OBJECTIVES : The federal government has proposed several policies for restricting drug prices. These policies could stagnate patient outcomes due to fewer pharmaceutical innovations after fewer resources for research and development (R&D). We developed a model to simulate the direct and indirect impacts of pricing policies on R&D investments.

METHODS : Using 2007-2018 revenue and R&D data for 144 pharmaceutical companies, we estimated the relationship between revenue and future R&D investments. We also developed a model component that demonstrates how drug prices that aren’t targeted by pricing policies are impacted (e.g., Medicaid drug prices through changes in average manufacturer prices). With our revenue-R&D elasticity, estimates of the direct impact on targeted drugs, and estimates of the indirect impact on non-targeted drugs, our model estimates a pricing policy’s overall impact on R&D investments. Furthermore, using data on 2006-2018 venture capital (VC) deals, we developed a model component that estimates the impact of pricing policies on the valuation and future VC deal sizes of early-stage pharmaceutical companies. Smaller deals may lead to decreases in R&D. As a case study, we used our model to calculate the impact of the International Pricing Index (IPI) Model for Medicare Part B Drugs.

RESULTS : Our model’s estimate of loss revenue due to IPI is more than 50% greater than HHS’s estimate. For each dollar of lost revenue by pharmaceutical firms, R&D investments decreased by $0.23. Revenue loss from non-targeted drugs is significant; under IPI this loss was nearly 10% of the loss from the policy’s direct impact. VC investments were fairly inelastic. Thus, the loss of R&D resources from smaller deals only contributed an additional 2%.

CONCLUSIONS : Pricing policies have great impacts on R&D investments and, thus, slow drug innovations vital to improving patient outcomes. Careful modeling of direct and indirect impacts is critical to fully understanding the results of these policies.