Paper Info
Title
Patent Citation Spectroscopy (PCS): Algorithmic retrieval of landmark patents.
Abstract
One essential component in the construction of patent landscapes in biomedical research and development (Ru0026D) 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 rapidly identifying landmark patents in user-specified areas of biomedical innovation. PCS mines the cited references within large sets of patents and provides an estimate of the most historically impactful prior work. The efficacy of PCS is shown in two case studies of biomedical innovation with clinical relevance: (1) RNA interference and (2) cholesterol. PCS mined and analyzed 4,065 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, PCS was applied 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 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. 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: www.leydesdorff.net/pcs/.
Year
Venue
Field
2017
arXiv: Digital Libraries
Data science,Data mining,Patent search,Information retrieval,Patent citation,Computer science,Subject-matter expert,Intellectual property,Landmark
DocType
Volume
Citations 
Journal
abs/1710.03349
1
PageRank 
References 
Authors
0.39
10
3
Name
Order
Citations
PageRank
Jordan A. Comins1556.51
Stephanie A. Carmack210.39
Loet Leydesdorff34987381.86