PAGE 2020 Satellite Workshop: Advanced QSP Modeling – From Clinical Data to Virtual Subjects, Cohorts, and Populations

PAGE2020 Workshop on Advanced QSP Modeling in R

On Tuesday, June 9, 2020, IntiQuan will present a full day hands-on workshop on Advanced QSP Modeling in R. Special emphasis is put on the estimation of individual parameters based on clinical data, allowing to determine Virtual Subjects, Cohorts, and Populations in an estimation-based approach that is suitable even for large scale models and a large number of patients in the considered data. The ability to estimate such individual level parameters in QSP models has the potential to open up advances in diagnostics through the use of advanced statistical methods.

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PAGE 2020 Satellite Workshop: Population PK/PD modeling in R

PAGE2020 Workshop on Population PKPD Modeling in R

On Tuesday, June 9, 2020, IntiQuan will present a full day hands-on workshop on PKPD/NLME modeling workflow from data exploration, parameter estimation, and reporting in the R environment using our IQR Tools R package. After the workshop, the participants will be able to set up their own PKPD/NLME workflow using IQR Tools to: explore the modeling dataset, perform parameter estimation in supported NLME tools, and evaluate parameter estimation results. Furthermore, participants will be able to generate a short report in Microsoft Word directly from the results generated in R.

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Population PK/PD modeling in R

WCoP2020 Workshop on Population PKPD Modeling in R

On Monday, April 6, 2020, IntiQuan will present a full day hands-on workshop on PKPD/NLME modeling workflow from data exploration, parameter estimation, and reporting in the R environment using our IQR Tools R package. After the workshop, the participants will be able to set up their own PKPD/NLME workflow using IQR Tools to: explore the modeling dataset, perform parameter estimation in supported NLME tools, and evaluate parameter estimation results. Furthermore, participants will be able to generate a short report in Microsoft Word directly from the results generated in R.

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Advanced QSP Modeling – From Clinical Data to Virtual Subjects, Cohorts, and Populations

COVID-19 Update: QSPC2020 Workshop replaced by Free Webinar

Special emphasis is put on the estimation of individual parameters based on clinical data, allowing to determine Virtual Subjects, Cohorts, and Populations in an estimation-based approach that is suitable even for large scale models and a large number of patients in the considered data. The ability to estimate such individual level parameters in QSP models has the potential to open up advances in diagnostics through the use of advanced statistical methods.

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Boston QSP Modeling Workshop

After the workshop, the participants will have learned to write their own mechanistic QSP models, simulate models, graphically explore their data, and perform parameter estimation – with and without consideration of parameter variability. In addition, participants will have gained insight into how models can be analyzed to better inform the design of new experiments to increase mechanistic understanding and trust in the models.

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QSP modeling in R

Are you faced with complex drug and disease models? Heterogeneous experimental data? The need for adequate characterization of the available data? A drug discovery and/or development team that requires you to convince them that they can trust in your model’s predictions? => Then our ACoP10 Workshop is probably the right thing for you!

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Population PK/PD modeling in R

PAGE2019 Workshop on Population PKPD Modeling in R
On Tuesday, June 11, 2019, IntiQuan will present a full day hands-on workshop on PKPD/NLME modeling workflow from data exploration, parameter estimation, and reporting in the R environment using our IQR Tools R package. After the workshop, the participants will be able to set up their own PKPD/NLME workflow using IQR Tools to: explore the modeling dataset, perform parameter estimation in supported NLME tools, and evaluate parameter estimation results. Furthermore, participants will be able to generate a short report in Microsoft Word directly from the results generated in R.

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