Competing pathways in drug metabolism. II. An identical, anterior enzymic distribution for 2- and 5-sulfoconjugation and a posterior localization for 5-glucuronidation of gentisamide in the rat liver

After 50 Years of Hepatic Clearance Models, Where Should We Go from Here? Improvements and Implications for Physiologically Based Pharmacokinetic Modeling

There is overwhelming preference for application of the unphysiologic, well-stirred model (WSM) over the parallel tube model (PTM) and dispersion model (DM) to predict hepatic drug clearance, CLH , despite that liver blood flow is dispersive and closer to the DM in nature. The reasoning is the ease in computation relating the hepatic intrinsic clearance ( CLint ), hepatic blood flow ( QH ), unbound fraction in blood ( fub ) and the transmembrane clearances ( CLin and CLef ) to CLH for the WSM. However, the WSM, being the least efficient liver model, predicts a lower EH that is associated with the in vitro CLint ( Vmax / Km ), therefore requiring scale-up to predict CLH in vivo. By contrast, the miniPTM, a three-subcompartment tank-in-series model of uniform enzymes, closely mimics the DM and yielded similar patterns for CLint versus EH , substrate concentration [S] , and KL / B , the tissue to outflow blood concentration ratio. We placed these liver models nested within physiologically based pharmacokinetic models to describe the kinetics of the flow-limited, phenolic substrate, harmol, using the WSM (single compartment) and the miniPTM and zonal liver models (ZLMs) of evenly and unevenly distributed glucuronidation and sulfation activities, respectively, to predict CLH For the same, given CLint ( Vmax and Km ), the WSM again furnished the lowest extraction ratio ( EH,WSM = 0.5) compared with the miniPTM and ZLM (>0.68). Values of EH,WSM were elevated to those for EH, PTM and EH, ZLM when the Vmax s for sulfation and glucuronidation were raised 5.7- to 1.15-fold. The miniPTM is easily manageable mathematically and should be the new normal for liver/physiologic modeling. SIGNIFICANCE STATEMENT: Selection of the proper liver clearance model impacts strongly on CLH predictions. The authors recommend use of the tank-in-series miniPTM (3 compartments mini-parallel tube model), which displays similar properties as the dispersion model (DM) in relating CLint and [ S ] to CLH as a stand-in for the DM, which best describes the liver microcirculation. The miniPTM is readily modified to accommodate enzyme and transporter zonation.

Hepatic clearance concepts and misconceptions: Why the well-stirred model is still used even though it is not physiologic reality?

The liver is the most important drug metabolizing organ, endowed with a plethora of metabolizing enzymes and transporters to facilitate drug entry and removal via metabolism and/or biliary excretion. For this reason, much focus surrounds the development of clearance concepts, which are based on normalizing the rate of removal to the input or arterial concentration. By so doing, some authors have recently claimed that it implies one specific model of hepatic elimination, namely, the widely used well-stirred or venous equilibration model (WSM). This commentary challenges this claim and aims to provide a comprehensive discussion of not only the WSM but other currently applied hepatic clearance models - the parallel tube model (PTM), the dispersion model (DM), the zonal liver model (ZLM), and the heterogeneous capillary transit time model of Goresky and co-workers (GM). The WSM, PTM, and DM differ in the patterns of internal blood flow, assuming bulk, plug, and dispersive flows, respectively, which render different degrees of mixing within the liver that are characterized by the magnitudes of the dispersion number (D_N), resulting in different implications concerning the (unbound) substrate concentration in liver (Cu_H). Early models assumed perfusion rate-limited distribution, which have since been modified to include membrane-limited transport. The recent developments associated with the misconceptions and the sensitivity of the models are hereby addressed. Since the WSM has been and will likely remain widely used, the pros and cons of this model relative to physiological reality are further discussed.

Formed and preformed metabolites: facts and comparisons

The administration of metabolites arising from new drug entities is often employed in drug discovery to investigate their associated toxicity. It is expected that administration of metabolites can predict the exposure of metabolites originating from the administration of precursor drug. Whether exact and meaningful information can be obtained from this has been a topic of debate. This communication summarizes observations and theoretical relationships based on physiological modelling for the liver, kidney and intestine, three major eliminating organs/tissues. Theoretical solutions based on physiological modelling of organs were solved, and the results suggest that deviations are expected. Here, examples of metabolite kinetics observed mostly in perfused organs that did not match predictions are provided. For the liver, discrepancies in fate between formed and preformed metabolites may be explained by the heterogeneity of enzymes, the presence of membrane barriers and whether transporters are involved. For the kidney, differences have been attributed to glomerular filtration of the preformed but not the formed metabolite. For the intestine, the complexity of segregated flows to the enterocyte and serosal layers and differences in metabolism due to the route of administration are addressed. Administration of the metabolite may or may not directly reflect the toxicity associated with drug use. However, kinetic data on the preformed metabolite will be extremely useful to develop a sound model for modelling and simulations; in-vitro evidence on metabolite handling at the target organ is also paramount. Subsequent modelling and simulation of metabolite data arising from a combined model based on both drug and preformed metabolite data are needed to improve predictions on the behaviours of formed metabolites.

Safety testing of metabolites: Expectations and outcomes

Metabolites arising from chemical entities, old or new, are often mediators of toxicity. Frequently, metabolites are investigated in test animals, with the expectation that the resultant toxicity or activity will mimic the exposure of their formed counterparts. This communication described observations that showed discrepant kinetics between formed and preformed metabolites in the liver, intestine, and kidney, major drug removal organs. Differences in the observed areas under the curve (AUCs) or the extraction ratios (Es) of formed and preformed metabolites in the liver had been attributed to zonal, enzyme heterogeneity, membrane barriers, or transporters. Preformed and formed metabolite also differed in their handling by the kidney; only the preformed and not the formed metabolite would be filtered. In the intestine, differences in the absorption of the precursor and the metabolite and the flow pattern in the intestine would bring about discrepancy in the time-courses of the formed vs. preformed metabolites. Analytical solutions of the AUCs of the metabolites and extraction ratios, based on physiological modeling of the liver, kidney, and intestine, showed that the AUC of the preformed, administered metabolite was dependent only on metabolite parameters, whereas the AUC of the formed metabolite was modulated additionally by the metabolic, secretory and intestinal absorptive intrinsic clearances of the precursor drug. Hence, administration of the synthetic metabolite would not reflect the toxicity associated with the metabolite formed via bioactivation. However, data on preformed metabolite may be used for simultaneous fitting by a combined model of drug and metabolite. Such a strategy is shown to be successful in risk assessment of environmental chemicals. Upon refinement of the resultant model with data on metabolite transport and handling by modeling and simulations, the resultant model would be more robust to provide improved predictions on metabolite toxicity pursuant to drug administration.

Carrier-mediated entry of 4-methylumbelliferyl sulfate: characterization by the multiple-indicator dilution technique in perfused rat liver

The hepatocellular entry of 4-methylumbelliferyl sulfate (4MUS) a highly ionized and highly bound anion capable of futile cycling, was examined in the single-pass albumin-free perfused rat liver preparation. Desulfation of 4MUS to 4-methylumbelliferone (4MU) was verified in vitro to be a low-affinity, high-capacity process (Km = 731 micromol/L; Vmax = 414 nmol min(-1) g(-1) liver). With 4MUS given to the perfused rat liver, sulfation of 4MU, the formed metabolite, was attenuated in the presence of 2,6-dichloro-4-nitrophenol (DCNP), a sulfation inhibitor, and when sulfate ion was substituted by chloride ion. 4MU sulfation, being a high-affinity system, was reduced most effectively at the lowest 4MUS concentration (15 micromol/L) used, evidenced by the increased (24%) net hepatic extraction ratio of 4MUS and reduced utilization (72%) of infused tracer 35SO4(2-) by 4MU for 4MU35S formation. Single-pass multiple indicator dilution (MID) studies were thus conducted under identical conditions (DCNP and absence of inorganic sulfate), with injection of [3H]4MUS and a set of noneliminated vascular and cellular reference indicators into the portal vein (prograde) or hepatic vein (retrograde), against varying background bulk concentrations of 4MUS (5 to 900 micromol/L). The steady-state removal rate of 4MUS and formation rates of 4MU and its glucuronide conjugate (4MUG) were not altered with perfusion flow direction, suggesting the presence of even or parallel distributions of 4MUS desulfation and 4MU glucuronidation activities. When the outflow dilution profile of [3H]4MUS was evaluated with the barrier-limited model of Goresky, a slight red cell carriage effect was found for 4MUS. The permeability surface area product for cellular entry for prograde showed a dramatic concentration-dependent decrease (from 0.13 to 0.01 mL sec(-1) g(-1), or 7.4 to 0.56 times the blood perfusate flow rate) and was resolved as saturable and nonsaturable components, while data for retrograde were more scattered, varying from 2.8 to 1 times the blood perfusate flow rate. Efflux (coefficient = 0.0096 +/- 0.0024 and 0.0088 +/- 0.0062 mL sec(-1) g(-1), respectively) was relatively insensitive to concentration and flow direction. The same was observed for the removal capacity for metabolism and excretion (sequestration coefficient: for prograde, 0.0056 +/- 0.0017 mL sec(-1) g(-1); for retrograde, 0.0056 +/- 0.003 mL sec(-1) g(-1)). The decrease in the apparent partition coefficient (ratio of 4MUS concentration estimated in tissue to unbound plasma concentration) and the increase in relative throughput component with concentration further substantiate the claim on the presence of concentrative processes at the sinusoidal membrane.

Membrane transport in hepatic clearance of drugs. II: Zonal distribution patterns of concentration-dependent transport and elimination processes

PURPOSE

The objective of the present simulation study was to investigate the effects of hepatic zonal heterogeneity of membrane transporter proteins and intrinsic elimination activities on hepatic clearance (CL) and drug concentration gradient profiles in the sinusoidal blood and hepatocytes.

METHODS

The model used in the simulations assumes an apparent unidirectional carrier-mediated transport and a bidirectional diffusion of substrates in the hepatic sinusoidal membrane as well as a nonlinear intrinsic elimination. Three different distribution patterns of the transporter and the metabolizing enzyme along the sinusoidal flow path were used for the simulations. The effects of changes in the Michaelis-Menten parameters for those nonlinear processes, and in the unbound fractions of the drug in blood and tissue components were investigated.

RESULTS

Significant differences in CL occurred when the distribution patterns of the transporter and/or the metabolizing enzyme activities were altered under nonlinear conditions. The highest CL values were observed when the transporter and the metabolizing enzyme had similar distribution patterns within the liver acinus, while opposite distribution patterns produced the lowest CL values. Tissue concentration profiles were significantly affected by the distribution patterns of the transporter, but the changes in blood concentration profiles were relatively small. Altering protein binding in blood produced significant changes in CL, and blood and tissue concentration gradients, while altering protein binding in tissue affected only drug accumulation patterns within hepatocytes, regardless of the distribution patterns of the transporter or the metabolizing enzyme.

CONCLUSIONS

The present simulations demonstrate that hepatic zonal heterogeneities in the transporter and the metabolizing enzyme activities can significantly influence hepatic clearance and/or drug concentration gradient profiles in the sinusoidal blood and hepatocytes.

Hepatic conjugation/deconjugation cycling pathways. Computer simulations examining the effect of Michaelis-Menten parameters, enzyme distribution patterns, and a diffusional barrier on metabolite disposition

Conjugation/deconjugation cycling plays an important role in the physiologic regulation of the concentration of endogenous compounds that form conjugated metabolites. Less is known concerning the deconjugation of xenobiotics. The model compound p-nitrophenol (pNP) is conjugated to sulfate and glucuronide metabolites which can also undergo hydrolysis, via separate enzyme systems, to regenerate pNP. In the present investigation, computer simulations were performed using literature values for the KM and Vmax for each of the four enzyme systems involved in net pNP conjugation. The apparent sulfation rate, apparent glucuronidation rate, and the extraction ratio (E) of pNP were each examined (i) as a function of pNP concentration, (ii) following alterations in the KM and Vmax values for the deconjugation enzymes, (iii) after modulating the enzyme distribution patterns along the liver flow path for both the conjugating and deconjugating enzymes, and (iv) in the presence of drug metabolite diffusional barriers for membrane transport. Results of these simulations demonstrated that changes in the KM or Vmax for deglucuronidation produced changes not only in net glucuronidation but also in net sulfation. Overall extraction (E) of the parent compound was only affected when glucuronidation was an important pathway, i.e., at higher pNP concentrations. Similar results were observed with changes in desulfation, with desulfation having the greatest effects at low pNP concentrations where sulfation represents the predominant metabolic pathway. Changes in the enzyme distribution patterns for the deconjugation pathways showed that the greatest influence on net conjugation rates occurred when hydrolase enzyme activity was distributed downstream from the respective forward reaction. In the presence of a diffusional barrier for metabolite transport (i.e., when the diffusional clearance was one tenth of blood flow), net metabolism of parent was diminished with E decreasing from 0.74, in the absence of a barrier, to 0.23, since the generated metabolite remained, to a great extent, within hepatocytes and underwent a more pronounced hydrolysis. In the presence of diffusional barriers for uptake of the conjugated metabolites, the lowest drug extraction and metabolite formation rates were observed when the distribution of the conjugation and deconjugation pathways across the liver were the same. Therefore, the effects of deconjugation on hepatic drug removal and metabolite formation are highly dependent on the enzymatic parameters of both the forward and reverse reactions, the parent drug concentration, the enzyme distribution patterns, and the presence of diffusional barriers for metabolite membrane transport. Since a change in the deconjugation of one metabolite can influence the net formation of not only itself but also other metabolites, and overall drug extraction, evaluation of conjugation/deconjugation cycling represents an important consideration in pharmacokinetic studies involving physiological-, pathological-, or pharmacological-induced alterations in conjugate formation.

Availability and mean transit times of phenol and its metabolites in the isolated perfused rat liver: normal and retrograde studies using tracer concentrations of phenol

Phenolic compounds are frequently detoxified by the formation of sulphate and glucuronic acid conjugates in the liver. These conjugates are formed in the hepatocytes and then either transported into the bile or back into the blood. In this study, we examined the transport kinetics of phenol and its metabolites in the isolated perfused rat liver by monitoring the outflow profiles of these compounds after a bolus input in a single pass preparation. Phenol was almost exclusively metabolized to phenyl sulphate (97%) at the trace concentrations used, with the amount of phenol and metabolites excreted into the bile being minimal (3.5%). The metabolite formed was rapidly transported back into the perfusate, with mean transit times of 17.4 and 12.3 s anterograde and 24.9 and 24.2 s retrograde at flow rates of 15 and 30 mL min-1 respectively, which were intermediate between those of Evans blue and water. The outflow concentration-time profile for phenyl sulphate formation was unaffected by the addition of another organic anion (bromosulphophthalein). The effect of enzyme zonation on outflow concentration-time profiles was also investigated using retrograde perfusions. The transit time ratios for generated metabolite to water for anterograde perfusions (0.6) was found to be more than twice that for retrograde perfusions (0.23) at 15 mL min-1 and approximately 1.6 times greater at 30 mL min-1, being 0.58 and 0.37 respectively. The relative ratios obtained are consistent with previous findings that normalized variance of solutes in the retrograde perfusions is greater than that for anterograde perfusions.

Transport, binding, and metabolism of sulfate conjugates in the liver

Sulfate conjugates are a heterogeneous class of polar, anionic metabolites that result from the conjugation of endogenous and exogenous compounds. Sulfate conjugates exhibit a high degree of binding to albumin, the extent of which usually exceeds those of their parent compounds. Preponderant direct and indirect evidence suggests that sulfation activity is slightly higher in the periportal than in the perivenous (centrilobular) region of the liver, but recent immunohistochemical studies imply that specific isoforms of the sulfotransferases may also be preferentially localized in the perivenous region. Entry of sulfate conjugates into the liver cell is poor unless discrete carriers are present. Although known transport carriers exist for the sulfated bile acids, the specificity of the carriers for drug sulfate conjugates is presently unknown. The removal of sulfates is usually by way of biliary excretion while, on occasion, sulfates can be desulfated and participate in futile cycling with their parent compounds. The binding, transport, and hepatic elimination of various drug sulfate conjugates are examined. Non-recirculating studies carried out in the perfused rat liver with the multiple indicator dilution technique under varying input sulfate conjugate concentrations have provided essential information on the effects of vascular (red blood cells and plasma protein) binding on transport and removal of the conjugates. These studies clearly demonstrate the need to study protein binding, transmembrane transfer characteristics across the liver basolateral (sinusoidal) and canalicular membranes, and enzyme zonation in a distributed-in-space fashion in order to properly define the handling of sulfate conjugates in the liver.

Nonlinear protein binding and enzyme heterogeneity: effects on hepatic drug removal

The kinetics of substrate removal by the liver and the resulting nonlinear changes in unbound fraction along the flow path at varying input drug concentrations were examined by a model simulation study. Specifically, we varied the binding association constant, KA, and the Michaelis-Menten constants (Km and Vmax) to examine the steady state drug removal (expressed as hepatic extraction ratio E) and changes in drug binding for (i) unienzyme systems and (ii) simple, parallel metabolic pathways; zonal metabolic heterogeneity was also added as a variable. At low KA, E declined with increasing input drug concentration, due primarily to saturation of enzymes; only small differences in binding were present across the liver. At high KA, a parabolic profile for E with concentration was observed; changes in unbound fraction between the inlet and the outlet of the liver followed in parallel fashion. Protein binding was the rate-determining step at low input drug concentrations, whereas enzyme saturation was the rate-controlling factor at high input drug concentration. Heterogeneous enzymic distribution modulated changes in unbound fraction within the liver and at the outlet. Despite marked changes in unbound fraction occurring within the liver for different enzymic distributions, the overall transhepatic differences were relatively small. We then investigated the logarithmic average unbound concentration and the length averaged concentration as estimates of substrate concentration in liver in the presence of nonlinear drug binding. Fitting of simulated data, with and without assigned random error (10%), to the Michaelis-Menten equation was performed; fitting was repeated for simulated data obtained with presence of a specific inhibitor of the high-affinity, anteriorly distributed pathway. Results were similar for both concentration terms: accurate estimates were obtained for anterior, high affinity pathways; an overestimation of parameters was observed for the lower affinity posteriorly distributed pathways. Improved estimations were found for posteriorly distributed pathways upon inhibition with specific inhibitors; with added random error, however, the improvement was much decreased. We applied the method for fitting of several sets of metabolic data obtained from rat liver perfusion studies performed with salicylamide (SAM) (i) without and (ii) with the presence of 2,6-dichloro-4-nitrophenol (DCNP), a SAM sulfation inhibitor. The fitted results showed that SAM sulfation was a high-affinity high-capacity pathway; SAM glucuronidation was of lower affinity but comparable capacity as the sulfation pathway, whereas SAM hydroxylation was of lower affinity and lower capacity.

A comparative investigation of hepatic clearance models: predictions of metabolite formation and elimination

Liver clearance models serve to improve our understanding of the relationships between the physiological determinants and hepatic clearance and predict changes in the disposition of substrates when homeostasis of the organ is perturbed. Their ability to describe metabolism was presently extended to the sequential formation and elimination of primary (M1), secondary (M2), and tertiary (M3) metabolites during a single passage of drug (P) across the liver, under steady state and first-order conditions. The well-stirred model is distinct from other models in that metabolite formation and elimination is independent of enzymic distributions, the number of steps involved in metabolite formation, and the intrinsic clearances of the precursors. This model predicts that the extraction ratio of a formed primary metabolite derived from drug (E[M1, P]) is identical to that for the preformed primary metabolite (E[M1]), and that the extraction ratios of a secondary metabolite derived from drug (E[M2, P]) and primary metabolite (E[M2, M1]) or preformed secondary metabolite (E[M2]) are identical. For the more physiologically acceptable, parallel-tube and dispersion models, metabolite sequential elimination is highly influenced by the intrinsic clearances of the precursors and the enzymic distributions that mediate removal of precursor species and the metabolites. Furthermore, the extent of sequential metabolism recedes as the number of steps involved for metabolite formation increases. These models predict that E[M1, P] less than E[M1], and E[M2, P] less than E[M2, M1] less than E[M2], with the magnitude of the changes being less for the dispersion model than for the parallel-tube model. Competing pathways that divert substrate from entering the sequential pathway were found to exert only minimal influence on the sequential pathway.

Hepatic modeling of metabolite kinetics in sequential and parallel pathways: salicylamide and gentisamide metabolism in perfused rat liver

Previous data on salicylamide (SAM) metabolism in the perfused rat liver had indicated that SAM was metabolized by three parallel (competing) pathways: sulfation, glucuronidation, and hydroxylation, whereas sequential metabolism of the hydroxylated metabolite, gentisamide (GAM), was solely via 5-glucuronidation to form GAM-5G. However, under comparable conditions, preformed GAM formed mainly two monosulfate conjugates at the 2- and 5-positions (GAM-2S and GAM-5S); 5-glucuronidation was a minor pathway. In the present study, the techniques of normal (N) and retrograde (R) rat liver perfusion with SAM and mathematic modeling on SAM and GAM metabolism were used to explore the role of enzymic distributions in determining the dissimilar fates of GAM, as a generated metabolite of SAM or as preformed GAM. Changes in the steady-state extraction ratio of SAM (E) and metabolite formation ratios between N and R perfusions were used as indices of the uneven distribution of enzyme activities. Two SAM concentrations (134 and 295 microM) were used for single-pass perfusion: the lower SAM concentration exceeded the apparent Km for SAM sulfation but was less than those for SAM glucuronidation and hydroxylation; the higher concentration exceeded the apparent Km's for SAM sulfation and glucuronidation but was less than the Km for hydroxylations. Simulation of SAM metabolism data was carried out with various enzyme distribution patterns and extended to include GAM metabolism. At both input concentrations, E was high (0.94 at 134 microM and 0.7 at 295 microM) and unchanged during N and R, with SAM-sulfate (SAM-S) as the major metabolite and GAM-5G as the only detectable metabolite of GAM. Saturation of SAM sulfation occurred at the higher input SAM concentration as shown by a decrease in E and a proportionally less increase in sulfation rates and proportionally more than expected increases in SAM hydroxylation and glucuronidation rates. At both SAM concentrations, the steady-state ratio of metabolite formation rates for SAM-S/SAM-G decreased when flow direction changed from N to R. An insignificant decrease in SAM-S/SAM-OH was observed at the low input SAM concentration, due to the small amount of SAM-OH formed and hence large variation in the ratio among the preparations, whereas at the high input SAM concentration, the decrease in SAM-S/SAM-OH with a change in flow direction from N to R was evident. The metabolite formation ratio, SAM-G/SAM-OH, however, was unchanged at both input concentrations and flow directions.(ABSTRACT TRUNCATED AT 400 WORDS)