Case Studies and White Papers
Using Design of Experiments to Optimize Chiral Separation
Via application of response surface methods, Wyeth Pharmaceuticals substantially increased yield of an active ingredient at more robust process conditions.
The statistical design of experiments is an essential ingredient of successful product development and improvement, and provides an efficient and scientific approach to obtaining meaningful information. In contrast to traditional vary one-factor-at-a-time (OFAT) experimentation, variables are changed together, permitting evaluation of interactions. Standard texts give details about the construction of specific test plans, such full and fractional factorial, and response surface designs, and the analysis of the resulting data. This article gives a brief overview. The focus here is on the fundamental elements of experimental design: defining the purpose and scope of the experiment, differentiating between alternative types of experimental variables, understanding the underlying environment and constraints, and conducting stage-wise experimentation. Brief discussions dealing with the statistical analysis tools, multiple response variables, and some historical background are also provided.
Schiff Nutrition used DOE to solve an intermittent problem with a multimineral tablet sticking inside the dies of a high-speed rotary tablet press. (To see the figures, download the manuscript from link below.)
This article details the role DOE in achieving Quality by Design (QbD) for the manufacture of active pharmaceutical ingredients (API). It features outputs from Design-Expert, the author's top choice for DOE software.
The Dresser Waukesha development team adopted the design of experiments (DOE) approach to increase the accuracy of performance estimates and reduce the number of required tests.
To accelerate their product development, Z Corporation tooled up their engineers with the knowledge and software to do statistical design of experiments (DOE). The company developed a procedure by which every factor with a reasonable chance of affecting product performance is systematically and simultaneously evaluated via these controlled experiments.
To accelerate their product development, Z Corporation tooled up their engineers with the knowledge and software to do statistical design of experiments (DOE). The company developed a procedure by which every factor with a reasonable chance of affecting product performance is systematically and simultaneously evaluated via these controlled experiments.
Aided by DOE, biochemists determined the statistically significant factors affecting the growth of an E. coli cell line in shaker flasks.
Design of Experiments Helps Optimize Cell Culture Bioproduction System
Invitrogen Corporation utilized response surface methods (RSM) to reveal a complicated array of multi-factor interactions involved in bioprocess development. Using advanced tools in Design-Expert, they achieved more desirable conditions in a minimal number of runs.
Making Use of Mixture Design to Optimize Olive Oil - A Case Study
Olive oil, an important commodity of the Mediterranean region and a main ingredient of their world-renowned diet (see sidebar), must meet stringent European guidelines to achieve the coveted status of "extra virgin." Oils made from single cultivars (a particular cultivated variety of the olive tree) will at times fall into the lower "virgin" category due to seasonal variation. Then it becomes advantageous to blend in one or more superior oils. This is a great case to become acquainted with the tools of mixture design for optimal formulation.