Background: A large number of highly impactful technologies originated from academic research, and the transfer of inventions from academic institutions to private industry is a major driver of economic growth, and a catalyst for further discovery. However, there are significant inefficiencies in academic technology transfer. In this work, we conducted a data-driven assessment of translational activity across United States (U.S.) institutions to better understand how effective universities are in facilitating the transfer of new technologies into the marketplace. From this analysis, we provide recommendations to guide technology transfer policy making at both the university and national level.
Methods: Using data from the Association of University Technology Managers U.S. Licensing Activity Survey, we defined a commercialization pipeline that reflects the typical path intellectual property takes; from initial research funding to startup formation and gross income. We use this pipeline to quantify the performance of academic institutions at each step of the process, as well as overall, and identify the top performing institutions via mean reciprocal rank. The corresponding distributions were visualized and disparities quantified using the Gini coefficient.
Results: We found significant discrepancies in commercialization activity between institutions; a small number of institutions contribute to the vast majority of total commercialization activity. By examining select top performing institutions, we suggest improvements universities and technology transfer offices could implement to emulate the environment at these high-performing institutions.
Conclusion: Significant disparities in technology transfer performance exist in which a select set of institutions produce a majority share of the total technology transfer activity. This disparity points to missed commercialization opportunities, and thus, further investigation into the distribution of technology transfer effectiveness across institutions and studies of policy changes that would improve the effectiveness of the commercialization pipeline is warranted.
Digital Object Identifier (DOI)
The AUTM Licensing Activity Survey data are available on the organization’s website (https://www.autm.net/resources-surveys/research-reports-databases/licensing-surveys/) by fee or institutional subscription/membership. As such, the raw data analyzed for this study cannot be provided in the context of this article.
Weis, James; Bashyam, Ashvin; Ekchian, Gregory J.; Paisner, Kathryn; and Vanderford, Nathan L., "Evaluating Disparities in the U.S. Technology Transfer Ecosystem to Improve Bench to Business Translation" (2018). Markey Cancer Center Faculty Publications. 113.