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.

Read more...

The USPTO has developed a new dataset to describe patents and patent applications in cancer-related fields, in support of the US Cancer Moonshot.  By harnessing the power of patent data, and accelerating the process for protecting the intellectual property that lead to cancer research breakthroughs, the USPTO is standing up and doing its part to help bring potentially life-saving treatments to patients, faster.

The USPTO Cancer Moonshot Patent Data consists of 269,353 patent documents (published patent applications and granted patents) ranging from 1976 to 2016.  USPTO is sharing this dataset with researchers and policy makers, so they might gain insight into innovations in cancer-related research and development.  

PatentsView is a patent data dissemination platform that uses advanced algorithms to identify inventors and their organizations and locations across 40 years of US patent data.  The PatentsView team used the Cancer Moonshot Patent Data to identify a subset of cancer-related granted patents from their database.   

The PatentsView team then developed an interactive map to visualize geographic trends in cancer-related innovations over time. Specifically, the map presents the numbers of inventors and patents in cities worldwide, year by year.  It represents 108,923 patents granted between 1976 and 2016 and 127,076 worldwide inventors listed on those patents.

More information is available at the USPTO Developer Site.