*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: https://zoom.us/webinar/register/WN_JxystoQ9Q7ilGi1Ncw5X0w 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 NLME modeling. · 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 metric o Targeted sensitivity analysis for specific model metrics of interest · Stepwise Parameter Modeling (SPM) for determination of parameters for which information in the data is contained. · Estimation of mean parameters on mean and individual level data. · Stepwise Parameter Modeling – Inter-Individual Variability (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 and 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 between different mechanistic hypotheses? *Target audience* The webinar is intended for people who · are actively working in the area of QSP modeling and would like 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, involving 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* Registration is free of charge and can be done using the following link: https://zoom.us/webinar/register/WN_JxystoQ9Q7ilGi1Ncw5X0w *Webinar material* Information about how to obtain the webinar material and potential preparations will be sent out a week before the Webinar. Best wishes, Henning ________________________________________________________________________________ IntiQuan GmbH Elisabethenstrasse 23 [see map] <https://goo.gl/maps/x5WM2wVdXK8qcn8c6> 4051 Basel, Switzerland Web: www.intiquan.com Tel: +41 76 603 28 06 *Confidentiality Note: *This message is intended solely for the designated recipient(s). It may contain confidential or proprietary information and may be subject to attorney-client privilege or other confidentiality protections. If you are not a designated recipient you may not review, copy or distribute this message. If you receive this in error, please notify the sender by reply e-mail and delete this message. Thank you. *Data Protection & Privacy:* The IntiQuan Data Protection statement applies for all communication. You can view it here: https://www.intiquan.com/data-protection. IntiQuan GmbH | Managing Director: Dr. Henning Schmidt | Trade register: Basel Stadt CH-270.4.004.907-8 | UID: CHE-181.306.905
