The objective of this course is to introduce advanced concepts of population pharmacokinetics in NONMEM.
Robert Bauer, PhD; Brian Sadler, PhD; Indrajit, Das, PhD
The course is targeted to individuals interested in solving population PK/PD problems using the new stochastic methods. The course is for those who are familiar with classic NONMEM methods (first order (FO)/first order conditional estimation (FOCE)/Laplace), and are familiar with constructing control stream files.
Most of the course is instructional, with several hands-on examples for attendee participation A thorough discussion of stochastic approximation expectation maximization (SAEM), Importance sampling (IMP), and Markov chain Monte Carlo Bayesian analysis (BAYES) will be presented, along with hands-on exercises.
After attending this course, the participant will know how to use advanced stochastic methods for analyzing population PK/PD data; structure the models into a MU-referencing format that will greatly increase the efficiency of the analyses; apply prior information from previous analyses to the present data; create population mixture models; create models for categorical data; use new abbreviated code features for easier modeling of inter-occasion variability; model additional mixed effects levels for grouping individuals, such as inter-clinical site variability; use the new DO loop feature in abbreviated code, such as for handling multiple bolus doses in transit compartment models that use the analytical absorption function.
Additional topics covered are: parallel computing and dynamic memory allocation for efficient memory usage; symbolic referencing to thetas, etas, and sigmas; Monte Carlo search algorithms to improve FOCE estimation; built-in individual weighted residuals; bootstrap tools for simulation; and greater control in average eta shrinkage calculations.
- Industry - $800
- Academia/Government - $700
- Student - $600
A 15% discount is available to groups of 3 or more from the same organization
More Information / Registration
Please contact Lisa Wilhelm-Lear to register or request more information.
Deadline for Registration
September 7, 2018