The effects of CYP3A4 inhibition on erlotinib pharmacokinetics: computer-based simulation (SimCYP™) predicts in vivo metabolic inhibition

Rakhit, Ashok; Pantze, Michael; Fettner, Scott; Jones, Hannah M.; Charoin, Jean-Eric; Riek, Myriam; Lum, Bert L.; Hamilton, Marta

doi:10.1007/s00228-007-0396-z

Cited by 110 publications

(80 citation statements)

References 20 publications

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“…2), it is advisable to revisit this conclusion. Similarly, studies that have used the ketoconazole model to estimate the true fraction metabolized by CYP3A in vivo should be re-evaluated (Rakhit et al, 2008;Yang et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

“…Preliminary assessments of the ketoconazole-midazolam interaction using that model concluded that predictive performance was poor (Guest et al, 2011). Despite this conclusion, model 2 has been used to determine whether static or dynamic plasma concentration approaches are most appropriate for predicting clinically important DDIs (Einolf, 2007;Guest et al, 2011;Peters et al, 2012), to validate in vitro technologies (Youdim et al, 2008), and to estimate the fraction metabolized by CYP3A (f m ) for new drugs after in vivo studies (Rakhit et al, 2008;Yang et al, 2012). Of importance, model 2 was used by the Food and Drug Administration (FDA) to recommend specific clinical study designs (Zhao et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimization of Drug-Drug Interaction Study Design: Comparison of Minimal Physiologically Based Pharmacokinetic Models on Prediction of CYP3A Inhibition by Ketoconazole

Han

Mao²,

Chien

et al. 2013

Drug Metab Dispos

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Ketoconazole is a potent CYP3A inhibitor used to assess the contribution of CYP3A to drug clearance and quantify the increase in drug exposure due to a strong inhibitor. Physiologically based pharmacokinetic (PBPK) models have been used to evaluate treatment regimens resulting in maximal CYP3A inhibition by ketoconazole but have reached different conclusions. We compare two PBPK models of the ketoconazole-midazolam interaction, model 1 (Chien et al., 2006) and model 2 implemented in Simcyp (version 11), to predict 16 published treatment regimens. With use of model 2, 41% of the study point estimates of area under the curve (AUC) ratio and 71% of the 90% confidence intervals were predicted within 1.5-fold of the observed, but these increased to 82 and 100%, respectively, with model 1. For midazolam, model 2 predicted a maximal midazolam AUC ratio of 8 and a hepatic fraction metabolized by CYP3A (f m ) of 0.97, whereas model 1 predicted 17 and 0.90, respectively, which are more consistent with observed data. On the basis of model 1, ketoconazole (400 mg QD) for at least 3 days and substrate administration within 2 hours is required for maximal CYP3A inhibition. Ketoconazole treatment regimens that use 200 mg BID underestimate the systemic fraction metabolized by CYP3A (0.86 versus 0.90) for midazolam. The systematic underprediction also applies to CYP3A substrates with high bioavailability and long half-lives. The superior predictive performance of model 1 reflects the need for accumulation of ketoconazole at enzyme site and protracted inhibition. Model 2 is not recommended for inferring optimal study design and estimation of fraction metabolized by CYP3A.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Drug-Drug Interaction Study Design: Comparison of Minimal Physiologically Based Pharmacokinetic Models on Prediction of CYP3A Inhibition by Ketoconazole

Han

Mao²,

Chien

et al. 2013

Drug Metab Dispos

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“…Furthermore, it cannot be excluded that as a consequence of P-gp and Bcrp1 gene deletion other transporters and/or drug-metabolizing enzymes involved in oral absorption of erlotinib are overexpressed in knockout mice, thus reducing the effect of Bcrp1/P-gp deletion on erlotinib pharmacokinetics. Indeed, considering that recently expression of CYP3A in the intestine has been shown to affect drug absorption (38) and that erlotinib has been reported to be susceptible to CYP3A-mediated metabolism (22,39,40), an altered expression/ activity of CYP3A in our mice model might affect the magnitude of our findings. However, the bioavailability observed in WT mice is of the same magnitude as observed in humans (41) and the experimental condition in this model may thus reflect the pharmacokinetic condition in patients.…”

Section: Effect Of P-gp Bcrp and Mrp2 On Erlotinib Dispositionmentioning

confidence: 95%

Effect of the ATP-binding cassette drug transporters ABCB1, ABCG2, and ABCC2 on erlotinib hydrochloride (Tarceva) disposition inin vitroandin vivopharmacokinetic studies employing Bcrp1−/−/Mdr1a/1b−/− (triple-knockout) and wild-type mice

Marchetti¹,

Vries

Buckle

et al. 2008

Molecular Cancer Therapeutics

183

129

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We tested whether erlotinib hydrochloride (Tarceva,, an orally active epidermal growth factor receptor tyrosine kinase inhibitor, is a substrate for the ATP-binding cassette drug transporters P-glycoprotein (Pgp; MDR1, ABCB1), breast cancer resistance protein (BCRP; ABCG2), and multidrug resistance protein 2 (MRP2; ABCC2) in vitro and whether P-gp and BCRP affect the oral pharmacokinetics of erlotinib hydrochloride in vivo. In vitro cell survival, drug transport, accumulation, and efflux of erlotinib were done using Madin-Darby canine kidney II [MDCKII; wild-type (WT), MDR1, Bcrp1, and MRP2] and LLCPK (WT and MDR1) cells and monolayers as well as the IGROV1 and the derived human BCRP-overexpressing T8 cell lines. In vivo, the pharmacokinetics of erlotinib after p.o. and i.p. administration was studied in Bcrp1/Mdr1a/1b -/-(triple-knockout) and WT mice. In vitro, erlotinib was actively transported by P-gp and BCRP/Bcrp1. No active transport of erlotinib by MRP2 was observed. In vivo, systemic exposure (P = 0.01) as well as bioavailability of erlotinib after oral administration (5 mg/kg) were statistically significantly increased in Bcrp1/Mdr1a/1b -/-knockout mice (60.4%) compared with WT mice (40.0%; P = 0.02). Conclusion: Erlotinib is transported efficiently by P-gp and BCRP/Bcrp1 in vitro. In vivo, absence of P-gp and Bcrp1 significantly affected the oral bioavailability of erlotinib. Possible clinical consequences for drug-drug and drug-herb interactions in patients in the gut between P-gp/BCRP-inhibiting substrates and oral erlotinib need to be addressed.

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“…For COMED, no specific model and parameters were needed according to assumption (2). The CL, F, V d , and k a of the drug of interest would be changed to reflect the effects of COMED (see Simulations and Glossary sections).…”

Section: Pharmacokinetic Modelmentioning

confidence: 99%

“…In the first category, AUC and C max have similar fold changes during DDI. [2,3] The second category includes the cases in which AUC has larger fold changes compared to C max . [4][5][6][7][8] In cases of the third category, C max has larger fold changes compared with AUC.…”

Section: Introductionmentioning

confidence: 99%

Drug-Drug Interaction Pattern Recognition

Duan

2010

Drugs R D

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Background and Objective: Drug-drug interaction (DDI) is an important aspect of drug development, especially for safety. When a drug is used concomitantly with other drug(s), one of the major concerns is the change of exposures, including the rate and extent of drug absorption, distribution, metabolism and elimination. To address the concerns, a common practice is to measure and report the differences between the exposure in the presence and in the absence of concomitant medication (COMED). The area under the plasma concentration versus time curve (AUC), maximum plasma concentration (C max ) and time to reach the C max (t max ) changes are usually measured in DDI studies. A usual observation is the different extents of changes among AUC, C max and t max , which may raise concerns in certain therapeutic areas or some special agents. The objective of this study was to investigate the variation among changes of AUC, C max and t max in DDI studies, and its pharmacokinetic manifestation. Data Sources: Based on a list of DDI results from the literature, with the assumptions that the primary parameters of a drug of interest were altered during a DDI, two sets of simulated data were generated according to a single oral dose, one-compartment model. The first set including 24 cases with different half-lives and absorption constants (k a ) considered the exposure changes upon independent variation of bioavailability (F), clearance (CL), volume of distribution (V d ) and k a up to 50-fold increases or decreases. The second set considered the exposure changes with simultaneous variation of F, CL, V d , and k a within 5-fold range (increase or decrease) for a case selected from the first set. Study Selection, Data Extraction and Synthesis: Parameter fold changes (defined in a fashion showing fold increase or fold decreases, including CL fold change, F fold change, V d fold change and k a fold change) and exposure changes (AUC fold change, C max fold change, t max fold change and fold change difference [AUC fold change -C max fold change]) were used to generate plots demonstrating various relationships between parameter fold changes and exposure changes. Based on the observations that AUC was influenced by CL and F, C max was affected by all four parameters, t max was mainly determined by CL and k a , F did little for t max and k a was unrelated to AUC, a chart was created for DDI pattern recognition.

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The effects of CYP3A4 inhibition on erlotinib pharmacokinetics: computer-based simulation (SimCYP™) predicts in vivo metabolic inhibition

Cited by 110 publications

References 20 publications

Optimization of Drug-Drug Interaction Study Design: Comparison of Minimal Physiologically Based Pharmacokinetic Models on Prediction of CYP3A Inhibition by Ketoconazole

Optimization of Drug-Drug Interaction Study Design: Comparison of Minimal Physiologically Based Pharmacokinetic Models on Prediction of CYP3A Inhibition by Ketoconazole

Effect of the ATP-binding cassette drug transporters ABCB1, ABCG2, and ABCC2 on erlotinib hydrochloride (Tarceva) disposition inin vitroandin vivopharmacokinetic studies employing Bcrp1−/−/Mdr1a/1b−/− (triple-knockout) and wild-type mice

Drug-Drug Interaction Pattern Recognition

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