Comparison of Fraction Unbound Between Liver Homogenate and Hepatocytes at 4°C

Riccardi, Keith; Ryu, Sangwoo; Tess, David A.; Li, Rui; Luo, Lina; Johnson, Nathaniel; Jordan, Samantha; Patel, Roshan; Di, Li

doi:10.1208/s12248-020-00476-7

Cited by 11 publications

(5 citation statements)

References 29 publications

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“…Previous IVIVE assessment has suggested that the under-prediction of CL is related to the extent of binding to PP (Ring et al, 2011;Bowman and Benet, 2016)a possibility which might now be interpreted as a consequence of the PMU effect. To improve IVIVE, addition of PP into in vitro CL assays (Shibata et al, 2000;Blanchard et al, 2004;Blanchard et al, 2005;Blanchard et al, 2006;Li et al, 2020), determination of unbound drug Kp in hepatocytes in the presence of PP (Li et al, 2020;Riccardi et al, 2020), or semi-empirically predicting the PMU-effect based on an apparent shift in fu between plasma and interstitial fluid (fu p-adjusted ) has previously been suggested (Poulin and Haddad, 2015). Whilst all methods reported improved IVIVE, determination of unbound Kp in hepatocytes requires additional experimentation, incorporation of fu p-adjusted has presently only been justified for acidic compounds, and the addition of PP in vitro has the disadvantage of reducing the total CL int in vitro measured, making reliable quantification of highly bound and/or low CL compounds challenging.…”

Section: Discussionmentioning

confidence: 99%

Impact of Plasma Protein Binding in Drug Clearance Prediction: A Data Base Analysis of Published Studies and Implications for In Vitro-In Vivo Extrapolation

2020

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Section: Discussionmentioning

confidence: 99%

Impact of Plasma Protein Binding in Drug Clearance Prediction: A Data Base Analysis of Published Studies and Implications for In Vitro-In Vivo Extrapolation

2020

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“…After compound spiking in the different matrixes, samples were either immediately processed for U(H)PLC-MS/MS analysis (C0) or kept at 4 °C and 37 °C for 360 min on an orbital shaker (600 rpm) before processing for U(H)PLC-MS/MS analysis. Stability was expressed as follows [54]:…”

Section: Fraction Unbound and Stability Assay In Placental Homogenatementioning

confidence: 99%

Placental Passage of Humulone and Protopine in an Ex Vivo Human Perfusion System

et al. 2021

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The placental passage of humulone and protopine was investigated with a human ex vivo placental perfusion model. The model was first validated with diazepam and citalopram, 2 compounds known to cross the placental barrier, and antipyrine as a positive control. All compounds were quantified by partially validated U(H)PLC-MS/MS bioanalytical methods. Only a small portion of humulone initially present in the maternal circuit reached the fetal circuit. The humulone concentration in the maternal circuit rapidly decreased, likely due to metabolization in the placenta. Protopine was transferred from the maternal to the fetal circuit, with a steady-state reached after 90 min. None of the study compounds affected placental viability or functionality, as glucose consumption, lactate production, beta-human chorionic gonadotropin, and leptin release remained constant. Histopathological evaluation of all placental specimens showed unremarkable, age-appropriate parenchymal maturation with no pathologic findings.

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“…where

f_{normalu, liver}

is unbound faction in liver homogenate (0.035 for GLB 29,30 ; 0.036 for PTV 29–31 ).…”

Section: Methodsmentioning

confidence: 99%

Successful Prediction of Human Hepatic Concentrations of Transported Drugs Using the Proteomics‐Informed Relative Expression Factor Approach

Yin,

Balhara,

Marie

et al. 2023

Clin Pharma and Therapeutics

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Tissue drug concentrations determine the efficacy and toxicity of drugs. When a drug is the substrate of transporters that are present at the blood:tissue barrier, the steady‐state unbound tissue drug concentrations cannot be predicted from their corresponding plasma concentrations. To accurately predict transporter‐modulated tissue drug concentrations, all clearances (CLs) mediating the drug's entry and exit (including metabolism) from the tissue must be accurately predicted. Because primary cells of most tissues are not available, we have proposed an alternative approach to predict such CLs, that is the use of transporter‐expressing cells/vesicles (TECs/TEVs) and relative expression factor (REF). The REF represents the abundance of the relevant transporters in the tissue vs. in the TECs/TEVs. Here, we determined the transporter‐based intrinsic CL of glyburide (GLB) and pitavastatin (PTV) in OATP1B1, OATP1B3, OATP2B1, and NTCP‐expressing cells and MRP3‐, BCRP‐, P‐gp‐, and MRP2‐expressing vesicles and scaled these CLs to in vivo using REF. These predictions fell within a priori set twofold range of the hepatobiliary CLs of GLB and PTV, estimated from their hepatic positron emission tomography imaging data: 272.3 and 607.8 mL/min for in vivo hepatic sinusoidal uptake CL, 47.8 and 17.4 mL/min for sinusoidal efflux CL, and 0 and 4.20 mL/min for biliary efflux CL, respectively. Moreover, their predicted hepatic concentrations (area under the hepatic concentration‐time curve (AUC) and maximum plasma concentration (Cmax)), fell within twofold of their mean observed data. These data, together with our previous findings, confirm that the REF approach can successfully predict transporter‐based drug CLs and tissue concentrations to enhance success in drug development.

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Comparison of Fraction Unbound Between Liver Homogenate and Hepatocytes at 4°C

Cited by 11 publications

References 29 publications

Impact of Plasma Protein Binding in Drug Clearance Prediction: A Data Base Analysis of Published Studies and Implications for In Vitro-In Vivo Extrapolation

Impact of Plasma Protein Binding in Drug Clearance Prediction: A Data Base Analysis of Published Studies and Implications for In Vitro-In Vivo Extrapolation

Placental Passage of Humulone and Protopine in an Ex Vivo Human Perfusion System

Successful Prediction of Human Hepatic Concentrations of Transported Drugs Using the Proteomics‐Informed Relative Expression Factor Approach

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