The Signaling Effects of the FDA Orphan Designation
While the FDA confers multiple different designations on drugs in development, this study will examine the signaling effects of the Orphan drug designation. The Orphan designation is given to drugs which treat a rare disease (defined as affecting fewer than 200,000 people in the US). This designation was created in 1983 by the Orphan Drug Act as a result of lobbying by patient groups to create additional incentives for firms to conduct drug research for rare diseases. Firms can apply for this designation after the drug has been approved to begin clinical trials. It is typically applied for early on in the drug development process, as receiving the designation confers additional tangible benefits for the firm (such as allowing for tax deductible clinical trial expenses).
This study will examine two main research questions: (1) whether the Orphan designation provides a signal of drug quality; and, (2) whether the strength of this signal has changed over time. To answer these questions, an event study methodology with the market model will be used. Event studies are used to determine whether there are abnormal stock returns after an event which is hypothesized to influence investors occurs. For this analysis, the event will be a firm’s announcement that it has received an Orphan designation from the FDA. Defining the study period as 1983-2012, a manual search for these announcements was conducted, and 718 unique announcements were found. Once the majority of inclusion criteria were applied, 332 announcements remained in the sample.
To evaluate whether the Orphan designation provides a signal of drug quality, a nonparametric t-test will be used to determine whether there are statistically significant abnormal returns present after the announcement of the receipt of the designation. To evaluate whether, over time, the average abnormal returns after an Orphan designation have changed, the announcements will be split into two time periods: 1983-2002 and 2002-2012. The average abnormal returns will be calculated for each of these two time periods, and then a nonparametric (Wilcoxon) test will be used to determine whether there is a statistically significant difference in returns between the two time periods.