Abstract
This article presents the global patent landscape for synthetic biology as a new and emerging area of science and technology. The aim of the article is to provide an overview of the emergence of synthetic biology in the patent system and to contribute to future research by providing a high quality tagged core dataset with 7,424 first filings and 71,887 family members. This dataset is intended to assist with evidence based exploration of synthetic biology in the patent system and with advancing methods for the analysis of new and emerging areas of science and technology.
The starting point for the research is recognition that traditional methods of patent landscape analysis based on key word searches face limitations when addressing new and emerging areas of science and technology. Synthetic biology can be broadly described as involving the design, synthesis and assembly of biological parts, circuits, pathways, cells and genomes. As such synthetic biology can be understood as emerging from a combination of overlaps and convergences between existing fields and disciplines, such as biotechnology, genetic engineering, protein engineering and systems biology. More precisely, synthetic biology can be understood as the synthetic phase of molecular biology and genetic engineering. This presents the problem that key word strategies may radically overestimate activity because they involve terms that are widely used in underlying fields that are contributing to synthetic biology.
In response to this problem we combined anthropology, scientometrics and data science to map authors from scientific publications on synthetic biology into the international patent system. We mapped 10,816 authors into the international patent system and identified 2,450 authors of articles on synthetic biology who are also inventors in the period to December 2017. By combining this data with citation information and a baseline keyword strategy we are able to describe the global patent landscape for synthetic biology and the wider patent universe in which synthetic biology is situated.
This article describes the main features of the global landscape and provides the tagged dataset as a contribution to evidence based debate on intellectual property and synthetic biology and methodological development. We anticipate that the data will prove useful in informing international policy debates on synthetic biology under the United Nations Convention on Biological Diversity.
