# Brand vs. Generic: Addressing Non-Adherence, Secular Trends, and Non-Overlap

## TL;DR

This paper develops a new method to assess the therapeutic equivalence of brand and generic drugs using insurance data, addressing challenges like non-adherence and secular trends, and applies it to venlafaxine without finding evidence of difference.

## Contribution

The paper introduces a novel causal inference approach extending regression discontinuity to survival analysis for post-market drug comparison.

## Key findings

- No evidence of therapeutic difference between brand and generic venlafaxine
- Method effectively accounts for non-adherence and secular trends
- Applicable to other post-market drug evaluations

## Abstract

While generic drugs offer a cost-effective alternative to brand name drugs, regulators need a method to assess therapeutic equivalence in a post market setting. We develop such a method in the context of assessing the therapeutic equivalence of immediate release (IM) venlafaxine, based on a large insurance claims dataset provided by OptumLabs\textsuperscript{\textregistered}. To properly address this question, our methodology must deal with issues of non-adherence, secular trends in health outcomes, and lack of treatment overlap due to sharp uptake of the generic once it becomes available. We define, identify (under assumptions) and estimate (using G-computation) a causal effect for a time-to-event outcome by extending regression discontinuity to survival curves. We do not find evidence for a lack of therapeutic equivalence of brand and generic IM venlafaxine.