An automated process for building reliable and optimal in vitro/in vivo correlation models based on Monte Carlo simulations
Journal Title: The AAPS Journal - Year 2006, Vol 8, Issue 2
Abstract
Many mathematical models have been proposed for establishing an in vitro/in vivo correlation (IVIVC). The traditional IVIVC model building process consists of 5 steps: deconvolution, model fitting, convolution, prediction error evaluation, and cross-validation. This is a time-consuming process and typically a few models at most are tested for any given data set. The objectives of this work were to (1) propose a statistical tool to screen models for further development of an IVIVC, (2) evaluate the performance of each model under different circumstances, and (3) investigate the effectiveness of common statistical model selection criteria for choosing IVIVC models. A computer program was developed to explore which model(s) would be most likely to work well with a random variation from the original for-mulation. The process used Monte Carlo simulation techniques to build IVIVC models. Data-based model selection criteria (Akaike Information Criteria [AIC],R2) and the probability of passing the Food and Drug Administration “prediction error” requirement was calculated. To illustrate this approach, several real data sets representing a broad range of release profiles are used to illustrate the process and to demonstrate the advantages of this automated process over the traditional approach. The Hixson-Crowell and Weibull models were often preferred over the linear. When evaluating whether a Level A IVIVC model was possible, the model selection criteria AIC generally selected the best model. We believe that the approach we proposed may be a rapid tool to determine which IVIVC model (if any) is the most applicable.
Authors and Affiliations
Steven C. Sutton, Mingxiu Hu
Keywords
Related Articles
- EP ID EP681782
- DOI 10.1007/BF02854901
- Views 106
- Downloads 0
Plant Phytochemicals as Epigenetic Modulators: Role in Cancer Chemoprevention
In recent years, “nutri-epigenetics,” which focuses on the influence of dietary agents on epigenetic mechanism(s), has emerged as an exciting novel area in epigenetics research. Targeting of aberrant epig...
Implementation and Evaluation of the SAEM Algorithm for Longitudinal Ordered Categorical Data with an Illustration in Pharmacokinetics–Pharmacodynamics
Analysis of longitudinal ordered categorical efficacy or safety data in clinical trials using mixed models is increasingly performed. However, algorithms available for maximum likelihood estimation using an approximation...
In Vitro Considerations to Support Bioequivalence of Locally Acting Drugs in Dry Powder Inhalers for Lung Diseases
Dry powder inhalers (DPIs) are used to deliver locally acting drugs (e.g., bronchodilators and corticosteroids) for treatment of lung diseases such as asthma and chronic obstructive pulmonary disease (COPD). Demonstratin...
Population Pharmacokinetic Modeling of the Enterohepatic Recirculation of Fimasartan in Rats, Dogs, and Humans
The online version of this article (doi:10.1208/s12248-015-9764-2) contains supplementary material, which is available to authorized users.
Emerging Applications of Metabolomics in Studying Chemopreventive Phytochemicals
Phytochemicals from diet and herbal medicines are under intensive investigation for their potential use as chemopreventive agents to block and suppress carcinogenesis. Chemical diversity of phytochemicals, together with...