Experience using Quality by Design in upstream processes has identified several things that can improve the application of
the method. When the experimental environment is diagnosed and strategies are developed to match the environment, experimentation
moves more quickly and the critical process variables are identified with higher probability. This article presents a process
for developing experimental strategies. The approach focuses on enhancing process understanding by developing the right data,
at the right time, and in the right amount to maximize the time-value of the data collected. The development and operation
of robust measurement methods that produce high quality data and streamlining of experimentation work processes also is discussed.
With the leadership of the FDA, there has been considerable focus on the use of Quality by Design (QbD) to accomplish the
goal of speeding up development and reducing costs in research and development and manufacturing; producing better quality
products and more effective, efficient, and robust manufacturing processes. Much has been learned about the use of QbD since
it was first proposed by the FDA.1–4 QbD also can be used to enhance the performance of existing products and processes.
There are many variables involved in improving an upstream process. Hulbert, et al. have shown an effective way to prioritize
the collection of variables.5 Now, we need a strategy to deal with the variables identified by the prioritization approach proposed by Hubert, et al.
Hubert, et al. point out that there are a lot of data involved in improving upstream productivity. The data can't be collected
all at once. The strategy selected must enable us to collect the right data, at the right time, and in the right amount, as
discussed by Lonardo, Snee, and Qi.6
Even when good QbD approaches are used, experimentation often is slowed down by poor processes. Personnel, materials, testing,
and equipment often are not available when needed, resulting in wasted time and effort. Additional time and effort are wasted
when analytical methods are of poor quality or the procedures in the analytical laboratory are inefficient.
Two methods can be used to increase the speed of upstream development, which in turn speeds up the development of process
- using Design of Experiments (DOE)-based strategies to design, analyze, and interpret experiments, resulting in getting better
information in a timely fashion
- using Lean principles to streamline the availability of information, materials, equipment, measurements, and personnel for
the experimental process, thereby accelerating the flow of the experimental process.
The overall strategy therefore is to speed up the experimental process by adopting strategies that collect the right data
when needed and to improve the work processes used for experimentation. The result is that the experimentation is speeded
up, in turn speeding up the development of process understanding, which is fundamental to improving upstream productivity
(Figure 1). Some critical principles in conducting upstream experimentation are summarized in the sidebar and discussed in
the following paragraphs.