Searching and Analyzing Patent-Relevant Information for Evaluating COVID-19 Innovation

60 Pages Posted: 26 Jan 2021

See all articles by Luca Falciola

Luca Falciola

Scibilis SRL

Massimo Barbieri

Politecnico di Milano (Technology Transfer Office)

Date Written: December 4, 2020

Abstract

The COVID-19 pandemic has prompted several institutions to offer free, dedicated websites and tools to foster research and access to urgently needed innovation by facilitating the search and analysis of information within the large amount of scientific and patent literature which was published in a very short period of time. This situation is clearly exceptional and challenging for patent information professionals searching for relevant data and disclosures in a reliable manner. This article provides an overview of search criteria and strategies, main databases and websites, origin and number of publications, biological sequence information, and experimental data sets covering COVID-19 findings within scientific and patent literature disclosed between January and August 2020. The analysis of non-patent literature is focused on the identification, date assignment, disambiguation, and access to experimental data. The analysis of patent literature is focused on the trends found within the earliest filed and published patent documents as observed in the patent databases, and for the main jurisdictions, worldwide. Some practical advice and strategies for future technical, medical, or patentability assessment of COVID-19-related innovations are suggested by this quantitative and qualitative analysis across information resources.

Keywords: SARS-CoV-2, patent databases, patent classifications, patent searching, open access, patent landscaping, scientific publishing, data-mining, coronavirus, pandemic, 2019-nCoV, viral proteins

JEL Classification: O31, O33, O34, I1, I10, I11, I15, I18, K11

Suggested Citation

Falciola, Luca and Barbieri, Massimo, Searching and Analyzing Patent-Relevant Information for Evaluating COVID-19 Innovation (December 4, 2020). Available at SSRN: https://ssrn.com/abstract=3771756 or http://dx.doi.org/10.2139/ssrn.3771756

Luca Falciola (Contact Author)

Scibilis SRL ( email )

Bruxelles
Belgium

Massimo Barbieri

Politecnico di Milano (Technology Transfer Office) ( email )

Piazza Leonardo da Vinci n. 32
Milan, Milano 20133
Italy
+390223999233 (Phone)

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