Patent Literature

Why to search in patent literature?

At the beginning of every research or development project, a thorough study of the state of the art should be conducted. This is particularly advisable for three reasons:

  • Gaining insight into the latest progress in the respective field.
  • Avoiding duplication of effort.
  • Protecting the project against possible future infringement proceedings as soon as possible.

One of the most effective information sources for studying the state of the art of a technology is the patent literature:

  • One estimates that  80% of current technical knowledge can only be found in patent documents.
  • Patents – due to their strict publishing procedures – contain very detailed technical information which often cannot be found in any other publicly availabe information.
  • Information in patents is always up-to-date, since the patent documents in their majority have to be publicly published 18 months after the first filing at the latest.
  • Commercially available databases (e.g. contain the complete set of patents worldwide and offer tools to efficiently search in huge collections, including semantic algorithms and statistical support.

Worldwide coverage

The database which is at the foundation of ChemAnalyser, currently contains records of about 100M patents worldwide, i.e. from 103 patent issuing authorities of all continents.

To give you a quick impression of this worldwide coverage, the approximate filing numbers of just the most important authorities (patent offices) in the last 20 years are listed below:

Chemical patents

In an ever increasing amount, chemical drawings are added to the text for illustration of the respective structure; standardized file formats for this purpose, implemented in our database, are CDX and MOL (information about the atoms and chemical bonding of a molecule).

To extract the chemistry specific knowledge as efficiently as possible, ChemAnalyser applies proprietary automated knowledge extraction processes based on chemical named entity recognition (NER) in a semantic context. Furthermore, ChemAnalyser recognizes and extracts relevant relationships between the NERs or identifies correlations between the chemical structure of a chemical compound and its biomedical impact.