UNCORRECTED PROOF DTD 5 TECHNOLOGIES DRUGDISCOVERY TODAY Competitive intelligence and patent analysis in drug discovery Mining the competitive knowledge bases and patents Nicolas Grandjean * , Brigitte Charpiot, Carlos Andres Pena, Manuel C. Peitsch Genome and Proteome Sciences, Novartis Institutes for Biomedical Research, Basel, Switzerland Patents are a major source of information in drug discovery and, when properly processed and analyzed, can yield a wealth of information on competitors activ- ities, R&D trends, emerging fields, collaborations, among others. This review discusses the current state-of-the-art in textual data analysis and exploration methods as applied to patent analysis. Section Editor: Manuel Peitsch – Novartis, Switzerland Introduction Current patent office procedures normally result in the pub- lication of patent applications 18 months after the filing date. Therefore, patent applications cover the discovery work that took place approximately 2 years before disclosure. Despite this delay and despite the widely varying filing practices, patents remain one of the most reliable and comprehensive source of information on R&D activity and together with the products in development and market data form the backbone of competitive intelligence activities in the pharmaceutical industry. All business-crucial inventions must be protected, and both for practical and legal reasons (such as unity of invention), every crucial invention results in a patent appli- cation. Taking into account the filing practices (broad or specific applications, filing routes, territorial protection sought, among others) associated with specific companies or domains (e.g. genomics), the analysis of patent portfolios can give a reasonably accurate idea of the volume of the activity in specific research areas, reveal the underlying trends, detect emerging or hidden information or deviations from expected patterns, among others. Patent analysis can also yield a wealth of information related to research activity, for example on collaborations, location of research work, key inventors and licensing. Quality of patent data Whereas new chemical entities, molecular targets and mechanisms are usually clearly described, patent applications often lack precision on potential therapeutic uses of an invention. Thus, the patent portfolio of a company can give some hints on its R&D strategy but might not be effectively predictive of the future clinical development activities. More sophisticated models based on past filing practices, products in development and/or internal project perimeters (physio- logical processes/pharmacological targets/therapeutic indica- tions) can be applied to gain a clearer understanding of a company’s strategy. The problem of the lack of precision of patent applications is compounded by the shortcomings of both the published applications (verbose and opaque descriptions of the inven- tion) and secondary sources. The indexing schemes applied Drug Discovery Today: Technologies Vol. xxx, No. xx 2005 Editors-in-Chief Kelvin Lam – Pfizer, Inc., USA Henk Timmerman – Vrije Universiteit, The Netherlands Knowledge management 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 7 8 9 7 8 9 10 7 8 9 10 11 7 8 9 10 11 12 7 8 9 10 11 12 13 7 8 9 10 11 12 13 14 7 8 9 10 11 12 13 14 15 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 16 17 18 10 11 11 12 13 12 13 14 15 13 14 15 13 14 15 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 *Corresponding author: N. Grandjean (nicolas.grandjean@novartis.com) 1740-6749/$ ß 2005 Elsevier Ltd. All rights reserved. DOI: 10.1016/j.ddtec.2005.08.007 www.drugdiscoverytoday.com 1 DDTEC 104 1–5