Teaching in population pharmacometrics
 
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Advanced methods for population model building and evaluation in NONMEM

Boston, MA, USA
November 28 - 30, 2018

Overview

The course presents the latest methods for model evaluation, strategies for model improvement as well as strategies to consider when utilizing models for informed drug development. The course will provide tools for fast, efficient and comprehensive model building, evaluation and usage.

The course will consist of lectures that describe and evaluate the various strategies used to develop robust and useful population models as well as hands-on computer exercises where students will actually use those strategies in the classroom. The hands-on material will be based on the most recent developments from NONMEM 7.4, Perl-speaks-NONMEM (PsN) and Xpose.

Topics covered

  • Model evaluation
    • Numerical
    • Prediction-Based
    • Residual-Based
    • Empirical Bayes Estimate (EBE)-Based
    • Simulation-Evaluation/Estimation-Based
    • Covariate model focused diagnostics
    • Parameter uncertainty
    • Automated model quality assesment (QA)
  • Model improvement strategies
    • Parameter variability
    • Covariate models
    • Residual error
    • Handling censored data (BQL)
  • To consider when applying models for informed drug development
    • Type I and II errors
    • Estimation methods
    • Model averaging

Intended course participants

The course is designed for those who have a good working knowledge of pharmacometric analysis with experience in performing NONMEM analyses and/or have attended a NONMEM basic workshop.

Instructors

Prof. Mats Karlsson
Assoc. Prof. Andrew Hooker

Practical Information

The course will run for 2.5 days, November 28 - 30 (10:00 AM - 5:30 pm on day 1, 8:30 am - 5:30 pm on day 2 and 8:30 am - 3:00 pm on day 3).

Computer hardware/software - The course will include hands-on training, with the participants working on their own computers.  All programs will run from a USB memory-stick and participants will not be required to install any programs on their computer. All participants must bring their own Windows laptops (for MAC OS and Linux users a virtual windows environment will work).

Course Fee

Regular fee: $1,700 (billed as €1,500)
Student fee: $1,100 (billed as €1,000)

Registration fee includes: extensive electronic material including lectures, exercises, programs (PsN and Xpose), additional self-study material including hands-on's and solutions. Morning and afternoon refreshments and lunches are included.

Sponsorship

Support from Alnylam for facilities is greatly acknowledged

Questions and registration

For questions, please e-mail Andrew Hooker.

To register follow this link: dinkurs.se/ModelBuildAndEvaluate