ACoP9 Meeting, October 6th Saturday, Loews Coronado Bay Resort near San Diego, CA, US
IntiQuan is running a full day hands-on workshop on PK/PD and QSP modeling, simulation, and parameter estimation in the open-source and freely available R environment. The major topics covered are:
- Morning session
- PK, PKPD, QSP modeling in R. Description of models and simulation
- Reuse of models from model databases – import of SBML models to R
- NLME parameter estimation in NONMEM, MONOLIX, SAEMIX, & NLMIXR
- Generation of model diagnostics and model development tables
- Automatic reporting of modeling and simulation results in Microsoft Word (quick intro – more details in second IntiQuan Workshop)
- Using R Shiny for PK modeling and reporting
- Afternoon session
- Introduction to a realistic QSP modeling example
- Robust parameter estimation based on sensitivity equations and multi-start optimization in R
- Analyzing models, informing modeling decisions, using profile likelihood
- Advanced simulation in R
- Doing QSP modeling and parameter estimation in R Shiny
After the workshop the participants will be able to write PK, PK/PD and more mechanistic QSP models, simulate them, and perform parameter estimation in supported NLME tools (such as NONMEM, MONOLIX, SAEMIX, and NLMIXR), and using a QSP type of parameter estimation method. Furthermore, participants will be able to generate standard model diagnostics and export all results to Microsoft Word.
The workshop is designed as a hands-on tutorial, allowing participants to work through all examples under guidance of the presenters. All material (slides, example models, R code, required R libraries, and additional software) will be shared with the participants. In case a participant would like to have hands-on experience during the workshop, a laptop with an R installation should be brought to the workshop. Some examples will use NONMEM and/or MONOLIX at the backend for parameter estimation, so it would be good if either of these tools were installed already. In the case that neither is available, the examples can be run with the open-source and freely available SAEMIX or NLMIXR R packages instead. No prior knowledge of either NONMEM, MONOLIX, SAEMIX, or NLMIXR is required. Basic knowledge of NLME modeling and R is of advantage.
|October 6th Saturday|
|8:00-8:15||Welcome and Introduction||Henning Schmidt|
|Daniel Kaschek, PhD, IntiQuan GmbH
Daniel Kaschek is an experienced modeler working in the field of Quantitative Systems Pharmacology and Systems Biology since 2008. Over the past years, he has actively worked on the developed of novel mathematical and statistical approaches to data analysis and parameter estimation in ordinary differential equations with applications in Quantitative Systems Pharmacology and Systems Biology. He is an enthusiast R package developer, authoring several open-source packages on Data pre-processing and dynamic modeling.
|Henning Schmidt, PhD, IntiQuan GmbH
Engineer by training with a long background in modeling of a wide range of general linear and non-linear systems (automotive & process industry, biological, physiological, and pharmacological systems), using both modeling and simulation results as a basis for impactful quantitative support of decision making in large and small, early and late phase drug development projects. Developer of several open source tools for modeling and simulation across Pharmacometrics, Systems Pharmacology, and Systems Biology.
Workshop location: The workshop will be held at the Loews Coronado Bay Resort near San Diego, CA, US, which is the venue for the ACoP9 meeting.
Workshop fee: Regular fee 600 USD. This includes workshop material, coffee breaks, and lunch. Students/Academia/Government/Non-profit employees may enroll at a fee of 300 USD.
Registration: This is a pre-meeting workshop that requires registering for the ACoP 2018 meeting. Please register ASAP in view of the limited course capacity.
Contact: Henning Schmidt, IntiQuan GmbH, Spalenring 150, 4055 Basel, Switzerland; Phone: +41 76 603 28 06; Email: email@example.com.