Erica Seiguer Shenoy
Assistant Professor of Medicine, Harvard Medical School
Dissertation Title： "Innovation and Incentives in Pharmaceutical Research and Development"
Research and development (R&D) in the pharmaceutical industry requires significant investment over long periods of time, with uncertain outcomes. This dissertation examines the economics of innovation and incentives in pharmaceutical R&D.
In Chapter 1, the peak revenue gains associated with order of entry as well as the peak revenue gains associated with molecule- and firm-specific characteristics for molecules launched in the United States over the 1994-2005 period are estimated. This research addresses whether or not a first-mover advantage can be demonstrated empirically, and thus sheds light on the economic incentives faced by firms as they choose which molecules to invest in and the amount of effort they dedicate to innovative R&D. The findings suggest that there is no first-mover advantage for the drugs in the sample, and that later entry to a class is associated with greater peak revenues. Molecule characteristics, however, are much more significant predictors of peak revenues than order of entry.
In Chapter 2, the impact of pre-market competition on success in pharmaceutical R&D is estimated using a discrete choice model.Using a large database of molecules in development from 1994-2004, and drawing from the literature on net present value, sequential development projects and real options, I consider the factors that explain molecule transitions through phases of development and examine how the pre-market competitive environment influences the probability that a molecule will move to the next stage. The parameter estimates suggest that the likelihood of a molecule transitioning is influenced by the successes and failures of other molecules in development, findings that are consistent with a model of learning.
In Chapter 3,the economic incentives for research and development of pharmacogenomic therapies are examined through simulations that compare the variables influencing the expected profits for firms considering investing in genomic-based therapies versus investing in non-targeted, or "conventional therapies." The findings suggest that firms face strong incentives to develop conventional therapies, which are more profitable in all of the simulations than targeted therapies. These findings, however, are most sensitive to market share and pricing, which suggest that factors influencing both could make targeted therapies more attractive investments to firms.