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Design of experiments (DoE) in pharmaceutical development.

Stavros N Politis1, Paolo Colombo2,3, Gaia Colombo4

  • 1a Department of Pharmaceutical Technology, Faculty of Pharmacy , National and Kapodistrian University of Athens , Athens , Greece.

Drug Development and Industrial Pharmacy
|February 7, 2017
PubMed
Summary

Quality by Design (QbD) principles, including statistical analysis and Design of Experiments (DoE), are crucial for pharmaceutical development. Implementing QbD ensures product quality by understanding process variables and their impact on critical quality attributes.

Keywords:
Experimental designdesign spacefactorial designsmixture designspharmaceutical developmentprocess knowledgestatistical thinking

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Area of Science:

  • Pharmaceutical Science
  • Statistical Methods
  • Quality Management

Background:

  • Traditional pharmaceutical development often relied on One Factor At a Time (OFAT) studies.
  • The pharmaceutical industry was slower to adopt modern engineering and statistical approaches compared to other sectors.
  • Sir Ronald Fisher's early work emphasized statistical analysis during research planning.

Purpose of the Study:

  • To review the evolution of Quality by Design (QbD) principles in pharmaceutical development.
  • To highlight the importance of statistical methods, particularly Design of Experiments (DoE), in implementing QbD.
  • To explain how QbD ensures final product quality through process and product understanding.

Main Methods:

  • Review of quality theory and contributions from major figures.
  • Detailed presentation of Design of Experiments (DoE) as a key tool for QbD implementation.
  • Explanation of establishing models to correlate inputs (CMAs, CPPs) with outputs (CQAs).

Main Results:

  • Quality by Design (QbD) enables building quality into products from the design phase.
  • Design of Experiments (DoE) is a primary statistical tool for implementing QbD in pharmaceuticals.
  • Understanding the relationships between Critical Material Attributes (CMAs), Critical Process Parameters (CPPs), and Critical Quality Attributes (CQAs) defines the design space.

Conclusions:

  • Implementing QbD and DoE leads to rational pharmaceutical development and a final product meeting the Quality Target Product Profile (QTPP).
  • Statistical thinking from the design phase, aligned with Deming's profound knowledge, is essential for pharmaceutical quality.
  • Modern engineering-based methodologies and QbD are vital for assuring quality in pharmaceutical manufacturing.