Extracting this information is of utmost importance to researchers. It requires testing various models against the data, determining pertinent model parameters through fitting procedures and deciding what is the most meaningful and reliable model. Pharmacokinetic models have been developed for several decades starting from mathematical expressions that are based on the underlying processes.
Even before the implementation of computers, fitting algorithms had been established to allow calculation of best model parameters. For the most part, the trend was to convert the data in a form that would generate a simple shape, e.g., a straight line. This apporach has several advantages, such as visual comparison and ease of calculation. Data transformations are associated with changes in the statistical weighting of individual data points.
Fitting algorithms and computer advances have made direct fitting to complicated (non-linear) models possible and fast, but the process is not automatic. Starting values for model parameters can be crucial for the determination of meaningful final parameters. It rests with the operator to decide if the model tried is the most appropriate. There are statistical criteria for unbiased decisions, but experience is a very important asset for the successful operator. Herein, we utilize PK models based on the concept of finite time of absorption, the so called Physiologically Based Finite Time Pharmacokinetic Models (PBFTPK).
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