Patent citation spectroscopy (PCS): Online retrieval of landmark patents based on an algorithmic approach

Jordan A. Comins, Stephanie A. Carmack and Loet Leydesdorff

Journal of Informetrics, 2018, vol. 12, issue 4, 1223-1231

Abstract: 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 article, 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, PCS mines the cited references within large sets of patents at the internet and provides an estimate of the historically most impactful prior work. We show the efficacy of PCS in three case studies of biomedical innovation with clinical relevance: (1) RNA interference (RNAi), (2) cholesterol and (3) cloning. PCS mined and analyzed cited references related to patents on RNA interference and correctly identified the foundational patent of this technology, as independently reported by subject matter experts on RNAi intellectual property. Secondly, we apply PCS to a broad set of patents dealing with cholesterol – a case study chosen to reflect a more general, as opposed to expert, patent search query. PCS mined through 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 final case study, cloning, highlights some of the advantages conferred by the PCS methodology in identifying seminal patents. These 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/index.html.

Keywords: Historiography; Landmark patents; Biomedicine; Cholesterol; Interference RNA; Cloning (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1751157717304492
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:12:y:2018:i:4:p:1223-1231

DOI: 10.1016/j.joi.2018.10.002

Access Statistics for this article

Journal of Informetrics is currently edited by Leo Egghe

More articles in Journal of Informetrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().