Analysis of drug dissolution data

On the estimate of the rate constant in the homogeneous dissolution model

The aim is to determine how well the rate parameter of the homogeneous model of dissolution can be estimated in dependency on the chosen times to measure the empirical data. The approach is based on the theory of Fisher information. We show that if the probability distribution of the measurement errors is known, the data should be collected at a single time instant or its close proximity in order to obtain the best estimate. This is in sharp contrast with commonly used experimental protocols. Further, from the properties of the Fisher information we deduce how suitable is the model of measurement error and we show that asymmetric distribution of data close to the time origin is unavoidable.

DDSolver: an add-in program for modeling and comparison of drug dissolution profiles

In recent years, several mathematical models have been developed for analysis of drug dissolution data, and many different mathematical approaches have been proposed to assess the similarity between two drug dissolution profiles. However, until now, no computer program has been reported for simplifying the calculations involved in the modeling and comparison of dissolution profiles. The purposes of this article are: (1) to describe the development of a software program, called DDSolver, for facilitating the assessment of similarity between drug dissolution data; (2) to establish a model library for fitting dissolution data using a nonlinear optimization method; and (3) to provide a brief review of available approaches for comparing drug dissolution profiles. DDSolver is a freely available program which is capable of performing most existing techniques for comparing drug release data, including exploratory data analysis, univariate ANOVA, ratio test procedures, the difference factor f (1), the similarity factor f (2), the Rescigno indices, the 90% confidence interval (CI) of difference method, the multivariate statistical distance method, the model-dependent method, the bootstrap f (2) method, and Chow and Ki's time series method. Sample runs of the program demonstrated that the results were satisfactory, and DDSolver could be served as a useful tool for dissolution data analysis.

Bayesian statistics in medicine: a 25 year review

This review examines the state of Bayesian thinking as Statistics in Medicine was launched in 1982, reflecting particularly on its applicability and uses in medical research. It then looks at each subsequent five-year epoch, with a focus on papers appearing in Statistics in Medicine, putting these in the context of major developments in Bayesian thinking and computation with reference to important books, landmark meetings and seminal papers. It charts the growth of Bayesian statistics as it is applied to medicine and makes predictions for the future. From sparse beginnings, where Bayesian statistics was barely mentioned, Bayesian statistics has now permeated all the major areas of medical statistics, including clinical trials, epidemiology, meta-analyses and evidence synthesis, spatial modelling, longitudinal modelling, survival modelling, molecular genetics and decision-making in respect of new technologies.

A novel bending point criterion for dissolution profile interpretation

A novel bending point criterion was developed and compared with a number of existing criteria for the interpretation of certain dissolution profiles; these comparison criteria were the percentage dissolved at a fixed time point, the fitted Weibull parameters, and the area under the dissolution curve (AUC). The statistical bending point model was applied to dissolution curves that showed linear dissolution. The bending point model is based on a general linear model, and its confidence information is obtained using the variance-covariance matrix of the parameter estimates. Practically, three time points in the linear part and two time points on the plateau level are used for a reliable bending point estimation. A comparative study with three batches and three storage conditions of slow-release mucoadhesive buccal tablets was performed. The relative standard deviation (RSD) values of the bending point were typically between 1% and 5% which are considerably lower than the corresponding values of the other criteria (typically between 3% and 15%). The bending point criterion is considered robust and stable for the characterization of certain dissolution profiles. Moreover, the bending point has a particular physical interpretation that is helpful in the framework of the slow-release application of this buccal tablet.