Christopher Anthony Cotropia, University of Richmond - School of Law and David L. Schwartz, Northwestern University - Pritzker School of Law

The economic literature emphasizes the importance of patent citations, particularly forward citations, as an indicator of a cited patent’s value. Studies have refined which forward citations are better indicators of value, focusing on examiner citations for example. We test a metric that arguably is closer tied to private value—the substantive use of a patent by an examiner in a patent office rejection of another pending patent application. This paper assesses how patents used in 102 and 103 rejections relate to common measures of private value—specifically patent renewal, the assertion of a patent in litigation, and the number of patent claims. We examine rejection data from U.S. patent applications pending from 2008 to 2017 and then link value data to rejection citations to patents issued from 1999 to 2007. Our findings show that rejection patents are independently, positively correlated with many of the value measurements above and beyond forward citations and examiner citations.

The Sankey diagram, above, shows the relationship between forward citation and 102 and 103 rejection use, depicting a shuffle amongst quartiles from the citation of a patent to its use in a rejection. Even patents in the lowest quartile of citation appear in the highest quartile of actual rejections, and vice versa, emphasizing the new and valuable information rejection use provides.

Download paper at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3274995

Jordan A. Comins[i],*,‡, Stephanie A. Carmack[ii], and Loet Leydesdorff[iii]

One essential component in the construction of patent landscapes in biomedical research and development (R&D) is identifying the most seminal patents. Hitherto, the identification of seminal patents required subject matter experts within biomedical areas. In this brief communication, we report an analytical method and tool, Patent Citation Spectroscopy (PCS), for the online identification of landmark patents in user-specified areas of biomedical innovation. Using USPTO data and the PatentsView API, PCS mines the cited references within large sets of patents and provides an estimate of the most historically impactful prior work.

The figure shows the results of PCS applied to a broad set of patents dealing with cholesterol. PCS mined through 11,326 cited references and identified the seminal patent as that for Lipitor, the groundbreaking medication for treating high cholesterol as well as the pair of patents underlying Repatha. The cases suggest that PCS provides a useful method for identifying seminal patents in areas of biomedical innovation and therapeutics. The interactive tool is free-to-use at: http://www.leydesdorff.net/comins/pcs/.

Figure: Image of the PCS web-application at http://leydesdorff.net/pcs. In this demo, the user queried patents containing either the key terms “RNAi” or “siRNA” or the phrases “interference RNA” or “RNA interference.” The system then searched the titles and abstracts of US patents within the PatentsView database for these search terms. The result was 1,217 granted US patents containing 4,065 unique patent references. The patent references were analyzed via PCS to produce a visualization of the spectrum of impactful historical patent references. PCS identified the most important historical patent for this field: US6506559 – Genetic inhibition by double-stranded RNA by Fire et al.  (2003), a finding that converges with independent reports from subject matter experts (Schmidt et al., 2007).

< preprint version at https://arxiv.org/abs/1710.03349 >

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[i] *corresponding author; Social and Behavioral Sciences Department, The MITRE Corporation, McLean, VA, United States; jcomins@gmail.com

‡ The author's affiliation with The MITRE Corporation is provided for identification purposes only, and is not intended to convey or imply MITRE's concurrence with, or support for, the positions, opinions or viewpoints expressed by the author. Approved for Public Release; Distribution Unlimited Case #17-0951.

[ii] National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, 21224

[iii] Amsterdam School of Communication Research (ASCoR), University of Amsterdam, PO Box 15793, 1001 NG Amsterdam, The Netherlands

The USPTO's Office of Chief Economist developed the InventorAnalyze package for bibliometric (and other) researchers studying the social networks of inventors, i.e., the community of inventors who collaborate on jointly invented patents. The InventorAnalyze package combines disambiguated patent data from the United States Patent and Trademark Office's PatentsView project with social network analysis tools from the Los Alamos National Laboratory's NetworkX library.  PatentsView uses a statistical algorithm for disambiguating patent inventor names, so that multiple variants of a name are assigned a common identifier and distinct inventors having a similar name are assigned separate identifiers. Such entity resolution is critical to identifying inventors and their collaborators over millions of distinct patents.

By importing disambiguated inventor data from PatentsView into NetworkX, InventorAnalyze enables researchers to more accurately study the entire inventor social network. Moreover, the package facilitates analysis of specific inventor network subgraphs generated via PatentsView API-based queries. InventorAnalyze then leverages NetworkX functionality to study the structure, dynamics, and functions of these inventor subnetworks.

The team provides two examples of the type of inventor social network analysis facilitated by InventorAnalyze. The first example demonstrates some of the network-level analysis capabilities that InventorAnalyze facilitates. The second example shows the potential information that network-based metrics can convey about individual inventors and their influence.

The package is a Python script authored by Jesse Frumkin at USPTO and available on GitHub. The full report is here.

Chris Baker, data scientist at the Virginia Tech Applied Research Corporation, developed the patentsview R package that is a wrapper around the PatentsView API. It contains a function that acts as a client to the API (search_pv()) as well as several supporting functions. Full documentation of the package can be found on its website.

The library offers ways to query the API, process the data, and develop visualizations to track interesting patterns in patenting activity. For analysis examples that go into a little more depth, check out the data applications vignettes on the package's website.

The R Open Science blog has more details.

Scientific American published an article on November 1, 2016, using PatentsView data and visualizations developed by Periscopic who are behind the PatentsView visualization interface and other tools. The U.S. Patent and Trademark Office analyzed patents for employees at three large tech companies: Tesla, Facebook, and Intrexon. The analysis reveals different patterns of collaboration in inventor teams and demonstrates there is more than one way to create success.

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