We aim to develop and test a dynamic model of R&D for new health technologies with the aim of increasing the understanding of the relationship between static and dynamic efficiency. Static efficiency is related to access to innovations by patients once they are approved for use within a health care system. Dynamic efficiency concerns the incentives that are in place for the pharmaceutical industry to invest in R&D, thereby creating future innovation. The key tension in the static-dynamic efficiency relationship is that trying to improve access to newly approved technologies in the short term, can damage the incentives for innovation over the longer term. Existing literature suggests that there is a dearth of high quality, theoretical and econometric research into the precise nature of this static-dynamic relationship to suggest what an “optimal” balance between the two should be. One reason for this may be the complexity of R&D, which typically span several years and have a high probability of failure. The empirical analysis is complicated by the fact that the (uncertain) outcome of an R&D process started at a certain point in time will only be observed several years later. Moreover, the monetary cost of access to information on R&D investments by the industry is a major barrier to research in this area.
The project aims to join the skills of researchers who so far have worked separately on the empirical and theoretical analysis in this area. The key expected outcomes of the project are: (i) a dynamic theoretical framework to characterize the optimal trade-off between static and dynamic efficiency; (ii) a theoretical analysis and an empirical test of the hypothesis suggested by some authors, that some countries may decide to free-ride on others in the provision of incentives to R&D (iii) an analysis of the equity dimension of R&D investment, with a focus on ‘orphan diseases’, and an empirical evaluation of the impact of regulation targeted to these diseases.