Masaru Hirano

DRUG-DRUG INTERACTION BETWEEN PITAVASTATIN AND VARIOUS DRUGS VIA OATP1B1

It has already been demonstrated that pitavastatin, a novel potent HMG-coenzyme A reductase inhibitor, is taken up into human hepatocytes mainly by organic anion transporting polypeptide (OATP) 1B1. Because OATP2B1 is also localized in the basolateral membrane of human liver, we took two approaches to further confirm the minor contribution of OATP2B1 to the hepatic uptake of pitavastatin. Western blot analysis revealed that the ratio of the band density of OATP2B1 in human hepatocytes to that in our expression system is at least 6-fold lower compared with OATP1B1 and OATP1B3. The uptake of pitavastatin in human hepatocytes could be inhibited by both estrone-3-sulfate (OATP1B1/OATP2B1 inhibitor) and estradiol-17β-d-glucuronide (OATP1B1/OATP1B3 inhibitor). These results further supported the idea that OATP1B1 is a predominant transporter for the hepatic uptake of pitavastatin. Then, to explore the possibility of OATP1B1-mediated drug-drug interaction, we checked the inhibitory effects of various drugs on the pitavastatin uptake in OATP1B1-expressing cells and evaluated whether the in vitro inhibition was clinically significant or not. As we previously reported, we used the methodology for estimating the maximum unbound concentration of inhibitors at the inlet to the liver (Iu,in,max). Judging from Iu,in,max and inhibition constant (Ki) for OATP1B1, several drugs (especially cyclosporin A, rifampicin, rifamycin SV, clarithromycin, and indinavir) have potentials for interacting with OATP1B1-mediated uptake of pitavastatin. The in vitro experiments could support the clinically observed drug-drug interaction between pitavastatin and cyclosporin A. These results suggest that we should pay attention to the concomitant use of some drugs with pitavastatin.

Effects of organic anion transporting polypeptide 1B1 haplotype on pharmacokinetics of pravastatin, valsartan, and temocapril.

Recent reports have shown that genetic polymorphisms in organic anion transporting polypeptide (OATP) 1B1 have an effect on the pharmacokinetics of drugs. However, the impact of OATP1B1*1b alleles, the frequency of which is high in all ethnicities, on the pharmacokinetics of substrate drugs is not known after complete separation of subjects with OATP1B1*1a and *1b. Furthermore, the correlation between the clearances of OATP1B1 substrate drugs in individuals has not been characterized. We investigated the effect of genetic polymorphism of OATP1B1, particularly the *1b allele, on the pharmacokinetics of 3 anionic drugs, pravastatin, valsartan, and temocapril, in Japanese subjects.

SLCO1B1 (OATP1B1, an Uptake Transporter) and ABCG2 (BCRP, an Efflux Transporter) Variant Alleles and Pharmacokinetics of Pitavastatin in Healthy Volunteers

To investigate the contribution of genetic polymorphisms of SLCO1B1 and ABCG2 to the pharmacokinetics of a dual substrate, pitavastatin, 2 mg of pitavastatin was administered to 38 healthy volunteers and pharmacokinetic parameters were compared among the following groups: 421C/C*1b/*1b (group 1), 421C/C*1b/*15 (group 2), 421C/C*15/*15 and 421C/A*15/*15 (group 3), 421C/A*1b/*1b (group 4), 421A/A*1b/*1b (group 5), and 421C/A*1b/*15 (group 6). In SLCO1B1, pitavastatin area under plasma concentration–time curve from 0 to 24 h (AUC0–24) for groups 1, 2, and 3 was 81.1±18.1, 144±32, and 250±57 ng h/ml, respectively, with significant differences among all three groups. In contrast to SLCO1B1, AUC0–24 in groups 1, 4, and 5 was 81.1±18.1, 96.7±35.4, and 78.2±8.2 ng h/ml, respectively. Although the SLCO1B1 polymorphism was found to have a significant effect on the pharmacokinetics of pitavastatin, a nonsynonymous ABCG2 variant, 421C>A, did not appear to be associated with the altered pharmacokinetics of pitavastatin.

The quantitative prediction of CYP-mediated drug interaction by physiologically based pharmacokinetic modeling.

PurposeThe objective is to confirm if the prediction of the drug–drug interaction using a physiologically based pharmacokinetic (PBPK) model is more accurate. In vivo Ki values were estimated using PBPK model to confirm whether in vitro Ki values are suitable.MethodThe plasma concentration–time profiles for the substrate with coadministration of an inhibitor were collected from the literature and were fitted to the PBPK model to estimate the in vivo Ki values. The AUC ratios predicted by the PBPK model using in vivo Ki values were compared with those by the conventional method assuming constant inhibitor concentration.ResultsThe in vivo Ki values of 11 inhibitors were estimated. When the in vivo Ki values became relatively lower, the in vitro Ki values were overestimated. This discrepancy between in vitro and in vivo Ki values became larger with an increase in lipophilicity. The prediction from the PBPK model involving the time profile of the inhibitor concentration was more accurate than the prediction by the conventional methods.ConclusionA discrepancy between the in vivo and in vitro Ki values was observed. The prediction using in vivo Ki values and the PBPK model was more accurate than the conventional methods.