Predicting Key Example Compounds in Competitors' Patent Applications Using Structural Information Alone

Abstract

In drug discovery programs, predicting key example compounds in competitors' patent applications is important work for scientists working in the same or in related research areas. In general, medicinal chemists are responsible for this work, and they attempt to guess the identity of key compounds based on information provided in patent applications, such as biological data, scale of reaction, and/or optimization of the salt form for a particular compound. However, this is sometimes made difficult by the lack of such information. This paper describes a method for predicting key compounds in competitors' patent applications by using only structural information of example compounds. Based on the assumption that medicinal chemists usually carry out extensive structure--activity relationship (SAR) studies around key compounds, the method identifies compounds located at the centers of densely populated regions in the patent examples' chemical space, as represented by Extended Connectivity Fingerprints (ECFPs). For the validation of the method, a total of 30 patents containing structures of launched drugs were selected to test whether or not the method is able to predict key compounds (the launched drugs). In 17 out of the 30 patents (57%), the method was able to successfully predict the key compounds. The result indicates that our method could provide an alternative approach to predicting key compounds in cases where the conventional medicinal chemist's approach does not work well. This method could also be used as a complement to the traditional medicinal chemist's approach.

Managing expectations: assessment of chemistry databases generated by automated extraction of chemical structures from patents

“…Examples of further data mining and cheminformatics methods applied to SureChEMBL compounds from patent documents are available as IPython Notebooks [ 16 ]. The notebooks aim to identify genuinely novel structures and series as claimed in a patent, along with methods to retrospectively flag key compounds [ 17 , 18 ].

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The Essential Roles of Chemistry in High-Throughput Screening Triage

“…We were eventually able to download approximately 10 K structures (at approximately US$1 per structure) and view a project chemical landscape where links to the literature were associated with structure, and structures were grouped by similarity. This project eventually died from lack of senior management support, although apparently similar ideas did surface elsewhere within the organization, as structures from patents were used to gauge the relative importance of claimed compounds [117].…”

SCRIPDB: a portal for easy access to syntheses, chemicals and reactions in patents

“…In addition to their direct value in intellectual property licensing (15) and competitive business analysis (16), patents can serve as a useful resource for a variety of academic research. We examine the datasets used in previous research and show that the data available in SCRIPDB is sufficient, quantitatively and qualitatively, to provide value for future investigations.…”