Hepatic clearance prediction

Houston JB, Carlile DJ. Prediction of hepatic clearance from microsomes, hepa-tocytes, and liver slices. Drug Metab Rev 1997 Nov 29(4) 891-922. 

As described above, it will be normal to assume that the dose interval is 24 hours, i.e., once-a-day dosing. Absorption can be estimated with good confidence from absorption in the rat (see Section 6.1). Clearance is the sum of the predicted hepatic, renal, biliary and extrahepatic clearance. Hepatic clearance can be derived from in vitro studies with the appropriate human system, using either microsomes or hepatocytes. We prefer to use an approach based on that described by Houston and Carlile [83], Renal clearance can be predicted allometrically (see section 6.8.1). The other two potential methods of clearance are difficult to predict. To minimize the risks, animal studies can be used to select compounds that show little or no potential for clearance by these routes. As volume can be predicted from that measured in the dog, after correction for human and dog plasma protein binding (see Section 6.2), it is possible to make predictions for all of the important parameters necessary. 

Lau, Y.Y. et al. 2002. Development of a novel in vitro model to predict hepatic clearance using fresh, cryopreserved, and sandwich-cultured hepatocytes. Drug Met. Disp. 30 1446. 

S. Suzuki, A. Kagayama, A. et ah Prediction of human hepatic clearance from in vivo animal experiments and in vitro metabolic studies with liver microsomes from animals and humans. Drug Metab Dispos 2001, 29, 1316-1324. 

Let us take the exposure packages as an example technically, most of these assays are highly automated, require small amount of compounds and have a brief cycle time. Scientifically, they fulfill requirements to predict exposure by addressing the three major contributing factors solubility, passive permeability and metabolic (hepatic) clearance. These type of packages are ideal to explore or diagnose scaffold characteristics and define project flowcharts. They can be used repeatedly to test newly synthesized compounds and guide SAR. A number of compounds within a... 

The analysis was completed for 12 compounds for which protein binding, renal and hepatic clearances and microsomal data were available. Plasma concentration versus time profiles in the rat were also available for these compounds. The approach taken was to simulate the individual processes (metabolic clearance, renal clearance, distribution, pharmacological activity). The ability of the PBPK model to simulate the in vivo behavior of the compound was verified in the rat. Thus, the metabolic clearance of the compounds could be reasonably well simulated, based on microsomal data and assuming no binding to microsomes less than twofold deviation between the observed and predicted clearance was achieved for about eight of the... 

Figure 7 Influence of changes in (a) organ blood flow on clearance, (b) fraction of the drug unbound in plasma (/u) on extraction ratio, and (c) intrinsic clearance on extraction ratio as predicted by the well-stirred model of hepatic clearance.

Due to its mathematical simplicity, most in vitro-in vivo correlations are based on a homogeneous, well-stirred model for the liver such that all metabolic enzymes in the liver are exposed to the same drug concentration [266]. Under steady-state conditions, the predicted hepatic clearance CLh for this model is... 

Niro, R., Byers, J., Fournier, R., and Bachmann, K., Application of a convective-dispersion model to predict in vivo hepatic clearance from in vitro measurements utilizing cryopreserved human hepatocytes, Current Drug Metabolism, Vol. 4, No. 5, 2003, pp. 357-369. 

Skaggs SM, Foti RS, Fisher MB. 2006. A streamlined method to predict hepatic clearance using human liver microsomes in the presence of human plasma. J Pharmacol Toxicol Methods 53 284-290. 

Child-Pugh clinical classification scheme (Table 7.5). Serum albumin concentrations were of greatest predictive value for two of the drugs shown in the table. However, this marker was not correlated with the hepatic clearance of lansoprazole, and a combination of all three laboratory tests was better correlated with hepatic clearance of atorvastatin than was serum albumin alone. Serum concentrations of aspartate aminotransferase (AST) or alanine transaminase (ALT) were not correlated with hepatic drug clearance, as might be expected from the fact that these enzymes reflect hepatocellular damage rather than hepatocellular function. 

FIGURE 30.13 Observed total elimination clearance (CLg) of midazolam (MDZ) in liver transplant patients versus hepatic clearance (CLjj) of 1 -OH MDZ predicted from biopsy specimens. The line is the predicted hepatic clearance of MDZ if the I -hydroxylation pathway accounts for 70% of the substrate loss. (Data from Thummel KE et al. J Pharmacol Exp Ther 1994 271 549-56.)... 

Vmax and Km for MDZ 1 -liydroxylation. V,nax determined for each biopsy sample was then scaled to the estimated total liver mass and intrinsic clearance estimated as total liver Vmax/Kn- Hepatic clearance then was predicted from Equation 7.6 in Chapter 7. Figure 30.13 compares the observed total elimination clearance with predicted hepatic clearance based on the assumption that the E-hydroxylation pathway accounts for 70% of the substrate loss. The prediction is quite good. The average absolute deviation between the five observed data points and their predicted values is only 28% and the differences are uniformly distributed. 

The hepatic clearance of drugs with an intermediate extraction ratio (Eh, 0.3-0.6) is affected by all three physiological variables blood flow to the liver, the unbound fraction in blood and the activity of hepatic drug-metabolizing enzymes. Disease-induced changes in the disposition of these drugs is least predictable. 

Nestorov I, Gueorguieva I, Jones HM, Houston B, Rowland M. Incorporating measures of variability and uncertainty into the prediction of in vivo hepatic clearance from in vitro data. Drug Metab Dispos, 2002 30 276-82. 

Table 8.1 Equations for predicting hepatic clearance using the well-stirred model...

Table 8.2 Comparison of the predicted in vivo hepatic clearance and the actual clearance values for compound X...

The first caveat is that all clearance pathways (hepatic, renal, biliary or other) must be taken into consideration. If a compound undergoes a high level of hepatic clearance, then in vitro-in vivo scaling may be used to predict the fraction of systemic clearance expected from this pathway. If a compound undergoes a high level of renal elimination, allometric scaling may be also used to predict the clearance attributed to this pathway. 

The second caveat is that, in order to accurately predict hepatic clearance, the correct in vitro system must be chosen. If the candidate drug is primarily oxidatively metabolized, then liver... 

The use of Caco-2 cell permeability studies has resulted in more accurate oral bioavailability predictions. Using the predicted hepatic clearance for compound X in humans (see above), estimating Fa by extrapolation from the Caco-2 cell Papp and assuming hepatic blood flow for humans (see, for example Rane et al., 1977) of 20 ml min 1 kg the human oral bioavailability of 69-98% is predicted for compound X. This compares well with the known oral bioavailability of this compound in rats and dogs (83 and 72%, respectively). 

They showed that the degree of the reduction in the hepatic clearance was overestimated by a simple calculation of the product of the reduction in the hepatic uptake and biliary excretion (Equation 11.6) and this method is useful to avoid the falsenegative predictions [246]. 

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