Clearance metabolic

PBPK models have also been used to explain the rate of excretion of inhaled trichloroethylene and its major metabolites (Bogen 1988 Fisher et al. 1989, 1990, 1991 Ikeda et al. 1972 Ramsey and Anderson 1984 Sato et al. 1977). One model was based on the results of trichloroethylene inhalation studies using volunteers who inhaled 100 ppm trichloroethylene for 4 horns (Sato et al. 1977). The model used first-order kinetics to describe the major metabolic pathways for trichloroethylene in vessel-rich tissues (brain, liver, kidney), low perfused muscle tissue, and poorly perfused fat tissue and assumed that the compartments were at equilibrium. A value of 104 L/hour for whole-body metabolic clearance of trichloroethylene was predicted. Another PBPK model was developed to fit human metabolism data to urinary metabolites measured in chronically exposed workers (Bogen 1988). This model assumed that pulmonary uptake is continuous, so that the alveolar concentration is in equilibrium with that in the blood and all tissue compartments, and was an expansion of a model developed to predict the behavior of styrene (another volatile organic compound) in four tissue groups (Ramsey and Andersen 1984). 

GIT, is considered to be lost from the absorption site, as is metabolic clearance and sequestration in various cell types and membranes (72,14). It is clear from Scheme I that the relative rates of the various processes will define the bioavailable fraction of the dose and understanding those factors which control pulmonary absorption kinetics is obviously the key to enhancing bioavailability via the lung. In a recent book (75) the molecular dependence of lung binding and metabolism was considered alongside the parallel processes of absorption, clearance and dissolution in the lung (14). Some key features of this work will be repeated as it relates to the systemic delivery of polypeptides. 

When a drug is eliminated by both metabolism and urinary excretion, it is possible to calculate the metabolic clearance rate (MCR) by the difference between TCR and RCR ... 

Instead of using the oral bioavailability of a drug, one can attempt to correlate PM values with permeability coefficients generated from in situ perfused intestinal preparations. Here, one eliminates the complexities of liver metabolism, clearance, and formulation variables. Recently, this type of in vitro-in situ correlation has been conducted using the model peptides (described previously in Section V.B.2). The permeabilities of these model peptides were determined using a perfused rat intestinal preparation which involved cannulation of the mesenteric vein (Kim et al., 1993). With this preparation, it was possible to measure both the disappearance of the peptides from the intestinal perfusate and the appearance of the peptides in the mesenteric vein. Thus, clearance values (CLapp) could be calculated for each peptide. Knowing the effective surface area of the perfused rat ileum, the CLapp values could be converted to permeability coefficients (P). When the permeability coefficients of the model peptides were plotted as a function of the lipophilicity of the peptides, as measured by partition coefficients in octanol-water, a poor correlation (r2 = 0.02) was observed. A better correlation was observed between the permeabilities of these peptides and the number of potential hydrogen bonds the peptide can make with water (r2 = 0.56,... 

The drawback of this approach is that it is essentially empirical, and does not allow for differences in metabolic clearance between the species, i.e., it assumes that clearance is proportional to blood flow. This works well for compounds that are highly extracted in the liver, and/or where passive renal clearance is the major pathway [5, 68]. An approach for compounds that are actively secreted into the urine has also been proposed [69], although the precise values of some of the physiological scaling factors have been questioned [70]. 

Lave, T., Coassolo, P., Reigner, B., Prediction of hepatic metabolic clearance based on interspecies allometric scaling techniques and in vitro-in vivo correlations, Clin. Pharmacokinet. 1999, 36, 211-321 and references cited therein. 

R. J., In vitro analysis of human drug glucuronidation and prediction of in vivo metabolic clearance, J. Pharmacol. Exp. Ther. 2002, 301, 382-390. 

An additional example of a bioavailability-predicted absorption plot is shown for a series of calcium antagonists (Fig. 19.8). Again there is considerable scatter in the data, and the four compounds - felodipine, nisoldipine, diltiazem, and verapamil -are predicted to be much better absorbed than was actually observed. Some of these compounds are known to undergo rapid first-pass metabolic clearance, and are also P-gp inhibitors or substrates (diltiazem and felodipine are P-gp substrates nicardipine and nitrendipine are P-gp inhibitors [25] verapamil is a P-gp inhibitor), and this might contribute to the scatter obtained in the graph. 

This model integrates existing in vitro data, such as Caco-2 permeability (Papp) and metabolic stability in liver S9 or microsomes, to estimate bioavailability as being either low, medium, or high. Oral bioavailability predictions for not only humans but also other species can be made by using the metabolic stability values of drugs in liver microsomal enzyme preparations from that species. A premise of this model is that metabolic clearance is more important than renal or biliary clearance in determining bioavailability. However, despite the lack of in vitro renal... 

Obach et al. [27] proposed a model to predict human bioavailability from a retrospective study of in vitro metabolism and in vivo animal pharmacokinetic (PK) data. While their model yielded acceptable predictions (within a factor of 2) for an expansive group of compounds, it relied extensively on in vivo animal PK data for interspecies scaling in order to estimate human PK parameters. Animal data are more time-consuming and costly to obtain than are permeability and metabolic clearance data hence, this approach may be limited to the later stages of discovery support when the numbers of compounds being evaluated are fewer. 

Hirom [71,72] demonstrated more than three decades ago that the route of excretion of xenobiotics is dependent upon MW by testing up to 75 compounds in rat, guinea-pigs, and rabbits. Lower MW compounds (< 350) were mainly eliminated in the urine (>90%). As MW increased from 350 to 450, a sharp increase in the fraction of compound eliminated in the bile occurred, and for MW > 450, compounds were eliminated 50-100% in the bile in all three species. Smith [73] correlated the log of free metabolic and renal clearance (ml/min/kg) with log D, and found a similar relationship. Metabolic clearance increases with increasing log D, while renal clearance decreases with increasing log D. 

Oxidative drug metabolism is extremely complex and possibly the most poorly understood ADME property. Rapid metabolism is unacceptable for drug candidates, except for drugs whose metabolite is the active moiety, because it causes duration of action to be too short. Considerable work has focused on the liver enzyme CYP3A4, which is responsible for the metabolic clearance of approximately 50% of marketed drugs. Recent approaches used to model and understand drug metabolism include database matching, quantum mechanics, QSAR, and structure-based analyses. 

Metabolic clearance of caffeine is altered according to menstrual phase and hormonal status in women (Lane et al. 1992). Clearance is slower during the late luteal phase compared to the follicular phase, prior to the onset of menstruation. However, the size of the effect and significance in everyday activity remains in question. 

The pharmacokinetics of ondansetron in man have been determined in healthy volunteers after single and repeat doses [84]. The clinical pharmacokinetics (Table 7.8) showed many similarities with the kinetics in animals, but also some important differences. Elimination is rapid, but less so than in animals. The volume of distribution is similar in animals and man. As in animals, the clearance of ondansetron in man is predominantly by metabolism. However, metabolic clearance in man is considerably lower than in animals, resulting in a lower first-pass metabolism and a significantly greater oral bioavailability of 60 %. Steady-state concentrations of ondansetron are consistent with the single-dose kinetics of the compound and show no evidence of significant accumulation. 

Kidney failure not only decreases renal clearance of nicotine and cotinine, but also metabolic clearance of nicotine (Molander et al. 2000). Metabolic clearance of nicotine is reduced by 50% in subjects with severe renal impairment compared to healthy subjects. It is speculated that accumulation of uremic toxins may inhibit CYP2A6 activity or downregulate CYP2A6 expression in liver. Hepatic metabolism of several drugs is reduced in kidney failure, mainly via downregulation of CYP enzymes and/or inhibition of transporters (Nolin et al. 2003). 

As mentioned previously, renal failure markedly reduces total renal clearance, as well as metabolic clearance of nicotine and cotinine (Molander et al. 2000). Reduction of renal clearance is correlated with the severity of kidney failure renal clearance is reduced by half in mild renal failure, and by 94% in severe renal impairment. Markedly elevated levels of serum nicotine have been detected in smoking patients with end-stage renal disease undergoing hemodialysis (Perry et al. 1984). This is explained not only by reduced renal clearance, but also by lower metabolic... 

Clearance of drug occurs by the perfusion of blood to the organs of extraction. Extraction (E) refers to the proportion of drug presented to the organ which is removed irreversibly (excreted) or altered to a different chemical form (metabolism). Clearance (Cl) is therefore related to the flow of blood through the organ (Q) and is expressed by the formula ... 

Fig. 5.4 Model for the hepatic processes involved in the clearance of the combined TxSI/TxRAs (see Figure 5.3). The clearance by hepatic uptake (Clup) is the rate-determining step in the removal of the compound from the perfusate. Compounds accumulate within the liver and are subsequently cleared by biliary (Clbii) or metabolic clearance (CIm) (modified from reference [2]).

Rather than looking at a metabolic pathway, similar models for the control of the mechanism of clearance by lipophilicity are demonstrated by considering drugs in general. Figure 5.7 illustrates free drug renal and metabolic clearance for a series of neutral compounds drawn from the literature [4]. 

For hydrophilic drugs (log D7 4 below 0) renal clearance is the predominant mechanism. For drugs with log D74 values above 0, renal clearance decreases with lipophilicity. In contrast to renal clearance, metabolic clearance increases with in-... 

Fig. 5.7 Relationship between lipophilicity and unbound renal (squares) and metabolic clearance (triangles) for a range of neutral drugs in...

When considering the Hkely pharmacokinetic profile of a novel compound in man, it is important to recognize the variability that may be encountered in the cHnical setting. Animal pharmacokinetic studies are generally conducted in inbred animal colonies that tend to show minimal inter-subject variabiHty. The human population contains a diverse genetic mix, without the additional variability introduced by age, disease states, environmental factors and co-medications. Hence any estimate of pharmacokinetic behaviour in man must be tempered by the expected inherent variability. For compounds with high metabolic clearance (e. g. midazolam), inter-individual variability in metabolic clearance can lead to greater than 10-fold variation in oral clearance and hence systemic exposure [1]. 

Species Scaling Incorporating Differences in Metabolic Clearance... 

The equation can be solved for intrinsic clearance (Clj) based upon systemic clearance (Clj) obtained after i.v. administration and hepatic blood flow (Q) in the test species. Intrinsic clearance in man can then be estimated based upon relative in vitro microsomal stabibty and the equation solved to provide an estimate for human systemic clearance. Hence this approach combines aUometry (by considering differences in organ blood flow) and species-specific differences in metabolic clearance. 

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