Using JMP® to Create Experiment Designs with Nonlinear Constraints: Two Examples from the Pharmaceuticals Industry
Paul Sauer, VP of Manufacturing, Igenica Patricia Dianne McNeill, Head of Fermentation Research, Alder Biopharmaceuticals William D. Kappele, President, ObDOE
Experiment designs provide a powerful planning tool for effective experimentation. Some experimental situations have physical limitations or constraints. The JMP Custom Designer provides for the inclusion of linear constraints in experiment designs. Some experiments have nonlinear constraints, and these are more difficult to work with. If a constraint requires more than just the simple sum of scaled factors, it is nonlinear and must be linearized to use the JMP Custom Designer. In this presentation, you will learn how to use the JMP Custom Designer to create experiment designs with nonlinear constraints. First, you will learn how to create a design with a simple nonlinear constraint. Next you will see two interesting examples from the pharmaceuticals industry that use JMP to create experiment designs with complex, nonlinear constraints: an osmolality constraint and a solubility constraint.