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

Abstract

In recent years, a cultural change in the handling of research Background: 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.: Principles and recommendations from a published consensus Methods 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.A detailed and comprehensive tabulation of individual processes Results: 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.The identification of the individual processes and Conclusions: 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.

Legal regulations, ethical guidelines and recent policies to increase transparency of clinical trials

“…Over recent years, the importance of sharing data from clinical trials has substantially grown and several major organizations and institutions have developed policies and recommendations to promote the development of data sharing . However, data sharing is a very complex enterprise, both legally and logistically . One of the main challenges in data sharing is obtaining consent of trial participants for future unspecified use of generated data, which is related to the necessity to ensure the compliance with the current legal data privacy protection standards .…”

“…This problem becomes even more complicated in view of differences in legal regulations relevant to data sharing adopted in different countries. In addition, a major logistical problems associated with data sharing is a lack of complete infrastructure to suport sharing data on a global scale …”

“…17 However, data sharing is a very complex enterprise, both legally and logistically. 17,18 One of the main challenges in data sharing is obtaining consent of trial participants for future unspecified use of generated data, which is related to the necessity to ensure the compliance with the current legal data privacy protection standards. 17 This problem becomes even more complicated in view of differences in legal regulations relevant to data sharing adopted in different countries.…”

“…In addition, a major logistical problems associated with data sharing is a lack of complete infrastructure to suport sharing data on a global scale. 18 Therefore, despite many benefits of data sharing and a wide promotion of this idea, 16,17 the access of investigators to individual participant-level datasets remains rather limited. For instance, a recent study showed that only 15% of clinical trials sponsored by pharmaceutical industry were available for data sharing 2 years after publication of primary results.…”

Individual Patient-Level Data Sharing for Continuous Learning: A Strategy for Trial Data Sharing

“…Although there are potential benefi ts to IPD sharing, there are also many barriers that have yet to be addressed [6,8,9,10,11]. Contentious issues include consent for data sharing and the sharing of anonymized data, sustainable infrastructure and resources to support the preparation of IPD and metadata, and the heterogeneity of data repositories and related tools [9,12,13]. Also, limited guidance exists on the role of the primary research team in preparing IPD, the responsibilities of secondary research teams to ensure valid analyses, and the process by which confl icting fi ndings should be reconciled [14,15].…”