樋坂 章博

BACKGROUND AND OBJECTIVE: Pharmacokinetic drug-drug interactions (DDIs) are one of the major causes of adverse events in pharmacotherapy, and systematic prediction of the clinical relevance of DDIs is an issue of significant clinical importance. In a previous study, total exposure changes of many substrate drugs of cytochrome P450 (CYP) 3A4 caused by coadministration of inhibitor drugs were successfully predicted by using in vivo information. In order to exploit these predictions in daily pharmacotherapy, the clinical significance of the pharmacokinetic changes needs to be carefully evaluated. The aim of the present study was to construct a pharmacokinetic interaction significance classification system (PISCS) in which the clinical significance of DDIs was considered with pharmacokinetic changes in a systematic manner. Furthermore, the classifications proposed by PISCS were compared in a detailed manner with current alert classifications in the product labelling or the summary of product characteristics used in Japan, the US and the UK. METHODS: A matrix table was composed by stratifying two basic parameters of the prediction: the contribution ratio of CYP3A4 to the oral clearance of substrates (CR), and the inhibition ratio of inhibitors (IR). The total exposure increase was estimated for each cell in the table by associating CR and IR values, and the cells were categorized into nine zones according to the magnitude of the exposure increase. Then, correspondences between the DDI significance and the zones were determined for each drug group considering the observed exposure changes and the current classification in the product labelling. Substrate drugs of CYP3A4 selected from three therapeutic groups, i.e. HMG-CoA reductase inhibitors (statins), calcium-channel antagonists/blockers (CCBs) and benzodiazepines (BZPs), were analysed as representative examples. The product labelling descriptions of drugs in Japan, US and UK were obtained from the websites of each regulatory body. RESULTS: Among 220 combinations of drugs investigated, estimated exposure changes were more than 5-fold for 41 combinations in which ten combinations were not alerted in the product labelling at least in one country; these involved buspirone, nisoldipine and felodipine as substrates, and ketoconazole, voriconazole, telithromycin, clarithromycin and nefazodone as inhibitors. For those drug combinations, the alert classifications were anticipated as potentially inappropriate. In the current product labelling, many inter-country differences were also noted. Considering the relationships between previously observed exposure changes and the current alert classifications, the boundaries between 'contraindication' and 'warning/caution' were determined as a 7-fold exposure increase for statins and CCBs, and as a 4-fold increase for BZPs. PISCS clearly discriminated these drug combinations in accordance with the determined boundaries. Classifications by PISCS were expected to be valid even for future drugs because the classifications were made by zones, not by designating individual drugs. CONCLUSION: The present analysis suggested that many current alert classifications were potentially inappropriate especially for drug combinations where pharmacokinetics had not been evaluated. It is expected that PISCS would contribute to constructing a leak-less alerting system for a broad range of pharmacokinetic DDIs. Further validation of PISCS is required in clinical studies with key drug combinations, and its extension to other CYP and metabolizing enzymes remains to be achieved.

BACKGROUND: Induction of cytochrome P450 (CYP) 3A4 potentially reduces the blood concentrations of substrate drugs to less than one-tenth, which results in ineffective pharmacotherapy. Although the prediction of drug-drug interactions (DDIs) that are mediated by induction of CYP3A4 has been performed mainly on the basis of in vitro information, such methods have met with limited success in terms of their accuracy and applicability. Therefore, a realistic method for the prediction of CYP3A4-mediated inductive DDIs is of major clinical importance. OBJECTIVE: The objective of the present study was to construct a robust and accurate method for the prediction of CYP3A4-mediated inductive DDIs. Such a method was developed on the basis of the principle applied for prediction of inhibitory DDIs in a previous report. A unique character of this principle is that the extent of alterations in the area under the plasma concentration-time curve (AUC) is predicted on the basis of in vivo information from minimal clinical studies without using in vitro data. METHODS: The analysis is based on 42 DDI studies in humans reported in 37 published articles over the period 1983-2007. Kinetic analysis revealed that the reduction in the AUC of a substrate of CYP3A4 produced by consecutive administration of an inducer of CYP3A4 could be approximated by the equation 1/(1 + CRCYP3A4 * ICCYP3A4), where CRCYP3A4 is the ratio of the apparent contribution of CYP3A4 to the oral clearance of a substrate and ICCYP3A4 is the apparent increase in clearance of a substrate produced by induction of CYP3A4. Using this equation, the ICCYP3A4 was calculated for seven inducers (bosentan, carbamazepine, efavirenz, phenytoin, pioglitazone, rifampicin [rifampin], and St John's wort [hypericum]) on the basis of the reduction in the AUC of a coadministered standard substrate of CYP3A4, such as simvastatin, in ten DDI studies. The CRCYP3A4 was calculated for 22 substrates on the basis of the previously reported method from inhibitory DDI studies using a potent CYP3A4 inhibitor such as itraconazole or ketoconazole. RESULTS: The proposed method enabled the prediction of AUC reduction by CYP3A4 induction with any combination of these substrates and inducers (total 154 matches). To assess the accuracy of the prediction, the AUC reductions in 32 studies were analysed. We found that the magnitude of the deviation between the mean values of the observed and predicted AUCs of all substrate drugs was <20% of the AUCs of the respective substrate drugs before administration of the inducers. In addition, rifampicin was found to be the most potent inducer among the compounds analysed in the present study, with an ICCYP3A4 value of 7.7, followed by phenytoin and carbamazepine, with values of 4.7 and 3.0, respectively. The ICCYP3A4 values of the other CYP3A4 inducers analysed in the present study were approximately 1 or less, which suggests that the AUCs of coadministered drugs may not be reduced to less than approximately half, even if the drug is metabolized solely by CYP3A4. CONCLUSION: By using the method reported in the present study, the susceptibilities of a substrate drug of CYP3A4 to inductive DDIs can be predicted quantitatively. It was indicated that coadministration of rifampicin, phenytoin and carbamazepine may reduce plasma AUCs to less than half for a broad range of CYP3A4 substrate drugs, with CRCYP3A4 values greater than 0.13, 0.21 and 0.33, respectively.

BACKGROUND: Cytochrome P450 (CYP) 3A4 is the most prevalent metabolising enzyme in the human liver and is also a target for various drug interactions of significant clinical concern. Even though there are numerous reports regarding drug interactions involving CYP3A4, it is far from easy to estimate all potential interactions, since too many drugs are metabolised by CYP3A4. For this reason, a comprehensive framework for the prediction of CYP3A4-mediated drug interactions would be of considerable clinical importance. OBJECTIVE: The objective of this study was to provide a robust and practical method for the prediction of drug interactions mediated by CYP3A4 using minimal in vivo information from drug-interaction studies, which are often carried out early in the course of drug development. DATA SOURCES: The analysis was based on 113 drug-interaction studies reported in 78 published articles over the period 1983-2006. The articles were used if they contained sufficient information about drug interactions. Information on drug names, doses and the magnitude of the increase in the area under the concentration-time curve (AUC) were collected. METHODS: The ratio of the contribution of CYP3A4 to oral clearance (CR(CYP)(3A4)) was calculated for 14 substrates (midazolam, alprazolam, buspirone, cerivastatin, atorvastatin, ciclosporin, felodipine, lovastatin, nifedipine, nisoldipine, simvastatin, triazolam, zolpidem and telithromycin) based on AUC increases observed in interaction studies with itraconazole or ketoconazole. Similarly, the time-averaged apparent inhibition ratio of CYP3A4 (IR(CYP)(3A4)) was calculated for 18 inhibitors (ketoconazole, voriconazole, itraconazole, telithromycin, clarithromycin, saquinavir, nefazodone, erythromycin, diltiazem, fluconazole, verapamil, cimetidine, ranitidine, roxithromycin, fluvoxamine, azithromycin, gatifloxacin and fluoxetine) primarily based on AUC increases observed in drug-interaction studies with midazolam. The increases in the AUC of a substrate associated with coadministration of an inhibitor were estimated using the equation 1/(1 - CR(CYP)(3A4) x IR(CYP)(3A4)), based on pharmacokinetic considerations. RESULTS: The proposed method enabled predictions of the AUC increase by interactions with any combination of these substrates and inhibitors (total 251 matches). In order to validate the reliability of the method, the AUC increases in 60 additional studies were analysed. The method successfully predicted AUC increases within 67-150% of the observed increase for 50 studies (83%) and within 50-200% for 57 studies (95%). Midazolam is the most reliable standard substrate for evaluation of the in vivo inhibition of CYP3A4. The present analysis suggests that simvastatin, lovastatin and buspirone can be used as alternatives. To evaluate the in vivo contribution of CYP3A4, ketoconazole or itraconazole is the selective inhibitor of choice. CONCLUSION: This method is applicable to (i) prioritize clinical trials for investigating drug interactions during the course of drug development and (ii) predict the clinical significance of unknown drug interactions. If a drug-interaction study is carefully designed using appropriate standard drugs, significant interactions involving CYP3A4 will not be missed. In addition, the extent of CYP3A4-mediated interactions between many other drugs can be predicted using the current method.

The dispersion model has been widely used to analyze local pharmacokinetics in the organs and the tissues since the 1980's. However, an ambiguity still remains in selecting the boundary conditions which are necessary to solve the basic equation of the model. In this note, theoretical considerations are given to this problem and we present here some deficiencies of the mixed boundary conditions. It seems that theoretical confusion exists in the literature for the mixed boundary conditions. It is well-known that the solution of the dispersion model with a bolus input is the inverse Gaussian distribution for the mixed boundary conditions. However, it is rarely recognized that the inverse Gaussian distribution requires an open boundary at either the inlet or the outlet. For the analysis of local pharmacokinetics, the use of the classical Danckwerts for closed). boundary conditions is recommended.

Purpose. To bridge in vitro, in situ and in vivo kinetic analyses of the hepatic clearance of a cyclopentapeptide, BQ-123, by using dispersion models that assume nonlinear pharmacokinetics. Methods. Rat livers were perfused by the multiple indicator dilution method with doses of BQ-123 ranging from 1-1000 mu g. The outflow dilution curves were fitted to a two-compartment dispersion model that was solved numerically by the finite difference method. Further, in vivo plasma concentrations of BQ-123 after bolus injection were analyzed with a hybrid physiological model that incorporates the hepatic dispersion model. Results. The calculated Michaelis-Menten constants (K-m = 12.0 mu M, V-max = 321 pmol/min/10(6) cells, P-dif = 1.2 mu l/min/10(6) cells) were comparable to those obtained previously from the in vitro isolated hepatocyte experiment (K-m = 9.5 mu M, V-max = 517 pmol/min/10(6) cells, P-dif = 1.1 mu l/min/10(6) cells). The plasma concentrations of BQ-123 at doses of 1-25 mg/kg were explained well by the hybrid physiological model. Conclusions, These results suggest that carrier-mediated transport on the sinusoidal membrane was responsible for the in vivo hepatic elimination of BQ-123.

A numerical calculation method for dispersion models was developed to analyze nonlinear and nonsteady hepatic elimination of substances. The finite difference method (FDM), a standard numerical calculation technique, was utilized to solve nonlinear partial differential equations of the dispersion model. Using this method, flexible application of the dispersion model becomes possible, because (i) nonlinear kinetics can be incorporated anywhere, (ii) the input function can be altered arbitrarily, and (iii) the number of compartments can be increased as needed. This method was implemented in a multipurpose nonlinear least-squares fitting computer program, Napp (Numeric Analysis Program for Pharmacokinetics). We simulated dilution curves for several nonlinear two-compartment hepatic models in which the saturable process is assumed in transport or metabolism, and investigated whether they could definitely be discriminated from each other. Preliminary analysis of the rat liver perfusion data of a cyclic pentapeptide. BQ-123, was performed by this method to demonstrate its applicability.

Recent cumulative evidence suggests the possibility of predicting the in vivo metabolic clearance and/or hepatic availability (F-h) from in vitro metabolism data under linear conditions. Under nonlinear conditions, however, it is essential to consider the rate constant for the absorption (k(a)) for predicting F-h after oral administration, because the time profiles for the portal vein concentration depends on k(a). In our study, we numerically solved the dispersion model under nonlinear conditions to propose a method to predict F-h after oral administration by taking k(a) into consideration. As a model compound, (S)-(-)-2,8-dimethyl-3-methylene-1-oxa-8-azaspiro [4,5] decane-L-tartrate monohydrate (YM796) was used. After oral administration, we found that the dose-normalized AUC (AUC(oral)/dose) was markedly increased in rats from 5.0 x 10(-6) to 33 x 10(-6) hr/ml.kg as the dose increased from 1 to 10 mg/kg, whereas the same value was relatively constant in dogs (87.7 x 10(-6) to 105 x 10(-6) hr/ml kg at 1 to 10 mg/kg) and in humans (1260 x 10(-6) to 1768 x 10(-6) hr/ml.kg at 5 to 60 mg/body). Kinetic analysis indicated that AUC(oral) could be accurately predicted at each dose if k(a) value was assumed as 0.07 min(-1) for all animal species examined in our study. These results suggest that it is possible to predict F-h even if the metabolism is composed of non-linear process by considering the absorption rate into the portal vein.

The nonlinearity in the pharmacokinetics of the cyclopentapeptide endothelin antagonist BQ-123 was studied. Both the total body clearance and tissue-to-plasma concentration ratio (K-p) were investigated in rats under a wide range of steady-state plasma concentrations (C-pss) obtained by changing the intravenous infusion rate of BQ-123. The total body clearance was constant up to a C-pss level of 50 mu M, although it was markedly decreased at higher C-pss values, which suggests the existence of a saturable elimination mechanism. A C-pss-dependent nonlinearity in the apparent K-p values (K-p,K-app) was clearly observed in many organs including lung, heart, spleen, pancreas, adrenal, stomach, intestine, colon, aorta, testis and muscle, where the endothelin ET(A) receptor is known to be localized. By fitting the saturation curves of the K-p,K-app values, a similar dissociation constant (K-d) was obtained for most organs at 5 to 10 nM, which is close to the reported K-d values of BQ-123 for the endothetin ET(A) receptor. The saturable portion of the K-p,K-app values observed in vivo showed a good correlation with reported values of the endothelin ET(A) receptor density. Binding of BQ-123 to isolated membrane fractions from several organs demonstrated clear saturability for the lung, heart, spleen and liver with K-d values of 1 to 3 nM. Such specific binding also showed a good correlation with the saturable portion of the K-p,K-app values. From these results, we concluded that the endothelin receptor(s) is responsible for the nonlinear tissue distribution of BQ-123 in rats.

The hepatic uptake mechanisms and pharmacokinetics of BQ-123, an anionic cyclopentapeptidic endothelin ET(A) receptor antagonist, were studied in rats. Elimination of BQ-123 from plasma after intravenous injection of the compound was very rapid as evidenced by high total body clearance (CL(tot), 50 ml/min/kg), which is comparable with hepatic blood flow rate. Within 1 hr after injection, 86% of the dose was excreted as its intact form in the bile. BQ-123 was taken up extensively by isolated rat hepatocytes both Na+-dependently and Na+-independently. The Na+-dependent system transported BQ-123 with higher affinity than did the Na+-independent system (K-m; 6 and 12 mu M, respectively), but its capacity was lower (V-max; 140 and 390 pmol/min/10(6) cells, respectively). Both uptake systems were found to be active transport systems because of explicit inhibition by metabolic inhibitors. BQ-485, an anionic linear tripeptide, strongly inhibited BQ-123 uptake with K-i values of 1.6 and 2.5 mu M for Na+-dependent and Na+-independent systems, respectively, whereas BQ-587, a cationic cyclo-pentapeptide, inhibited BQ-123 uptake only slightly. Considering this in vitro finding and the low in vivo CL(tot) of BQ-587 together, the carrier systems for BQ-123 seem to recognize negatively charged substances selectively. Both Na+-dependent and Na+-independent uptake of BQ-123 were competitively inhibited by a bile acid (taurocholate) and an organic anion (dibromosulfophthalein). The K-i values were comparable with the K-m values of taurocholate and dibromosulfophthalein transport, which suggests that the Na+-dependent system corresponds to the bile acid transporter and that the Na+-independent system corresponds to the organic anion transporter.