Full Agenda - ICON plc

Introductory NONMEM & PDx-Pop & New and Advanced Features of NONMEM 7 and
PDx-POP 5 Workshop
Date of Meeting: 9-11 April 2013 & 10-12 September 2013
Location:
Presenters:
Ellicott City, Maryland
William Bachman, PhD; Robert Bauer, PhD
Agenda Items:
DAY 1 - "Introductory NONMEM & PDx-Pop" - Presentation: Instructor Time
1. Course Introduction William Bachman, PhD
9:00 –
9:15 AM
2.
Introduction to Population Pharmacokinetics (2hrs)
- Classical Population Analysis Principles/Methodologies
- Sums of Squares Objective Functions
- Extended Least Squares
- Fixed and Random effects
- Population Analysis Methods
- First Order
- First Order Conditional Estimation
- Model Development Validation
- data exploration
- structural and error model development
- goodness of fit diagnostics
- diagnostic plots
Robert Bauer, PhD
William Bachman, PhD
9:15 –
11:15 AM
3. Coffee Break
11:15 –
11:30 AM
4.
Analysis of Data from One Subject (3hrs)
- Example (PK, Variance Models)
- Introduction to NONMEM Files and Analysis
Robert Bauer, PhD 11:30 –
12:30 AM
5. Lunch
6. Analysis of Data from One Subject (continued)
7. Break
12:30 –
1:30 AM
Robert Bauer, PhD 1:30 –
3:30 PM
3:30 –
3:45 PM
8. Population Analysis with No Covariates (1.75hrs) William Bachman, PhD
3:45 –
5:30 PM
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2012
DAY 2 – "Introductory NONMEM & PDx-Pop" - Presentation: Presenter Time
1. Population Analysis with No Covariates (continued) William Bachman, PhD
8:30 –
9:00 AM
2.
Population Analysis with Covariates (3.25hrs)
- NONMEM Files
- Exploratory Analysis
- Model Building Example
Robert Bauer, PhD 9:00 –
10:00 AM
3. Break
4. Population Analysis with Covariates (continued)
5. Lunch
6. Population Analysis with Covariates (continued)
10:00 –
10:15 AM
Robert Bauer, PhD 10:15 –
11:30 AM
11:30 –
12:30 AM
Robert Bauer, PhD 12:30 –
1:30 PM
7.
Introduction to Model Evaluation Methods
- User-Written Models in NONMEM (1.75hrs)
* A PK-PD Example
* NONMEM Files
William Bachman, PhD
1:30 –
2:30 PM
8. Break
2:30 –
2:45 PM
9.
User-Written Models (continued)
PK-PD Model Problem
Robert Bauer, PhD 2:45 –
3:30 PM
10. Population Analysis Final Example & Practice Session William Bachman, PhD
3:30 –
5:00 PM
DAY 3 - "New and Advanced Features of NONMEM 7 and
PDx-POP 5" – Presentation:
1. Introduction Robert Bauer, PhD
2.
Modifications and Enhancements to NONMEM 7
- Conversion of Fortran 77 to Fortran 90/95
- Centralized Error Processing
- Improvements in Gradient Methods
- Decreased Incidence of Estimation Failure Due to Numerical
Problems
- Added Option to Specify Step-Size for Gradient Calculation
- Increased Number of Data Items and Label Lengths
- Flexible Numerical Formats for Input and Output
- Added Information in Standard Results File
- Identifier Tags for Certain Sections
- Shrinkage of Variance
- Additional Output Files Easily Readable by Post-Processing Software
William Bachman, PhD
8:30 –
8:45 AM
8:45 –
9:30 AM
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2012
- Additional Weighted Residuals outputs (conditional, exact versions)
3.
New Methods Available in NONMEM 7, Theory, Overview
- Monte Carlo Importance Sampling Expectation Maximization (EM)
(IMP)
- Markov Chain Monte Carlo (MCMC) Stochastic Approximation EM
(SAEM)
- Iterative Two Stage (ITS)
Robert Bauer, PhD
9:30 –
10:00 AM
4. Break
10:00 –
10:15 AM
5.
Mu Modeling
- Model Modifications That Improve Efficiency of EM Methods (Mu
Modeling)
Robert Bauer, PhD
10:15 –
11:00 AM
6.
Examples for EM Methods (hands-on)
- Basic two compartment model problem, incorporate Mu Model
Robert Bauer, PhD
11:00 –
11:45 AM
7. Lunch
11:45 –
12:45 PM
8.
Examples for EM Methods (hands-on)
- Two compartment model with age and gender covariates Robert Bauer, PhD
12:45 –
1:45 PM
9.
Bayesian Analysis (hands-on)
- MCMC Bayesian Analysis (BAYES)
- Prior information for MCMC Bayesian Analysis
- Revisit two compartment model, adding Bayesian analysis
Robert Bauer, PhD
1:45 –
2:45 PM
10. Break
11.
More Examples with EM and Bayesian Analysis
- Population mixture model problem
- Interoccasion variability problem
- Categorical data problem
2:45 –
3:00 PM
3:00-3:30
12.
13.
Additional Considerations for EM and Bayesian Analysis
- Termination Testing
- Making Numerically Stable Models
- Gibbs vs. Metropolis-Hastings
Creating Random Initial Parameters for Multiple Chains (CHAIN)
- Chain command syntax
- Thetas: univariate or normal randomization
- Sigmas: univariate randomization
- Omegas: Wishart randomization
- Using random samples for immediate, or later problems
- Creating random initial values example
Robert Bauer, PhD
3:30-4:00
4:00 –
4:30 PM
14.
PDx-Pop Interface For NONMEM 7
- Real-Time Graphical Monitoring of Objective Function
- Interaction with NONMEM Run
- Toggle Switch for Console Printing of Iterations
- Switch to End a Problem Gracefully
- Switch to End a NONMEM Gracefully
William Bachman, PhD
4:30 –
5:00 PM
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- Extended Summary Output
- Graphical Display of Parameter Sampling History (BAYES)
- Setting Up and Running Multiple Analysis Chains Simultaneously
- Graphical and Tabular Summary of Multiple Analysis Chains (BAYES)
- nitial Parameters Variation Test
- PDx-Pop on Linux and MAC OS X
15. Question and Answer Session, Demonstrations 5:00 PM
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