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

20世纪90年代末，美国政府将基础生物医学研究的投资增加了一倍，以刺激制药创新。该政策战略基于这样一种假设，即更多的基础研究将带来更多的创新技术机会。然而，增加研发支出的预期结果并未实现。21世纪初，在研发支出增加后，美国制药公司从美国食品和药物管理局(FDA)获得的候选药物数量比上世纪90年代初有所减少。以FDA批准的药物数量衡量研发支出的回报表明，生产率停滞不前，增长可能会下降。制药业生产率的明显下降可能反映出技术机会和研发过程的性质发生了变化。没有考虑到公司将科学技术进步融入创新活动的方法的生产率衡量标准可能是不准确的。本论文的研究构建了一个新的数据集，可用于通过公共资助的研究绘制科学进步的成果图，并随后用于项目层面的下游创新活动。这项研究开发并应用了创新生产率的多种衡量标准，包括创新活动的完成状况和完成创新活动的时间，以制定有关公司利用公共资助研究产生的科学进步的风格化事实。这项研究通过更多地揭示企业利用外部产生的知识投入来提高生产率的创新活动，促进了对科学进步在制药创新中的作用的理解。本研究所建立的项目级生产率模型可供政策制定者用来评估政府资助研究产生的科学进步对私营部门创新活动的影响，并应适用于其他科学密集型产业，如纳米技术、能源技术和信息技术。本研究分析了促进政府资助研究产生的科学进步的扩散，从而激励创新的机会。政策制定者应该能够使用这项研究产生的模型和风格化的事实，以确定如何构建研究计划，以更有效地刺激商业创新。这项研究的结果可能有助于设计知识产权、组织和资助公私研究联盟，以及制定与行业需求相一致的研究优先事项。

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.