Predictions of Cytochrome P450-Mediated Drug-Drug Interactions Using Cryopreserved Human Hepatocytes: Comparison of Plasma and Protein-Free Media Incubation Conditions

Mao, Jialin; Mohutsky, Michael A.; Harrelson, John; Wrighton, Steven; Hall, Stephen D.

doi:10.1124/dmd.111.043158

Cited by 37 publications

(39 citation statements)

References 72 publications

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“…Generally, the known CYP3A inhibitors showed a less potent TDI in HEP relative to HLM, which have yielded an impact on the in vivo DDI prediction (Xu et al, 2009;Chen et al, 2011;Kirby et al, 2011). Furthermore, it has been reported that cryopreserved human hepatocytes suspended in human plasma (HSP), compared with those in protein-free media, showed better DDI predictions for some of cytochrome P450 inhibitors (Mao et al, 2011(Mao et al, , 2012.…”

Section: Introductionmentioning

confidence: 99%

“…This dynamic approach is increasingly being employed in drug discovery and development setting to predict pharmacokinetics (PK) and DDI potential in the clinic. Traditionally, DDI predictions have been performed with static mathematical models using various inhibitor concentrations such as hepatic inlet or outlet concentrations in total (protein bound plus unbound) or unbound form (Mayhew et al, 2000;Obach et al, 2007;Fahmi et al, 2009;Boulenc and Barberan, 2011;Mao et al, 2012). In these reports, hepatic DDI magnitudes for RI were reasonably predicted using the projected unbound portal vein (or hepatic inlet) concentration (C inlet,u ), whereas the use of unbound systemic (or hepatic outlet) concentration (C sys,u ) yielded better prediction for TDI and EI compared with C inlet,u .…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Crizotinib-Midazolam Interaction Using the Simcyp Population-Based Simulator: Comparison of CYP3A Time-Dependent Inhibition between Human Liver Microsomes versus Hepatocytes

et al. 2012

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Crizotinib (Xalkori) is an orally available potent inhibitor of multiple tyrosine kinases, including anaplastic lymphoma kinase and mesenchymal-epithelial transition factor. Objectives of the present study were as follows: 1) to characterize crizotinib time-dependent inhibition (TDI) potency for CYP3A in human liver microsomes (HLM) and cryopreserved human hepatocytes suspended in human plasma (HSP); 2) to characterize crizotinib enzyme induction potency on CYP3A4 in cryopreserved human hepatocytes; 3) to predict crizotinib steady-state plasma concentrations in patients (e.g., autoinhibition and autoinduction) using the mechanistic dynamic model, Simcyp population-based simulator; and 4) to predict a clinical crizotinib-midazolam interaction using the dynamic model as well as the static mathematical model. Crizotinib inactivation constant (K I ) and maximum inactivation rate constant (k inact ) for TDI were estimated as, respectively, 0.37 mM and 6.9 h 21 in HLM and 0.89 mM and 0.78 h 21 in HSP.Thus, crizotinib inactivation efficiency (k inact /K I ) was ∼20-fold lower in HSP relative to HLM. Crizotinib E max and EC 50 for CYP3A4 induction (measured as mRNA expression) were estimated as 6.4-to 29-fold and 0.47 to 3.1 mM, respectively. Based on these in vitro parameters, the predicted crizotinib steady-state area under plasma concentration-time curve (AUC) with HLM-TDI was 2.1-fold higher than the observed AUC, whereas that with HSP-TDI was consistent with the observed result (£1.1-fold). The increase in midazolam AUC with coadministration of crizotinib (21-fold) was significantly overpredicted using HLM-TDI, whereas the prediction using HSP-TDI (3.6-fold) was consistent with the observed result (3.7-fold). Collectively, the present study demonstrated the value of HSP to predict in vivo CYP3A-mediated drugdrug interaction.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction of Crizotinib-Midazolam Interaction Using the Simcyp Population-Based Simulator: Comparison of CYP3A Time-Dependent Inhibition between Human Liver Microsomes versus Hepatocytes

et al. 2012

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“…However, the reported approaches have employed a static model that requires [I] as a parameter and they are not practical in early phase drug discovery, in which information for [I] is lacking. Although [I] would become accessible surrogates in late phase drug discovery, several investigators used different [I] for DDI prediction (Lu et al, 2006(Lu et al, , 2008Mao et al, 2011Mao et al, , 2012Shibata et al, 2008). Thus, it has not been clarified which inhibitor concentration is appropriate in the use of hepatocytes suspended in serum/plasma.…”

Section: Introductionmentioning

confidence: 99%

Risk assessment of drug–drug interactions using hepatocytes suspended in serum during the drug discovery process

et al. 2013

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1. This study optimized the reported approach for the prediction of drug-drug interactions (DDIs) using hepatocytes suspended in serum (HHSS) and provided a practical usage of HHSS in the early and late phases of drug discovery. 2. First, the IC50 was determined using HHSS and evaluated as a qualitative index for DDI risks in the early phase. A retrospective study on clinical DDI cases revealed that inhibitors with IC50 < 100 μmol/L caused clinical DDIs while those with IC50 > 100 μmol/L showed weak or no potential for DDIs. Meanwhile, a pragmatic cutoff value could not be determined using previously reported Ki values of recombinant human cytochrome P450s. 3. Second, for a more substantial DDI risk assessment in the later phase, quantitative predictions of clinical DDI based on a static model were attempted by optimizing the most appropriate inhibitor concentration ([I]). The use of hepatic input plasma concentrations as a surrogate for [I] achieved the most successful predictions of the magnitude of increase in the AUC (within a 2-fold range of the observed values for 93.8% of inhibitors). 4. Through this study, we proposed the practical application of HHSS for an effective workflow to explore and profile candidates with less DDI liability.

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“…The majority were below a 5 times interaction factor (multiplier) (USEPA 2000b(USEPA , 2003. The U.S. Food and Drug Administration (USFDA) has draft guidelines for running pharmaceutical interaction studies based on a comparisons of enzyme induction potentials and clinical pharmacokinetics (USFDA 2012; Mao et al 2011Mao et al , 2012. In Table 2 the USFDA categories and their associated increases in internal exposure as AUC or "area under the curve" from clinical samples.…”

Section: Range Of Interaction Valuesmentioning

confidence: 99%

“…The "Comments" column has a "Default," where the group default value is used, from Table 2, when definite DDI values cannot be determined based on the USFDA categories (Mao et al 2011(Mao et al , 2012. If two pharmaceuticals are not documented having interactions based on the data available, the pair is not included in Table 3.…”

Section: Range Of Interaction Valuesmentioning

confidence: 99%

The Cumulative Risk to Human Health of Pharmaceuticals in New Jersey Surface Water

Roden

Sargent

DiFerdinando

et al. 2014

Human and Ecological Risk Assessment: An International Journal

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Surface water in New Jersey is used by many residential drinking water facilities. Like many water sources it is contaminated by upstream industrial and residential sources, including pharmaceutical residues. This research examines the concentrations of 18 pharmaceuticals in 30 New Jersey locations, their acceptable daily exposures (ADE), and potential drug-drug interactions (DDI). The surface water data was provided by the U.S. Geological Survey (USGS). ADEs for human health were set for each pharmaceutical in the study. The pharmaceuticals were evaluated for known adverse health interactions and their potential health impact. These factors were brought together using a cumulative hazard index (HI) risk assessment calculation to assess the overall risk of pharmaceuticals in NJ surface water to human health. When examining the potential for DDI in this assessment, the risk increased but not appreciably. The HI for the sample locations ranged from <0.00001 to 0.01 with the DDI adding less than 1.2× increase to the overall risk. The calculated risk of these mixtures was also increased to an extreme DDI of 7 times per interaction. A noticeable increase in the calculated risk was seen, but in no cases did it reach a level of concern.

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Predictions of Cytochrome P450-Mediated Drug-Drug Interactions Using Cryopreserved Human Hepatocytes: Comparison of Plasma and Protein-Free Media Incubation Conditions

Cited by 37 publications

References 72 publications

Prediction of Crizotinib-Midazolam Interaction Using the Simcyp Population-Based Simulator: Comparison of CYP3A Time-Dependent Inhibition between Human Liver Microsomes versus Hepatocytes

Prediction of Crizotinib-Midazolam Interaction Using the Simcyp Population-Based Simulator: Comparison of CYP3A Time-Dependent Inhibition between Human Liver Microsomes versus Hepatocytes

Risk assessment of drug–drug interactions using hepatocytes suspended in serum during the drug discovery process

The Cumulative Risk to Human Health of Pharmaceuticals in New Jersey Surface Water

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