Awareness and use of quantitative decision-making methods in pharmaceutical development

TL;DR

This paper explores the awareness, adoption, and potential for growth of quantitative decision-making methods in pharmaceutical development, highlighting current practices and areas for increased statisticians' involvement.

Contribution

It introduces key components of QDM, presents survey results on its current use in pharma, and discusses opportunities for enhancing statisticians' leadership in decision-making.

Findings

QDM is used at various development levels but not universally.

Statisticians need greater visibility and leadership in decision processes.

There are clear areas for future improvement in QDM adoption.

Abstract

The pharmaceutical industry has experienced increasing costs and sustained high attrition rates in drug development over the last years. One proposal that addresses this challenge from a statistical perspective is the use of quantitative decision-making (QDM) methods to support a data-driven, objective appraisal of the evidence that forms the basis of decisions at different development levels. Growing awareness among statistical leaders in the industry has led to the creation of the European EFSPI/PSI special interest group (ESIG) on quantitative decision making to share experiences, collect best practices, and promote the use of QDM. In this paper, we introduce key components of QDM and present examples of QDM methods on trial, program, and portfolio level. The ESIG created a questionnaire to learn how and to what extent QDM methods are currently used in the different development phases. We present the main questionnaire findings, and we show where QDM is already used today but also where areas for future improvement can be identified. In particular, statisticians should increase their visibility, involvement, and leadership in cross-functional decision-making.