The cost of US pharmaceutical price regulation: a financial simulation model of R&D decisions

Previous empirical studies that have examined the links between pharmaceutical price controls, profits, cash flows, and investment in research and development (R&D) have been largely based on retrospective statistical analyses of firm- and/or industry-level data. These studies, which have contributed numerous insights and findings to the literature, relied upon ad hoc reduced-form model specifications. In the current paper we take a very different approach: a prospective micro-simulation approach. Using Monte Carlo techniques we model how future price controls in the US will impact early-stage product development decisions in the pharmaceutical industry. This is done within the context of a net present value (NPV) framework that appropriately reflects the uncertainty associated with R&D project technical success, development costs, and future revenues. Using partial-information estimators calibrated with the most contemporary clinical and economic data available, we demonstrate how pharmaceutical price controls will significantly diminish the incentives to undertake early-stage R&D investment. For example, we estimate that cutting prices by 40-50% in the US will lead to between 30 and 60% fewer R&D projects being undertaken (in early-stage development). Given the recent legislative efforts to control prescription drug prices in the US and the likelihood that price controls will prevail as a result, it is important to better understand the firm response to such a regulatory change.