Tag: QbD

The QbD Column: Applying QbD to make analytic methods robust

In our previous blog post, we wrote about using designed experiments to develop analytic methods. This post continues the discussion of analytic methods and shows how a new type of experimental design, the Definitive Screening Design[1] (DSD), can be used to assess and improve analytic methods. We begin with a

The QbD Column: Is QbD applicable for developing analytic methods?

Development of measurement or analytic methods parallels the development of drug products. Understanding of the process monitoring and control requirements drives the performance criteria for analytical methods, including the process critical quality attributes (CQAs) and specification limits. Uncovering the characteristics of a drug substance that require control to ensure safety

The QbD Column: Split-plot experiments

Split-plot experiments are experiments with hard-to-change factors that are difficult to randomize and can only be applied at the block level. Once the level of a hard-to-change factor is set, we can run experiments with several other factors keeping that level fixed. To illustrate the idea, we refer in this

The QbD Column: Response surface methods and sequential exploration

George Box and K.B. Wilson introduced the idea of response surface methodology in a famous article[1] in 1951. There were several novel and extremely useful ideas in the article: Designed experiments can be a great tool in experimentally optimizing conditions. When feedback is rapid, there are great benefits to breaking

The QbD Column: Mixture designs

Scientists in the pharmaceutical industry must often determine product formulations. The properties of a formulation, or mixture, are usually a function of the relative proportions of the ingredients rather than their absolute amounts. So, in experiments with mixtures, a factorʹs value is its proportion in the mixture, which must fall

The QbD Column: Achieving robustness with stochastic emulators

In an earlier installment of The QbD Column titled A QbD factorial experiment, we described a case study where the focus was on modeling the effect of three process factors on one response, viscosity. Here, we expand on that case study to show how to optimize process parameters of a

The QbD Column: A QbD fractional factorial experiment

The first two posts in this series described the principles and methods of Quality by Design (QbD) in the pharmaceutical industry. The focus now shifts to the role of experimental design in QbD. Quality by Design in the pharmaceutical industry is a systematic approach to development of drug products and

The QbD Column: A QbD factorial experiment

A quick review of QbD The first blog post in this series described Quality by Design (QbD) in the pharmaceutical industry as  a systematic approach for developing drug products and drug manufacturing processes. Under QbD, statistically designed experiments are used to efficiently and effectively investigate how process and product factors

The QbD Column: Overview of Quality by Design

Developing new drugs is a complex, lengthy and expensive endeavor. When the process leads to an approved drug, the result is improved patient care and great benefits for the developers. But many promising drugs never live up to expectations. The US Food and Drug Administration (FDA), observing that new drug