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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

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PopED: an extended, parallelized, nonlinear mixed effects models optimal design tool.

Joakim Nyberg¹, Sebastian Ueckert, Eric A Strömberg

¹The Pharmacometrics Research Group, Department of Pharmaceutical Biosciences, Faculty of Pharmacy, Uppsala University, P.O. Box 591, SE-751 24 Uppsala, Sweden.

Computer Methods and Programs in Biomedicine

|May 30, 2012

Summary

This summary is machine-generated.

Optimal design for nonlinear mixed effects models is now more accessible due to software advancements. The enhanced PopED software offers faster calculations and new features for experimental design, improving efficiency and cost-effectiveness.

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Area of Science:

Pharmacometrics
Statistical Modeling
Experimental Design

Background:

Optimal design for nonlinear mixed effects models (NLMEM) has seen increased practical application.
Advancements include new methodologies for pharmacometric models, faster optimization algorithms, and user-friendly software.
These developments facilitate the broader use of optimal design in research.

Purpose of the Study:

To present an enhanced version of the optimal design software PopED with a graphical user interface (GUI).
To introduce new solutions for experimental design challenges, including faster FIM calculations and cost/utility optimization.
To demonstrate the utility of PopED's new features through various examples.

Main Methods:

Extension of the PopED software with an enhanced GUI.
Development of faster and more robust Fisher Information Matrix (FIM) calculations and optimizations.
Incorporation of cost/utility function optimization and design performance diagnostic tools.
Implementation of parallel computing for optimization.

Main Results:

The enhanced PopED software integrates recent advances for optimal NLMEM design.
New solutions address challenges in FIM calculations, optimization, and design evaluation.
Demonstrations cover group size optimization, cost/constraint optimization, FIM approximations, and parallel computing.

Conclusions:

The enhanced PopED software provides an accessible and powerful tool for optimal experimental design in pharmacometrics.
New features improve efficiency, robustness, and cost-effectiveness in designing experiments.
PopED's capabilities support informed decision-making in experimental planning.