BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//Telerik Inc.//Sitefinity CMS 15.4//EN BEGIN:VTIMEZONE TZID:UTC BEGIN:STANDARD DTSTART;VALUE=DATE:20250101 TZNAME:UTC TZOFFSETFROM:+0000 TZOFFSETTO:+0000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DESCRIPTION:Date: \;Tuesday 26th March 2024\nTime: \;15:00-16:00 GM T\nLocation: \;Online via Zoom\nSpeaker: \;Peter Goos \;(KU Le uven).\n\nWho is this event intended for? Statisticians in the Pharmaceuti cal Industry who are keen to learn more about OMARS DoE and its applicatio n in a pre/non clinical setting.\nWhat is the benefit of attending? \; Learning about OMARS Design of Experiments in Pre-Clinical settings from P eter Goos the Co-Founder EFFEX (https://www.effex.app/).\nRegistration\nTh is event is free to attend for both Members of PSI and Non-Members. To reg ister your place\, please \;click here.\nOverview\nProfessor 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.\nSpeaker details\n\n\n\n \n \n \n Speaker\n \n \n Bi ography\n \n \n Abstract\n \n \n \n \n \n Peter Goos\n \n \n Peter Goos is a full professor at the Faculty of Bio-Science Engineering of KU Leuven\, and at the Faculty of B usiness and Economics of the University of Antwerp\, where he teaches vari ous introductory and advanced courses on statistics and probability. His m ain research area is the statistical design and analysis of experiments. B esides numerous influential articles in various kinds of scientific journa ls\, he published the books The Optimal Design of Blocked and Split-Plot E xperiments\, Optimal Experimental Design: A Case-Study Approach\, Statisti cs with JMP: Graphs\, Descriptive Statistics and Probability and Statistic s with JMP: Hypothesis Tests\, ANOVA and Regression. For his work\, Peter Goos has received four Shewell Awards\, two Lloyd S. Nelson Awards\, a Bru mbaugh Award and the Youden Award of the American Society for Quality\, th e Ziegel Award and the Statistics in Chemistry Award from the American Sta tistical Association\, and the Young Statistician Award of the European Ne twork for Business and Industrial Statistics (ENBIS). Peter Goos is known for this ability to introduce new design of experiments concepts in an acc essible fashion to non-academics.\n \n \n OMARS Designs: Factor Screening and Response Surface Optimization in a Si ngle Step\n The family of orthogonal minimally aliased response surface designs or OMARS designs bridges the gap between the small defini tive screening designs and classical response surface designs\, such as ce ntral composite designs and Box-Behnken designs. The initial OMARS designs involve three levels per factor and allow large numbers of quantitative f actors to be studied efficiently using limited numbers of experimental tes ts. 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 s ingle step\, and thereby offer the opportunity to speed up innovation and process improvement. A technical feature of the initial OMARS designs is t hat they study every quantitative factor at its middle level the same numb er of times. In this talk\, we relax this constraint and arrange the desig ns in blocks\, and thereby broaden the family of OMARS designs tremendousl y. We also present a successful application of OMARS designs in the pharma ceutical and chemical industries.\n \n \n \n\n \; DTEND:20240326T160000Z DTSTAMP:20260813T152804Z DTSTART:20240326T150000Z LOCATION: SEQUENCE:0 SUMMARY:Joint PSI/EFSPI Pre-Clinical SIG Webinar: Mixed-Level OMARS Designs for Quantitative and Categorical Factors: Theory and Application UID:RFCALITEM639222316844664038 X-ALT-DESC;FMTTYPE=text/html:Date: \;Tuesday 26th Marc h 2024
\nTime: \;15:00-16:00 GMT
\n Location: \;Online via Zoom
\nSpeaker:& nbsp\;Peter Goos \;(KU Leuven).
\n
\nWho is this event intended for? Statisticians in the Pharmaceutical Ind ustry who are keen to learn more about OMARS DoE and its application in a pre/non clinical setting.
\nWhat 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/).
\n

Registration

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

\n

Overview

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Professor G oos will present a framework on mixed level OMARS designs and will illustr ate the proposed approach using a case study from a medical-chemical examp le. This will be followed by Q&\;A.

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Speaker details

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Speaker< /strong>

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Biography

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Abstract

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Peteredit
\n Peter Goos

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Peter Goos is a full professor at the F aculty of Bio-Science Engineering of KU Leuven\, and at the Faculty of Bus iness and Economics of the University of Antwerp\, where he teaches variou s introductory and advanced courses on statistics and probability. His mai n research area is the statistical design and analysis of experiments. Bes ides numerous influential articles in various kinds of scientific journals \, he published the books The Optimal Design of Blocked and Split-Plot Exp eriments\, 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 Go os has received four Shewell Awards\, two Lloyd S. Nelson Awards\, a Brumb augh Award and the Youden Award of the American Society for Quality\, the Ziegel Award and the Statistics in Chemistry Award from the American Stati stical Association\, and the Young Statistician Award of the European Netw ork for Business and Industrial Statistics (ENBIS). Peter Goos is known fo r this ability to introduce new design of experiments concepts in an acces sible fashion to non-academics.

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

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The family of orthogonal minimally aliased response surface designs or OMARS designs bridges the gap between the small defini tive screening designs and classical response surface designs\, such as ce ntral composite designs and Box-Behnken designs. The initial OMARS designs involve three levels per factor and allow large numbers of quantitative f actors to be studied efficiently using limited numbers of experimental tes ts. 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 s ingle step\, and thereby offer the opportunity to speed up innovation and process improvement. A technical feature of the initial OMARS designs is t hat they study every quantitative factor at its middle level the same numb er of times. In this talk\, we relax this constraint and arrange the desig ns in blocks\, and thereby broaden the family of OMARS designs tremendousl y. We also present a successful application of OMARS designs in the pharma ceutical and chemical industries.

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