Model metabolic-inhibition

In the case of dmg interactions involving metabolic inhibition, little increase in the substrate concentration is expected when the inhibition constant (K ) determined in in vitro studies using human liver samples is larger than the inhibitor concentration in vivo. Various approaches have been adopted using mathematical models in attempts to quantitatively predict in vivo dmg interactions from in vitro data [5]. 

Among all the interactions-based PBTK models published to date, reversible metabolic inhibition is by far the most frequently encountered type of interaction. There are 3 types of reversible enzyme inhibition competitive, noncompetitive, and uncompetitive (Table 2.2), and examples of all are listed in Table 2.3. A large number of examples of such metabolic inhibition in humans and laboratory animals are available for specific CYP enzymes and therapeutic drugs (Dome et al. 2007b). 

For noncancer effects the use of PBTD models has elucidated the fundamental mechanisms of toxicological interactions. Such mechanistic knowledge linked with Monte Carlo simulations has initially been employed in in silico toxicology to develop models that predict the toxicity of mixtures in time. The combination of PBTK/TD models for individual compounds with binary PBTK/TD models can be achieved by incorporating key mechanistic knowledge on metabolism inhibitions and interactions through shared enzyme pathways. Simulations of such models can then be compared to experimental data and allow conclusions to be reached about their pharmacokinetics and the likelihood of effects being dose additive. 

Finally, other aspects that can be investigated with a relevant BBB model involve BBB metabolism, inhibition of endogenous transporters, and effects of sequestration. Such data may enhance... 

Table 12.4 Recent P450 models for inhibition and site of metabolism. 

Mc hadamnia AA, Rostami-Hodj an Abdul-Man R, Wright CE, Mwice AH, Tucker GT. Physiolc ically based modelling of inhibition of metabolism and assessment of relative potency of dri and metabohte dextrcmethorphan vs. dextrorphan using quinidine inhibition. BrJ Clin Pharmacol (2003) 56,57-67. 

Any substance present in great excess can inhibit growth or even cause death. Metabolic products are often toxic to the organism that produces them. Thus, a batch fermentation can be limited by accumulation of products as well as by depletion of the substrate. A simple model for growth in the presence of an inhibitor is... 

Idarubicin inhibits both DNA and RNA polymerase, as well as topoisomerase II. The pharmacokinetics of idarubicin can best be described by a three-compartment model, with an a half-life of 13 minutes, a (3 half-life of 2.4 hours, and a terminal half-life of 16 hours.22 Idarubicin is metabolized to an active metabolite, idarubicinol, which has a half-life of 41 to 69 hours. Idarubicin and idarubicinol are eliminated by the liver and through the bile. Idarubicin has shown clinical activity in the treatment of acute leukemias, chronic myelogenous leukemia, and myelodysplastic syndromes. Idarubicin causes cardiomyopathy at cumulative doses of greater than 150 mg/m2 and produces cumulative cardiotoxic effects with other anthracyclines. Idarubicin is a vesicant and causes red-orange urine, mucositis, mild to moderate nausea and vomiting, and bone marrow suppression. 

Mitomycin C is an alkylating agent that forms cross-links with DNA to inhibit DNA and RNA synthesis. The pharmacokinetics of mitomycin C are best described by a two-compartment model, with an a half-life of 8 minutes and a terminal half-life of 48 minutes.31 Liver metabolism is the primary route of elimination. Mitomycin C has shown clinical activity in the treatment of anal, bladder, cervix, gallbladder, esophageal, and stomach cancer. Side effects consist of myelosuppression and mucositis, and it is a vesicant. 

Researchers focused on the metabolically competent human hepatoma cell line HepG2 as a model of human liver. HepG2 cells are a well-known hepatoma cell line that retains many of the morphological characteristics of liver parenchymal cells. This model is often used as a useful tool for HRA/ERA-oriented chemical risk assessment due to the expression of antioxidant and xenobiotic metabolizing enzymes (in particular phase I and phase II enzymes responsible for the bioactivation/detoxification of various xenobiotics) that can be induced or inhibited by dietary and non-dietary agents [28-30]. 

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