Doctoral Dissertation Research in Science of Science and Innovation Policy: Modeling Pharmaceutical Innovation Pipelines

University Of Texas At Austin, Austin TX

Investigators

Abstract

In the late 1990s, the U.S. government doubled investment in basic biomedical research to spur pharmaceutical innovation. The policy strategy was based on the assumption that more basic research would lead to greater technological opportunities for innovation. However, the anticipated results from increased R&D spending have not been realized. U.S. pharmaceutical companies received approval from the U.S. Food and Drug Administration (FDA) for fewer drug candidates in the early 2000s, after the increases in R&D spending, than in the early 1990s. Measures of returns to R&D spending in terms of the number of FDA approved drugs indicate stagnating productivity and likely declines in growth. The apparent declines in the productivity of the pharmaceutical industry may reflect changes in the nature of technological opportunities and the R&D process. Productivity metrics that do not account for the methods used by firms integrate scientific and technological advances into innovation activities may be inaccurate. Intellectual merit. This dissertation research construcs a new data set that can be utilized to map the production of scientific advances through publicly funded research, and subsequent use in downstream innovation activities at the project level. The research develops and applies multiple metrics of innovative productivity, including the completion status of innovation activities and the time to complete an innovation activity to develop stylized facts about the use of scientific advances generated from publicly funded research by firms. Broader impact. This research advances the understanding of the role of scientific advances in pharmaceutical innovation by shedding more light on the innovation activities in which firms use externally generated knowledge inputs to improve productivity. The project-level models of productivity that are developed in this research may be used by policy makers to evaluate the impact of the scientific advances generated through publicly funded research on private-sector innovation activities, and should be applicable in other science intensive-industries, such as nanotechnology, energy technologies, and information technology. This dissertation research analyzes opportunities to promote the diffusion of scientific advances generated through government funded research, and thereby stimulate innovation. Policy makers should be able to use the models and stylized facts generated by this research in order to identify ways in which research programs can be structured to more effectively stimulate commercial innovation. The results of this research are likely to be useful in designing intellectual property rights, organizing and funding public-private research consortia, and developing research priorities that align with industry needs.