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Introduction Advanced QSP Modeling in R - Free Webinar

From: Henning Schmidt <>
Date: Sun, 24 May 2020 15:40:44 +0200

*Introduction Advanced QSP Modeling in R*

*“From Clinical Data to Virtual Subjects, Cohorts, and Populations=

Wednesday, June 10th, 2020 2:30pm to 6:30pm CEST
Register for free at:

Due to the cancellation of the PAGE conference, IntiQuan is providing its
PAGE Advanced QSP modeling workshop as a free webinar.

The webinar is split into three parts with the following topics:

*Part 1: General model implementation and simulation*

· Model representation and simulation:

o ODE based syntax

o Biochemical reaction-based syntax

· Standardized general data format applicable to both QSP and N=

· Import of models from SimBiology and Berkeley Madonna into R.

*Part 2: Realistic QSP modeling example*

· Representation of example model and available clinical data.

· Sensitivity analysis aiming at identification of influential
parameters in the model:

o General sensitivity analysis based on mean normalized sensitivity metri=

o Targeted sensitivity analysis for specific model metrics of interest

· Stepwise Parameter Modeling (SPM) for determination of parame=
for which information in the data is contained.

· Estimation of mean parameters on mean and individual level da=

· Stepwise Parameter Modeling – Inter-Individual Variab=
(SPM-IIV) for determination of parameters for which information about
variability is contained in the data.

· Estimation of individual level parameters based on individual
level clinical data

· Generation, representation, and simulation of:

o Virtual subjects

o Virtual cohorts

o Virtual populations

*Part 3: Can I trust my model / the parameter estimates?*

· Robust parameter estimation based on sensitivity equations an=
multi-start optimization in R.

· Analyzing models, informing modeling decisions, using profile
likelihood and other methods.

· Which experiments should be conducted to be able to decide be=
different mechanistic hypotheses?

*Target audience*

The webinar is intended for people who

· are actively working in the area of QSP modeling and would li=
ke to
improve their parameter estimation results, learn how to efficiently assess
non-identifiability, or define new experiments that are critical to inform
their models.

· are interested in applying QSP models to clinical data, invol=
consideration of inter-individual variability in the parameter estimation.

· are simply interested in advanced QSP modeling techniques.

A basic knowledge of R and writing R scripts is an advantage.

*Webinar objectives*

After the workshop, the participants will have learned to write their own
mechanistic QSP models, simulate models, 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. All material and tools to perform
the different steps in the webinar will be provided. Application to own
modeling projects should be feasible after the webinar.


Registration is free of charge and can be done using the following link:

*Webinar material*

Information about how to obtain the webinar material and potential
preparations will be sent out a week before the Webinar.

Best wishes,



IntiQuan GmbH
Elisabethenstrasse 23 [see map] <>
4051 Basel, Switzerland
Tel: +41 76 603 28 06

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IntiQuan GmbH | Managing Director: Dr. Henning Schmidt | Trade register:
Basel Stadt CH- | UID: CHE-181.306.905

Received on Sun May 24 2020 - 09:40:44 EDT

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