European Journal of Human Genetics (2015) 23, 141–146; doi:10.1038/ejhg.2014.71; published online 7 May 2014

Dynamic consent: a patient interface for twenty-first century research networks

Jane Kaye1, Edgar A Whitley2, David Lund3, Michael Morrison1, Harriet Teare1 and Karen Melham1

  1. 1Centre for Health, Law and Emerging Technologies (HeLEX), Nuffield Department of Population Health, University of Oxford, Oxford, UK
  2. 2Information Systems and Innovation Group, Department of Management, London School of Economics and Political Science, London, UK
  3. 3HW Communications Ltd, Parkfield, Lancaster, UK

Correspondence: Dr J Kaye, Centre for Health, Law and Emerging Technologies (HeLEX), Nuffield Department of Population Health, University of Oxford, Rosemary Rue Building, Old Road Campus, Oxford OX3 7LF, UK. Tel: +44 01865 287898; Fax: +44 01865 617792; E-mail:

Received 25 November 2013; Revised 25 February 2014; Accepted 18 March 2014
Advance online publication 7 May 2014



Biomedical research is being transformed through the application of information technologies that allow ever greater amounts of data to be shared on an unprecedented scale. However, the methods for involving participants have not kept pace with changes in research capability. In an era when information is shared digitally at the global level, mechanisms of informed consent remain static, paper-based and organised around national boundaries and legal frameworks. Dynamic consent (DC) is both a specific project and a wider concept that offers a new approach to consent; one designed to meet the needs of the twenty-first century research landscape. At the heart of DC is a personalised, digital communication interface that connects researchers and participants, placing participants at the heart of decision making. The interface facilitates two-way communication to stimulate a more engaged, informed and scientifically literate participant population where individuals can tailor and manage their own consent preferences. The technical architecture of DC includes components that can securely encrypt sensitive data and allow participant consent preferences to travel with their data and samples when they are shared with third parties. In addition to improving transparency and public trust, this system benefits researchers by streamlining recruitment and enabling more efficient participant recontact. DC has mainly been developed in biobanking contexts, but it also has potential application in other domains for a variety of purposes.



The twenty-first century has been marked by considerable innovation in the field of information technology (IT), which has led to rapid changes in the way that biomedical research is carried out.1 Biomedical research is now heavily dependent upon infrastructures such as biobanks and data repositories and is ‘increasingly of a global nature with data and samples exchanged, accumulated and created through a number of dynamic research networks and consortia that involve multi-disciplinary teams located in different countries’.2 This new way of doing research has been accompanied by the development of new ethical norms, practices and standards particularly in the area of consent.3 Despite innovations in the use of technology to develop research capabilities, the potential to use technology to address some of the ethical and legal issues around research participation has not been fully realised.4

This paper describes the dynamic consent model, which is an example of how IT can be used to satisfy the legal and regulatory requirements for research consent, while at the same time providing a personalised communication interface for interacting with patients, participants and citizens. It was initially developed in the field of biobanking but has the potential to be applied more broadly to situations where there are multiple and varied uses of data requiring different kinds of consent over a long period of time. Therefore, ‘dynamic consent’ refers to a specific project in the field of biobanking but is also a more general concept and approach that has the potential to radically change the nature of participation in both clinical care and research.



Implementing a dynamic consent model requires cultural change for both health-care professionals and individuals. It requires partnerships for health that are open, transparent and engaging, and which understand and value the central role that patients have in research as the providers of information and biological material. It also requires development of new policies, standards and ways of working that can accompany this approach. The system must have the technical capacity to interface with the systems of the biobanks and research organisations so it can provide information and feedback to participants. New processes and technology for testing and monitoring the integrity of dynamic consent technologies must be developed, to provide operational control for managing risk throughout the lifetime of the data holding. This requires investment of resources such as time, money, expertise and, most importantly, a commitment to such a vision by clinicians and researchers, health-care services, research institutions and governments. Although there are a number of challenges for implementing dynamic consent, the opportunities that the model will provide, using technology to streamline recruitment, consent and re-consent processes and involve more people in research, will be substantial.



New technologies have improved biomedical research and have led to significant changes in practice. Dynamic consent is an example of using IT to meet the ethical and legal requirements for consent and also providing a means to communicate, engage and recruit individuals into research.

The initial work for dynamic consent was carried out in the EnCoRe project (June 2008 to April 2012).42 It was developed in the context of three biobanks – the Oxford Radcliffe Biobank, the Oxford Musculoskeletal Biobank, and the Oxford Biobank. Another high-profile example of the dynamic consent concept is Reg4All.43

Currently, dynamic consent systems are being designed for the biobanking context. The technical design of the dynamic consent architecture enables the same interface to be used in clinical or other research contexts. Consent could be obtained for research uses of surplus tissue, de novo research projects, organ donation and clinical trials. These consents could support the flow of new knowledge between the laboratory and the clinic that is central to translational research and personalised medicine. Research continues to develop, and new questions arise. As discussion continues about feedback relating to incidental findings discovered during medical research (particularly genomic analysis), the interface would provide a useful means to broach this issue with participants. It could enable researchers to gain a better sense of participants' views on incidental findings and could ultimately provide the opportunity for participants to be better informed and to set specific preferences relating to what feedback they would like, and when and how it is received. Therefore, while dynamic consent is currently a biobanking project, it is also an approach or concept that is being applied more broadly, not only within health but also in other fields.


Conflict of interest

The authors declare no conflict of interest.



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JK is funded under Wellcome Trust Award 096599/2/11/Z and the EU F7 project BIOSHARE. MM is funded through Innovative Medicines Initiative Joint Undertaking under grant agreement number 115439 (StemBANCC), resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution. HT is funded under the Innovative Medicines Initiative joint Undertaking under grant agreement number 115005, resources of which are composed of financial contribution from the European Union‘s seventh Framework Programme (FP7/2007–2013) and EFPIA companies’ in kind contribution. KM is funded under the NIHR Biomedical Research Centre, Oxford. Background work was partially supported by the Technology Strategy Board; the Engineering and Physical Sciences Research Council and the Economic and Social Research Council (grant number EP/G002541/1) for JK, EW and DL.

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