Patents and licensing and the commercialization of academic biomedical research

Abstract

This thesis is part of a larger body of research being undertaken by Dr. Fiona Murray and colleagues examining value creation and sharing between and among the three principal players in the commercialization of academic biomedical research: universities, biotech firms, and big pharma. The Recombinant Capital database provided access to contracts for biomedical technology licensed from academe to biotech, and also subsequent contracts that included that same technology from biotech to big pharma. These two contracts comprise a contract "pair". Importantly, these contract "pairs" were unredacted, that is., all parts of the contracts, including the commercial terms, were available. This thesis will lay the foundation for later work by examining the contracts between university and biotech, from the University's point of view. The goal is to identify factors that give the university more power in a pricing negotiation, and that predict higher economic value for the contract. The Specific Aim is to determine if certain University factors have a significant effect on predicting the economic value of the university-biotech licensing agreement. Four groups of readily quantifiable factors that contain attributes that might add power to the University in its pricing negotiation with the Biotech firm were identified: Institutional factors, Single Inventor factors, Aggregate factors, and Invention factors. The hypothesis is that at least one of these factors will have a significant effect on predicting the value of the licensing agreement, as determined using ordinary- and multiple-linear regression models. In formulistic terms, the null- and test-hypotheses are: (HO) no factor has a significant effect on predicting economic value, and (HI) at least one

(cont.) one factor has a significant effect on predicting economic value. A multiple regression model of the factors as explanatory variables for the economic value of the license revealed that two independent university factors significantly predict economic value of the contract. These combined factors account for 64% of the variance of the dependent variable (in excess of control), and have coefficients that are significant (p < 0.001). The results are discussed in the context of its importance to university technology transfer officers, biotech firms and venture capitalists.