Biotechnology

Standards, Data Exchange and Intellectual Property Rights in Systems Biology

By Timo Minssen I am happy to announce that our recent paper on “Standards, Data Exchange and Intellectual Property Rights in Systems Biology” has been published in the Biotechnology Journal Vol 11, Issue 12, pp. 1477-1480.  The paper was co-authored by Esther Van Zimmeren from the University of Antwerp, Berthold Rutz from the European Patent Office and me. Please…

By Timo Minssen

I am happy to announce that our recent paper on “Standards, Data Exchange and Intellectual Property Rights in Systems Biology” has been published in the Biotechnology Journal Vol 11, Issue 12, pp. 1477-1480.  The paper was co-authored by Esther Van Zimmeren from the University of Antwerp, Berthold Rutz from the European Patent Office and me. Please find a summary below:

Intellectual property rights (IPRs) represent a key concern for researchers and industry in basically all high-tech sectors. IPRs regularly figure prominently in scientific journals and at scientific conferences and lead to dedicated workshops to increase the awareness and “IPR savviness” of scientists. In 2015, Biotechnology Journal published a report from an expert meeting on “Synthetic Biology & Intellectual Property Rights” organized by the Danish Agency for Science, Technology and Innovation sponsored by the European Research Area Network (ERA-Net) in Synthetic Biology (ERASynBio), in which we provided a number of recommendations for a variety of stakeholders. The current article offers some deeper reflections about the interface between IPRs, standards and data exchange in Systems Biology resulting from an Expert Meeting funded by another ERA-Net, ERASysAPP. The meeting brought together experts and stakeholders (e.g. scientists, company representatives, officials from public funding organizations) in systems biology (SysBio) from different countries.  Despite the different profiles of the stakeholders at the meeting and the variety of interests, many concerns and opinions were shared. In case particular views were expressed by a specific type of stakeholder, this will be explicitly mentioned in the text. This article reflects on a number of particularly relevant issues that were discussed at the meeting and offers some recommendations.

SysBio involves the study of biological systems at a so-called systems level. This is not a new concept in the life sciences – many former approaches in physiology, enzymology and other scientific disciplines have already taken a systemic view of selected biological subjects. Yet, SysBio has gained strong interest within the past 10 to 15 years. One predominant reason and a critical prerequisite for this success story being that the relevant scientific methodologies and research tools have become far more powerful and accurate.  Remarkable technical progress allows scientists to generate, collect, display and analyse quantitative and qualitative data on biological processes and activities in much greater volumes, velocity, variety and veracity. The skilful integration of multiple heterogeneous data sets allows scientists to model and predict biological processes. SysBio’s interdisciplinary nature requires data, models and other research assets to be formatted and described in standard ways to enable exchange and reuse of high quality data. This allows a more effective utilisation of the enormous potential that rests in “big data” analysis. Finally, SysBio is often closely linked to or provides the foundation for Synthetic Biology (SynBio). Standardization and data exchange in SysBio may result in challenges and opportunities related to IPRs.

The aim of this article is to raise awareness on these issues within the SysBio scientific community and to stimulate exploration of different strategies for dealing with IPRs in order to optimize access to and use of valuable research results.

Original language English
Journal Biotechnology Journal
ISSN 1860-6768
State

Published 14 December 2016, available at: https://onlinelibrary.wiley.com/doi/10.1002/biot.201600109/full

DOI 10.1002/biot.201600109