Non-Patent Literature

The purpose of this study is to ascertain the hierarchical importance of a patent's characteristics to licensing. This research has a causal‐exploratory purpose, in that it sought to establish relationships between variables. This research aims to identify which characteristics are influential in the licensing of Brazilian academic patents in the biotechnology and pharmaceutical technology fields, based on the mining of data contained in licensed and unlicensed patent documents. Which characteristics of Brazilian academic patents are most influential in their licensing potential? An analysis through Random Forest was performed. To the best of our knowledge, there are no studies in Brazil using machine learning to identify which characteristics are influential in licensing a particular academic patent, especially given the difficulty of gathering this information. We found that regardless of the measure used, the three most critical licensing characteristics for the Biotechnology and Pharmaceutical patents analysed are Patent Scope, Life Cycle, and Claims. At the same time, the least important is the Patent Cooperation Treaty. The relevance of this research is based on the fact that after identifying which intrinsic characteristics influence the final value and licensing probabilities of a given patent, it will be possible to develop mathematical models that provide accurate information for establishing technology transfer agreements. In practical terms, the results suggest that greater patent versatility, combined with lifecycle management and a technical effort to build strong claims, increases the licensing potential of academic biopharmaceutical patents.

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Non-Patent Literature

Cited by 5 publications

References 16 publications

Mapping the technological impact of chitosan research through patent citations

Mapping the technological impact of chitosan research through patent citations

Indicators for measuring the impact of scientific citations in patents

The hierarchical importance of patent's characteristics to licensing: An analysis through Random Forest

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