伊藤 清美

Purpose. The aim of this study is to compare the accuracy of five methods for predicting in vivo intrinsic clearance (CLint) and seven for predicting hepatic clearance (CLh) in humans using in vitro microsomal data and/or preclinical animal data. Methods. The human CLint was predicted for 33 drugs by five methods that used either in vitro data with a physiologic scaling factor (SF), with an empirical SF, with the physiologic and drug-specific (the ratio of in vivo and in vitro CLint in rats) SFs, or rat CLint directly and with allometric scaling. Using the estimated CLint, the CLh in humans was calculated according to the well-stirred liver model. The CLh was also predicted using additional two methods: using direct allometric scaling or drug-specific SF and allometry. Results. Using in vitro human microsomal data with a physiologic SF resulted in consistent underestimation of both CLint and CLh. This bias was reduced by using either an empirical SF, a drug-specific SF, or allometry. However, for allometry, there was a substantial decrease in precision. For drug-specific SF, bias was less reduced, precision was similar to an empirical SF. Both CLint and CLh were best predicted using in vitro human microsomal data with empirical SF. Use of larger data set of 52 drugs with the well-stirred liver model resulted in a best-fit empirical SF that is 9-fold increase on the physiologic SF. Conclusions. Overall, the empirical SF method and the drug-specific SF method appear to be the best methods; they show lower bias than the physiologic SF and better precision than allometric approaches. The use of in vitro human microsomal data with an empirical SF may be preferable, as it does not require extra information from a preclinical study.

Purpose. To compare three liver models (well-stirred, parallel tube, and dispersion) for the prediction of in vivo intrinsic clearance (CLint), hepatic clearance (CLh), and hepatic availability (F-h) of a wide range of drugs in the rat using in vitro data from two in vitro sources. Methods. In vitro CLint was obtained from studies using isolated rat hepatocytes (35 drugs) or rat liver microsomes (52 drugs) and used to predict in vivo CLint using reported scaling factors, and subsequently CLh and F-h were predicted based on the three liver models. In addition, in vivo CLint values were calculated from the reported values of CLh based on each of the three models. Results. For all of the parameters, predictions from hepatocyte data were consistently more accurate than those from microsomal data. Comparison of in vitro and in vivo CLint values demonstrated that the dispersion model and the parallel tube model were comparable and more accurate (less bias, more precise) than the well-stirred model. For CLh and F-h prediction, the three models performed similarly. Conclusions. Considering the statistics of the predictions for three liver models, the use of parallel tube model is recommended for the evaluation of in vitro CLint values both from microsomes and hepatocytes. However, for the prediction of the in vivo drug (hepatic) clearance from in vitro data, as there are minimal differences between the models, the use of the well-stirred liver model is recommended.

Aims In theory, the magnitude of an in vivo drug-drug interaction arising from the inhibition of metabolic clearance can be predicted using the ratio of inhibitor concentration ([I]) to inhibition constant (K-i). The aim of this study was to construct a database for the prediction of drug-drug interactions from in vitro data and to evaluate the use of the various estimates for the inhibitor concentrations in the term [I]/K-i. Methods One hundred and ninety-three in vivo drug-drug interaction studies involving inhibition of CYP3A4, CYP2D6 or CYP2C9 were collated from the literature together with in vitro K-i values and pharmacokinetic parameters for inhibitors, to allow calculation of average/maximum systemic plasma concentration during the dosing interval and maximum hepatic input plasma concentration (both total and unbound concentration). The observed increase in AUC (decreased clearance) was plotted against the estimated [I]/K-i ratio for qualitative zoning of the predictions. Results The incidence of false negative predictions (AUC ratio > 2, [I]/K-i < 1) was largest using the average unbound plasma concentration and smallest using the hepatic input total plasma concentration of inhibitor for each of the CYP enzymes. Excluding mechanism-based inhibition, the use of total hepatic input concentration resulted in essentially no false negative predictions, though several false positive predictions (AUC ratio < 2, [I]/K-i > 1) were found. The incidence of true positive predictions (AUC ratio > 2, [I]/K-i > 1) was also highest using the total hepatic input concentration. Conclusions The use of the total hepatic input concentration of inhibitor together with in vitro K-i values was the most successful method for the categorization of putative CYP inhibitors and for identifying negative drug-drug interactions. However this approach should be considered as an initial discriminating screen, as it is empirical and requires subsequent mechanistic studies to provide a comprehensive evaluation of a positive result.

Clinical studies have revealed that plasma concentrations of midazolam after oral administration are greatly increased by coadministration of erythromycin and clarithromycin, whereas azithromycin has little effect on midazolam concentrations. Several macrolide antibiotics are known to be mechanism-based inhibitors of CYP3A, a cytochrome P450 isoform responsible for midazolam hydroxylation. The aim of the present study was to quantitatively predict in vivo drug interactions in humans involving macrolide antibiotics with different inhibitory potencies based on in vitro studies. alpha- and 4-Hydroxylation of midazolam by human liver microsomes were evaluated as CYP3A-mediated metabolic reactions, and the effect of preincubation with macrolides was examined. The hydroxylation of midazolam was inhibited in a time- and concentration-dependent manner following preincubation with macrolides in the presence of NADPH, whereas almost no inhibition was observed without preincubation. The kinetic parameters for enzyme inactivation (K'(app) and k(inact)) involved in midazolam alpha-hydroxylation were 12.6 muM and 0.0240 min(-1), respectively, for erythromycin, 41.4 muM and 0.0423 min(-1), respectively, for clarithromycin, and 623 muM and 0.0158 min(-1), respectively, for azithromycin. Similar results were obtained for the 4-hydroxylation pathway. These parameters and the reported pharmacokinetic parameters of midazolam and macrolides were then used to simulate in vivo interactions based on a physiological flow model. The area under the concentration-time curve (AUC) of midazolam after oral administration was predicted to increase 2.9- or 3.0-fold following pretreatment with erythromycin (500 mg t.i.d. for 5 or 6 days, respectively) and 2.1- or 2.5-fold by clarithromycin (250 mg b.i.d. for 5 days or 500 mg b.i.d. for 7 days, respectively), whereas azithromycin (500 mg o.d. for 3 days) was predicted to have little effect on midazolam AUC. These results agreed well with the reported in vivo observations.

When the metabolism of a drug is competitively or noncompetitively inhibited by another drug, the degree of in vivo interaction can be evaluated from the [I] (u)/K (i) ratio, where [I] (u) is the unbound concentration around the enzyme and K (i) is the inhibition constant of the inhibitor. In the present study, we evaluated the metabolic inhibition potential of drugs known to be inhibitors or substrates of cytochrome P450 by estimating their [I] (u)/K (i) ratio using literature data. The maximum concentration of the inhibitor in the circulating blood ([I] (max)), its maximum unbound concentration in the circulating blood ([I] (max,u)), and its maximum unbound concentration at the inlet to the liver ([I] (in,max,u)) were used as [I] (u), and the results were compared with each other. In order to calculate the [1], /K (i) ratios, the pharmacokinetic parameters of each drug were obtained from the literature, together with their reported K (i) values determined in in vitro studies using human liver microsomes. For most of the drugs with a calculated [I] (in,max,u) /K (i) ratio less than 0.25, which applied to about half of the drugs investigated, no in vivo interactions had been reported or "no interaction" was reported in clinical studies. In contrast, the [I] (max,u)/K (j) and [1] (max)/K (i) ratio was calculated to be less than 0.25 for about 90% and 65% of the drugs, respectively, and more than a 1.25-fold increase was reported in the area under the concentration-time curve of the co-administered drug for about 30% of such drugs. These findings indicate that the possibility of underestimation of in vivo interactions (possibility of false-negative prediction) is greater when [I] (max,u) or [I] (max) values are used compared with using [I] (in,max,u) values.

Purpose. To evaluate the effects of gut metabolism and efflux on drug absorption by simulation studies using a pharmacokinetic model involving diffusion in epithelial cells. Methods. A pharmacokinetic model for drug absorption was constructed including metabolism by CYP3A4 inside the epithelial cells, P-gp-mediated efflux into the lumen, intracellular diffusion from the luminal side to the basal side, and subsequent permeation through the basal membrane. Partial differential equations were solved to yield an equation for the fraction absorbed from gut to the blood. Effects of inhibition of CYP3A4 and/or P-gp on the fraction absorbed were simulated for a hypothetical substrate for both CYP3A4 and P-gp. Results. The fraction absorbed after oral administration was shown to increase following inhibition of P-gp. This increase was more marked when the efflux clearance of the drug was greater than the sum of the metabolic and absorption clearances and when the intracellular diffusion constant was small. Furthermore, it was demonstrated that the fraction absorbed was synergistically elevated by simultaneous inhibition of both CYP3A4 and P-gp. Conclusions. The analysis using our present diffusion model is expected to allow the prediction of in vivo intestinal drug absorption and related drug interactions from in vitro studies using human intestinal microsomes, gut epithelial cells, CYP3A4-expressed Caco-2 cells, etc.

Purpose. The purpose of this study is to evaluate the central benzodiazepine (BZP) receptor binding of iomazenil (IMZ) by pharmacokinetic analysis and to establish a methodology for the diagnosis of CNS disorders with abnormalities in BZP receptor binding. Methods. BZP receptor binding of IMZ was analyzed kinetically using plasma concentration-time profiles and dynamic single photon emission computed tomography (SPECT) data obtained after the intravenous administration of IMZ to patients with neuropsychiatric diseases. The analysis was based on a 3-compartmental model including the processes of both blood-brain barrier (BBB) transport and BZP receptor binding. Results. Hydrolized metabolite of IMZ was detected in plasma, indicating the need for separation by HPLC. The BBB influx clearance and the receptor binding potential of IMZ in the medial temporal region was reduced in the epileptic patient. Conclusions. Our findings suggest the possibility of detecting the epileptic focus by using our method.

Many benzodiazepines (BZPs) are now used as anxiolytics with nearly 200-fold variety of therapeutic doses. The variation of the doses of BZPs is due to differences both in their pharmacokinetics and in their receptor binding characteristics. The purpose of this study is to clarify the mechanism of the differences in therapeutic dose by retrospective analyses and to develop a system for the quantitative estimation of optimal doses of BZPs. The values of receptor dissociation constant (K-d), which indicates the binding affinity of each BZP at the receptor site, were obtained from a number of works based on in vitro binding experiments. The plasma unbound concentrations of the BZPs and their active metabolites were calculated using the reported values of their total plasma concentrations after average oral doses of the BZPs and the values of their plasma unbound fractions, which were also taken from the literature. There were log-linear relationships between the K-d values of BZPs and their average therapeutic doses or maximum plasma concentrations, but the correlation coefficients were relatively small (r < 0.77). In contrast, a good log-linearity (r = 0.96) was observed in the correlation between their K-d values and the effective plasma unbound concentrations considering the active metabolites. This finding indicates that the receptor occupancy after administration of therapeutic dose of BZPs is consistent (52.3 +/- 3.2%) among the BZPs. In this study, we also develop a possible system for estimating the appropriate doses of BZPs based on receptor occupancy theory. (C) 1997 by John Wiley & Sons, Ltd.

The effect of muscimol, a GABA(A), receptor agonist, on the basic metabolic activity was investigated in the mouse brain and was correlated with its receptor occupancy. For the quantitative evaluation of the functional activity of the mouse brain, the cerebral glucose utilization was measured by the double tracer technique, using [C-14] 2-deoxyglucose and [H-3]3-O-methylglucose. The dose dependent reduction in the cerebral glucose utilization was observed after intravenous administration of various doses of muscimol (0.3-1.5 mg/kg). On the other hand, the GABA(A) receptor occupancy of muscimol was determined by using the values of the unbound drug concentration in the brain tissue and the receptor dissociation constant based on the in vitro binding experiments using the dissociated brain cells. The tissue unbound concentration of muscimol was calculated by multiplying the total concentration in the brain after administration of muscimol and the tissue unbound fraction, which was measured by the equilibrium dialysis method using brain tissue homogenate. A linear relationship was observed between the GABA(A) receptor occupancy of muscimol and the decrease in the cerebral glucose utilization. This finding indicates that the simple receptor occupancy theory holds for this receptor-ligand system, and there is a large difference in the effect on glucose metabolic response between GABA(A) receptor-agonist interaction and benzodiazepine receptor agonist interaction.

種々のβ刺激薬の血中濃度と効果との関係についてレセプター結合占有理論に基づいた解析を行い、前臨床試験結果から適切な臨床用量を推定する方法論を提唱した。

Benzodiazepine (BZP) hypnotics are now classified into four groups according to their plasma elimination rates: ultrashort-, short-, intermediate-, and long-acting drugs. Since the specific binding affinities for the BZP receptor vary widely among the BZPs and their active metabolites, it may be more reasonable to correlate their pharmacological activities with the BZP receptor occupancy rather than with their plasma concentrations. The time courses of total plasma concentrations of BZPs and their active metabolites after a single oral administration were obtained from the literature, and their unbound concentrations (Cu) were calculated from the reported values of their plasma unbound fractions. The data of the receptor binding affinities of the BZPs, reported as dissociation constants (Kd) determined by in vitro binding experiments, were also obtained from the literature. Using these values, the time courses of receptor occupancies [Cu/(Kd + Cu) x 100%] were calculated for the various BZPs. A mutual competitive inhibition was considered in the case of the drugs that had active metabolites. Although plasma total and unbound concentration time profiles of the BZPs showed a wide variation, similar patterns were obtained for the time courses of the receptor occupancy among the BZPs in each group, indicating that the BZP hypnotics can be classified more conveniently based on receptor occupancy theory.

In vivo receptor occupancy of psychotropic drugs in brain can be estimated by measuring the tissue radioactivity of the tracer, which binds specifically to the receptor unoccupied by the drugs (back titration method). In this study, the validity of this method was evaluated by computer simulation, using various values for the plasma elimination rate, rate of transport across the blood-brain barrier, rate of receptor association and dissociation for both drug and tracer, and the sampling time. The differential equations based on a nonlinear three-compartment model including a plasma pool, precursor pool, and specific binding pool were solved numerically by the Runge-Kutta-Gill method. The receptor occupancy calculated by this method was close to the true value when the plasma concentration and specific binding fraction of the drug did not change greatly during circulation of the tracer. Although the error in calculated occupancy at 5 min after the tracer administration was smaller than that at 20 min, tracer may not greatly accumulate in brain tissue during the initial 5 min in some situations. Our analysis shows that it is necessary to adequately control the elimination rate of drug from plasma and to allow sufficient time for radioactivity to accumulate in the tissue. Therefore, this method requires previous knowledge of the pharmacokinetic behavior of both the drug and the tracer in plasma and tissue. The operation scheme that we suggest for the accurate measurement of the receptor occupancy in vivo can be used in human studies with positron emission tomography and may be useful for therapeutic drug monitoring.