Assessment of a demonstrator repository for individual clinical trial data built upon DSpace.

Background: Given the increasing number and heterogeneity of data repositories, an improvement and harmonisation of practice within repositories for clinical trial data is urgently needed. The objective of the study was to develop and evaluate a demonstrator repository, using a widely used repository system (DSpace), and then explore its suitability for providing access to individual participant data (IPD) from clinical research. Methods: After a study of the available options, DSpace (version 6.3) was selected as the software for developing a demonstrator implementation of a repository for clinical trial data. In total, 19 quality criteria were defined, using previous work assessing clinical data repositories as a guide, and the demonstrator implementation was then assessed with respect to those criteria. Results: Generally, the performance of the DSpace demonstrator repository in supporting sensitive personal data such as that from clinical trials was strong, with 14 requirements demonstrated (74%), including the necessary support for metadata and identifiers. Two requirements could not be demonstrated (the ability to include de-identification tools and the availabiltiy of a self-attestation system) and three requirements were only partially demonstrated (ability to provide links to de-identification tools and requirements, incorporation of a data transfer agreement in system workflow, and capability to offer managed access through application on a case by case basis). Conclusions: Technically, the system was able to support most of the pre-defined requirements, though there are areas where support could be improved. Of course, in a productive repository, appropriate policies and procedures would be needed to direct the use of the available technical features. A technical evaluation should therefore be seen as indicating a system's potential, rather than being a definite assessment of its suitability. DSpace clearly has considerable potential in this context and appears a suitable base for further exploration of the issues around storing sensitive data.

Evaluation of repositories for sharing individual-participant data from clinical studies.

BACKGROUND: Data repositories have the potential to play an important role in the effective and safe sharing of individual-participant data (IPD) from clinical studies. We analysed the current landscape of data repositories to create a detailed description of available repositories and assess their suitability for hosting data from clinical studies, from the perspective of the clinical researcher. METHODS: We assessed repositories that enable storage, sharing, discoverability, re-use of the IPD and associated documents from clinical studies using a pre-defined set of 34 items and publicly available information from April to June 2018. For this purpose, we developed an indicator set to capture the maturity of the repositories' procedures and their suitability for the hosting of IPD. The indicators cover guidelines for data upload and data de-identification, data quality controls, contracts for upload and storage, flexibility of access, application of identifiers, availability of metadata, and long-term preservation. RESULTS: We analysed 25 repositories, from an initial set of 55 identified as possibly relevant. Half of the included repositories were generic, i.e. not limited to a specific disease or clinical area and 13 were launched in the last 8 years. The sample was extremely heterogeneous and included repositories developed by research funders, infrastructures, universities, and editors. All but three repositories do not apply a fee for uploading, storage or access to data. None of the repositories completely demonstrated all the items included in the indicator set, but three repositories (Dryad, Drum, EASY) met - fully or partially - all items. Flexibility of data-access modalities appears to be limited, being lacking in half of the repositories. CONCLUSIONS: Our evaluation, though often hampered by the lack of sufficient information, can help researchers to find a suitable repository for their datasets. Some repositories are more mature because of their support for clinical dataset preparation, contractual agreements, metadata and identifiers, different modalities of access, and long-term preservation of data. Further work is now required to achieve a more robust and accurate system for evaluation, which in turn may encourage the sharing of clinical study data. TRIAL REGISTRATION: Study protocol available at https://zenodo.org/record/1438261#.W64kW9Egrcs .

Classification of processes involved in sharing individual participant data from clinical trials.

Background: In recent years, a cultural change in the handling of research data has resulted in the promotion of a culture of openness and an increased sharing of data. In the area of clinical trials, sharing of individual participant data involves a complex set of processes and the interaction of many actors and actions. Individual services and tools to support data sharing are becoming available, but what is missing is a detailed, structured and comprehensive list of processes and subprocesses involved and the tools and services needed. Methods: Principles and recommendations from a published consensus document on data sharing were analysed in detail by a small expert group. Processes and subprocesses involved in data sharing were identified and linked to actors and possible supporting services and tools. Definitions adapted from the business process model and notation (BPMN) were applied in the analysis. Results: A detailed and comprehensive tabulation of individual processes and subprocesses involved in data sharing, structured according to 9 main processes, is provided. Possible tools and services to support these processes are identified and grouped according to the major type of support. Conclusions: The identification of the individual processes and subprocesses and supporting tools and services, is a first step towards development of a generic framework or architecture for the sharing of data from clinical trials. Such a framework is needed to provide an overview of how the various actors, research processes and services could interact to form a sustainable system for data sharing.

Sharing and reuse of individual participant data from clinical trials: principles and recommendations.

OBJECTIVES: We examined major issues associated with sharing of individual clinical trial data and developed a consensus document on providing access to individual participant data from clinical trials, using a broad interdisciplinary approach. DESIGN AND METHODS: This was a consensus-building process among the members of a multistakeholder task force, involving a wide range of experts (researchers, patient representatives, methodologists, information technology experts, and representatives from funders, infrastructures and standards development organisations). An independent facilitator supported the process using the nominal group technique. The consensus was reached in a series of three workshops held over 1 year, supported by exchange of documents and teleconferences within focused subgroups when needed. This work was set within the Horizon 2020-funded project CORBEL (Coordinated Research Infrastructures Building Enduring Life-science Services) and coordinated by the European Clinical Research Infrastructure Network. Thus, the focus was on non-commercial trials and the perspective mainly European. OUTCOME: We developed principles and practical recommendations on how to share data from clinical trials. RESULTS: The task force reached consensus on 10 principles and 50 recommendations, representing the fundamental requirements of any framework used for the sharing of clinical trials data. The document covers the following main areas: making data sharing a reality (eg, cultural change, academic incentives, funding), consent for data sharing, protection of trial participants (eg, de-identification), data standards, rights, types and management of access (eg, data request and access models), data management and repositories, discoverability, and metadata. CONCLUSIONS: The adoption of the recommendations in this document would help to promote and support data sharing and reuse among researchers, adequately inform trial participants and protect their rights, and provide effective and efficient systems for preparing, storing and accessing data. The recommendations now need to be implemented and tested in practice. Further work needs to be done to integrate these proposals with those from other geographical areas and other academic domains.

Orchestrating differential data access for translational research: a pilot implementation.

BACKGROUND: Translational researchers need robust IT solutions to access a range of data types, varying from public data sets to pseudonymised patient information with restricted access, provided on a case by case basis. The reason for this complication is that managing access policies to sensitive human data must consider issues of data confidentiality, identifiability, extent of consent, and data usage agreements. All these ethical, social and legal aspects must be incorporated into a differential management of restricted access to sensitive data. METHODS: In this paper we present a pilot system that uses several common open source software components in a novel combination to coordinate access to heterogeneous biomedical data repositories containing open data (open access) as well as sensitive data (restricted access) in the domain of biobanking and biosample research. Our approach is based on a digital identity federation and software to manage resource access entitlements. RESULTS: Open source software components were assembled and configured in such a way that they allow for different ways of restricted access according to the protection needs of the data. We have tested the resulting pilot infrastructure and assessed its performance, feasibility and reproducibility. CONCLUSIONS: Common open source software components are sufficient to allow for the creation of a secure system for differential access to sensitive data. The implementation of this system is exemplary for researchers facing similar requirements for restricted access data. Here we report experience and lessons learnt of our pilot implementation, which may be useful for similar use cases. Furthermore, we discuss possible extensions for more complex scenarios.

Legal assessment tool (LAT): an interactive tool to address privacy and data protection issues for data sharing.

BACKGROUND: In an unprecedented rate data in the life sciences is generated and stored in many different databases. An ever increasing part of this data is human health data and therefore falls under data protected by legal regulations. As part of the BioMedBridges project, which created infrastructures that connect more than 10 ESFRI research infrastructures (RI), the legal and ethical prerequisites of data sharing were examined employing a novel and pragmatic approach. METHODS: We employed concepts from computer science to create legal requirement clusters that enable legal interoperability between databases for the areas of data protection, data security, Intellectual Property (IP) and security of biosample data. We analysed and extracted access rules and constraints from all data providers (databases) involved in the building of data bridges covering many of Europe's most important databases. These requirement clusters were applied to five usage scenarios representing the data flow in different data bridges: Image bridge, Phenotype data bridge, Personalised medicine data bridge, Structural data bridge, and Biosample data bridge. A matrix was built to relate the important concepts from data protection regulations (e.g. pseudonymisation, identifyability, access control, consent management) with the results of the requirement clusters. An interactive user interface for querying the matrix for requirements necessary for compliant data sharing was created. RESULTS: To guide researchers without the need for legal expert knowledge through legal requirements, an interactive tool, the Legal Assessment Tool (LAT), was developed. LAT provides researchers interactively with a selection process to characterise the involved types of data and databases and provides suitable requirements and recommendations for concrete data access and sharing situations. The results provided by LAT are based on an analysis of the data access and sharing conditions for different kinds of data of major databases in Europe. CONCLUSIONS: Data sharing for research purposes must be opened for human health data and LAT is one of the means to achieve this aim. In summary, LAT provides requirements in an interactive way for compliant data access and sharing with appropriate safeguards, restrictions and responsibilities by introducing a culture of responsibility and data governance when dealing with human data.

Clinical Trial Information Mediator.

For research in biomedical sciences, cross-domain searches through several different databases are an increasingly necessary task that often becomes a time consuming and labour-intense process. This is especially the case when different domain databases have to be combined, for example combined searches in clinical trials registries, publication databases and research databases. The Clinical Trial Information Mediator (CTIM) addresses this problem and offers a novel way for the combined search in ClinicalTrials.gov, PubMed and BioSamples. CTIM was developed based on a requirements analysis and implemented using open source technology. A search engine with a graphical user interface was developed in order to search linked data in the three databases ClinicalTrials.gov, PubMed and BioSamples; thereby enabling CTIM to bridge the gap between different knowledge domains of clinical trials, publications of research results and biosamples/genetic information. CTIM was applied in three use cases demonstrating that information retrieval could be considerably improved in sense for complex queries. These use cases show that more relevant results were obtained and more associated publications and biosamples could be retrieved in comparison to a separate single search. Main advantages of CTIM are identifying related information between clinical trials and publications employing a clinical trial centred kind of search, simplified access to its databases and thus reduced search time. In addition it can be used by researchers without prior training because of the intuitive usage.

Ensuring sustainability of software tools and services by cooperation with a research infrastructure.

Sustainability of project output and especially of the maintenance and further development of software is of growing concern for the research community. In the personalized medicine project p-medicine solutions that address this sustainability problem were developed and discussed in a workshop. They involve a number of interrelated and mutually supportive measures including the creation of a service center, building modular software, using common data standards, mutual service exchange with a research infrastructure, Open Source and fee-based software provision, joint promotion and deployment of tools in a regulated, clinical trial situation. These ideas join a nascent literature seeking to understand how project output can be put into a sustainable environment and to suggest solutions that may be useful for academic projects in general.

Translational Medicine and Patient Safety in Europe: TRANSFoRm--Architecture for the Learning Health System in Europe.

UNLABELLED: The Learning Health System (LHS) describes linking routine healthcare systems directly with both research translation and knowledge translation as an extension of the evidence-based medicine paradigm, taking advantage of the ubiquitous use of electronic health record (EHR) systems. TRANSFoRm is an EU FP7 project that seeks to develop an infrastructure for the LHS in European primary care. METHODS: The project is based on three clinical use cases, a genotype-phenotype study in diabetes, a randomised controlled trial with gastroesophageal reflux disease, and a diagnostic decision support system for chest pain, abdominal pain, and shortness of breath. RESULTS: Four models were developed (clinical research, clinical data, provenance, and diagnosis) that form the basis of the projects approach to interoperability. These models are maintained as ontologies with binding of terms to define precise data elements. CDISC ODM and SDM standards are extended using an archetype approach to enable a two-level model of individual data elements, representing both research content and clinical content. Separate configurations of the TRANSFoRm tools serve each use case. CONCLUSIONS: The project has been successful in using ontologies and archetypes to develop a highly flexible solution to the problem of heterogeneity of data sources presented by the LHS.

Proposal for a European Public Health Research Infrastructure for Sharing of health and Medical administrative data (PHRIMA).

In Europe, health and medical administrative data is increasingly accumulating on a national level. Looking further than re-use of this data on a national level, sharing health and medical administrative data would enable large-scale analyses and European-level public health projects. There is currently no research infrastructure for this type of sharing. The PHRIMA consortium proposes to realise the Public Health Research Infrastructure for Sharing of health and Medical Administrative data (PHRIMA) which will enable and facilitate the efficient and secure sharing of healthcare data.

Extension of the primary care research object model (PCROM) as clinical research information model (CRIM) for the "learning healthcare system".

BACKGROUND: Patient data from general practices is already used for many types of epidemiological research and increasingly, primary care systems to facilitate randomized clinical trials. The EU funded project TRANSFoRm aims to create a "Learning Healthcare System" at a European level that is able to support all types of research using primary care data, to recruit patients and follow patients in clinical studies and to improve diagnosis and therapy. The implementation of such a Learning Healthcare System needs an information model for clinical research (CRIM), as an informational backbone to integrate aspects of primary care with clinical trials and database searches. METHODS: Workflow descriptions and corresponding data objects of two clinical use cases (Gastro-Oesophageal Reflux Disease and Type 2 Diabetes) were described in UML activity diagrams. The components of activity diagrams were mapped to information objects of PCROM (Primary Care Research Object Model) and BRIDG (Biomedical Research Integrated Domain Group) and evaluated. The class diagram of PCROM was adapted to comply with workflow descriptions. RESULTS: The suitability of PCROM, a primary care information model already used for clinical trials, to act as an information model for TRANSFoRm was evaluated and resulted in its extension with 14 new information object types, two extensions of existing objects and the introduction of two new high-ranking concepts (CARE area and ENTRY area). No PCROM component was redundant. Our result illustrates that in primary care based research an important but underestimated portion of research activity takes place in the area of care (e.g. patient consultation, screening, recruitment and response to adverse events). The newly introduced CARE area for care-related research activities accounts for this shift and includes Episode of Care and Encounter as two new basic elements. In the ENTRY area different aspects of data collection were combined, including data semantics for observations, assessment activities, intervention activities and patient reporting to enable case report form (CRF) based data collection combined with decision support. CONCLUSIONS: Research with primary care data needs an extended information model that covers research activities at the care site which are characteristic for primary care based research and the requirements of the complicated data collection processes.

A standardised graphic method for describing data privacy frameworks in primary care research using a flexible zone model.

PURPOSE: To develop a model describing core concepts and principles of data flow, data privacy and confidentiality, in a simple and flexible way, using concise process descriptions and a diagrammatic notation applied to research workflow processes. The model should help to generate robust data privacy frameworks for research done with patient data. METHODS: Based on an exploration of EU legal requirements for data protection and privacy, data access policies, and existing privacy frameworks of research projects, basic concepts and common processes were extracted, described and incorporated into a model with a formal graphical representation and a standardised notation. The Unified Modelling Language (UML) notation was enriched by workflow and own symbols to enable the representation of extended data flow requirements, data privacy and data security requirements, privacy enhancing techniques (PET) and to allow privacy threat analysis for research scenarios. RESULTS: Our model is built upon the concept of three privacy zones (Care Zone, Non-care Zone and Research Zone) containing databases, data transformation operators, such as data linkers and privacy filters. Using these model components, a risk gradient for moving data from a zone of high risk for patient identification to a zone of low risk can be described. The model was applied to the analysis of data flows in several general clinical research use cases and two research scenarios from the TRANSFoRm project (e.g., finding patients for clinical research and linkage of databases). The model was validated by representing research done with the NIVEL Primary Care Database in the Netherlands. CONCLUSIONS: The model allows analysis of data privacy and confidentiality issues for research with patient data in a structured way and provides a framework to specify a privacy compliant data flow, to communicate privacy requirements and to identify weak points for an adequate implementation of data privacy.

Usability on the p-medicine infrastructure: an extended usability concept.

Usability testing methods are nowadays integrated into the design and development of health-care software, and the need for usability in health-care information technology (IT) is widely accepted by clinicians and researchers. Usability assessment starts with the identification of specific objectives that need to be tested and continues with the definition of evaluation criteria and monitoring procedures before usability tests are performed to assess the quality of all services and tasks. Such a process is implemented in the p-medicine environment and gives feedback iteratively to all software developers in the project. GCP (good clinical practice) criteria require additional usability testing of the software. For the p-medicine project (www.p-medicine.eu), an extended usability concept (EUC) was developed. The EUC covers topics like ease of use, likeability, and usefulness, usability in trial centres characterised by a mixed care and research environment and by extreme time constraints, confidentiality, use of source documents, standard operating procedures (SOA), and quality control during data handling to ensure that all data are reliable and have been processed correctly in terms of accuracy, completeness, legibility, consistence, and timeliness. Here, we describe the p-medicine EUC, focusing on two of the many key tools: ObTiMA and the Ontology Annotator (OA).

Revising the ECRIN standard requirements for information technology and data management in clinical trials.

The pilot phase of the ECRIN (European Clinical Research Infrastructure Network) certification programme for European data centres, in late 2011, led to a substantial revision of the original ECRIN standards, completed by June 2012. The pilot phase, the conclusions drawn from it and the revised set of standards are described. Issues concerning the further development of standards and related material are discussed, as are the methods available to best support that development. A strategy is outlined based on short-lived specific task groups, established as necessary by a steering group drawn from ECRIN-ERIC. A final section discusses possible future developments.

Typical investigational medicinal products follow relatively uniform regulations in 10 European Clinical Research Infrastructures Network (ECRIN) countries.

BACKGROUND: In order to facilitate multinational clinical research, regulatory requirements need to become international and harmonised. The EU introduced the Directive 2001/20/EC in 2004, regulating investigational medicinal products in Europe. METHODS: We conducted a survey in order to identify the national regulatory requirements for major categories of clinical research in ten European Clinical Research Infrastructures Network (ECRIN) countries-Austria, Denmark, France, Germany, Hungary, Ireland, Italy, Spain, Sweden, and United Kingdom-covering approximately 70% of the EU population. Here we describe the results for regulatory requirements for typical investigational medicinal products, in the ten countries. RESULTS: Our results show that the ten countries have fairly harmonised definitions of typical investigational medicinal products. Clinical trials assessing typical investigational medicinal products require authorisation from a national competent authority in each of the countries surveyed. The opinion of the competent authorities is communicated to the trial sponsor within the same timelines, i.e., no more than 60 days, in all ten countries. The authority to which the application has to be sent to in the different countries is not fully harmonised. CONCLUSION: The Directive 2001/20/EC defined the term 'investigational medicinal product' and all regulatory requirements described therein are applicable to investigational medicinal products. Our survey showed, however, that those requirements had been adopted in ten European countries, not for investigational medicinal products overall, but rather a narrower category which we term 'typical' investigational medicinal products. The result is partial EU harmonisation of requirements and a relatively navigable landscape for the sponsor regarding typical investigational medicinal products.

Standard requirements for GCP-compliant data management in multinational clinical trials.

BACKGROUND: A recent survey has shown that data management in clinical trials performed by academic trial units still faces many difficulties (e.g. heterogeneity of software products, deficits in quality management, limited human and financial resources and the complexity of running a local computer centre). Unfortunately, no specific, practical and open standard for both GCP-compliant data management and the underlying IT-infrastructure is available to improve the situation. For that reason the "Working Group on Data Centres" of the European Clinical Research Infrastructures Network (ECRIN) has developed a standard specifying the requirements for high quality GCP-compliant data management in multinational clinical trials. METHODS: International, European and national regulations and guidelines relevant to GCP, data security and IT infrastructures, as well as ECRIN documents produced previously, were evaluated to provide a starting point for the development of standard requirements. The requirements were produced by expert consensus of the ECRIN Working group on Data Centres, using a structured and standardised process. The requirements were divided into two main parts: an IT part covering standards for the underlying IT infrastructure and computer systems in general, and a Data Management (DM) part covering requirements for data management applications in clinical trials. RESULTS: The standard developed includes 115 IT requirements, split into 15 separate sections, 107 DM requirements (in 12 sections) and 13 other requirements (2 sections). Sections IT01 to IT05 deal with the basic IT infrastructure while IT06 and IT07 cover validation and local software development. IT08 to IT015 concern the aspects of IT systems that directly support clinical trial management. Sections DM01 to DM03 cover the implementation of a specific clinical data management application, i.e. for a specific trial, whilst DM04 to DM12 address the data management of trials across the unit. Section IN01 is dedicated to international aspects and ST01 to the competence of a trials unit's staff. CONCLUSIONS: The standard is intended to provide an open and widely used set of requirements for GCP-compliant data management, particularly in academic trial units. It is the intention that ECRIN will use these requirements as the basis for the certification of ECRIN data centres.

Compassionate use of interventions: results of a European Clinical Research Infrastructures Network (ECRIN) survey of ten European countries.

BACKGROUND: 'Compassionate use' programmes allow medicinal products that are not authorised, but are in the development process, to be made available to patients with a severe disease who have no other satisfactory treatment available to them. We sought to understand how such programmes are regulated in ten European Union countries. METHODS: The European Clinical Research Infrastructures Network (ECRIN) conducted a comprehensive survey on clinical research regulatory requirements, including questions on regulations of 'compassionate use' programmes. Ten European countries, covering approximately 70% of the EU population, were included in the survey (Austria, Denmark, France, Germany, Hungary, Ireland, Italy, Spain, Sweden, and the UK). RESULTS: European Regulation 726/2004/EC is clear on the intentions of 'compassionate use' programmes and aimed to harmonise them in the European Union. The survey reveals that different countries have adopted different requirements and that 'compassionate use' is not interpreted in the same way across Europe. Four of the ten countries surveyed have no formal regulatory system for the programmes. We discuss the need for 'compassionate use' programmes and their regulation where protection of patients is paramount. CONCLUSIONS: 'Compassionate use' is a misleading term and should be replaced with 'expanded access'. There is a need for expanded access programmes in order to serve the interests of seriously ill patients who have no other treatment options. To protect these patients, European legislation needs to be more explicit and informative with regard to the regulatory requirements, restrictions, and responsibilities in expanded access programmes.

Heterogeneity prevails: the state of clinical trial data management in Europe - results of a survey of ECRIN centres.

BACKGROUND: The use of Clinical Data Management Systems (CDMS) has become essential in clinical trials to handle the increasing amount of data that must be collected and analyzed. With a CDMS trial data are captured at investigator sites with "electronic Case Report Forms". Although more and more of these electronic data management systems are used in academic research centres an overview of CDMS products and of available data management and quality management resources for academic clinical trials in Europe is missing. METHODS: The ECRIN (European Clinical Research Infrastructure Network) data management working group conducted a two-part standardized survey on data management, software tools, and quality management for clinical trials. The questionnaires were answered by nearly 80 centres/units (with an overall response rate of 47% and 43%) from 12 European countries and EORTC. RESULTS: Our survey shows that about 90% of centres have a CDMS in routine use. Of these CDMS nearly 50% are commercial systems; Open Source solutions don't play a major role. In general, solutions used for clinical data management are very heterogeneous: 20 different commercial CDMS products (7 Open Source solutions) in addition to 17/18 proprietary systems are in use. The most widely employed CDMS products are MACRO and Capture System, followed by solutions that are used in at least 3 centres: eResearch Network, CleanWeb, GCP Base and SAS. Although quality management systems for data management are in place in most centres/units, there exist some deficits in the area of system validation. CONCLUSIONS: Because the considerable heterogeneity of data management software solutions may be a hindrance to cooperation based on trial data exchange, standards like CDISC (Clinical Data Interchange Standard Consortium) should be implemented more widely. In a heterogeneous environment the use of data standards can simplify data exchange, increase the quality of data and prepare centres for new developments (e.g. the use of EHR for clinical research). Because data management and the use of electronic data capture systems in clinical trials are characterized by the impact of regulations and guidelines, ethical concerns are discussed. In this context quality management becomes an important part of compliant data management. To address these issues ECRIN will establish certified data centres to support electronic data management and associated compliance needs of clinical trial centres in Europe.

Common definition for categories of clinical research: a prerequisite for a survey on regulatory requirements by the European Clinical Research Infrastructures Network (ECRIN).

BACKGROUND: Thorough knowledge of the regulatory requirements is a challenging prerequisite for conducting multinational clinical studies in Europe given their complexity and heterogeneity in regulation and perception across the EU member states. METHODS: In order to summarise the current situation in relation to the wide spectrum of clinical research, the European Clinical Research Infrastructures Network (ECRIN) developed a multinational survey in ten European countries. However a lack of common classification framework for major categories of clinical research was identified, and therefore reaching an agreement on a common classification was the initial step in the development of the survey. RESULTS: The ECRIN transnational working group on regulation, composed of experts in the field of clinical research from ten European countries, defined seven major categories of clinical research that seem relevant from both the regulatory and the scientific points of view, and correspond to congruent definitions in all countries: clinical trials on medicinal products; clinical trials on medical devices; other therapeutic trials (including surgery trials, transplantation trials, transfusion trials, trials with cell therapy, etc.); diagnostic studies; clinical research on nutrition; other interventional clinical research (including trials in complementary and alternative medicine, trials with collection of blood or tissue samples, physiology studies, etc.); and epidemiology studies. Our classification was essential to develop a survey focused on protocol submission to ethics committees and competent authorities, procedures for amendments, requirements for sponsor and insurance, and adverse event reporting following five main phases: drafting, consensus, data collection, validation, and finalising. CONCLUSION: The list of clinical research categories as used for the survey could serve as a contribution to the, much needed, task of harmonisation and simplification of the regulatory requirements for clinical research in Europe.

CDISC standard-based electronic archiving of clinical trials.

OBJECTIVES: Our objectives were to develop, based on the analysis of archived clinical trial documents and data and on the requirements of GCP-compliant electronic archiving, a concept for legally secure and technically feasible archiving of the entire clinical trial, including the essential documents of the trial master file and the study database. METHODS: Based on own experiences with CDISC, existing implementations and future developments, CDISC standards were evaluated concerning requirements for archiving clinical studies. Trial master files of a small, medium and large clinical study were analyzed to collect specifications for electronic archiving of records. RESULTS: Two different ways of long-term storage exist for the clinical trial archive: document-oriented archival and data archiving of the study database. The trial master file has a highly complex structure; its different parts can vary greatly in size, depending of the working style of investigators, number of patients recruited, the number of adverse event reports and the number of queries. The CDISC standard ODM is especially suited for archiving clinical trials, because among other features it contains the entire clinical trial data and full audit trail information. On the other hand SDTM is a content standard suited for data warehouses. Two recent developments in CDISC will affect the archival of studies: the further development of ODM in the area of "eCRF submission" and the use of "Electronic Source Data". CONCLUSIONS: The complexity and size of the trial master file requires new solutions. Though ODM provides effective means to archive the study database, it shows still deficiencies, especially for the joint archiving of data and the complex documentation of the trial master file. A concept was developed in which the ODM standard is part of an integrated archiving of the trial data and documents. ODM archiving of the study database enables long-term storage which is GCP-compliant. Archiving of documents of the trial master file in PDF/A, including links and electronic signatures, as well as the storage of selected study data in a data warehouse at the sponsor site in SDTM are the other components of the concept.