Relative Activity Factor (RAF)-Based Scaling of Uptake Clearance Mediated by Organic Anion Transporting Polypeptide (OATP) 1B1 and OATP1B3 in Human Hepatocytes

Izumi, Saki; Nozaki, Yoshitane; Kusuhara, Hiroyuki; Hotta, Koichiro; Mochizuki, Toshiki; Komori, Takafumi; Maeda, Kazuya; Sugiyama, Yuichi

doi:10.1021/acs.molpharmaceut.0c00025

Cited by 7 publications

(11 citation statements)

References 4 publications

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“…42 A recent in vitro study suggested that OATP2B1 would play a more important role than OATP1B3 in the hepatic uptake of telmisartan. 5 In our study, SNVs in SLCO2B1 were not, however, associated with telmisartan pharmacokinetics. The analysis included, for example, the c.601G>A SNV associated previously with 3S,5R-fluvastatin and the c.1457C>T SNV associated previously with 3S,5R-fluvastatin, fexofenadine, and celiprolol pharmacokinetics.…”

Section: Pharmacodynamicscontrasting

confidence: 52%

“…3 Furthermore, in vitro studies have suggested the involvement of OATP1B3 (encoded by SLCO1B3) and 2B1 (encoded by SLCO2B1) transporters in the cellular uptake and P-gp/MDR1 (encoded by ABCB1) in the cellular efflux of telmisartan. [4][5][6][7] Telmisartan acyl-glucuronide is a substrate of OATP1B3 and it is eliminated mainly by biliary excretion. 2,8,9 High interindividual variability exists in the pharmacokinetics of telmisartan and low exposure to telmisartan is associated with poor blood pressure-lowering effect.…”

Section: Ugt1a3 and Sex Are Major Determinants Of Telmisartan Pharmacmentioning

confidence: 99%

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UGT1A3 and Sex Are Major Determinants of Telmisartan Pharmacokinetics—A Comprehensive Pharmacogenomic Study

Hirvensalo

Tornio

Launiainen

et al. 2020

Clin Pharma and Therapeutics

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To investigate how variability in multiple pharmacokinetic genes associates with telmisartan exposure, we determined telmisartan single‐dose (40 mg) pharmacokinetics and sequenced 379 genes in 188 healthy volunteers. Intronic UGT1A variants showed the strongest associations with the area under the plasma concentration‐time curve from zero hours to infinity (AUC0–∞) and peak plasma concentration (Cmax) of telmisartan. These variants were strongly linked with the increased function UGT1A3*2 allele, suggesting that it is the causative allele underlying these associations. In addition, telmisartan plasma concentrations were lower in men than in women. The UGT1A3*2 was associated with a 64% and 63% reduced AUC0‐∞ of telmisartan in UGT1A3*2 heterozygous and homozygous men, respectively (P = 1.21 × 10−16 and 5.21 × 10−8). In women, UGT1A3*2 heterozygosity and homozygosity were associated with 57% (P = 1.54 × 10−11) and 72% (P = 3.31 × 10−15) reduced AUC0‐∞, respectively. Furthermore, a candidate gene analysis suggested an association of UGT1A3*3 and the SLCO1B3 c.767G>C missense variant with telmisartan pharmacokinetics. A genotype score, which reflects the effects of sex and genetic variants on telmisartan AUC0–∞, associated with the effect of telmisartan on diastolic blood pressure. These data indicate that sex and UGT1A3 are major determinants and suggest a role for OATP1B3 in telmisartan pharmacokinetics.

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Section: Pharmacodynamicscontrasting

confidence: 52%

Section: Ugt1a3 and Sex Are Major Determinants Of Telmisartan Pharmacmentioning

confidence: 99%

UGT1A3 and Sex Are Major Determinants of Telmisartan Pharmacokinetics—A Comprehensive Pharmacogenomic Study

Hirvensalo

Tornio

Launiainen

et al. 2020

Clin Pharma and Therapeutics

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“…5 using pharmacokinetic parameters summarized in Supplemental Table 3 (Table 1). Contribution ratio (f value) of OATP1B1-mediated uptake to overall uptake of the three OATP1B1 substrates in human hepatocytes was estimated as the average of previously reported values (Kunze et al, 2014;Izumi et al, 2018;Zhang et al, 2019) (Table 1). The R 0 values of CsA without consideration of the preincubation effect were first calculated by eq.…”

Section: Resultsmentioning

confidence: 99%

Static Model–Based Assessment of OATP1B1-Mediated Drug Interactions with Preincubation-Dependent Inhibitors Based on Inactivation and Recovery Kinetics

Taguchi

Masuo

Futatsugi

et al. 2020

Drug Metabolism and Disposition

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Quantitative assessment of drug-drug interactions (DDIs) via organic anion transporting polypeptide (OATP) 1B1 is one of the key issues in drug development. Although OATP1B1 inhibition exhibits unique characteristics, including preincubation dependence for some inhibitors, a limited approach has been attempted based on the static model that considers such preincubation dependence in the prediction of DDIs via OATP1B1. The present study aimed to establish the prediction of DDIs via OATP1B1 using preincubationdependent inhibitors based on the static model and incorporating both inactivation and recovery of OATP1B1 activity. Cyclosporine A was selected as a preincubation-dependent inhibitor, as well as five substrates that include probes and pharmaceuticals. The inhibition ratio (R value) calculated on the basis of a conventional static model, considering inhibition of OATP1B1 and contribution ratio of OATP1B1 to the overall hepatic uptake, was much lower than the reported AUC ratio, even when IC 50 values were estimated after preincubation conditions. Conversely, the R value that was estimated by considering inactivation and recovery parameters was closer to the AUC ratio. The R value that was calculated assuming the complete contribution of OATP1B1 was much higher than the AUC ratio, avoiding false-negative prediction. The R value estimated by considering inactivation and recovery for another combination of a preincubation-dependent inhibitor, asunaprevir, and substrate drug, rosuvastatin, was also closer to the AUC ratio. Thus, R values calculated based on such OATP1B1 kinetics would be potential alternative indexes for the quantitative prediction of OATP1B1-mediated DDIs using preincubation-dependent inhibitors, although this prediction is affected by estimation of the contribution ratio of substrates. SIGNIFICANCE STATEMENTStatic model-based quantitative prediction of organic anion transporting polypeptide 1B1-mediated drug-drug interactions induced by preincubation-dependent inhibitors was newly proposed to avoid false-negative prediction.

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“…Instead of using the global CL int,T determined from fitting of in vivo data and assigning percentages to each hepatic uptake transporter involved for input, M-IV used in vitro transporter data and scaled it up to predict in vivo values. The CL int from a suspension hepatocyte study with and without sodium-containing buffer was input for NTCP 48 , while J max and K m values from HEK293 cells overexpressing transporters were input for OATP1B1, 1B3, and 2B1 45,49 . MRP4 was included for sinusoidal efflux as it was with M-III, but instead of model fitting to obtain a value, here experimental J max and K m values from membrane vesicles were input 47 .…”

Section: Accepted Articlementioning

confidence: 99%

Examination of Physiologically‐Based Pharmacokinetic Models of Rosuvastatin

Bowman¹,

Ma²,

Mao³

et al. 2020

CPT Pharmacom & Syst Pharma

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Physiologically‐based pharmacokinetic (PBPK) modeling is increasingly used to predict drug disposition and drug–drug interactions (DDIs). However, accurately predicting the pharmacokinetics of transporter substrates and transporter‐mediated DDIs (tDDIs) is still challenging. Rosuvastatin is a commonly used substrate probe in DDI risk assessment for new molecular entities (NMEs) that are potential organic anion transporting polypeptide 1B or breast cancer resistance protein transporter inhibitors, and as such, several rosuvastatin PBPK models have been developed to try to predict the clinical DDI and support NME drug labeling. In this review, we examine five representative PBPK rosuvastatin models, discuss common challenges that the models have come across, and note remaining gaps. These shared learnings will help with the continuing efforts of rosuvastatin model validation, provide more information to understand transporter‐mediated drug disposition, and increase confidence in tDDI prediction.

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Relative Activity Factor (RAF)-Based Scaling of Uptake Clearance Mediated by Organic Anion Transporting Polypeptide (OATP) 1B1 and OATP1B3 in Human Hepatocytes

Cited by 7 publications

References 4 publications

UGT1A3 and Sex Are Major Determinants of Telmisartan Pharmacokinetics—A Comprehensive Pharmacogenomic Study

UGT1A3 and Sex Are Major Determinants of Telmisartan Pharmacokinetics—A Comprehensive Pharmacogenomic Study

Static Model–Based Assessment of OATP1B1-Mediated Drug Interactions with Preincubation-Dependent Inhibitors Based on Inactivation and Recovery Kinetics

Examination of Physiologically‐Based Pharmacokinetic Models of Rosuvastatin

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