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Life sciences intellectual property licensing at the Massachusetts Institute of Technology

Nature Biotechnology volume 39, pages 293–301 (2021)Cite this article

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Abstract

Academic institutions play a central role in the biotech industry through technology licensing and the creation of startups, but few data are available on their performance and the magnitude of their impact. Here we present a systematic study of technology licensing by one such institution, the Massachusetts Institute of Technology (MIT). Using data on the 76 therapeutics-focused life sciences companies formed through MIT’s Technology Licensing Office from 1983 to 2017, we construct several measures of impact, including MIT patents cited in the Orange Book, capital raised, outcomes from mergers and acquisitions, patents granted to MIT intellectual property licensees, drug candidates discovered and US drug approvals—a key benchmark of innovation in the biopharmaceutical industry. As of December 2017, Orange Book listings for four approved small-molecule drugs cite MIT patents, but another 31 FDA-approved drugs (excluding candidates acquired after phase 3) had some involvement of MIT licensees. Fifty-five percent of the latter were either a new molecular entity or a new biological entity, and 55% were granted priority review, an indication that they address an unmet medical need. The methodology described here may be a useful framework for other academic institutions to track outcomes of intellectual property in the therapeutics domain.

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Fig. 1: Highest stage of development of pipeline candidates of MIT licensees as of December 2017.
Fig. 2: Indication groups of pipeline candidates of MIT licensees as of December 2017.

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Acknowledgements

We thank MIT’s Technology Licensing Office for agreeing to participate in this study and providing access to their historical data, in particular, G. Lindsay, J. Lura and L. Millar-Nicholson. We thank D. Gifford, R. Horvitz, R. Langer, H. Lodish, E. Roberts, P. Sharp, P. Szolovits, C. Westphal and H. Williams for helpful comments and discussion, and J. Cummings for editorial assistance. Research support from the MIT Laboratory for Financial Engineering is gratefully acknowledged. The views and opinions expressed in this article are those of the authors alone, and do not necessarily represent the views and opinions of any institution or agency, any of their affiliates or employees, or any of the individuals acknowledged above.

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Author notes

  1. These authors contributed equally: Samuel Huang, Kien Wei Siah.

Authors and Affiliations

  1. MIT Laboratory for Financial Engineering, Sloan School of Management, Cambridge, MA, USA

    Samuel Huang, Kien Wei Siah, Detelina Vasileva, Shirley Chen, Lita Nelsen & Andrew W. Lo

  2. MIT Department of Electrical Engineering and Computer Science, Cambridge, MA, USA

    Kien Wei Siah & Andrew W. Lo

  3. MIT Technology Licensing Office, Cambridge, MA, USA

    Lita Nelsen

  4. MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA

    Andrew W. Lo

  5. Santa Fe Institute, Santa Fe, NM, USA

    Andrew W. Lo

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Correspondence to Andrew W. Lo.

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Competing interests

All authors were affiliated with MIT during the course of this project. L.N. was head of MIT’s Technology Licensing Office at the start of the project, and currently consults for biopharma companies and investors. A.W.L. reports personal investments in private and public biotech companies, biotech venture capital funds, and life sciences mutual funds, and is a cofounder and partner of QLS Advisors, a healthcare analytics company; an advisor to BrightEdge Ventures; a director of Roivant Sciences Ltd, BridgeBio Pharma and Annual Reviews; chairman emeritus and senior advisor to the AlphaSimplex Group; and a member of the Board of Overseers at Beth Israel Deaconess Medical Center and the NIH’s National Center for Advancing Translational Sciences Advisory Council and Cures Acceleration Network Review Board.

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Supplementary Note, Figs. 1–7 and Tables 1–12.

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Huang, S., Siah, K.W., Vasileva, D. et al. Life sciences intellectual property licensing at the Massachusetts Institute of Technology. Nat Biotechnol 39, 293–301 (2021). https://doi.org/10.1038/s41587-021-00843-5

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