Joint PSI/EFSPI Pre-Clinical SIG Webinar: Mixed-Level OMARS Designs for Quantitative and Categorical Factors: Theory and Application

Date: Tuesday 26th March 2024
Time: 15:00-16:00 GMT
Location: Online via Zoom
Speaker: Peter Goos (KU Leuven).

Who is this event intended for? Statisticians in the Pharmaceutical Industry who are keen to learn more about OMARS DoE and its application in a pre/non clinical setting.
What is the benefit of attending? Learning about OMARS Design of Experiments in Pre-Clinical settings from Peter Goos the Co-Founder EFFEX (https://www.effex.app/).


This event is free to attend for both Members of PSI and Non-Members. To register your place, please click here.


Professor Goos will present a framework on mixed level OMARS designs and will illustrate the proposed approach using a case study from a medical-chemical example. This will be followed by Q&A.

Speaker details




Peter Goos

Peter Goos is a full professor at the Faculty of Bio-Science Engineering of KU Leuven, and at the Faculty of Business and Economics of the University of Antwerp, where he teaches various introductory and advanced courses on statistics and probability. His main research area is the statistical design and analysis of experiments. Besides numerous influential articles in various kinds of scientific journals, he published the books The Optimal Design of Blocked and Split-Plot Experiments, Optimal Experimental Design: A Case-Study Approach, Statistics with JMP: Graphs, Descriptive Statistics and Probability and Statistics with JMP: Hypothesis Tests, ANOVA and Regression. For his work, Peter Goos has received four Shewell Awards, two Lloyd S. Nelson Awards, a Brumbaugh Award and the Youden Award of the American Society for Quality, the Ziegel Award and the Statistics in Chemistry Award from the American Statistical Association, and the Young Statistician Award of the European Network for Business and Industrial Statistics (ENBIS). Peter Goos is known for this ability to introduce new design of experiments concepts in an accessible fashion to non-academics.

OMARS Designs: Factor Screening and Response Surface Optimization in a Single Step

The family of orthogonal minimally aliased response surface designs or OMARS designs bridges the gap between the small definitive screening designs and classical response surface designs, such as central composite designs and Box-Behnken designs. The initial OMARS designs involve three levels per factor and allow large numbers of quantitative factors to be studied efficiently using limited numbers of experimental tests. Many of the OMARS design possess good projection properties and offer better powers for quadratic effects than definitive screening designs with similar numbers of runs. Therefore, OMARS designs offer the possibility to perform a screening experiment and a response surface experiment in a single step, and thereby offer the opportunity to speed up innovation and process improvement. A technical feature of the initial OMARS designs is that they study every quantitative factor at its middle level the same number of times. In this talk, we relax this constraint and arrange the designs in blocks, and thereby broaden the family of OMARS designs tremendously. We also present a successful application of OMARS designs in the pharmaceutical and chemical industries.


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