Abstract
The pharmaceutical industry is one of the most research and development (R&D)-intensive industries. This industry has tried many strategies to overcome the limitations of a business model that had a high return and high risk. In recent years, the fourth industrial revolution has affected many industries, causing them to update their traditional production and business strategies to a “data science-based” approach. This data science methodology, based on the largely increased size of the data environment, has actively changed the pharmaceutical industry. Therefore, this study aimed to identify specific characteristics of data science innovation in the pharmaceutical industry through the analysis of patent data from the triadic patent databases from the United States, Japan, and Europe.
Highlights
The pharmaceutical industry is a highly research and development (R&D)-intensive sector.Since the 1970s, R&D activity in the pharmaceutical industry has increased rapidly
This study will present the association rules and maps representing the relationship of technologies for a specific innovation regime
Data science-based innovation in the pharmaceutical industry has been represented by the period between 2008 and 2015
Summary
The pharmaceutical industry is a highly research and development (R&D)-intensive sector. Since the 1970s, R&D activity in the pharmaceutical industry has increased rapidly. In addition to the intensive use of R&D, the challenges faced in pharmaceutical R&D have increased considerably. Developments in the pharmaceutical industry have taken place as a result of the increased difficulties encountered in the pharmaceutical R&D [1,2]. Pharmaceutical companies have attempted to find novel materials that are different from incumbent and traditional materials, such as small molecules and the so-called new molecular entities (NMEs), through the use of biologics and biological entities. Changes in the type of pharmaceutical R&D companies have taken place; more recently, small companies have increased and, from 2004, these exceeded the productivity of the R&D departments of bigger companies [2]
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