Re-writing Oral Pharmacokinetics Using Physiologically Based Finite Time Pharmacokinetic (PBFTPK) Models

Purpose To develop physiologically based finite time pharmacokinetic (PBFTPK) models for the analysis of oral pharmacokinetic data. Methods The models are based on the passive drug diffusion mechanism under the sink conditions principle. Up to three drug successive input functions of constant rate operating for a total time tau are considered. Differential equations were written for all these models assuming linear one- or two-compartment-model disposition. The differential equations were solved and functions describing the concentration of drug as a function of time for the central and the peripheral compartment were derived. The equations were used to generate simulated data and they were also fitted to a variety of experimental literature oral pharmacokinetic data. Results The simulated curves resemble real life data. The end of the absorption processes tau is either equal to t(max) or longer than t(max) at the descending portion of the concentration time curve. Literature oral pharmacokinetic data of paracetamol, ibuprofen, almotriptan, cyclosporine (a total of four sets of data), and niraparib were analyzed using the PBFTPK models. Estimates for tau corresponding to a single or two or three different in magnitude input rates were derived along with the other model parameters for all data analyzed. Conclusions The PBFTPK models are a powerful tool for the analysis of oral pharmacokinetic data since they rely on the physiologically sound concept of finite absorption time.

Automated summary

The purpose of this study was to develop physiologically based finite time pharmacokinetic models for the analysis of oral pharmacokinetic data. The models were based on the passive drug diffusion mechanism under the sink conditions principle. Simulated data and experimental literature data were used to validate the models. The results showed that the PBFTPK models are a powerful tool for analyzing oral pharmacokinetic data.