gms | German Medical Science

53. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

15. bis 18.09.2008, Stuttgart

Developing your current eClinical systems for improved efficiency. End-to-end electronic data flow from protocol to submission

Meeting Abstract

Suche in Medline nach

  • Henning Lux - Quadratek Data Solutions Ltd., Berlin, Deutschland

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 53. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds). Stuttgart, 15.-19.09.2008. Düsseldorf: German Medical Science GMS Publishing House; 2008. DocMI5-5

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Veröffentlicht: 10. September 2008

© 2008 Lux.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen ( Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.



In the recent years EDC has been widely adopted by all major pharmaceutical companies. The industry has gone through a steep learning curve to find ways to make EDC work in the real world. This has resulted in a better understanding of the issues encountered with the early adoption of EDC, requiring changes in roles and workflow rather than technical solutions.

To fulfil the vast requirements of data management and integration at the back-end, EDC systems had to evolve beyond the initial scope of electronic data capture into ‘eClinical Solutions’. More and more people have identified EDC as the central component of eClinical and have moved away from their traditional central CDM systems.

Now, with solid and comprehensive data standards and new software technology on the horizon, the perception of eClinical is changing. Rather than seeing it as one monolithic system, an eClinical solution can be built by combining the best-of-breed-systems in the various fields of eClinical into one seamlessly integrated solution. This approach not only helps to improve efficiency and data quality but also to protect the substantial financial investment in eClinical technology.

The backbone of a modular eClinical system is a comprehensive metadata model that allows the definition of study metadata in a system and technology neutral way. Standards based on CDISC ODM enable the seamless integration of already existing EDC and patient diary solutions. In addition, a technology independent definition of metadata forms the basis for other data management and analysis tools such as SAS or SQL based reporting tools.

A modular eClinical solution requires comprehensive support for the integration of data from various sources. A repository for all combined study data should support a company standard data format that is ideally suited for reporting, analysis and exporting into the standard CDISC submission format. This task of data integration is central to the efficient operation of an eClinical solution and should not be compromised by tedious data conversions and mappings.

The role of EDC within a modular eClinical approach is focused around the efficient collection of quality data at the investigational site and data monitoring. New technologies such as AJAX can help to greatly improve the user experience and to provide a much more structured and informative eCRF. The aim is to provide the investigator with an eCRF that resembles the richness of traditional paper CRFs and at the same time provides much more active support and guidance.

Laboratory Data is a central component of clinical trials and therefore demands particular attention in any eClinical system. Although it is similar in nature to other data it has a substantially different lifecycle. Experience has shown problems with loading laboratory data directly into the eCRF of EDC systems. A more promising approach is to merge laboratory data with data from other data sources into a central data repository. To display the data within a eCRF, EDC systems can provide views on that data without the need for actually making the data part of the eCRF. This helps to solve the issues of mass import of laboratory data and at the same time supports the challenging data workflow of clinical significance judgement.