The pharmaceutical industry is going through a revival since the publication of guidelines on Quality by Design (QbD) by the ICH. QbD techniques that have been used over the past 40 years in industries including automotive, aerospace and semiconductor manufacturing are now modernizing the pharmaceutical development process.
Fundamental to these techniques is the use of carefully designed experiments to identify the causational relationships between process inputs and outputs and create effective quality controls.
A common hurdle to gaining acceptance of the QbD paradigm is a culture rooted in unstructured, one factor at a time (OFAT) experimentation. While this approach can seem “scientific,” it can lead to suboptimal results and inefficiencies in comparison to multivariate experimental designs.
This chapter lays the groundwork for making a case to leadership for multivariate experimentation in early stage pharmaceutical product development and includes:
- The problems with experiments that lack structure.
- The benefits of testing more than one factor at a time.
- The best way to estimate process performance.
- How data visualization can help to justify multivariate design.