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Essay On Intestinal Metabolism

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Prediction of potential DDIs
To date, tremendous efforts have been made to predict the magnitude of in vivo DDIs. Several well-established animal and cell-based models are used for studying intestinal metabolism. The traditional method of predicting intestinal metabolism using information from preclinical studies in animals has changed to the use of physiologically based pharmacokinetic models (PBPK) with in vitro-in vivo extrapolation. These models allowed incorporating intestinal transit times and heterogeneous expression levels of drug-metabolizing enzymes and transport proteins into mechanistic predictions of intestinal absorption and metabolism. In addition, these models divided the gastrointestinal tract into several compartments
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In another study, Heikkinen et al [79] used PBPK modeling to predict intestinal metabolism of the investigated drugs. They used GastroPlus™ software to predict Fg for 20 CYP3A substrates using in vitro and in silico input data for metabolic clearance and membrane permeability. Their research shed the light over some important aspects in using PBPK models in Fg predictions. First, CYP3A-mediated metabolic clearance measured in human liver microsomes can be used to predict gut wall metabolism [79]. Second, using values scaled from in vitro cell permeability as input for effective jejunal permeability resulted in good Fg prediction accuracy compared to the in silico predicted permeability [79]. Third, poor solubility or dissolution may either decrease Fg by preventing saturation of metabolism or increase Fg by shifting the site of absorption towards the colon, where the expression of CYP3A is low [79]. Karlsson et al [80] conducted a study to explore the utility of intestinal S9 fractions, human liver microsomes, and recombinant cytochromes P450 to quantify CYP3A-mediated intestinal extraction in humans for selecting marketed drugs that are predominantly metabolized by CYP3A4. They used a competing rates model to predict the Fg of these drugs comparing to PBPK models and concluded that the use of PBPK model is preferable over the indirect method for deriving Fg
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