Statistics in Pharmaceutical Development and Manufacturing

TLDR

The pharmaceutical industry faces rapid change, global competition, and regulatory demands for quality by design and process analytical technology, and statistical thinking is key to addressing these challenges. This article provides an overview of the use of statistical thinking and methods in R&D and manufacturing functions. The authors review the evolution of pharmaceutical quality regulation, development phases, core statistical tools, emerging methods, software impacts, and the role of statisticians, illustrated by four case studies. The article concludes that the complex, technical nature of pharmaceutical development offers many opportunities for effective statistical use, positioning statisticians as catalysts for process understanding and product‑quality improvement. Additional details are available in Peterson et al.

Abstract

The pharmaceutical industry is undergoing rapid change and facing numerous challenges, including the demands of global competition, the need to speed up the drug-development process, and the Food and Drug Administration's (FDA's) expectations for the incorporation of the principles of quality by design (QbD) and process analytical technology (PAT) in process and analytical development. Statistical thinking and methods play a significant role in addressing these issues. This article provides an overview of the use of statistical thinking and methods in the R&D and manufacturing functions of the pharmaceutical industry. The exposition includes the history of pharmaceutical quality and regulation, phases of pharmaceutical development and manufacturing and the basic quality and statistical tools employed in each, emerging statistical methods, the impact of statistical software and information technology, and the role of statisticians in pharmaceutical development and manufacturing. Four case studies are included to illustrate how these issues play out in actuality. A summary provides a succinct synopsis of those issues and concludes that the complex, technical nature of pharmaceutical development and manufacturing offers many opportunities for the effective use of statistical thinking and methods and that those who use these methods can become catalysts for both process-development understanding and product-quality improvement. Additional details can be found in our technical report (Peterson et al. (2009)).