Prediction of Hepatobiliary Clearances and Hepatic Concentrations of Transported Drugs in Humans Using Rosuvastatin as a Model Drug

Storelli, Flavia; Li, Cindy Yanfei; Sachar, Madhav; Kumar, Vineet; Heyward, Scott; Sáfár, Zsolt; Kis, Emese; Unadkat, Jashvant D.

doi:10.1002/cpt.2556

Cited by 6 publications

(19 citation statements)

References 34 publications

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“…The next frontier in this area of research is to predict and validate fetal tissue drug exposure. We have already shown that the ER‐REF approach is successful in predicting human adult brain and liver drug concentrations where the drugs are actively transported across the tissue : blood barrier 126,127 . Thus, there is every reason to believe that this approach will be successful in predicting fetal tissue drug exposure provided the relevant data on the ontogeny of transporters and enzymes in these tissues are available.…”

mentioning

confidence: 99%

Predicting Human Fetal Drug Exposure Through Maternal‐Fetal PBPK Modeling and In Vitro or Ex Vivo Studies

Balhara

Kumar

Unadkat

2022

The Journal of Clinical Pharma

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Medication (drug) use in human pregnancy is prevalent. Determining fetal safety and efficacy of drugs is logistically challenging. However, predicting (not measuring) fetal drug exposure (systemic and tissue) throughout pregnancy is possible through maternal‐fetal physiologically based pharmacokinetic (PBPK) modeling and simulation. Such prediction can inform fetal drug safety and efficacy. Fetal drug exposure can be quantified in 2 complementary ways. First, the ratio of the steady‐state unbound plasma concentration in the fetal plasma (or area under the plasma concentration–time curve) to the corresponding maternal plasma concentration (ie, Kp,uu). Second, the maximum unbound peak (Cu,max,ss,f) and trough (Cu,min,ss,f) fetal steady‐state plasma concentrations. We (and others) have developed a maternal‐fetal PBPK model that can successfully predict maternal drug exposure. To predict fetal drug exposure, the model needs to be populated with drug specific parameters, of which transplacental clearances (active and/or passive) and placental/fetal metabolism of the drug are critical. Herein, we describe in vitro studies in cells/tissue fractions or the perfused human placenta that can be used to determine these drug‐specific parameters. In addition, we provide examples whereby this approach has successfully predicted systemic fetal exposure to drugs that passively or actively cross the placenta. Apart from maternal‐fetal PBPK models, animal studies also have the potential to estimate fetal drug exposure by allometric scaling. Whether such scaling will be successful is yet to be determined. Here, we review the above approaches to predict fetal drug exposure, outline gaps in our knowledge to make such predictions and map out future research directions that could fill these gaps.

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confidence: 99%

Predicting Human Fetal Drug Exposure Through Maternal‐Fetal PBPK Modeling and In Vitro or Ex Vivo Studies

Balhara

Kumar

Unadkat

2022

The Journal of Clinical Pharma

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“…In conclusion, using the REF approach, we have now successfully predicted CL s,uptake , CL s,efflux , CL bile , and human hepatic concentrations of the drugs, GLB, PTV, and RSV 8 that are transported by multiple transporters (OATPs, NTCP, MRP2, MRP3, BCRP, and P‐gp). In addition, we have verified the ability of the TECs/REF approach to predict the brain and fetal unbound tissue‐to‐plasma concentration ratio of several transported substrates 10–12 .…”

Section: Discussionmentioning

confidence: 92%

“…Furthermore, the REF‐predicted mean GLB AUC and C max were not significantly different from those observed ( P > 0.05). Whereas the prediction of hepatic 18 F‐PTV AUC and C max met the success criteria, like RSV 8 the hepatic concentration‐time profile was modestly underpredicted due to underprediction of its CL s,uptake . We note that modest underprediction of this magnitude has also been widely reported for IVIVE of metabolic CL of drugs 5 …”

Section: Discussionmentioning

confidence: 99%

“…This is particularly important where primary cells (e.g., blood‐brain barrier and intestinal enterocytes) are not available. Second, we have previously shown that human hepatocytes (PH, SH, or SCHH) underpredict the sinusoidal uptake clearance while the SCHH overpredict the biliary efflux clearance of drugs 7,8,33 . This is because biliary efflux transporters' abundance is dramatically increased in SCHH vs. human liver tissue 34 .…”

Section: Discussionmentioning

confidence: 99%

“…The efflux assay by TEVs was conducted as described previously 8 . The GLB and PTV concentration used in the assay was 50 nM glyburide (10 nM 3 H‐GLB + 40 nM GLB) or 500 nM PTV (100 nM 3 H‐PTV + 400 nM PTV).…”

Section: Methodsmentioning

confidence: 99%

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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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The next frontier in ADME science: Predicting transporter-based drug disposition, tissue concentrations and drug-drug interactions in humans

Storelli

Yin

Kumar

et al. 2022

Pharmacology & Therapeutics

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Prediction of Hepatobiliary Clearances and Hepatic Concentrations of Transported Drugs in Humans Using Rosuvastatin as a Model Drug

Cited by 6 publications

References 34 publications

Predicting Human Fetal Drug Exposure Through Maternal‐Fetal PBPK Modeling and In Vitro or Ex Vivo Studies

Predicting Human Fetal Drug Exposure Through Maternal‐Fetal PBPK Modeling and In Vitro or Ex Vivo Studies

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

The next frontier in ADME science: Predicting transporter-based drug disposition, tissue concentrations and drug-drug interactions in humans

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