Advanced compartmental absorption and

Other than the different approaches mentioned above, commercial packages such as GastroPlus (Simulations Plus, Lancaster, CA) [19] and IDEA (LionBioscience, Inc. Cambridge, MA) [19] are available to predict oral absorption and other pharmacokinetic properties. They are both based on the advanced compartmental absorption and transit (CAT) model [20], which incorporates the effects of drug moving through the gastrointestinal tract and its absorption into each compartment at the same time (see also Chapter 22). 

GastroPlus [137] and IDEA [138] are absorption-simulation models based on in vitro input data like solubility, Caco-2 permeability and others. They are based on advanced compartmental absorption and transit (ACAT) models in which physicochemical concepts are incorporated. Both approaches were recently compared and are shown to be suitable to predict the rate and extent of human absorption [139]. 

Furthermore, the Pefr data can be integrated with solubility/dissolution data to predict the oral absorption from the solid dosage form (see Chapter 10). Gastrointestinal transit absorption model (GITA) [12, 13], advanced compartmental absorption and transit model (ACAT, GastroPlus), advanced drug absorption and metabolism model (ADAM, SimCYP) and so on have been reported as useful integration models (see Chapter 10). 

Figure 10.2 Schematic diagram of the advanced compartmental absorption and transit (ACAT) model [18].

These simple models based on the assumption of a single intestinal compartment have been refined to the advanced compartmental absorption and transport model that allows transit and differential expression of enzymes and transporters down the length of the gastrointestinal tract including pH, fluid, and blood flow differences [3]. The ACAT model is based on a series of integrated differential equations and has been implemented in the commercial software Gastroplus (see Chapter 17). 

ACAT Advanced compartmental absorption and transit model... 

We have developed a two-step procedure for the in silico screening of compound libraries based on biopharmaceutical property estimation linked to a mechanistic simulation of GI absorption. The first step involves biopharmaceutical property estimation by application of machine learning procedures to empirical data modeled with a set of molecular descriptors derived from 2D and 3D molecular structures. In silico methods were used to estimate such biopharmaceutical properties as effective human jejunal permeability, cell culture permeability, aqueous solubility, and molecular diffusivity. In the second step, differential equations for the advanced compartmental absorption and transit model were numerically integrated to determine the rate, extent, and approximate GI location of drug liberation (for controlled release), dissolution, and absorption. Figure 17.3 shows the schematic diagram of the ACAT model in which each one of the arrows represents an ordinary differential equation (ODE). 

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