Population Analysis of Complex Multidimensional Responses Using Phoenix NLME

On-Demand Webinar

During this webinar, Dr. Serge Guzy demonstrated how Phoenix NLME’s unique interface facilitates a whole new way of thinking about Pop PK/PD that is well-suited to both beginning and advanced modelers. He also highlighted Phoenix NLME’s robust optimization engines, including the recent updates to the QRPEM engine.

The webinar showed how easy Phoenix NLME makes validation of model results through visual predictive checks for both continuous and categorical reposes. Finally, he demonstrated how to simulate optimally designed future clinical trials with an emphasis on how simple Phoenix NLME makes simulation of multi-dimensional and mixed response (continuous and categorical) trials.

About Our Speaker

Serge Guzy, President & CEO, Pop-Pharm. Serge Guzy is currenlty Professor (affiliate) at the University of Maryland, Professor (adjunct) at the University of Minessota, visiting Professor at the school of medicine (Jerusalem) and adjunct associate professor at SUNY Buffalo. He is involved in both research and teaching at all these academic institutions.

Serge is also president and CEO of POP_PHARM, a company that signed a strategic alliance with Certara to develop the Phoenix population software and provide professional training services to assist Phoenix NLME users.

Serge is the co-developer of the MCPEM algorithm that is today implemented in almost all population modeling software.

During this webinar, Dr. Serge Guzy demonstrated how Phoenix NLME’s unique interface facilitates a whole new way of thinking about Pop PK/PD that is well-suited to both beginning and advanced modelers. He also highlighted Phoenix NLME’s robust optimization engines, including the recent updates to the QRPEM engine.

The webinar showed how easy Phoenix NLME makes validation of model results through visual predictive checks for both continuous and categorical reposes. Finally, he demonstrated how to simulate optimally designed future clinical trials with an emphasis on how simple Phoenix NLME makes simulation of multi-dimensional and mixed response (continuous and categorical) trials.