"Stick or Twist?" Negotiating Price and Data in an Era of Conditional Approval

Changes in the regulatory context enable faster approval of transformative medicines. They also lead to health technology assessment (HTA) agencies having to make decisions with less evidence. In response, HTA agencies have also initiated forms of conditional approval. When the evidence base for a new oncology treatment leaves substantial uncertainty, the new Cancer Drugs Fund allows the National Institute for Heath and Care Excellence to give the manufacturer two options: (1) offer a low price based on conservative assumptions and obtain immediate approval ("stick") or (2) wait until the evidence base has further matured before finalizing a potentially higher agreed price ("twist").

The purpose of this article is to explain how, using the theoretical framework of the expected value of sample information, simulation methods can help inform a manufacturer's decisions when faced with the option to stick or twist.

We first summarize a general model to help frame the manufacturer's negotiating strategy. We then use a motivating case study, based on a hypothetical immunotherapy, to illustrate how manufacturers can use simulation methods to robustly characterize the uncertainty inherent to further data collection and incorporate this uncertainty within their decision making.

Our approach allows us to estimate the commercial value of generating additional data (the difference between the estimated net present value of stick and twist). We test the sensitivity of the results to different assumptions via scenario analyses.

This article shows that simulation methods can be used to help pharmaceutical managers make informed strategic decisions in contexts of uncertainty.