The U.S. Food and Drug Administration’s Orphan Drug Designation (ODD) program, established in 1983, aims to stimulate innovation for rare diseases by offering incentives such as tax credits, user fee waivers, and seven years of market exclusivity. While the program has spurred investment in treatments for small patient populations, its application at the drug-indication level creates opportunities for strategic behavior. Using a novel panel dataset from Cortellis Competitive Intelligence, we document how firms combine rare and non-rare indications within single drug development projects to exploit economies of scope and, in some cases, to extend market exclusivity beyond the regulation’s intent.

Descriptive evidence reveals frequent indication expansion during clinical development, particularly among partial orphan projects (mix of both rare and larger-market diseases). Building on these patterns, we develop an econometric framework to estimate the causal impact of ODD on drug development outcomes and to identify spillovers to non-orphan indications. Our results inform the policy debate on whether current ODD incentives effectively promote socially valuable innovation or inadvertently invite strategic behavior that dilutes program efficiency.

This paper studies how patent trading affects innovation in the U.S. pharmaceutical industry. I construct a novel dataset linking the timing of patent transfers to drug development stages and show that 82% of trades occur before launch, and that such trades significantly increase success rates. To interpret these patterns, I develop and estimate a dynamic model where firms differ in stage-specific expertise and can trade patents under search frictions and transaction costs. The model reveals that transferring patents to experienced firms raises success rates and innovation value, but trade frictions hinder efficient transfers. Counterfactuals show that reducing transaction costs boosts launch rates and innovation value, while targeted subsidies at specific stages outperform uniform ones in efficiency and cost-effectiveness.

This paper studies how patent trade affects subsequent innovation. Using U.S. pharmaceutical patent, reassignment, and firm-level data, I develop and estimate a dynamic model of patenting, buying, and selling that allows internally generated and acquired patents to affect future innovation differently. The estimates show that internally generated patent capital strongly supports subsequent innovation, while the effect of acquired patents varies across firms with different commercialization capabilities. Transaction costs significantly affect firms’ patent-trading decisions. A 50 percent reduction in transaction costs increases patent trading for all firms but raises innovation mainly among innovation-specialized firms, particularly smaller ones. At the industry level, the long-run patent stock increases by about 0.5 percent. The results show that patent-market frictions shape not only the reallocation of existing inventions, but also the location and amount of future innovation.

Open Science Partnerships (OSPs)— mission-oriented, public-private collaborations that share research outputs with minimal IP claims—are attracting growing policy interest as mechanisms through which to advance biopharmaceutical drug development. This article argues that OSPs generate positive economic effects through three underappreciated mechanisms: they can reallocate early-stage scientific risk and change firms’ investment incentives; they generate longer-run spillovers through reusable platforms, human capital, and networks; and they build shared standards and infrastructures that shape participation in the innovation ecosystem. Because many effects emerge later and outside the original partnership, conventional output metrics systematically understate OSP value. To properly evaluate the impact of OSPs on drug development, the article calls for the development of linked evidence connecting partnership activity to downstream scientific, commercial, and clinical outcomes.