These classes provide fundamental software modules for pharmacokinetic and pharmacodynamic (PKPD) modeling. There is no support for non-linear mixed effects (NLME) modeling. The classes may significantly facilitate implementation of tailored solutions to automate PKPD analysis (1). There are classes for representing an experiment, a dosing, observed data, and a model, as well as functions for simulating a model and for parameter estimation. There is also support for reading and writing data from/to Excel (Matlab built-in).
The classes are best explored by a couple of commented examples:
example_fit_inf: fits infusion data to a PKPD model (2-comp PK model, Emax PD model)
example_fit_ev_iv: fits extravascular (ev) and intravascular (iv) data at the same time to a 1-compartment model.
example_readExcel_PKPD_analysis: reads data from Excel file in.xlsx, performs PKPD analysis (2-comp. PK model, receptor occupancy PD model), and writes output to the Excel file.
example_fit_turnover_model: fits PK data to a 1-compartment linear model, then uses the PK parameters to fit a PKPD model (PK 1-comp + turnover model with inhibition of the loss term) to PD data (holding PK parametrs, as well as Imax and n constant).
(1) Lindhardt E, Gennemark P. Automated analysis of routinely generated preclinical pharmacokinetic and pharacodynamic data. J Bioinform Comput Biol. 2014 Jun;12(3):1450010
Peter Gennemark (2020). Preclinical PKPD modeling (https://www.mathworks.com/matlabcentral/fileexchange/43521-preclinical-pkpd-modeling), MATLAB Central File Exchange. Retrieved .
Three-comparment PK model, and PD turnover models added.
Several new PD models (e.g. PD turnover models)
Added reference to published paper
PK_2comp_Ka_Cl_ode was updated.
2013-10-25: corrected calculation of coefficient of variation in Model.m. Revised example_readExcel_PKPD_writePowerPoint.m to improve readability.