Noah Gans, Operations, Information and Decisions, The Wharton School; Ozge Yapar, Kelley School of Business, Indiana University; and Steve Chick, INSEAD
Abstract: The clinical-trial data used to make approval decisions for medical therapies are collected from a relatively small patient sub-populations. Given small sample sizes, trial data may suggest that treatments are medically or economically nonviable, even though they ultimately may be, or vice versa. New flexible-pricing and cost-sharing protocols seek to reduce the risk of these information failures. These schemes allow firms that provide new therapies to obtain qualified market approval and continue collecting clinical data from the market, post-approval, with the hope that additional clinical evidence will confirm the treatments’ value.
We seek to characterize the impact of these schemes on the development and marketing of novel medical therapies.
- Does the use of post-approval data change the regulatory and cost-benefit standards to be used?How much effort and expense should a therapy’s provider incur to collect post-approval clinical data?
- How does the availability of these schemes affect outcomes? Can we characterize what types of therapies might benefit from the new, flexible arrangements and which would not? Can we characterize associated societal benefit?
- Are there other forms risk-sharing schemes that could be of interest to firms, regulators, and payers? If so, what are they? How do they perform?