What would be the rationale for placing a higher priority on certain types of data or analyses? What might be the advantages and disadvantages of distinguishing highest priority sharing of clinical trial data from other sharing activities? x What might be the advantages and disadvantages to various stake- holders of sharing different types of datasets, at different points in time after the completion of a clinical trial? x Should programs or approaches calling for or requiring new data sharing apply only to new trials undertaken from the date of a new program forward, or retroactively apply to clinical trials started before the data sharing program was initiated? Mitigating Risks x What might be done to minimize the risks to patients and to public health from the dissemination of findings from invalid analyses of shared clinical trial data? x What measures should be deployed to minimize the privacy and confidentiality risks to trial participants? For example, are current anonymization or de-identification methodologies sufficient? x Under what circumstances are identifiable data needed to fulfill ar- ticulated purposes of a data sharing activity? Under what circum- stances might re-identification of trial participants be beneficial (for the participants or the public)? Have there been there examples of instances of re-identification of trial participants (e.g., for safety rea- sons to warn a patient of a potential risk, or for questionable and potentially unethical reasons) and what were the impacts?

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 7 Enhancing Incentives x What incentives and protections might be established to encourage clinical trial sponsors and clinical investigators to continue to con- duct clinical trials in the future, without unduly restricting the sharing of certain types of data? How do we protect or provide incentives for researchers to share data? x What is the appropriate responsibility of the primary investigator(s) or research institution(s) to support secondary users in their inter- pretation of shared data, and what infrastructure or resources are needed to enable such ongoing support? For those with experience in data sharing, what is the burden of providing such support to help others understand and use the provided information? Measuring Impact x What would be appropriate outcome measures to assess the use- fulness of different models of clinical trial data sharing, and how can they be used to guide improvements in data sharing practices? Invitation for Public Comments The issues identified and the options and observations described in this framework are preliminary and do not represent a comprehensive review of the subject. This framework does not assess the benefits and risks of different options and, consistent with its charge, does not contain conclusions or recommendations. Instead, this framework serves to iden- tify areas of interest and concern that will be pursued in greater detail during the second phase of the project and addressed in the final report. The final report will also analyze the risks and benefits of options and make conclusions and recommendations. As required in the charge to the committee, the framework is being released for public comment. The committee welcomes comments from interested parties to help ensure that major concerns and issues are not overlooked, and particularly in- vites comments on the difficult or complex issues outlined in Box 1 be- low. Comments may be submitted to the committee at either of two forthcoming public workshops, or via the committee’s project website, http://www8.nationalacademies.org/cp/projectview.aspx?key=49578. During the course of the study, members of the public are encour- aged to provide comments on this framework, as well as general com- ments on issues within the scope of the charge to the committee. The committee is also interested in receiving testimony and suggestions on

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8 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING topics that are likely to be particularly complex, and where differing per- spectives are likely to reside. At future meetings, the public will be invit- ed to discuss these issues or to submit written statements. GUIDING PRINCIPLES FOR RESPONSIBLE SHARING OF CLINICAL TRIAL DATA In this framework for discussion, the committee proposes four high- level principles as a starting point for developing a framework for re- sponsible sharing of clinical trial data (see Box 2; the principles are discussed individually below). By explicitly articulating these guiding principles and the rationale behind them, the committee hopes to bring into sharper relief the values of concern for different stakeholders that need to be acknowledged and balanced in data sharing policies and procedures. In developing this provisional set of guiding principles, the commit- tee drew on recent proposals for principles of data sharing in clinical tri- als from scholars and working groups (AllTrials, 2013; EMA, 2013; FDA, 2013; Godlee and Groves, 2012; Mello, 2013; PhRMA and EFPIA, 2013; Wellcome Trust, 2011; YODA, 2013), as well as widely accepted guiding principles articulated in official statements of research ethics and international standards, such as the Declaration of Helsinki, the Belmont Report (which presents the ethical rationale for current U.S. regulations for human subjects research), and others (Childress et al., 2005; CIOMS, 2002; ICH, 1996; National Commission, 1979; WMA, 2013). Policies regarding clinical trial data sharing will have a stronger intellectual foundation and practical applicability if they take into ac- count policies on related topics. A framework for sharing clinical trial BOX 2 Provisional Guiding Principles for Responsible Sharing of Clinical Trial Data x Respect the individual participants whose data are shared. x Maximize benefits to participants in clinical trials and to society, while minimizing harms. x Increase public trust in clinical trials. x Carry out sharing of clinical trial data in a manner that enhances fairness.

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 9 data should therefore be consistent with the principles guiding related issues, including the protection of human research participants, regula- tion of drugs and medical devices, scientific publications, and intellectual property protections. In this section the committee presents potential consequences of clin- ical trial data sharing, which may or may not occur in any particular data sharing activity. In its further deliberations and final report, the commit- tee will assess these potential consequences of clinical trials data sharing. Respect the Individual Participants Whose Data Are Shared The committee’s first provisional guiding principle stems from the broadly articulated concept that respect for research participants is a fun- damental principle of research ethics (ICH, 1996; National Commission, 1979). Respect Through Research Participant Protections Respect for research participants requires protecting their dignity, integrity, and right to self-determination; this includes, at a minimum, compliance with applicable regulations and ethical standards for the con- duct of clinical trials and handling of the resulting data. Respect for re- search participants has historically been understood to require specific informed consent from participants (including consent for how their data will be used) before they enroll in a clinical trial in which the interven- tion is carried out at the individual participant level (Childress et al., 2005; CIOMS, 2002; WMA, 2013).5 For existing trials, data sharing (particularly sharing beyond other investigators in the trial) might not have been explicitly discussed with participants during the consent pro- cess. Sharing of data without specific participant consent might be ethi- cally acceptable and legally permitted in certain instances. For example, if the shared data are de-identified, current U.S. federal regulations on human research protections and U.S. health information privacy regula- tions (e.g., the Health Insurance Portability and Accountability Act 5 Specific informed consent is not necessarily required for trials at the group level, such as in certain cluster-randomized trials (Weijer and Emanuel, 2000) or for certain compar- ative effectiveness trials (Faden et al., 2013).

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10 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING [HIPAA] of 1996)6 allow other researchers to use the data for research under certain conditions without consent from the original participants.7 Respect also suggests a need to protect the confidentiality and priva- cy of trial participants when data are shared. Questions have been raised about the sufficiency of commonly used de-identification methodologies (Benitez and Malin, 2010; El Emam, 2013; McGraw, 2012); consequent- ly, additional protections may be needed. Respect Through Engagement Respect can also be demonstrated and advanced through efforts to engage participants and their representatives in the development of pro- cesses for sharing of clinical trial data (CTSA, 2011). For example, new policies and procedures regarding data sharing and subsequent additional analyses (particularly for specific trials or classes of trials as relevant) could be developed with input and feedback from representatives of re- search participants, disease advocacy groups, community advisory boards, and the public (Jiang et al., 2013). Such an approach would also include dissemination of information and calls for input about data shar- ing policies and procedures and a rationale for data sharing that is acces- sible and understandable to the public. The act of seeking and obtaining such input would not in itself constitute surrogate consent or authoriza- tion for data sharing. Rather, it would respect participants by actively seeking to identify concerns about and potential unappreciated benefits of data sharing that were not previously taken into account, and allow participants or their advocates to suggest how the process of data sharing might be improved (Stiles and Petrila, 2011). Maximize Benefits to Participants in Clinical Trials and to Society, While Minimizing Harm Understanding and balancing the potential benefits and harms of health interventions is a significant component of health care and of health intervention research and development. Similarly, there are poten- 6 Public Law 104-191, 104th Cong. (August 21, 1996). 7 The U.S. example has been described here for illustrative purposes. Privacy protec- tions with respect to sharing anonymized data without reconsent vary across jurisdictions. For example, the European Union has strong data privacy protections that need to be observed when clinical trial data are shared by its member states (Article 29 Data Protection Working Party, 2013).

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 11 tial benefits and harms associated with the sharing of clinical trial data. Strategies for data sharing should maximize benefits to those who give of themselves to participate—and to society as a whole—while minimizing potential harms for various stakeholders. This provisional guiding prin- ciple for responsible sharing of clinical trial data is derived from the ethi- cal concept of beneficence. Potential Benefits International ethical standards identify beneficence as a basic ethical principle and obligation of research involving human subjects. The Inter- national Conference on Harmonisation (ICH) Guideline for Good Clini- cal Practice declares: “Before a trial is initiated, foreseeable risks and inconveniences should be weighed against the anticipated benefit for the individual trial subject and society. A trial should be initiated and contin- ued only if the anticipated benefits justify the risks” and “the rights, safety, and well-being of the trial subjects are the most important considerations and should prevail over interests of science and society” (ICH, 1996). Benefits include both the immediate knowledge gained from answering the hypothesis of a particular clinical trial and the broader utility of the study data in informing development of effective new interventions. As discussed in the Belmont Report, practitioners are faced with deciding “when it is justifiable to seek certain benefits despite the risks involved” (National Commission, 1979, p. 5). The potential utility of data is a com- ponent in the balance of potential benefits and risks when making the decision to expose individual participants to risk in order to seek benefits to society as a whole. Clinical trials are designed and carried out to address research ques- tions about the safety and efficacy (or effectiveness) of one or more health interventions. The interventions that participants receive are de- termined by the study protocol, not by what their personal physicians consider best for them as individuals. In consenting to participate, clini- cal trial participants also accept that complying with the study protocol potentially entails inconvenience and risks (Lidz et al., 2004). Although participation in clinical trials, on the whole, might not be significantly riskier than ordinary clinical care or receiving the same intervention out- side the trial (Gross et al., 2006), in a specific trial the benefits and risks of the study arms are not known at the outset. In some instances the in- tervention arm of a trial will be shown to have significantly worse out-

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26 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING and the corresponding primary and secondary outcome measures; the methods used to gather and adjudicate adverse events; other measures intended to evaluate the intervention; and a full description of the inter- vention and how it is administered. While a trial protocol provides the overall experimental design, a detailed manual of operations describes how the trial was conducted. A copy of the template for the informed consent form describes what participants agreed to, what hypotheses were included, and the additional purposes for which their data might be used. Case report forms capture precisely what measures were made, and at what time points during the trial, as defined in the protocol. The SAP sets out how each data element was analyzed, what specific statistical method was used for each analysis, and how adjustments were made for testing multiple variables. If some analysis methods required critical as- sumptions, data users would need to understand how those assumptions were verified. For key analyses, full use of the shared data would be aid- ed by providing the computer software and version used, as well as the statistical programming code for the statistical software used for each analysis. BOX 4 Metadata and Additional Documentation to Support the Use of Shared Clinical Trial Data x Clinical trial registration number and dataset (available through ClinicalTrials.gov and other registries) x Full protocol (e.g., all outcomes, study structure), including first ver- sion, last version, and all amendments x Manual of operations (e.g., assay method) and standard operating procedures, including names of parties involved, specifically: o names of persons on the clinical trial team, trial sponsor team, data management team, and data analysis team; and o names of members of the steering committee, clinical events committee (CEC, which adjudicates end points), data and safe- ty monitoring board (DSMB) or data monitoring committee (DMC), as well as committee charters x Details of study execution (e.g., participant flow, deviations from protocol) x Case report forms, informed consent forms, biospecimen information x SAP, all amendments, and all documentation for additional work processes (including codes, software, and audit of the statistical workflow) x Publications and report documents (see Box 3)

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 27 Summaries and reports (e.g., publications from the trial, lay- language summary of trial results, trial registry results summary, CSR synopsis) would also help shared-data recipients understand and make the most efficient use of shared data. There are variations in how these data elements are defined and in the terminology used to describe them. In its future deliberations, the committee will seek clarity and consistency in use of the terms. The final report will include discussion of how the information in the analyzable dataset, CSR, and IPD differ and which types of analyses, either con- firmatory or exploratory, require which level of data sharing. Who Are the Providers of Shared Data? Data are generated at almost every step in the clinical research pro- cess, from the initial collection of baseline participant data to the analysis of the analyzable dataset. Different individuals or organizations hold or control the data at different times during the course of the trial (e.g., la- boratory technicians, investigators, database administrators, statisticians, DSMBs, sponsors, and regulatory agencies). A data holder may or may not have legal authority to share the data with others. In contrast, an in- dividual or organization with the authority to share the data might not have physical possession of the data at a particular time. Thus, responsi- bility for providing data for sharing might need to be coordinated among several entities. Potential entities that are likely to be data providers in- clude (but are not limited to) the following: x Individual participants in a clinical trial (the initial “providers” of data to researchers). Some participants might hold data to the extent that they self-generate and transmit the data (from self- quantifying devices), retain copies of the data, or receive infor- mation from investigators. Participants could, in turn, share their information with organizations that aggregate data from many participants (e.g., disease advocacy groups, research platforms such as PatientsLikeMe, Reg4ALL, or Sage Bionetwork’s Bridge). x Clinical trial funders (e.g., government, industry, foundations, or advocacy organizations). x Contract research organizations that collect source data from par- ticipants on behalf of sponsors. x Principal investigators or their institutions.

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28 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING x Site principal investigators of a multisite trial or their institutions. x The data or biostatistics coordinating center or the institution hosting the center. x Regulatory agencies to which data are submitted. x Systematic reviewers and guideline developers. Potential users of shared data will need to know whom to contact to obtain the data they seek, who owns the data, who controls the data, and where they can get answers to questions that will inevitably arise about the dataset. As such, data providers might have an ongoing resource role, beyond simply sending data and metadata to recipients. The final report will include analysis of the advantages and disadvantages of various ac- tors having responsibility for providing data to be shared. Who Are the Recipients of Shared Data? Many individuals and entities could be recipients of shared data from clinical trials. These include (but are not limited to) the following: x Individuals participating in the trial, as a part of the agreement for participation, for a variety of reasons described above (e.g., trust, transparency, respect, engagement). x Researchers seeking to reanalyze a study or explore new scien- tific questions. x The institutions supporting the researchers. x Funding agencies (e.g., government, private sector). x IRBs or scientific peer review committees reviewing a new study of the same or a similar intervention in order to have a more comprehensive safety profile of the intervention. x The DSMB or DMC for another clinical trial, whose decision to recommend continuing or stopping that trial can be informed by the results of a completed trial that has not yet been or will never be published. x Educators requesting to use a dataset for teaching purposes (e.g., in a biostatistics class). x A disease advocacy group seeking to advance research. x Prospective plaintiffs or attorneys seeking information that could be used in current or future litigation.

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 29 x Competitors of the industry sponsor of the intervention studied in the trial. x Members of the media. x Interested members of the public. Potential data recipients are interested in different types of data for potentially very different purposes. When Might Clinical Trial Data Be Shared? Data might be shared at various points in the timeline of a clinical trial, for instance, x After publication of the primary results of the clinical trial in a peer-reviewed journal. x After discontinuation of development of an intervention by a sponsor. x After completion or early termination of a clinical trial. x After regulatory approval of a new intervention or a new indica- tion for the intervention. x Following the occurrence of serious adverse events. x Earlier, at the discretion of the data provider or generator. The final report will include consideration of the advantages and dis- advantages associated with disclosure of clinical trial data at various time points. The timing of data sharing could have very important implica- tions that need serious consideration. For example, timing of release of the data will have consequences for the interests of the clinical trial team (e.g., the impact of data sharing on the timing of further publications from the data). Timing is also of great interest to the trial sponsor (e.g., relative to the timing of securing intellectual property rights or regulatory approval). How Might Data Be Shared? A variety of models for clinical trial data sharing have been proposed, planned, or implemented (select examples are summarized in Box 5). The types of data that are shared differ across the models. Proposed models of data sharing have generally imposed some sort of restriction on the sharing of data that could directly or potentially identify trial partici-

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30 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING pants, as well as data that reveal CCI or trade secrets or might result in inaccurate analysis. Access to clinical trial data in current models ranges from essentially full access to de-identified data to fully restricted or no access. Open Access In an open or public access model, data are made available, at a de- fined time, to any party who seeks them, for any purpose. For example, the EMA has announced that it will release, to any data requester that is a known entity to the agency, both summary and participant-level data (excluding, for example, personally identifiable data and information the EMA deems to be CCI) immediately after a regulatory decision about a new drug (Eichler et al., 2013; EMA 2013; Immport, 2013; Immune Tolerance Network, 2013; NHLBI, 2007). Controlled Access In some models of data sharing, access is restricted to specific clas- ses of user or for specific purposes. Requestors might need to demon- strate that they meet specified eligibility criteria. Some models require only the name and contact information of the requestor, while others re- quire information about the proposed use of the requested data or how the data will be analyzed. Some models might also impose conditions relating to whether the data generators would receive credit in publications. In some cases, the actual data are not provided to the requestor. In- stead, data holders might run specific data analyses for approved reques- tors and deliver to the requestors only the results of the requested analyses. In another model, recipients receive credentials to access and run queries on the data, but are not able to download or obtain copies of the data. Data sharing can also take place indirectly, through a “trusted inter- mediary” or “honest broker,” who either negotiates the conditions for data sharing (with the data provider retaining control over the data and its release) or takes full control of the data and brokers both the conditions for data release and the delivery to recipients (Mello et al., 2013). Trust- ed intermediaries might also accept and facilitate data analysis queries from secondary investigators, as mentioned above. The use of a trusted intermediary raises a number of issues, including selection, administra- tion, funding, and compensation.

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 31 A controlled-access data sharing model could implicitly or explicitly address issues such as specification of data that will be shared; any cate- gories of data that are to be specifically restricted; and how to address risks of breaches of confidentiality, attempts to re-identify trial partici- pants, data retention periods, scientifically inappropriate analyses, and the need for timely responses to data requests. To obtain shared data under a controlled-access model, a recipient typically must execute a data use agreement (DUA). Conditions in the DUA might include x prohibitions on re-identification or contact of individual trial par- ticipants; x requirements to acknowledge the providers of the data in any publications resulting from the shared data; x requirements to send copies of submitted manuscripts and publi- cations to the trial investigators or study sponsor; x restrictions on further sharing of the data with additional parties or using the data for purposes other than originally proposed; x assignment of intellectual property rights for discoveries from the shared data; x requirements to publish or post findings from the data; and x requirements to notify industry sponsors of the trial of any find- ings that raise safety concerns. There might also be limits on the length of time that a recipient may use or access shared data (ADNI, 2013; Harvard University MRCT, 2013; Nisen and Rockhold, 2013; PhRMA and EFPIA, 2013; YODA, 2013). Selected Set of Clinical Trial Data Sharing Activities The possible models and approaches to clinical trial data sharing, and the purposes motivating that sharing, are extensive. The rationale, bene- fits, risks, and burdens associated with one particular data sharing activi- ty could differ from those of another data sharing activity, depending on the data elements and parties involved. To stimulate public comments and to provide heuristic organization- al structure to its work, the committee has described a selected set of data sharing activities as examples of the types of arrangements or approaches under which clinical trial data might be shared (see Box 5). To derive this selected set, the committee reviewed a range of existing and pro-

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32 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING posed data sharing activities and distilled them into four conceptual cate- gories that represent broad “families” of activities that have key features in common. No single proposed or enacted data sharing activity has all of the characteristics in the familial description, and different data shar- ing activities in the same category can have important differences. The categories therefore are derived from, but do not describe any specific, data sharing activities currently underway or proposed. To the extent there are redundancies in characteristics within the models, the commit- tee will address them or take them into account in its forthcoming analysis. Each activity is described according to the type(s) of data that could be shared; provider(s) of data; recipients of data; timing of data sharing; conditions or qualifications for access; and conditions of data use. The descriptive characteristics are an illustrative but not exhaustive list. De- tailed descriptions and, particularly, conclusions and recommendations regarding those descriptive characteristics or strategies and approaches for sharing will be included in the final report. BOX 5 Set of Clinical Trial Data Sharing Activities 1. Open Access A data sharing program or system in which data are made broadly available to the public through an open-access website. Data might be aggregated from multiple sources (i.e., more than one institution, company, or researcher), or the website might provide open access to data from one trial or one institutional or individual researcher. Aggre- gated data might require trial- or institution-specific queries. An open- access data sharing activity could have some or many of the following descriptive characteristics: a. Type of data: summary data or anonymized IPD b. Providers of data: as determined by the organizational structure of the data sharing activity. Providers could include sponsors of appli- cations for regulatory approval of products, researchers funded by a government source, or other data generators or aggregators (such as regulatory agencies) required or agreeing to share data c. Recipients of data: all members of the public via a website d. Timing of sharing: upon publication or after regulatory decision or abandonment of drug development e. Conditions or qualifications for access: none; no or minimal iden- tification/log-in requirements; no governing body to make access determinations f. Conditions of data use: no conditions of use or requirement for signed data use agreement; expectation to abide by applicable

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 33 law (e.g., intellectual property protections, privacy protections) a. Example activities:a EMA Category 2, National Institute of Allergy and Infectious Diseases’ Trial Share, Immunology Database and Analysis Portal (ImmPort); National Heart, Lung, and Blood Insti- tute’s BioLINCC 2. Controlled Access to Individual Company, Institution, or Researcher Data A data sharing program or system in which data are made available to requestors on a controlled-access basis, pursuant to defined re- strictions or conditions. Data are from one institution or researcher. Data might require or permit trial- or product/intervention-specific que- ries. A controlled access–individual entity data sharing activity could have some or many of the following descriptive characteristics: a. Type of data: summary data, anonymized, or limited dataset b. Providers of data: an individual company, institution, researcher, or other entity generating or assembling data (e.g., a patient ad- vocacy organization) c. Recipients of data: members of the public via a website d. Timing of sharing: upon publication or after regulatory decision or abandonment of drug development e. Conditions or qualifications for access: access controlled by the institution/data generator or by a specified governing body such as a learned intermediary. Controls could include requirements to register, have specified expertise (e.g., statistics), successfully complete a test to demonstrate expertise, disclose funding sources, provide a purpose for the data request that meets specified criteria (e.g., related to public health or patient care), or provide an analysis plan (which might or might not need to meet specified criteria) f. Conditions of data use: restrictions or conditions on data use might include a requirement to sign a data use agreement, re- quirement to provide and adhere to a publication plan (which might need to meet specified criteria), prohibition on use of data for commercial purposes, prohibition on attempts to re-identify data, requirement to inform data generator about any safety con- cerns identified, agreement that the data generator retains exclu- sive rights to inventions or other intellectual property generated by the data recipient, or requirement to acknowledge the source of the shared data and the investigators in the original clinical trial g. Example activities: PhRMA/EFPIA commitments, Harvard Multi- Regional Clinical Trials Center proposal, Yale Open Data Access  Controlled Access to Pooled or Multiple Data Sources A data sharing program or system in which data are made available to requestors on a controlled-access basis pursuant to defined re- strictions or conditions. Data are aggregated from multiple sources (i.e., more than one institution, company, or researcher). Aggregated data might require or permit trial- or institution-specific queries. A con- trolled access–multiple entity data sharing activity could have some or many of the following descriptive characteristics:

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34 DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING a. Type of data: summary data or anonymized IPD b. Providers of data: as determined by the organizational structure of the data sharing activity. Providers could include sponsors of applications for regulatory approval of products, researchers funded by a government source, or other data generators as re- quired or agreed on c. Recipients of data: members of the public via a website d. Timing of sharing: upon publication or after regulatory decision or abandonment of drug development e. Conditions or qualifications for access: access controlled by the institution/data generator or by a specified governing body, such as a learned intermediary. Controls could include requirements to register, have specified expertise (e.g., statistics), successfully com- plete a test to demonstrate expertise, disclose funding sources, pro- vide a purpose for the data request that meets specified criteria (e.g., related to public health or patient care), or provide an analy- sis plan (which might or might not need to meet specified criteria) f. Conditions of data use: restrictions or conditions on data use might include a requirement to sign a data use agreement, re- quirement to provide and adhere to a publication plan (which might need to meet specified criteria), prohibition on use of data for commercial purposes, prohibition on attempts to re-identify data, requirement to inform that data generator about any safety concerns identified, agreement that the data generator retains ex- clusive rights to inventions or other intellectual property generated by the data recipient, requirement to acknowledge the source of the shared data and the investigators in the original clinical trial g. Example activities: GSK, EMA Category 3 (clinical trial data with Protection of Personal Data concerns), Alzheimer’s Disease Neu- roimaging Initiative . Closed Partnership/Consortium A data sharing program in which data are shared between or among two or more parties. Arrangements could be between or among public, nonprofit, or for-profit entities. Data are not intended to be shared with individuals or others who are not party to the partnership or consortium arrangement. A closed partnership/consortium data sharing activity could have some or many of the following descriptive characteristics a. Type of data: summary data, IPD (anonymized or not) b. Providers of data: as determined by the parties to the arrange- ment or initiators of the data sharing activity. Providers could in- clude companies or other product development organizations, in- dividual researchers or institutions, or other entities generating data (e.g., a patient advocacy organization) as agreed upon c. Recipients of data: members of the partnership or consortium d. Timing of sharing: as agreed upon by the terms of the partnership or consortium arrangement

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DISCUSSION FRAMEWORK FOR CLINICAL TRIAL DATA SHARING 35 e. Conditions or qualifications for access: access controls deter- mined by partnership/consortium arrangement f. Conditions of data use: restrictions or conditions on data use might include a requirement to sign a partnership/consortium agreement, an agreement governing rights to inventions or other intellectual property generated by the data sharing activity, or an agreement dictating whether and how future publications will be undertaken g. Example activities: PatientsLikeMe ____________________ a Activities listed here are considered examples of the described data sharing activity because they have some or many of the listed descriptive characteris- tics. No one activity would necessarily have all of the listed characteristics (and some of those characteristics might be mutually exclusive). The activities cited as examples could vary substantially from each other depending on their de- scriptive characteristics.

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