Box-Behnken design: an alternative for the optimization of analytical methods

Area of Science:

• Analytical Chemistry
• Method Optimization
• Experimental Design

Background:

• Optimization is crucial for analytical methods.
• Various experimental designs exist for optimization.
• Understanding design limitations and advantages is key.

Purpose of the Study:

• To detail the Box-Behnken design (BBD) for analytical method optimization.
• To compare BBD with other statistical designs.
• To discuss factors, responses, and robustness in analytical optimization.

Main Methods:

• Description of Box-Behnken design (BBD) fundamentals.
• Comparative analysis of BBD against central composite, full factorial, and Doehlert designs.
• Exploration of multiple response calculation functions, including desirability functions.

Main Results:

• Box-Behnken design (BBD) presents specific benefits and drawbacks for analytical method optimization.
• Comparison highlights differences between BBD and other common experimental designs.
• The study details factors, responses, and robustness evaluation for analytical systems.

Conclusions:

• Box-Behnken design (BBD) is a valuable tool for analytical method optimization.
• Understanding comparative designs and response functions enhances optimization strategies.
• Robustness evaluation is essential for reliable analytical methods.