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Research ArticleArticle

A New Physiologically Based, Segregated-Flow Model to Explain Route-Dependent Intestinal Metabolism

Diem Cong, Margaret Doherty and K. Sandy Pang
Drug Metabolism and Disposition February 2000, 28 (2) 224-235;

Abstract

Processes of intestinal absorption, metabolism, and secretion must be considered simultaneously in viewing oral drug bioavailability. Existing models often fail to predict route-dependent intestinal metabolism, namely, little metabolism occurs after systemic dosing but notable metabolism exists after oral dosing. A physiologically based,Segregated-Flow Model (SFM) was developed to examine the influence of intestinal transport (absorption and exsorption), metabolism, flow, tissue-partitioning characteristics, and elimination in other organs on intestinal clearance, intestinal availability, and systemic bioavailability. For the SFM, blood flow to intestine was effectively segregated for the perfusion of two regions, with 10% reaching an absorptive layer–the enterocytes at the villus tips of the mucosa where metabolic enzymes and the P-glycoprotein reside, and the remaining 90% supplying the rest of the intestine (serosa and submucosa), a nonabsorptive layer. The traditional, physiologically-based model, which regards the intestine as a single, homogeneous compartment with all of the intestinal blood flow perfusing the tissue, was also examined for comparison. The analytical solutions under first order conditions were essentially identical for the SFM and traditional model, differing only in the flow rate to the absorptive/removal region. The presence of other elimination organs did not affect the intestinal clearance and bioavailability estimates, but reduced the percentage of dose metabolized by the intestine. For both models, intestinal availability was inversely related to the intrinsic clearances for intestinal metabolism and exsorption, and was additionally affected by both the rate constant for absorption and that denoting luminal loss when drug was exsorbed. However, the effect of secretion by P-glycoprotein became attenuated with rapid absorption. The difference in flow between models imparted a substantial influence on the intestinal clearance of flow-limited substrates, and the SFM predicted markedly higher extents of intestinal metabolism for oral over i.v. dosing. Thus, the SFM provides a physiological view of the intestine and explains the observation of route-dependent, intestinal metabolism.

Drugs administered orally must first be absorbed, either passively or via facilitated transport, across the intestinal luminal membrane to reach the systemic circulation. Much is known about the various intestinal transport proteins that participate in the uptake of drugs (Tsuji and Tamai, 1996; Lin et al., 1999). Additionally, the intestine possesses metabolic enzymes, notably the conjugating enzymes, UDP-glucuronosyltransferases, glutathione S-transferases (Dubey and Singh, 1988; Ilett et al., 1990; Koster et al., 1995), and cytochrome P-450 3A (Watkins et al., 1987; Peters and Kremers, 1989;Kolars et al., 1992; Lampen et al., 1995; Paine et al., 1996, 1997). In some instances, metabolism by the intestine was noted only during absorption and not on subsequent circulation through the intestinal tissue. That intestinal metabolism is “route dependent”, being greater with oral than with i.v. dosing, was observed for acetaminophen (Pang et al., 1986), enalapril (Pang et al., 1985), and morphine (Doherty and Pang, 2000), and for the conversion of the prodrug (−)6-aminocarbovir to (−)carbovir (Wen et al., 1999) in the perfused rat small intestine preparation. The observation was repeated for the oxidation of midazolam in man (Paine et al., 1996, 1997). Furthermore, a 170-kDa protein, the P-glycoprotein (Pgp),2 has been identified to be responsible for drug efflux into the intestinal lumen (Thiebault et al., 1987; Hunter et al., 1990; Hsing et al., 1992; Saitoh and Aungst, 1995; Smit et al., 1998). Intestinal metabolism and exsorption effectively reduce the bioavailability of orally administered agents (Gibaldi et al., 1971; Leu and Huang, 1995; Doherty and Pang, 1997; Lown et al., 1997; Arimori and Nakano, 1998; Wacher et al., 1998; Hall et al., 1999; Lin et al., 1999).

Despite the large body of information on intestinal exsorption and metabolism, only a few models exist to correlate these physiological processes with the overall drug absorption or bioavailability (Barr and Riegelman, 1970; Crouthamel et al., 1975; Stigsby and Krag, 1983;Nakashima et al., 1984; Choi et al., 1995; Yu and Amidon, 1998; Ito et al., 1999). Although the models would account for multiple-site/regional absorption, metabolism, secretion, or even diffusion within the tissue, few would forecast route-dependent intestinal metabolism. An exception is the model proposed by Klippert and Noordhoek (1985) that suggests shunting of intestinal blood for prediction of route-dependent metabolism.

In this communication, a physiologically basedSegregated-Flow Model (SFM) was developed to explain route-dependent intestinal metabolism; the model encompassed differential blood perfusions to distinct tissue layers of the intestine. The properties of the model were investigated upon engendering intestinal blood flow, the intestinal metabolic, secretory, and intrinsic clearances, tissue-partitioning characteristics (diffusion-limited versus flow-limited distribution) of substrate, and presence of eliminatory pathways in parallel organs to predict the intestinal clearance and systemic availability. The segregated flows could be rationalized because distinct blood flow patterns have been noted for various tissue layers of the intestine—the mucosa, submucosa, and muscularis—with each contributing to one of three functions of the small intestine, absorption, secretion, and motility (Granger et al., 1980), and the serosa that lies inferior to the muscularis. The large surface area for absorption is attributed to the villi and microvilli of the mucosa, and metabolizing enzymes are located within enterocytes at the villus tip (Kolars et al., 1992; Lown et al., 1997). It has been noted that the majority of “resting” intestinal blood flow, some 60 to 70% of the intestinal flow, is distributed to the mucosa-submucosa because of greater metabolic demand (Schurgers and de Blaey, 1984), with approximately 18% (MacFerran and Mailman, 1977), 5 to 7% (Mailman, 1978; Granger et al., 1980), or 10 to 30% (Svanvik, 1973; Micflikier et al., 1976) of the intestinal blood flow perfusing the enterocyte layer of the villus tips where the majority of the absorptive, metabolic, and Pgp activities reside. Because flow perfusing the site of elimination can influence the disposal of drugs and because there are differing blood flow distributions to various tissue layers of the small intestine, it becomes important to view intestinal drug metabolism beyond what is ordinarily considered in traditional, compartmental, or physiological models, in which the absorptive layer is assumed to receive 100% of the total intestinal blood flow.

Two physiological models for the intestine were examined: theTraditional Model (TM) (Fig.1A) and the SFM (Fig. 1B). Removal by other parallel eliminating organs exists, and the effective clearance is described by CLothers. Common features of the models include the interconnection of the blood compartment (central or reservoir compartment in this instance) to the intestinal tissue via the circulation. Only first order transport and removal processes are considered, and for the sake of simplicity, the drug is assumed to be completely unbound.

Figure 1
Figure 1

Schematic presentations of TM (A) and SFM (B) for intestinal absorption, metabolism, and secretion of substrates given orally or i.v.; the conditions considered mimic the recirculating perfused small intestine preparation with additional (parallel) clearances occurring within the central or reservoir compartment.

Refer to text for details.

Traditional Model.

The intestine is subdivided into the vascular (intestinal blood), cellular (tissue), and luminal subcompartments (Fig. 1A). The tissue is supplied with blood from the superior mesenteric artery with the flow rate, QI; venous blood returns through the portal vein to the reservoir. The exchange of substrate between the cellular and vascular compartments is described by the intrinsic transport clearance terms CLd1 and CLd2 that characterize, respectively, transport from intestinal blood into intestinal tissue and vice versa. The rate constant for absorption of the substrate across the luminal membrane is denoted by ka, whereas luminal removal of the drug, either by metabolism, fecal excretion, and/or gastrointestinal transit, is represented by rate constant kg. Once in the intestinal tissue, the drug undergoes biotransformation, and is transported out to blood or effluxed into lumen—processes that are described by intrinsic clearance terms CLm, CLd2, and CLsec, respectively (Doherty and Pang, 2000).

Segregated-Flow Model.

This model is an expansion of the physiological model normally developed for the intestine, but it further recognizes the subtle demarcation of tissue layers and distributions in blood supply. The notion of flow-bypass of tissular regions of the intestine was also recognized by Klippert and Noordhoek (1985). Drug in the serosal blood compartment equilibrates with tissue with the transfer clearances CLd3 and CLd4, whereas drug in the mucosal-blood/enterocyte-blood compartment equilibrates with tissue with the transfer clearances CLd1and CLd2. The absorptive, metabolic, and efflux activities within the villus tips of the enterocyte compartment are denoted by the rate constant, ka, and the intrinsic clearances, CLm and CLsec, respectively (see Fig. 1B).

Experimental Procedures

Mass-balanced equations were written for the TM and the SFM. For emphasis of intestinal metabolism, secretion, and absorption, the system described was similar to that for the recirculating system of the perfused intestine preparation (Doherty and Pang, 2000).

Traditional Model.

For the rate of change of drug in the reservoir (compartment “R”):dARdt=QIAint,bVint,b−(QI+CLothers)ARVR Equation 1For the rate of change of drug in the intestinal blood (compartment “int,b”):dAint,bdt=QIARVR−(CLd1+QI)Aint,bVint,b+CLd2AintVint Equation 2For the rate of change of drug and formation of metabolite {mi} in the intestinal tissue (compartment “int”):dAintdt=kaAlumen−(CLd2+CLsec+CLm)AintVint+CLd1Aint,bVint,b Equation 3dAint{mi}dt=CLmAintVint Equation 3AFor the rate of change of drug in the intestinal lumen (compartment “lumen”):dAlumendt=CLsecAintVint−(ka+kg)Alumen Equation 4

Segregated-Flow Model.

For the rate of change of drug in the reservoir (compartment “R”):dARdt=QsAs,bVs,b+QenAen,bVen,b−(QI+CLothers)ARVR Equation 5For the rate of change of drug and rate of formation of metabolite {mi} in enterocyte layer of mucosa (compartment “en”):dAendt=kaAlumen−(CLd2+CLsec+CLm)AenVen+CLd1Aen,bVen,b Equation 6dAen{mi}dt=CLmAenVen Equation 6AFor the rate of change of drug in the mucosal blood to enterocyte compartment (compartment “en,b”):dAen,bdt=QenARVR+CLd2AenVen−(CLd1+Qen)Aen,bVen,b Equation 7For the rate of change of drug in the serosal blood (compartment “s,b”):dAs,bdt=QsARVR+CLd4AsVs−(CLd3+Qs)As,bVs,b Equation 8For the rate of change of drug in the compartment comprising of the serosa and other intestinal structures (compartment “s”):dAsdt=CLd3As,bVs,b−CLd4AsVs Equation 9For the rate of change of drug in the intestinal lumen (compartment “lumen”):dAlumendt=CLsecAenVen−(ka+kg)Alumen Equation 10It is noteworthy that if Qen equals QI, the SFM simplifies to the TM.

The coefficients in the mass-balanced rate equations for drug with the TM (eqs. 1 to 4) and SFM (eqs. 5 to 10) were represented as elements in 4 × 4 and 6 × 6 matrices, respectively. Inversion of these matrices with the software Theorist on a Macintosh computer (Power Macintosh 9500/120) provided the analytical solutions for areas under the amount-time curves per unit i.v. or p.o. dose. Multiplication of these by the ratios of administered doses to reservoir volumes furnished areas under the concentration-time curves (AUC). With the assumption that clearance is constant under first order conditions, the dose-corrected areas under the curves were used to estimate model-independent parameters: 1) the total body or systemic clearance (CLt) from Dosei.v./AUCR,i.v., 2) the intestinal clearance (CLI) or (CLt− CLothers), and 3) the systemic bioavailability (Fsys) or AUCR,p.o./AUCR,i.v.. The fraction of drug that ultimately reaches the systemic circulation, Fsys, is a product of the fraction of drug that is absorbed across the intestinal membrane (Fabs) and that portion that escapes intestinal metabolism and exsorption (FI). Based on the calculated Fsys and the definition of the fraction absorbed [Fabs, the ratio of the absorption rate constant to the sum of the absorption and luminal degradation rate constants or ka/(ka + kg)], intestinal availability (FI) was calculated as Fsys/Fabs.

Simulation.

Values of the intestinal clearance and the systemic and intestinal availabilities were either simulated with the equations (eqs. 1 to 10, with the program, Scientist, Micromath, Salt Lake City, UT) or calculated using the solutions obtained for both the TM and the SFM. Various values for the volume, flow, and transport and intrinsic clearances (Table 1) were placed into rows and columns of the worksheet in Excel (Version 5.0 for Macintosh, Microsoft, Seattle, WA) and substituted into the solved equations (see Table 2) for estimation of the various parameters. The overall intestinal flow rate was set as 8 ml/min. Because literature values for the blood flow to the absorptive enterocyte layer of the mucosa vary greatly, ranging from 5 to 30% (Svanvik, 1973; MacFerran and Mailman, 1977; Mailman, 1978; Granger et al., 1980), the average flow to this compartment was assigned 10% of intestinal flow for the sake of simplicity, and the remaining compartment—the serosa and other intestinal structures—received the other 90% of flow; the volumes were partitioned in the same fashion. Furthermore, simulation was performed with transport clearances between blood and tissue compartments being identical for the TM (CLd = CLd1 = CLd2) and for SFM (CLd = CLd1 = CLd2 = CLd3 = CLd4). The value of CLd was set either as 0.5 or 50 ml/min, because these represented conditions of drugs of low (diffusion-limited distribution) and high (flow-limited distribution) permeability, respectively. The intestinal metabolic intrinsic clearance (CLm, ranging from 0.1 to 50 ml/min), the exsorption or secretory intrinsic clearance (CLsec, ranging from 0 to 50 ml/min), and values of the absorption rate constant (ka, from 0.01 to 10 min−1) were varied under a nonchanging kg (0.5 min−1) to study the influence of these factors on the area under the curve, clearance, and bioavailability estimates.

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Table 1

Input parameters used for simulations according to both TM and SFM on intestinal clearance and bioavailability

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Table 2

Analytical solutions based on the traditional intestinal model for the CLI, AUC, and availabilities (Fsys, FI), when metabolism occurs only within the intestinal tissue

To assess the importance of intestinal exsorption by Pgp on drug bioavailability, the metabolic component was set to zero (CLm = 0). The secretory intrinsic clearance (CLsec), the absorption rate constant (ka), and the rate constant for gastrointestinal transit/loss (kg = 0.01, 0.5, or 10 min−1) were varied for a substrate with CLd = 0.5 and 50 ml/min. Lastly, the extents of intestinal drug metabolism after i.v. and p.o. dosing were compared between the models. In these simulations, CLsec and kg were set as zero whereas CLd, CLothers, and CLm were varied.

Fitting of Morphine Data to the TM and SFM.

The utility of the SFM versus the TM was appraised with the recent data of Doherty and Pang (2000) in which morphine (M), a substrate which is absorbed, glucuronidated, and secreted, was given both systemically and intraduodenally to the recirculating, vascularly perfused rat small intestine preparation. The models (Fig. 1) were extended to describe not only the disposition of M but also for the formation of the metabolite, morphine-3β-glucuronide (M3G), by the rat intestine preparation; in this instance, CLothers was set to zero (Fig. 2). For TM, influx/efflux of M into the intestinal tissue from the blood is characterized by the transport clearance parameter, CL1 and CL2, respectively (Fig. 2A). Once M enters the intestinal tissue, it undergoes biotransformation to M3G with the intestinal metabolic clearance, CL11, or is exsorbed across the luminal (denoted by the secretory intrinsic clearance CL3). The absorption intrinsic clearance of M from the intestinal lumen is denoted by CL4, and the luminal degradation clearance, CL12. M3G, once formed in the intestinal tissue, can either efflux out to the perfusate blood (CL10) or be excreted into the lumen (CL7), where there exists deconjugation of the glucuronide metabolite (with CL5) and glucuronidation of M (with CL6). The influx and efflux clearances for M3G across the basolateral membrane are denoted by CL9 and CL10, respectively. The data had been fitted to mass balance relationships developed previously (see Appendix of Doherty and Pang, 2000) to describe events occurring during the traverse of M and M3G across the intestine. The intrinsic clearances for drug and metabolite absorption and luminal degradation, CL4, CL8, and CL12, respectively, become the corresponding rate constants upon division by the volume of the lumen, Vlumen.

Figure 2
Figure 2

Models for the TM and SFM in describing the metabolism of M to M3G in the recirculating, perfused rat liver preparation.

The TM was described previously by Doherty and Pang (2000).

The SFM was used for the simultaneous fitting of the data (Fig. 2B). The distinction of this model from the TM lies in that only a fraction (fQ) of the intestinal flow (QI) perfuses the enterocyte layer of the mucosa where both CYP3A and Pgp reside. The remaining flow of the intestine or (1 − fQ)QI perfuses the serosa and other structures. If fQ is unity, the SFM simplifies to the TM. In the SFM, substrate in the serosal blood (s,b) and mucosal blood to the enterocyte layer (en,b) equilibrates with that in tissue; these are described by transport clearances for M (CLd1 and CLd2) and M3G (CLd1,M3Gand CLd2,M3G). Conversion and secretion of M proceed with the intrinsic clearances of CLm and CLsec, respectively. The intrinsic clearances for drug and metabolite absorption and luminal degradation, CLa, CLa,M3G, and CLgut, respectively, are related to the rate constants ka, ka,M3G, and kg by the volume of the lumen: intrinsic clearance = Vlumen × rate constant. The metabolite, M3G, is secreted with an intrinsic clearance, CLsec,M3G. In the lumen, hydrolysis of M3G is associated with the hydrolytic intrinsic clearance, CLh whereas M glucuronidation is denoted by the luminal glucuronidation intrinsic clearance CLg. Mass balance rate equations were further developed to describe events pertaining to the metabolite, M3G (see equations in ).

Data for M and the formed M3G were used for fitting (see Table 1 ofDoherty and Pang, 2000). The effects of binding of M at tracer concentration were neglected because binding was linear and constant and would not contribute to changes. Equivalent total values of volume and flows were assigned, although the flows and tissue volumes were partitioned for the SFM, with 10% of the total volume assigned to the tissue and blood volumes for the enterocyte region and the remaining 90% for the serosal tissue and blood (see volumes and flows in Table1). Due to published accounts on the lack of deglucuronidation of M3G to M (Kenyon and Calabrese, 1993) and absence of M glucuronidation to M3G in lumen in our systemic studies, CL5 and CL6 for the TM or CLh and CLg for the SFM were set to zero. Fitting was performed with differential equations for the SFM with Scientist. Initial estimates were obtained with the Simplex method, then least square optimization was performed on data after the administration of trace doses of [3H]M alone (systemic and duodenal administration). Various weighting schemes were used to arrive at optimal fits; the weighting of unity furnished the best fit.

Results

Analytical Solutions.

Mathematical solutions for the AUC values of i.v. and p.o. administrations, obtained from inversion of the square matrices, were used to calculate the total and intestinal clearances, and systemic and intestinal availabilities for both the TM and SFM, when membrane transport clearances were distinct (CLd1 ≠ CLd2, and CLd1 ≠ CLd2 ≠ CLd3≠ CLd4) (Table 2); these solutions readily provided simplified versions when the transport clearances were equal (CLd1 = CLd2, and CLd1 = CLd2 = CLd3 = CLd4). The solutions differed only in the flow rate terms: QI for the TM and Qen for SFM. The presence of other clearance (CLothers > 0) did not influence expressions for the intestinal clearance and systemic bioavailability, solved for the first time when absorption, luminal degradation, and intestinal secretion and metabolism are all present. The solutions were complex relations encompassing the terms—blood flow rate to the intestinal tissue/enterocyte layer, transport clearance, intestinal metabolic intrinsic clearance, exsorption intrinsic clearance, and the luminal degradation (kg) and absorption (ka) rate constants, and CLothers. The AUC values were simplified when CLothers was zero: AUCR,p.o. were the same for the TM and SFM although the AUCR,i.v. differed due to the flow terms: QI for the TM and Qen for SFM, as did CLI, Fsys, and FI. Interestingly, the transport clearances of drug across the serosal membrane (CLd3 and CLd4) and the serosal flow rate (Qs) were absent in the solutions of the SFM. This is due to the role of the serosa serving only as a noneliminating, drug-distribution compartment (Fig. 1B). Because of exsorption of drug and readsorption, the absorption rate constant, ka, and the luminal degradation rate constant, kg, were present in the solutions of CLt, CLI, Fsys, and FI. In the absence of secretion by Pgp, the constants kaand kg are absent in the equations for CLt, CLI, and FI, except for AUCR,p.o. and Fsys, which are influenced by Fabs (Table 2).

Simulations.

Effects of intestinal metabolism and secretion on CLI, Fsys, and FI at constant Fabs (0.667, with ka and kg equal to 1 and 0.5 min−1, respectively)

The intestinal clearance (CLI), systemic availability ( Fsys), and intestinal availability ( FI) were found not to be influenced by the presence of other eliminatory pathways (CLothers > 0). CLIwas affected directly by both the intestinal secretory and metabolic intrinsic clearances (Fig. 3). The magnitude of the intestinal clearance for any combination of CLsec (from 0 to 50 ml/min) and CLm (from 0.1 to 50 ml/min) was greater for the TM (Fig. 3, A and B, top) than for the SFM (Fig. 3, C and D, bottom). As expected, CLI increased with increasing CLsec and CLm, and the increases were more obvious for a highly permeable (flow-limited) substrate (transport intrinsic clearance = 50 ml/min, Fig. 3, B and D). These changes were more gradual for the TM (Fig. 3B), but were more abrupt for the SFM (Fig. 3D). By contrast, FI was modulated by CLsecand CLm in an inverse manner (Fig.4), and the changes were more gradual for drugs with high permeability (cf. Fig. 4, B and D to Fig. 4, A and C) and with the TM. For drugs will low permeability, values of FI decreased dramatically to almost a constant value upon increasing the CLm and CLsec from 0 to 10 ml/min; further increases in CLm and CLsec were, however, ineffective in decreasing the value of Fsys, which was already close to zero (Fig. 4, A and C). The trends for Fsys were identical to those for FI inasmuch as Fabs was constant due to the nonchanging ka and kg (data not shown; values were lower because of the fraction, Fabs).

Figure 3
Figure 3

Simulated effects of CLsec and CLm on CLI for the TM (A and B) and the SFM (C and D), based on parameters shown in Table 1 (ka and kg = 1 and 0.5 min−1, respectively).

Membrane transport clearance (CLd) was fixed at 0.5 ml/min and at 50 ml/min for illustration of drugs of the low and high permeability, respectively.

Figure 4
Figure 4

Simulated effects of CLsec and CLm on FI for the TM (A and B) and the SFM (C and D), based on parameters shown in Table 1 (ka and kg = 1 and 0.5 min−1, respectively).

CLd was fixed at 0.5 and 50 ml/min for illustration of drugs of the low and high permeability, respectively.

General trends were identified with the simulations. The values of the intestinal clearance (CLI), and systemic ( Fabs) and intestinal ( FI) availabilities simulated with varying values of CLm and CLsecfor SFM were consistently lower against corresponding values based on the TM. The ratios of the values for SFM to TM were all less than unity (Fig. 5). The smallest difference between the two models existed when intestinal metabolism and secretion were absent, i.e., CLsec = 0 and CLm = 0; a greater discrepancy was observed for the flow-limited substrate (cf. Fig. 5, B versus A). An increase of either CLm or CLsec from zero resulted in a dramatic disparity in parameter values between the two models.

Figure 5
Figure 5

Comparison of the ratios of CLI, Fabs, and FI simulated for the SFM and the traditional model when the CLsec and CLm were altered.

The absorption and luminal degradation constants, ka and kg, were kept constant at 1 and 0.5 min−1, respectively.

Effects of CLsec, ka, and kg on F sys when CLm = 0.

In absence of metabolism, secretion and absorption represented the processes effecting the cycling of drug between lumen and intestine. However, the overall bioavailability depended not only on the values of CLsec and ka, but also on kg, the “luminal degradation” constant associated with gastrointestinal transit time or loss. When kg was set to zero, CLIbecame zero regardless of the value of CLsecbecause of drug reabsorption and total lack of loss in the system (CLm and kg = 0). High secretion tended to be offset with rapid absorption (high ka) when minimal loss existed in the lumen (kg = 0.01 min−1), and the systemic availability tended to remain close to unity (data not shown). At increasing values of kg (0.5 min−1), however, Fsys became attenuated (Fig. 6), and the trend persisted with even higher kg (10 min−1) (data not shown).

Figure 6
Figure 6

Effects of ka and CLsec on Fsys according to the TM (A and B) and the SFM (C and D), based on parameters shown in Table 1.

CLd was fixed at 0.5 and 50 ml/min for illustration of drugs of the low and high permeability, respectively. CLm was fixed at 0 ml/min, and kg was set as 0.01 min−1; similar trends with lower values for Fsys were observed at kg = 10 min−1.

Effects of CLm and ka on F sys when CLsec = 0 and kg = 0.5 min−1.

In the absence of secretion (CLsec = 0), increasing the values of ka failed to alter AUCR,i.v. or CLI (see Table 2) but increased values of Fsys, the single parameter changing with ka. The greatest changes existed for drugs with low CLd; whereas changes were more gradual for the high-permeability drugs (Fig.7). Similar trends were observed at CLsec = 5 ml/min, albeit the values for Fsys were attenuated (data not shown). Fsys bore an inverse relation to CLm. It was noted that values of Fsys for the SFM were consistently smaller than those for the TM, and the ratios of the values were always less than one.

Figure 7
Figure 7

Effect of ka and CLmon Fsys according to the TM (A and B) and the SFM (C and D), based on parameters shown in Table 1.

CLd was fixed at 0.5 and 50 ml/min for illustration of drugs of the low and high permeability, respectively. CLsec was fixed at 0 ml/min, and kg was set as 0.5 min−1.

Effects of CLothers, CLm, and CLd on metabolism with constant ka (0.05 min−1).

The simulation with Scientist according to the differential equations revealed different extents in intestinal metabolism between i.v. and p.o. doses for the SFM and TM when values of CLothers, CLm, and CLd were varied in the absence of secretion and luminal loss (CLsec and kg = 0). When CLothers = 0, intestinal metabolism accounted for 100% of the administered i.v. and p.o. doses regardless of the value of CLd for drug because metabolism was the only route of removal (data not shown). With degradation or loss occurring within the lumen (kg > 0), however, the percentage of dose metabolized by intestine could become greater for the i.v. over the p.o. dose due to incomplete absorption ( Fabs < 1).

In the presence of alternate, parallel pathways (CLothers > 0), both models displayed route-dependent metabolism, with a greater extent of intestinal metabolism occurring with p.o. than with i.v. dosing. However, the difference was much greater with the SFM. The SFM predicted that because there was slower intestinal flow rate (10% flow rate) to the enterocyte layer, the absorbed drug tended to remain longer in the intestinal tissue due to the sluggish flow, thereby allowing a greater extent of intestinal metabolism. The difference in flow for the models led to a smaller intestinal clearance for the SFM, leading to much reduced intestinal metabolism after i.v. dosing. Hence discrepancy in intestinal metabolism between the p.o. and i.v. doses was greater with the SFM, and this trend was augmented at low CLd(Fig. 8, A versus B). The same reasoning may be used to explain the intestinal metabolism for the TM. The greater intestinal flow rate to the site of absorption would effect the dispersal of the orally absorbed drug rapidly into the systemic circulation, thereby reducing the extent of intestinal metabolism. Moreover, due to the greater flow rate to the absorptive and metabolic region of the intestine, CLI and intestinal metabolism would be high with i.v. dosing. For this reason, there was less discrepancy in intestinal metabolism between the p.o. and i.v. doses with the TM. There was no change in extent of intestinal metabolism with increasing values of ka, but the time course was shifted to the left.

Figure 8
Figure 8

Effect of CLd and CLothers on intestinal metabolism when intestinal secretion and luminal loss are nonexistent (CLsec and kg = 0) according to the TM (A) and the SFM (B).

Application of SFM: Fitting of Morphine Data.

The optimized parameters obtained from simultaneous fitting of the systemic and oral data of M and M3G to the TM and SFM are summarized in Table 3. Parameter estimation for M was more reliable because the S.D. values of the estimates were less than the values of the estimates. Expectedly, those for M3G were much less reliable due to the very high S.D. values of the estimates. This situation was not unique because the metabolite was not given, and there were too many fitted parameters. Nonetheless, least-square fitting was best with a weighting scheme of unity, and the resultant fits generally yielded good correlation with the data (Table 3, Fig.9). The quality of the fits was, however, better for the SFM. Although an adequate fit of the TM was observed for intraduodenal data (Fig. 9B), a systematic trend existed for the fit to the i.v. data of M; M3G formation, though not detected in the system, was over-predicted (Fig. 9A). The SFM furnished, in comparison, superior fits, as shown by the higher value for the MSC (Model Selection Criterion), the slightly improved correlation coefficient, the lower RSS or residual sum of square of residuals (Table 3), and increased randomness in the residual plots (Fig. 10). An improved fit was observed with the i.v. data since the serosal compartment effectively provided a distribution space for M (Fig. 9A). The fitted value for the fraction of the intestinal flow perfusing the enterocyte layer ( fQ) was very low, representing only 2.4% of the total intestinal flow, and was different from zero or unity. If fQ were unity, the SFM would simplify to the TM.

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Table 3

Fitted parameters from the simultaneous fitting of systemic and intraduodenal data of M and M3G from the recirculating, vascularly perfused rat small intestine with the SFM (Fig. 2B), compared to those obtained previously according to the TM (Fig. 2A)3-a

Figure 9
Figure 9

Fitting of the SFM (- - - -) to data on the metabolism of M to M3G.

M was given i.v. (A) and intraduodenally (B) to the recirculating perfused rat liver preparation (data of Doherty and Pang, 2000). The SFM was more superior in describing the data compared to TM (—) described by Doherty and Pang (2000). Note that M3G was not observed after the i.v. dosing of M although a trace amount of M3G was predicted to be formed according to the SFM, and 3-fold that was predicted with the TM (A).

Discussion

The overall systemic availability of an orally administered substrate depends on the outcome between intestinal absorption and elimination by first-pass organs such as the intestine, liver, and lungs. Indeed, the importance of the intestine as an ingress organ in regulating the net absorption of drugs into the portal circulation is well recognized (Rowland 1972; Doherty and Pang, 1997). However, unlike the attention given to the examination of physiological variables influencing liver drug clearance (for review, see Pang et al., 1998), removal processes such as metabolism and secretion (or exsorption) and the physiological variables such as intestinal flow and gastrointestinal transit time on intestinal clearance and availability have not been fully investigated.

Until now, modeling and computer fitting of drug absorption have been based on a simplistic view of the intestine, where the tissue is considered as a homogeneous compartment separated from the lumen compartment by an apical membrane and from the organ blood by a basolateral membrane. Although these compartmental models have been applied to describe the intestinal absorption of various agents, the models lack consideration of one or more of the processes that are critical in determining reliably the overall clearance of the intestine. More specifically, the model assumed by Barr and Riegelman (1970) allowed for efflux and intracellular metabolism of orally administered drugs but did not include the transfer constant from the blood compartment to the tissue. Crouthamel et al. (1975), on the other hand, included the reversible transfer of drugs between the tissue and blood compartments, but both intestinal secretion and metabolism were ignored in modeling of the pharmacokinetics of sulfaethidole. Transport processes, such as the exchange from blood to tissue or the efflux from tissue to lumen, and intestinal metabolic activities were absent in the kinetic models proposed by Choi et al. (1995) and Nakashima et al. (1984). Recently, Ito et al. (1999) introduced a theoretical pharmacokinetic model to relate the influence of intestinal CYP3A4 metabolism, Pgp efflux, and intracellular diffusion on drug absorption. Not unlike both of our TM and SFM, Ito's model was able to predict the inverse relationship between bioavailability and metabolism and/or efflux. However, the transport clearance term that describes the partitioning of drug from the circulation to the epithelial cells was absent, precluding the intestinal accumulation or exsorption of i.v. administered drugs, and transfer processes between the gut lumen and epithelial cells were omitted in their definition of absorption clearance. The extended compartmental absorption and transit model developed by Yu and Amidon (1998) had simultaneously considered passive absorption, saturable absorption, degradation, and transit kinetics in the small intestine. But processes such as luminal and intracellular metabolism and exsorption were excluded. The present model is developed to comprehensively illustrate the interaction between the effective flow to the intestine, the absorption rate constant, intestinal enzymatic and secretory activities, and the influence of other clearances on systemic bioavailability. The SFM, based on the view that the absorptive site of the intestine receives only a portion of the overall organ blood flow, is in theory not dissimilar to the bypass phenomenon proposed by Klippert and Noordhoek (1985), with the exception that the flow rate to the intestinal tissue is conserved and drug distributes into the nonabsorptive and noneliminatory layer of the serosa and submucosa.

A close scrutiny of the SFM and TM reveals notable differences because of the different effective perfusion of the absorptive/metabolic/secretory layer. Theoretical solutions for both the TM and SFM differ only in the flow terms (QIversus Qen) (see Table 2). Elimination within other parallel (non first pass) organs fails to affect the intestinal clearance, as expected of the additivity of organ clearances among parallel elimination pathways, and does not impact on bioavailability. The present communication also uncovers that, for both the SFM and TM, CLI and FI are directly/inversely related to the intestinal metabolic and exsorption intrinsic clearances (CLm and CLsec) and blood flow to the absorptive layer (Figs. 3 and 4); the parameters are additionally affected by ka and kg when there is drug exsorption (Table 2). Values for the SFM are, however, consistently lower than those for the TM (Fig. 5).

The frequent question addressed on whether the role of Pgp on secretion is overemphasized (Lin et al., 1999) can now be answered. The exsorption of substrate from the intestinal tissue to the lumen (CLsec > 0) exerts a direct influence on Fsys; the larger the exsorption clearance, the less the systemic availability. Drug secretion by Pgp, viewed best in absence of metabolism and loss from lumen, reveals that secretion may be obliterated when drug absorption is rapid (Fig. 6). However, the concurrent absence of secretion and metabolism (CLsec = 0; CLm= 0) will result in a dramatic increase in the systemic (or intestinal) availability.

The difference in flow between the models also affects the extents of intestinal metabolism. The condition was best shown when CLsec and kg = 0; a greater difference in the extent of intestinal metabolism is found between the p.o. and i.v. doses with the SFM (see Fig. 8). According to the SFM, the lowered flow rate perfusing the enterocyte layer renders lower values of intestinal clearance, because there is reduced drug delivery to intestinal enzymes or secretory sites. However, during oral absorption, the entire orally administered dose must traverse the enterocyte layer before the substrate enters the circulation. The consequence of the partial flow to the enterocyte compartment leads to sluggish dispersal of drug into the circulation and a longer transit time within the intestinal tissue. The differential exposure with the site of administration results in different extents of metabolism by intestinal enzymes and exsorption, and contributes to the observation of route-dependent metabolism (Klippert and Noordhoek, 1985; Pang et al., 1985, 1986; Wen et al., 1999). Intestinal metabolism may then be viewed effectively as a single preabsorptive event, occurring predominantly during the absorption of the substrate across the luminal membrane and is substantially lower upon recirculation of the drug. It has been noted that flow can also be a limiting factor of intestinal absorption because it affects the net substrate flux from the lumen into the circulation and vice versa (Crouthamel et al., 1975;Winne, 1978; Schurgers and de Blaey, 1984). However, the flow rate to the enterocyte layer is now recognized as critical to intestinal clearance and bioavailability. Although the nature of the change remains largely untested, the magnitude of this flow is expected to be of paramount importance to the initial absorptive flux and drug extraction as well as on subsequent recirculation of the substrate.

Finally, the confirmatory evidence that the SFM is the better explanation of intestinal metabolism is substantiated by the fit to the experimental data of M. Statistically, the fits of the SFM to data on route-dependent glucuronidation of M in the vascularly perfused intestine preparation (data of Doherty and Pang, 2000) are improved over those afforded by the TM (Table 3, Fig. 9). In particular, the fit of the SFM to the i.v. data of M was superior because the distribution phase was better described by the SFM due to the presence of the serosal compartment acting as the storage/distribution compartment (Fig. 9A). The tissue partitioning ratio (value of 8) for M for the SFM was more reasonable than the much higher value of 22 predicted for the TM (CL2/CL1 or CLd2/CLd1), when levels of total radioactivity in the tissue were low (5 to 6% dose). Although there were notable levels of M3G accumulated in the reservoir after the intraduodenal dose, M3G was not detected after i.v. administration. The total level of M3G predicted by the SFM was lower for the SFM (6.6% for TM and 2% for the SFM).

Currently, the intestine is regarded as a single compartment. The SFM is physiologically sound and affords a plausible explanation of route-dependent metabolism. Due to the many examples of route-dependent metabolism of the intestine, it is anticipated that the proposed intestinal SFM may be important in future endeavors to accurately relate in vitro parameters with in vivo physiological events on absorption and bioavailability. Moreover, this model may be readily expanded to describe the physiological segmental divisions of the intestine—duodenum, jejunum, and ileum—and transport and metabolic or secretory heterogeneity within these segments (Dubey and Singh, 1988;Fei et al., 1994; Saitoh and Aungst, 1995; Aldini et al., 1996; Paine et al., 1997). With the development of these kinds of models, predictions on the first pass removal/metabolism and drug-drug interactions within the intestinal tissue would then be made accurately.

Appendix

The equations for the TM were presented earlier (see ,Doherty and Pang, 2000), and the equations for the SFM are presented below. There were segregated flows to the enterocyte layer of the mucosa [which comprised of a fraction ( fQ) of the total intestinal flow, QI] and to the serosa and other remaining intestinal tissues [or (1 − fQ) QI]. The enzymatic and Pgp activities are present in the enterocytes of the mucosa (Fig.2B). The mass transfer equations that describe the rates of changes of M and M3G in the reservoir (R), the serosa (s), the enterocytes of the mucosal layer (en), and blood in serosal compartment (s,b) and enterocyte layer of the mucosal compartment (en,b), and lumen are:

For M and M3G in reservoir (R) compartment,dMRdt=fQQIMen,bVen,b+(1−fQ)QIMs,bVs,b−QIMRVR Equation EB1dM3GRdt=fQQIM3Gen,bVen,b+(1−fQ)QIM3Gs,bVs,b−QIM3GRVR Equation EB2For M and M3G in serosa and other nonmucosal tissue(s) compartmentdMsdt=CLd1Ms,bVs,b−CLd2MsVs Equation EB3dM3Gsdt=CLd1,M3GM3Gs,bVs,b−CLd2,M3GM3GsVs Equation EB4For M and M3G in enterocyte layer (en) in mucosal compartment,dMendt=CLaMlumenVlumen−(CLsec+CLd2+CLm)MenVen+CLd1Men,bVen,b Equation EB5dM3Gendt=CLmMenVen+CLa,M3GM3GlumenVlumen Equation EB6−(CLsec,M3G+CLd2,M3G)M3GenVen+CLd1,M3GM3Gen,bVen,b For M and M3G in serosal blood (s,b) compartmentdMs,bdt=(1−fQ)QIMRVR+CLd2MsVs−[CLd1+(1−fQ)QI]Ms,bVs,b Equation EB7dM3Gs,bdt=(1−fQ)QIM3GRVR+CLd2,M3GM3GsVs Equation EB8−[CLd1,M3G+(1−fQ)QI]M3Gs,bVs,b For M and M3G in blood to enterocyte layer (en,b) in mucosal compartmentdMen,bdt=fQQIMRVR+CLd2MenVen−[CLd1+fQQI]Men,bVen,b Equation EB9dM3Gen,bdt=fQQIM3GRVR+CLd2,M3GM3GenVen Equation EB10−(CLd1,M3G+fQQI)M3Gen,bVen,b For M and M3G in lumen (lumen) compartmentdMlumendt=CLsecMenVen−(CLg+CLa+CLGIT)MlumenVlumen+CLhM3GlumenVlumen Equation EB11dM3Glumendt=CLsec,M3GM3GenVen−(CLh+CLa,M3G+CLGIT)M3GlumenVlumen+CLgMlumenVlumen Equation EB12The amounts of M in exudate and lumen were summed to provide the total amount collected in the sampling tube at 120 min. The same was done for M3G.

Footnotes

  • Send reprint requests to: Dr. K. S. Pang, Faculty of Pharmacy, University of Toronto, 19 Russell Toronto, Ontario, Canada M5S 2S2. E-mail: pang{at}phm.utoronto.ca

  • ↵1 Present address: Victoria College of Pharmacy, Monash University, Melbourne, Australia.

  • This work was supported by the Medical Research Council of Canada (MA9104 and MOP36,457); D.C. was a recipient of the Ontario Graduate Scholarship, Canada.

  • Abbreviations:
    Pgp
    P-glycoprotein
    AUC
    area under the concentration-time curve
    CLd1
    influx intrinsic clearance from blood compartment to enterocyte compartment
    CLd2
    efflux intrinsic clearance from enterocyte compartment to blood compartment
    CLd3
    influx intrinsic clearance from blood compartment to serosal compartment
    CLd4
    efflux intrinsic clearance from serosal compartment to blood compartment
    CLI
    intestinal clearance
    CLothers
    clearance by other parallel organs
    CLm
    metabolic intrinsic clearance of intestine
    CLsec
    secretory intrinsic clearance of intestine
    CLt
    total body or systemic clearance
    Fabs
    fraction absorbed
    FI
    intestinal availability
    Fsys
    systemic bioavailability
    ka
    absorption rate constant
    kg
    luminal degradation constant
    Qen
    flow to the enterocyte layer of the mucosa
    QI
    total flow to the intestine
    SFM
    segregated-flow model
    TM
    traditional model
    M
    morphine
    M3G
    morphine-3β-glucuronide
    • Received May 24, 1999.
    • Accepted October 1, 1999.

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A New Physiologically Based, Segregated-Flow Model to Explain Route-Dependent Intestinal Metabolism

Diem Cong, Margaret Doherty and K. Sandy Pang
Drug Metabolism and Disposition February 1, 2000, 28 (2) 224-235;
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