Dysregulation of the mRNA Expression of Human Renal Drug Transporters by Proinflammatory Cytokines in Primary Human Proximal Tubular Epithelial Cells.

Proinflammatory cytokines, which are elevated during inflammation or infections, can affect drug pharmacokinetics (PK) due to the altered expression or activity of drug transporters and/or metabolizing enzymes. To date, such studies have focused on the effect of cytokines on the activity and/or mRNA expression of hepatic transporters and drug-metabolizing enzymes. However, many antibiotics and antivirals used to treat infections are cleared by renal transporters, including the basal organic cation transporter 2 (OCT2), organic anion transporters 1 and 3 (OAT1 and 3), the apical multidrug and toxin extrusion proteins 1 and 2-K (MATE1/2-K), and multidrug resistance-associated protein 2 and 4 (MRP2/4). Here, we determined the concentration-dependent effect of interleukin-6 (IL-6), IL-1ß, tumor necrosis factor (TNF)-α, and interferon-γ (IFN-γ) on the mRNA expression of human renal transporters in freshly isolated primary human renal proximal tubular epithelial cells (PTECs, n = 3-5). PTECs were exposed to either a cocktail of cytokines, each at 0.01, 0.1, 1, or 10 ng/mL or individually at the same concentrations. Exposure to the cytokine cocktail for 48 h was found to significantly downregulate the mRNA expression, in a concentration-dependent manner, of OCT2, the organic anion transporting polypeptides 4C1 (OATP4C1), OAT4, MATE2-K, P-glycoprotein (P-gp), and MRP2 and upregulate the mRNA expression of the organic cation/carnitine transporter 1 (OCTN1) and MRP3. OAT1 and OAT3 also appeared to be significantly downregulated but only at 0.1 and 10 ng/mL, respectively, without a clear concentration-dependent trend. Among the cytokines, IL-1ß appeared to be the most potent at down- and upregulating the mRNA expression of the transporters. Taken together, our results demonstrate for the first time that proinflammatory cytokines transcriptionally dysregulate renal drug transporters in PTECs. Such dysregulation could potentially translate into changes in transporter protein abundance or activity and alter renal transporter-mediated drug PK during inflammation or infections.

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

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.

Toward improved predictions of pharmacokinetics of transported drugs in hepatic impairment: Insights from the extended clearance model.

Hepatic impairment (HI) moderately (<5-fold) affects the systemic exposure (i.e., area under the plasma concentration-time curve [AUC]) of drugs that are substrates of the hepatic sinusoidal organic anion transporting polypeptide (OATP) transporters and are excreted unchanged in the bile and/or urine. However, the effect of HI on their AUC is much greater (>10-fold) for drugs that are also substrates of cytochrome P450 (CYP) 3A enzymes. Using the extended clearance model, through simulations, we identified the ratio of sinusoidal efflux clearance (CL) over the sum of metabolic and biliary CLs as important in predicting the impact of HI on the AUC of dual OATP/CYP3A substrates. Because HI may reduce hepatic CYP3A-mediated CL to a greater extent than biliary efflux CL, the greater the contribution of the former versus the latter, the greater the impact of HI on drug AUC ratio (AUCRHI ). Using physiologically-based pharmacokinetic modeling and simulation, we predicted relatively well the AUCRHI of OATP substrates that are not significantly metabolized (pitavastatin, rosuvastatin, valsartan, and gadoxetic acid). However, there was a trend toward underprediction of the AUCRHI of the dual OATP/CYP3A4 substrates fimasartan and atorvastatin. These predictions improved when the sinusoidal efflux CL of these two drugs was increased in healthy volunteers (i.e., before incorporating the effect of HI), and by modifying the directionality of its modulation by HI (i.e., increase or decrease). To accurately predict the effect of HI on AUC of hepatobiliary cleared drugs it is important to accurately predict all hepatobiliary pathways, including sinusoidal efflux CL.

Successful Prediction of Fetal Exposure to Dual BCRP/P-gp Drug Substrates Using the Efflux Ratio-Relative Expression Factor Approach and PBPK M&S.

To inform fetal drug safety, it is important to determine or predict fetal drug exposure throughout pregnancy. The former is not possible in the first or second trimester. In contrast, at the time of birth, fetal drug exposure, relative to maternal exposure, can be estimated as Kp,uu (unbound fetal umbilical venous (UV) plasma area under the curve (AUC)/unbound maternal plasma (MP) AUC), provided the observed UV/MP values, spanning the dosing interval, are available from multiple maternal-fetal dyads. However, this fetal Kp,uu cannot be extrapolated to other drugs. To overcome the above limitations, we have used an efflux ratio-relative expression factor (ER-REF) approach to successfully predict the fetal Kp,uu of P-gp substrates. Because many drugs taken by pregnant people are also BCRP substrates, here, we extend this approach to drugs that are effluxed by both placental BCRP and P-gp or P-gp alone. To verify our predictions, we chose drugs for which UV/MP data were available at term: glyburide and imatinib (both BCRP and P-gp substrates) and nelfinavir (only P-gp substrate). First, the ER of the drugs was determined using Transwells and MDCKII cells expressing either BCRP or P-gp. Then, the ER was scaled using the proteomics-informed REF value to predict the fetal Kp,uu of the drug at term. The ER-REF predicted fetal Kp,uu of glyburide (0.43), imatinib (0.42), and nelfinavir (0.40) fell within two-fold of the corresponding in vivo fetal Kp,uu (0.44, 0.37, and 0.46, respectively). These data confirm that the ER-REF approach can successfully predict fetal drug exposure to BCRP/P-gp and P-gp substrates, at term.

The Impact of Inflammation on the In Vivo Activity of the Renal Transporters OAT1/3 in Pregnant Women Diagnosed with Acute Pyelonephritis.

Inflammation can regulate hepatic drug metabolism enzymes and transporters. The impact of inflammation on renal drug transporters remains to be elucidated. We aimed to quantify the effect of inflammation (caused by acute pyelonephritis) on the in vivo activity of renal OAT1/3, using the probe drug furosemide. Pregnant women (second or third trimester) received a single oral dose of furosemide 40 mg during acute pyelonephritis (Phase 1; n = 7) and after its resolution (Phase 2; n = 7; by treatment with intravenous cefuroxime 750 mg TID for 3-7 days), separated by 10 to 14 days. The IL-6, IFN-γ, TNF-α, MCP-1, and C-reactive protein plasma concentrations were higher in Phase I vs. Phase II. The pregnant women had a lower geometric mean [CV%] furosemide CLsecretion (3.9 [43.4] vs. 6.7 [43.8] L/h) and formation clearance to the glucuronide (1.1 [85.9] vs. 2.3 [64.1] L/h) in Phase 1 vs. Phase 2. Inflammation reduced the in vivo activity of renal OAT1/3 (mediating furosemide CLsecretion) and UGT1A9/1A1 (mediating the formation of furosemide glucuronide) by approximately 40% and 54%, respectively, presumably by elevating the plasma cytokine concentrations. The dosing regimens of narrow therapeutic window OAT drug substrates may need to be adjusted during inflammatory conditions.

Interpretation of Protein-Mediated Uptake of Statins by Hepatocytes Is Confounded by the Residual Statin-Protein Complex.

Inclusion of plasma (or plasma proteins) in human hepatocyte uptake studies narrows, but does not close, the gap in in vitro to in vivo extrapolation (IVIVE) of organic anion transporting polypeptide (OATP)-mediated hepatic clearance (CLh) of statins. We have previously shown that this "apparent" protein-mediated uptake effect (PMUE) of statins by OATP1B1-expressing cells, in the presence of 5% human serum albumin (HSA), is mostly an artifact caused by residual statin-HSA complex remaining in the uptake assay. We determined if the same was true with plated human hepatocytes (PHH) and if this artifact can be reduced using suspended human hepatocytes (SHH) and the oil-spin method. We quantified the uptake of a cocktail of five statins by PHH and SHH in the absence and presence of 5% HSA. After terminating the uptake assay, the amount of residual HSA was quantified by quantitative targeted proteomics. For both PHH and SHH, except for atorvastatin and cerivastatin, the increase in total, active, and passive uptake of the statins, in the presence of 5% HSA, was explained by the estimated residual stain-HSA complex. In addition, the increase in active statin uptake by SHH, where present, was marginal (<50%), much smaller than that observed with PHH. Such a marginal increase cannot bridge the gap in IVIVE of CLh of statins. These data disprove the prevailing hypotheses for the in vitro PMUE. A true PMUE should be evaluated using the uptake data corrected for the residual drug-protein complex. SIGNIFICANCE STATEMENT: We show that the apparent protein-mediated uptake (PMUE) of statins by human hepatocytes is largely confounded by residual statin when plated or suspended human hepatocytes are used. Therefore, mechanisms other than PMUE need to be explored to explain the underprediction of the in vivo human hepatic clearance of statins by human hepatocyte uptake assays.

Understanding the Mechanism and Extent of Transplacental Transfer of (-)-∆9 -Tetrahydrocannabinol (THC) in the Perfused Human Placenta to Predict In Vivo Fetal THC Exposure.

Cannabis use during pregnancy may cause fetal toxicity driven by in utero exposure to (-)-∆9 -tetrahydrocannabinol (THC) and its psychoactive metabolite, (±)-11-hydroxy-∆9 -THC (11-OH-THC). THC concentrations in the human term fetal plasma appear to be lower than the corresponding maternal concentrations. Therefore, we investigated whether THC and its metabolites are effluxed by placental transporters using the dual cotyledon, dual perfusion, term human placenta. The perfusates contained THC alone (5 µM) or in combination (100-250 nM) with its metabolites (100 nM or 250 nM 11-OH-THC, 100 nM COOH-THC), plus a marker of P-glycoprotein (P-gp) efflux (1 or 10 µM saquinavir), and a passive diffusion marker (106 µM antipyrine). All perfusions were conducted with (n = 7) or without (n = 16) a P-gp/BCRP (breast-cancer resistance protein) inhibitor, 4 µM valspodar. The maternal-fetal and fetal-maternal unbound cotyledon clearance indexes (m-f-CLu,c,i and f-m-CLu,c,i ) were normalized for transplacental antipyrine clearance. At 5 µM THC, the m-f-CLu,c,i , 5.1 ± 2.1, was significantly lower than the f-m-CLu,c,i , 13 ± 6.1 (P = 0.004). This difference remained in the presence of valspodar or when the lower THC concentrations were perfused. In contrast, neither metabolite, 11-OH-THC/COOH-THC, had significantly different m-f-CLu,c,i vs. f-m-CLu,c,i . Therefore, THC appears to be effluxed by placental transporter(s) not inhibitable by the P-gp/BCRP antagonist, valspodar, while 11-OH-THC and COOH-THC appear to passively diffuse across the placenta. These findings plus our previously quantified human fetal liver clearance, extrapolated to in vivo, yielded a THC fetal/maternal steady-state plasma concentration ratio of 0.28 ± 0.09, comparable to that observed in vivo, 0.26 ± 0.10.

Increased renal elimination of endogenous and synthetic pyrimidine nucleosides in concentrative nucleoside transporter 1 deficient mice.

Concentrative nucleoside transporters (CNTs) are active nucleoside influx systems, but their in vivo roles are poorly defined. By generating CNT1 knockout (KO) mice, here we identify a role of CNT1 in the renal reabsorption of nucleosides. Deletion of CNT1 in mice increases the urinary excretion of endogenous pyrimidine nucleosides with compensatory alterations in purine nucleoside metabolism. In addition, CNT1 KO mice exhibits high urinary excretion of the nucleoside analog gemcitabine (dFdC), which results in poor tumor growth control in CNT1 KO mice harboring syngeneic pancreatic tumors. Interestingly, increasing the dFdC dose to attain an area under the concentration-time curve level equivalent to that achieved by wild-type (WT) mice rescues antitumor efficacy. The findings provide new insights into how CNT1 regulates reabsorption of endogenous and synthetic nucleosides in murine kidneys and suggest that the functional status of CNTs may account for the optimal action of pyrimidine nucleoside analog therapeutics in humans.

Evaluation of Cytochrome P450-Mediated Cannabinoid-Drug Interactions in Healthy Adult Participants.

Understanding cannabis-drug interactions is critical given regulatory changes that have increased access to and use of cannabis. Cannabidiol (CBD) and Δ-9-tetrahydrocannabinol (Δ9-THC), the most abundant phytocannabinoids, are in vitro reversible and time-dependent (CBD only) inhibitors of several cytochrome P450 (CYP) enzymes. Cannabis extracts were used to evaluate quantitatively potential pharmacokinetic cannabinoid-drug interactions in 18 healthy adults. Participant received, in a randomized cross-over manner (separated by ≥ 1 week), a brownie containing (i) no cannabis extract (ethanol/placebo), (ii) CBD-dominant cannabis extract (640 mg CBD + 20 mg Δ9-THC), or (iii) Δ9-THC-dominant cannabis extract (20 mg Δ9-THC and no CBD). After 30 minutes, participants consumed a cytochrome P450 (CYP) drug cocktail consisting of caffeine (CYP1A2), losartan (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and midazolam (CYP3A). Plasma and urine samples were collected (0-24 hours). The CBD + Δ9-THC brownie inhibited CYP2C19 > CYP2C9 > CYP3A > CYP1A2 (but not CYP2D6) activity, as evidenced by an increase in the geometric mean ratio of probe drug area under the plasma concentration-time curve (AUC) relative to placebo (AUCGMR ) of omeprazole, losartan, midazolam, and caffeine by 207%, 77%, 56%, and 39%, respectively. In contrast, the Δ9-THC brownie did not inhibit any of the CYPs. The CBD + Δ9-THC brownie increased Δ9-THC AUCGMR by 161%, consistent with CBD inhibiting CYP2C9-mediated oral Δ9-THC clearance. Except for caffeine, these interactions were well-predicted by our physiologically-based pharmacokinetic model (within 26% of observed interactions). Results can be used to help guide dose adjustment of drugs co-consumed with cannabis products and the dose of CBD in cannabis products to reduce interaction risk with Δ9-THC.

A Physiologically-Based Pharmacokinetic Model for Cannabidiol in Healthy Adults, Hepatically-Impaired Adults, and Children.

Cannabidiol (CBD) is available as a prescription oral drug that is indicated for the treatment of some types of epilepsy in children and adults. CBD is also available over-the-counter and is used to self-treat a variety of other ailments, including pain, anxiety, and insomnia. Accordingly, CBD may be consumed with other medications, resulting in possible CBD-drug interactions. Such interactions can be predicted in healthy and hepatically-impaired (HI) adults and in children through physiologically based pharmacokinetic (PBPK) modeling and simulation. These PBPK models must be populated with CBD-specific parameters, including the enzymes that metabolize CBD in adults. In vitro reaction phenotyping experiments showed that UDP-glucuronosyltransferases (UGTs, 80%), particularly UGT2B7 (64%), were the major contributors to CBD metabolism in adult human liver microsomes. Among the cytochrome P450s (CYPs) tested, CYP2C19 (5.7%) and CYP3A (6.5%) were the major CYPs responsible for CBD metabolism. Using these and other physicochemical parameters, a CBD PBPK model was developed and validated for healthy adults. This model was then extended to predict CBD systemic exposure in HI adults and children. Our PBPK model successfully predicted CBD systemic exposure in both populations within 0.5- to 2-fold of the observed values. In conclusion, we developed and validated a PBPK model to predict CBD systemic exposure in healthy and HI adults and children. This model can be used to predict CBD-drug or CBD-drug-disease interactions in these populations. SIGNIFICANCE STATEMENT: Our PBPK model successfully predicted CBD systemic exposure in healthy and hepatically-impaired adults, as well as children with epilepsy. This model could be used in the future to predict CBD-drug or CBD-drug-disease interactions in these special populations.

Assessment of Orally Administered Δ9-Tetrahydrocannabinol When Coadministered With Cannabidiol on Δ9-Tetrahydrocannabinol Pharmacokinetics and Pharmacodynamics in Healthy Adults: A Randomized Clinical Trial.

Importance: Controlled clinical laboratory studies have shown that cannabidiol (CBD) can sometimes attenuate or exacerbate the effects of Δ9-tetrahydrocannabinol (Δ9-THC). No studies have evaluated differences in pharmacokinetics (PK) of Δ9-THC and pharmacodynamics (PD) between orally administered cannabis extracts that vary with respect to Δ9-THC and CBD concentrations. Objective: To compare the PK and PD of orally administered Δ9-THC-dominant and CBD-dominant cannabis extracts that contained the same Δ9-THC dose (20 mg). Design, Setting, and Participants: This randomized clinical trial was a within-participant, double-blind, crossover study conducted from January 2021 to March 2022 at the Johns Hopkins University Behavioral Pharmacology Research Unit, Baltimore, MD. Eighteen healthy adults completed 3 randomized outpatient experimental test sessions that were each separated by at least 1 week. Interventions: Brownies containing (1) no cannabis extract (ie, placebo); (2) Δ9-THC-dominant extract (20 mg Δ9-THC with no CBD); and (3) CBD-dominant extract (20 mg Δ9-THC + 640 mg CBD) were administered to participants 30 minutes prior to administering a cytochrome P450 (CYP) probe drug cocktail, which consisted of 100 mg caffeine, 20 mg omeprazole, 25 mg losartan, 30 mg dextromethorphan, and 2 mg midazolam. Main Outcomes and Measures: Change-from-baseline plasma concentrations for Δ9-THC or Δ9-THC metabolites and scores for subjective drug effects, cognitive and psychomotor performance, and vital signs. The area under the plasma vs concentration vs time curve (AUC) and maximum plasma concentration (Cmax) were determined. Results: The participant cohort of 18 adults included 11 males (61.1%) and 7 females (38.9%) with a mean (SD) age of 30 (7) years who had not used cannabis for at least 30 days prior to initiation of the study (mean [SD] day since last cannabis use, 86 [66] days). The CYP cocktail + placebo brownie and the CYP cocktail did not affect any PD assessments. Relative to CYP cocktail + Δ9-THC, CYP cocktail + Δ9-THC + CBD produced a higher Cmax and area under the plasma concentration vs time curve for Δ9-THC, 11-OH-Δ9-THC, and Δ9-THC-COOH. The CYP cocktail + Δ9-THC + CBD increased self-reported anxiety, sedation, and memory difficulty, increased heart rate, and produced a more pronounced impairment of cognitive and psychomotor performance compared with both CYP cocktail + Δ9-THC and CYP cocktail + placebo. Conclusions and Relevance: In this randomized clinical trial of oral Δ9-THC and CBD, stronger adverse effects were elicited from a CBD-dominant cannabis extract compared with a Δ9-THC-dominant cannabis extract at the same Δ9-THC dose, which contradicts common claims that CBD attenuates the adverse effects of Δ9-THC. CBD inhibition of Δ9-THC and 11-OH-Δ9-THC metabolism is the likely mechanism for the differences observed. An improved understanding of cannabinoid-cannabinoid and cannabinoid-drug interactions are needed to inform clinical and regulatory decision-making regarding the therapeutic and nontherapeutic use of cannabis products. Trial Registration: clinicaltrials.gov Identifier: NCT04201197.

Predicting changes in the pharmacokinetics of CYP3A-metabolized drugs in hepatic impairment and insights into factors driving these changes.

Physiologically based pharmacokinetic models, populated with drug-metabolizing enzyme and transporter (DMET) abundance, can be used to predict the impact of hepatic impairment (HI) on the pharmacokinetics (PK) of drugs. To increase confidence in the predictive power of such models, they must be validated by comparing the predicted and observed PK of drugs in HI obtained by phenotyping (or probe drug) studies. Therefore, we first predicted the effect of all stages of HI (mild to severe) on the PK of drugs primarily metabolized by cytochrome P450 (CYP) 3A enzymes using the default HI module of Simcyp Version 21, populated with hepatic and intestinal CYP3A abundance data. Then, we validated the predictions using CYP3A probe drug phenotyping studies conducted in HI. Seven CYP3A substrates, metabolized primarily via CYP3A (fraction metabolized, 0.7-0.95), with low to high hepatic availability, were studied. For all stages of HI, the predicted PK parameters of drugs were within twofold of the observed data. This successful validation increases confidence in using the DMET abundance data in HI to predict the changes in the PK of drugs cleared by DMET for which phenotyping studies in HI are not available or cannot be conducted. In addition, using CYP3A drugs as an example, through simulations, we identified the salient PK factors that drive the major changes in exposure (area under the plasma concentration-time profile curve) to drugs in HI. This theoretical framework can be applied to any drug and DMET to quickly determine the likely magnitude of change in drug PK due to HI.

Maternal and Fetal Exposure to (-)-Δ9-tetrahydrocannabinol and Its Major Metabolites in Pregnant Mice Is Differentially Impacted by P-glycoprotein and Breast Cancer Resistance Protein.

(-)-Δ9-tetrahydrocannabinol (THC) is the primary pharmacological active constituent of cannabis. 11-hydroxy-THC (11-OH-THC) and 11-nor-9-carboxy-THC (THC-COOH) are respectively the active and nonactive circulating metabolites of THC in humans. While previous animal studies reported that THC could be a substrate of mouse P-glycoprotein (P-gp) and breast cancer resistance protein (Bcrp), we have shown, in vitro, that only THC-COOH is a weak substrate of human BCRP, but not of P-gp. To confirm these findings and to investigate the role of P-gp and/or Bcrp in the maternal-fetal disposition of THC and its metabolites, we administrated 3 mg/kg of THC retro-orbitally to FVB wild-type (WT), P-gp -/-, Bcrp -/-, or P-gp-/- /Bcrp-/- pregnant mice on gestation day 18 and estimated the area under the concentration-time curve (AUC) of the cannabinoids in the maternal plasma, maternal brain, placenta, and fetus, as well as the tissue/maternal plasma AUC geometric mean ratios (GMRs) using a pooled data bootstrap approach. We found that the dose-normalized maternal plasma AUCs of THC in P-gp-/- and P-gp-/- /Bcrp-/- mice, and the placenta-to-maternal plasma AUC GMR of THC in Bcrp-/- mice were 279%, 271%, and 167% of those in WT mice, respectively. Surprisingly, the tissue-to-maternal plasma AUC GMRs of THC and its major metabolites in the maternal brain, placenta, or fetus in P-gp -/-, Bcrp -/- or P-gp-/- /Bcrp-/- mice were 28-78% of those in WT mice. This study revealed that P-gp and Bcrp do not play a role in limiting maternal brain and fetal exposure to THC and its major metabolites in pregnant mice. SIGNIFICANCE STATEMENT: This study systematically investigated whether P-gp and/or Bcrp in pregnant mice can alter the disposition of THC, 11-OH-THC, and THC-COOH. Surprisingly, except for Bcrp, which limits placental (but not fetal) exposure to THC, we found that P-gp-/- , Bcrp-/- , and/or P-gp-/- /Bcrp-/- significantly decreased exposure to THC and/or its metabolites in maternal brain, placenta, or fetus. The mechanistic basis for this decrease is unclear and needs further investigation. If replicated in humans, P-gp- or BCRP-based drug-cannabinoid interactions are not of concern.

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

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.

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

Predicting transporter-based drug clearance (CL) and tissue concentrations (TC) in humans is important to reduce the risk of failure during drug development. In addition, when transporters are present at the tissue:blood interface (e.g., in the liver, blood-brain barrier), predicting TC is important to predict the drug's efficacy and safety. With the advent of quantitative targeted proteomics, in vitro to in vivo extrapolation (IVIVE) of transporter-based drug CL and TC is now possible using transporter-expressing models (cells lines, membrane vesicles) and the in vivo to in vitro relative expression of transporters (REF) as a scaling factor. Unlike other approaches based on physiological scaling, the REF approach is not dependent on the availability of primary cells. Here, we review the REF approach and compare it with other IVIVE approaches such as the relative activity factor approach and physiological scaling. For each of these scaling approaches, we review their underlying principles, assumptions, methodology, predictive performance, as well as advantages and limitations. Finally, we discuss current gaps in IVIVE of transporter-based CL and TC and propose possible reasons for these gaps as well as areas to investigate to bridge these gaps.

Applications, Challenges, and Outlook for PBPK Modeling and Simulation: A Regulatory, Industrial and Academic Perspective.

Several regulatory guidances on the use of physiologically based pharmacokinetic (PBPK) analyses and physiologically based biopharmaceutics model(s) (PBBM(s)) have been issued. Workshops are routinely held, demonstrating substantial interest in applying these modeling approaches to address scientific questions in drug development. PBPK models and PBBMs have remarkably contributed to model-informed drug development (MIDD) such as anticipating clinical PK outcomes affected by extrinsic and intrinsic factors in general and specific populations. In this review, we proposed practical considerations for a "base" PBPK model construction and development, summarized current status, challenges including model validation and gaps in system models, and future perspectives in PBPK evaluation to assess a) drug metabolizing enzyme(s)- or drug transporter(s)- mediated drug-drug interactions b) dosing regimen prediction, sampling timepoint selection and dose validation in pediatric patients from newborns to adolescents, c) drug exposure in patients with renal and/or and hepatic organ impairment, d) maternal-fetal drug disposition during pregnancy, and e) pH-mediated drug-drug interactions in patients treated with proton pump inhibitors/acid-reducing agents (PPIs/ARAs) intended for gastric protection. Since PBPK can simulate outcomes in clinical studies with enrollment challenges or ethical issues, the impact of PBPK models on waivers and how to strengthen study waiver is discussed.

Characterizing and Quantifying Extrahepatic Metabolism of (-)-Δ9-Tetrahydrocannabinol (THC) and Its Psychoactive Metabolite, (±)-11-Hydroxy-Δ9-THC (11-OH-THC).

(-)-Δ9-Tetrahydrocannabinol (THC) is the psychoactive constituent of cannabis, a drug recreationally consumed orally or by inhalation. Physiologically based pharmacokinetic (PBPK) modeling can be used to predict systemic and tissue exposure to THC and its psychoactive metabolite, (±)-11-hydroxy-Δ9-THC (11-OH-THC). To populate a THC/11-OH-THC PBPK model, we previously characterized the depletion clearance of THC (by CYP2C9) and 11-OH-THC (by UDP-glucuronosyltransferase (UGT), CYP3A, and CYP2C9) in adult human liver microsomes. Here we focused on quantifying extrahepatic depletion clearance of THC/11-OH-THC, important after oral (intestine) and inhalational (lung) consumption of THC as well as prenatal THC use (placenta and fetal liver). THC (500 nM) was metabolized in adult human intestinal microsomes (n = 3-5) by CYP2C9 [Vmax: 1.1 ± 0.38 nmol/min/mg; Michaelis-Menten constant (Km): 70 nM; intrinsic clearance (CLint): 15 ± 5.4 ml/min/mg; fraction metabolized (fm): 0.89 ± 0.31 at concentration ≪ 70 nM] and CYP3A (CLint: 2.0 ± 0.86 ml/min/mg; fm: 0.11 ± 0.050). 11-OH-THC (50 nM) was metabolized by CYP3A (CLint: 0.26 ± 0.058 ml/min/mg; fm: 0.51 ± 0.11) and UGT2B7 (CLint: 0.13 ± 0.027 ml/min/mg; fm: 0.25 ± 0.053). THC at 500 nM (CLint: 4.7 ± 0.22 ml/min/mg) and 11-OH-THC at 50 nM (CLint: 2.4 ± 0.13 ml/min/mg) were predominately (fm: 0.99 and 0.80, respectively) metabolized by CYP3A in human fetal liver microsomes (n = 3). However, we did not observe significant depletion of THC/11-OH-THC in adult lung, first trimester, second trimester, or term placentae microsomes. Using PBPK modeling and simulation, these data could be used in the future to predict systemic and tissue THC/11-OH-THC exposure in healthy and special populations. SIGNIFICANCE STATEMENT: This is the first characterization and quantification of (-)-Δ9-tetrahydrocannabinol (THC) and (±)-11-hydroxy-Δ9-THC (11-OH-THC) depletion clearance by cytochrome P450 and UDP-glucuronosyltransferase enzymes in extrahepatic human tissues: intestine, fetal liver, lung, and placenta. These data can be used to predict, through physiologically based pharmacokinetic modeling and simulation, systemic and tissue THC/11-OH-THC exposure after inhalational and oral THC use in both healthy and special populations (e.g., pregnant women).

Is the Protein-Mediated Uptake of Drugs by Organic Anion Transporting Polypeptides a Real Phenomenon or an Artifact?

Plasma proteins or human serum albumin (HSA) have been reported to increase the in vitro intrinsic uptake clearance (CLint,uptake) of drugs by hepatocytes or organic anion transporting polypeptide (OATP)-transfected cell lines. This so-called protein-mediated uptake effect (PMUE) is thought to be due to an interaction between the drug-protein complex and the cell membrane causing an increase in the unbound drug concentration at the cell surface, resulting in an increase in the apparent CLint,uptake of the drug. To determine if the PMUE on OATP-mediated drug uptake is an artifact or a real phenomenon, we determined the effect of 1%, 2%, and 5% HSA on OATP1B1-mediated [human embryonic kidney (HEK)293 transfected cells] and passive CLint,uptake (mock HEK293 cells) on a cocktail of five statins. In addition, we determined the non-specific binding (NSB) of the statin-HSA complex to the cells/labware. The increase in uptake of atorvastatin, fluvastatin, and rosuvastatin in the presence of HSA was completely explained by the extent of NSB of the statin-HSA complex, indicating that the PMUE for these statins is an artifact. In contrast, this was not the case for OATP1B1-mediated uptake of pitavastatin and passive uptake of cerivastatin, suggesting that the PMUE is a real phenomenon for these drugs. Additionally, the PMUE on OATP1B1-mediated uptake of pitavastatin was confirmed by a decrease in its unbound IC50 in the presence of 5% HSA versus Hank's balanced salt solution buffer (HBSS). These data question the utility of routinely including plasma proteins or HSA in uptake experiments and the previous findings on PMUE on OATP-mediated drug uptake. SIGNIFICANCE STATEMENT: Here we report, for the first time, that the protein-mediated uptake effect (PMUE) on organic anion transporting polypeptide (OATP)-transported drugs could be an artifact of the non-specific binding (NSB) of the drug-albumin complex to cells/labware. Future experiments on PMUE must take into consideration such NSB. In addition, mechanisms other than PMUE need to be explored to explain the underprediction of in vivo OATP-mediated hepatic drug clearance from in vitro uptake studies.

Predicting Regional Respiratory Tissue and Systemic Concentrations of Orally Inhaled Drugs through a Novel PBPK Model.

Oral inhalation (OI) of drugs is the route of choice to treat respiratory diseases or for recreational drug use (e.g., cannabis). After OI, the drug is deposited in and systemically absorbed from various regions of the respiratory tract. Measuring regional respiratory tissue drug concentrations at the site of action is important for evaluating the efficacy and safety of orally inhaled drugs (OIDs). Because such a measurement is routinely not possible in humans, the only alternative is to predict these concentrations, for example by physiologically based pharmacokinetic (PBPK) modeling. Therefore, we developed an OI-PBPK model to integrate the interplay between regional respiratory drug deposition and systemic absorption to predict regional respiratory tissue and systemic drug concentrations. We validated our OI-PBPK model by comparing the simulated and observed plasma concentration-time profiles of two OIDs, morphine and nicotine. Furthermore, we performed sensitivity analyses to quantitatively demonstrate the impact of key parameters on the extent and pattern of regional respiratory drug deposition, absorption, and the resulting regional respiratory tissue and systemic plasma concentrations. Our OI-PBPK model can be applied to predict regional respiratory tissue and systemic drug concentrations to optimize OID formulations, delivery systems, and dosing regimens. Furthermore, our model could be used to establish the bioequivalence of generic OIDs for which systemic plasma concentrations are not measurable or are not a good surrogate of the respiratory tissue drug concentrations. SIGNIFICANCE STATEMENT: Our OI-PBPK model is the first comprehensive model to predict regional respiratory deposition, as well as systemic and regional tissue concentrations of OIDs, especially at the drug's site of action, which is difficult to measure in humans. This model will help optimize OID formulations, delivery systems, dosing regimens, and bioequivalence assessment of generic OID. Furthermore, this model can be linked with organs-on-chips, pharmacodynamic and quantitative systems pharmacology models to predict and evaluate the safety and efficacy of OID.