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导致更多的技术创新机会。然而，增加研发支出的预期结果并没有实现。21世纪初，随着研发支出的增加，美国制药公司获得美国食品和药物管理局（FDA）批准的候选药物数量比20世纪90年代初要少。以FDA批准的药物数量来衡量研发支出的回报，表明生产率停滞不前，增长可能下降。制药工业生产率的明显下降可能反映了技术机会和研发过程性质的变化。不考虑企业将科技进步融入创新活动的方法的生产率指标可能是不准确的。知识价值。本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来绘制科学进步的生产，并随后在项目层面的下游创新活动中使用。该研究开发并应用了创新生产力的多种指标，包括创新活动的完成状态和完成一项创新活动的时间，以形成有关企业利用公共资助研究产生的科学进步的程式化事实。更广泛的影响。本研究通过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。在这项研究中开发的项目级生产力模型可以被决策者用来评估通过公共资助的研究对私营部门创新活动产生的科学进步的影响，并且应该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。本文的研究分析了促进政府资助研究所产生的科学进步扩散的机会，从而刺激创新。政策制定者应该能够使用本研究产生的模型和程式化事实，以确定研究项目可以更有效地刺激商业创新的方式。这项研究的结果可能在设计知识产权、组织和资助公私研究联盟以及制定与工业需求一致的研究优先事项方面有用。

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.