Rapid Sample Size Calculations for a Defined Likelihood Ratio Test-Based Power in Mixed-Effects Models
Journal Title: The AAPS Journal - Year 2012, Vol 14, Issue 2
Abstract
Efficient power calculation methods have previously been suggested for Wald test-based inference in mixed-effects models but the only available alternative for Likelihood ratio test-based hypothesis testing has been to perform computer-intensive multiple simulations and re-estimations. The proposed Monte Carlo Mapped Power (MCMP) method is based on the use of the difference in individual objective function values (ΔiOFV) derived from a large dataset simulated from a full model and subsequently re-estimated with the full and reduced models. The ΔiOFV is sampled and summed (∑ΔiOFVs) for each study at each sample size of interest to study, and the percentage of ∑ΔiOFVs greater than the significance criterion is taken as the power. The power versus sample size relationship established via the MCMP method was compared to traditional assessment of model-based power for six different pharmacokinetic and pharmacodynamic models and designs. In each case, 1,000 simulated datasets were analysed with the full and reduced models. There was concordance in power between the traditional and MCMP methods such that for 90% power, the difference in required sample size was in most investigated cases less than 10%. The MCMP method was able to provide relevant power information for a representative pharmacometric model at less than 1% of the run-time of an SSE. The suggested MCMP method provides a fast and accurate prediction of the power and sample size relationship.
Authors and Affiliations
Camille Vong, Martin Bergstrand, Joakim Nyberg, Mats O. Karlsson
Keywords
Related Articles
- EP ID EP681202
- DOI 10.1208/s12248-012-9327-8
- Views 47
- Downloads 0
Commentary: Where and how could biomarkers be used in 2016
Since the beginning of the human genome project there has been considerable speculation about how this resource and the knowledge creation it enabled would change therapeutic discovery, development, and delivery. As the...
Predicting Drug–Drug Interactions: An FDA Perspective
Pharmacokinetic drug interactions can lead to serious adverse events, and the evaluation of a new molecular entity’s drug–drug interaction potential is an integral part of drug development and regulatory...
Mechanisms of drug-induced liver injury
The idiosyncratic nature and poor prognosis of drug-induced liver injury (DILI) make this type of reaction a major safety issue during drug development, as well as the most common cause for the withdrawal of drugs from t...
Meeting Report: Metabolites in Safety Testing (MIST) Symposium—Safety Assessment of Human Metabolites: What’s REALLY Necessary to Ascertain Exposure Coverage in Safety Tests?
In the 2012 AAPS metabolites in safety testing (MIST) symposium held in Chicago, IL, USA, on October 15, 2012, regulatory experts and industrial scientists joined together to discuss their perspectives and strategies in...
Preparation, characterization, and biodistribution study of technetium-99m-labeled leuprolide acetate-loaded liposomes in ehrlich ascites tumor-bearing mice
The purpose of this study was to prepare conventional and sterically stabilized liposomes containing leuprolide acetate in an attempt to prolong the biological half life of the drug, to reduce the uptake by reticuloendot...