Counting Clinical Trials: New Evidence on Pharmaceutical Sector Productivity

TL;DR

This paper introduces a new method for labeling unstructured text, applies it to create a comprehensive census of clinical trials, and challenges prior claims of declining pharmaceutical productivity by showing stable trial metrics since 2010.

Contribution

It develops a novel text labeling approach and provides new evidence that pharmaceutical sector productivity has remained stable, countering previous reports of decline.

Findings

Clinical trial quantity and quality have been stable since 2010.

Previous declines in productivity were due to biases in research composition.

New data challenges existing narratives on pharmaceutical productivity trends.

Abstract

We develop a method for assigning high-quality labels to unstructured text. This method is based on fine-tuning an efficient, open-source language model with data extracted from a large, proprietary language model. We apply this method to construct a census of published clinical trials. With these data, we revisit a literature that contends that pharmaceutical sector productivity is declining. Central to this conclusion are measurements of substantial increases in the quantity of clinical trials over time, unmatched by trends in measures of output. In our data, the quantity, quality, and composition of clinical trials are stable since 2010. We show that previous measurements are an artifact of biases introduced by shifts in the composition of other forms of research.