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The fraction of drug transported (ft) into or out of a tissue is a concept useful to understand the impact of transporters on absorption, distribution, metabolism, and excretion (ADME) and tissue distribution of a drug. Here, ft is utilized to explain the impact of transporters on central nervous system (CNS) distribution of drugs, drug interactions (DDI), and to predict the unbound brain concentration (Cu,b) of the drug. The latter is important to ascertain if Cu,b is sufficient for efficacy. [ABSTRACT FROM AUTHOR]

Background and Purpose: Changes in tissue P-glycoprotein (P-gp) activity during pregnancy could affect the pharmacokinetics and thus the efficacy and toxicity of many drugs. Therefore, using positron emission tomography (PET) imaging, we tested whether gestational age affects tissue P-gp activity in the pregnant non-human primate, Macaca nemestrina.Experimental Approach: Mid-gestational (day 75 +/- 13, n= 7) and late-gestational (day 150 +/- 10, n= 5) age macaques were imaged after administration of a prototypic P-gp substrate, (11)C-verapamil (13.7-75.4 MBq.kg(-1)), before and during intravenous infusion of a P-gp inhibitor, cyclosporin A (CsA) (12 or 24 mg.kg(-1).h(-1)). Accumulation of radioactivity in the fetal liver served as a reporter of placental P-gp activity. P-gp activity was expressed as CsA-induced percent change in the ratio of the area (0-9 min) under the (11)C-radioactivity concentration-time curve in the tissue (AUC(tissue)) to that in the maternal plasma (AUC(plasma)).Key Results: The CsA-induced change in AUC(fetal liver)/AUC(maternal)(plasma) of (11)C-radioactivity significantly increased from mid- (35 +/- 25%) to late gestation (125 +/- 66%). Likewise, the CsA-induced change in AUC(maternal brain)/AUC(plasma) increased from mid- (172 +/- 80%) to late gestation (337 +/- 148%). The AUC ratio for the other maternal tissues was not significantly affected. Neither the CsA blood concentrations nor the level of circulating (11)C-verapamil metabolites were significantly affected by gestational age.Conclusions and Implications: P-gp activity at the blood-brain barrier and the placental barrier in the macaque increased with gestational age. If replicated in humans, the exposure of the fetus and maternal brain to P-gp substrate drugs, and therefore their efficacy and toxicity, will change during pregnancy. [ABSTRACT FROM AUTHOR]

Digoxin and midazolam are routinely used as probe drugs to measure in vivo activity of P-glycoprotein (P-gp) and cytochrome P450 3A4/5 (CYP3A), respectively. We investigated whether digoxin and midazolam could be coadministered to simultaneously determine P-gp and CYP3A activity without a significant pharmacokinetic interaction. In a randomized crossover design, digoxin (0.5 mg oral) or midazolam (2.0 mg oral) was administered individually or in combination (digoxin 1 hour after midazolam) to 14 healthy volunteers. Blood and urine samples were collected for up to 48 hours. Pharmacokinetic parameters of digoxin, midazolam and 1'-OH midazolam were evaluated to determine the presence of an interaction. The geometric mean ratios of all measured pharmacokinetic parameters of digoxin and midazolam were not significantly affected by coadministration. Coadministration of digoxin and midazolam can be used to simultaneously phenotype P-gp and CYP3A activity without a significant pharmacokinetic interaction. [ABSTRACT FROM AUTHOR]

1 Two methods of estimating the average plasma drug concentration at plateau Cav are considered. 2 Given an acceptable error in the estimate of Cav, a range of sampling times, rather than a single time, during the dosing interval, can be calculated. This range depends on the variability of the half-life within the patient population, the dosing interval, the error in assay measurement and the therapeutic index of the drug. 3 When the minimum plasma drug concentration is monitored, an estimate of the individual's half-life is needed, unless the dosing interval is short. Then the population half-life may be used to obtain a reasonable estimate of Cav. [ABSTRACT FROM AUTHOR]

Proinflammatory cytokines, elevated during inflammation caused by infection and/or autoimmune disorders, result in reduced clearance of drugs eliminated primarily by cytochrome P450 enzymes (CYPs). However, the effect of cytokines on hepatic drug transporter expression or activity has not been well-studied. Here, using plated human hepatocytes (PHHs; n = 3 lots), we investigated the effect of interleukin (IL)-6, IL-1 β , tumor necrosis factor- α (TNF- α ), and interferon-γ (IFN-γ), on the mRNA expression and activity of hepatic drug transporters. PHHs were incubated for 72 hours at their pathophysiologically relevant plasma concentrations, both individually (0.01, 0.1, 1, 10 ng/ml) or as a cocktail (i.e., when each was combined at 0.1 or 1 ng/ml). Following cytokine cocktail exposure (1 ng/ml), significant downregulation of mRNA expression of organic anion transporting polypeptide 1B1 (OATP1B1), OATP1B3, sodium/taurocholate cotransporting polypeptide (NTCP), breast cancer resistance protein (BCRP), P-glycoprotein (P-gp), multidrug and toxin extrusion protein 1, multidrug resistance proteins (MRP) 2, 3, and 4 was observed. While the mRNA expression of organic anion transporter (OAT) 2 and organic cation transporter (OCT) 1 was downregulated in two lots, it was upregulated in one lot. In agreement (mostly), the 1 ng/ml cytokine cocktail reduced OATP1B1/3, OATP2B1, OAT2, OCT1, and NTCP activity by 75%, 44%, 82%, 47%, and 80%, respectively. Interestingly, upregulation of OAT2 and OCT1 mRNA in one donor did not translate into the same directional change in activity. Although significant interlot variability was observed, in general, the above effects, using individual cytokines, could be attributed to IL-1 β , TNF- α , and IFN-γ. SIGNIFICANCE STATEMENT: To date, this is the first comprehensive study to investigate the effect of four major proinflammatory cytokines, both individually and as a cocktail, on the mRNA expression and activity of human hepatic drug transporters. The data obtained can be used in the future to predict transporter-mediated drug clearance changes during inflammation through physiologically based pharmacokinetic modeling and simulation., (Copyright © 2024 by The American Society for Pharmacology and Experimental Therapeutics.)

Introduction: Pregnancy results in significant changes in drug pharmacokinetics (PK). While previous studies have elucidated the impact of pregnancy-related hormones (PRH) on mRNA or protein expression and activity of major hepatic metabolizing enzymes, their effect on hepatic drug transporters remains largely unexplored. Therefore, we investigated the effect of a cocktail of PRH on the mRNA expression and activity of hepatic transporters., Methods: Plated human hepatocytes (PHH) from 3 premenopausal donors were incubated, in triplicate, for 72 h, with vehicle (DMSO < 0.01%), rifampin (10 μM; positive control) or a cocktail of PRH consisting of estrone, estradiol, estriol, estetrol, progesterone, cortisol, testosterone, oxytocin, and placental growth hormone. The PRH concentrations replicated 0.1×, 1×, or 10× of the plasma concentrations of these hormones observed during each of the three trimesters of pregnancy. After treatment, mRNA expression (quantified by qPCR) of hepatic influx and efflux transporters as well as the activity of influx transporters was quantified (uptake of a selective substrate ± corresponding transporter inhibitor). The data were expressed relative to that in the control (vehicle) group. Significance was evaluated by ANOVA (followed by Dunn's multiple comparisons) or unpaired t -test when the within-lot data were analyzed, or repeated measures ANOVA (followed by Dunn's multiple comparisons) or paired t -test when data from all 3 lots were analyzed ( p < 0.05)., Results and Discussion: In general, a) PRH cocktails significantly induced transporter mRNA expression in the following order OAT2 ≈ NTCP ≈ OCT1 > OATP2B1 and repressed mRNA expression in the following order OATP1B3 > OATP1B1; b) these changes translated into significant induction of OAT2 (T1-T3) and NTCP (T2-T3, in only two lots) activity at the 1× PRH concentration. Compared with the influx transporters, the induction of mRNA expression of efflux transporters was modest, with mRNA expression of MRP2 and BSEP being induced the most., Conclusion: Once these data are verified through in vivo probe drug PK studies in pregnancy, they can be populated into physiologically based pharmacokinetic (PBPK) models to predict, for all trimesters of pregnancy, transporter-mediated clearance of any drug that is a substrate of the affected transporters., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Benzi, Tsang and Unadkat.)

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 K p,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 K p,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 K p,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 K p,uu of the drug at term. The ER-REF predicted fetal K p,uu of glyburide (0.43), imatinib (0.42), and nelfinavir (0.40) fell within two-fold of the corresponding in vivo fetal K p,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., (© 2023 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

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 (C max )), 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., (© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

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-1β, 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-1β 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.

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 (AUCR HI ). Using physiologically-based pharmacokinetic modeling and simulation, we predicted relatively well the AUCR HI of OATP substrates that are not significantly metabolized (pitavastatin, rosuvastatin, valsartan, and gadoxetic acid). However, there was a trend toward underprediction of the AUCR HI 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., (© 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

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 CL secretion ) 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.

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 (CL h ) 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 CL h 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., (Copyright © 2023 by The American Society for Pharmacology and Experimental Therapeutics.)

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 (AUC GMR ) 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 AUC GMR 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., (© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

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-CL u,c,i and f-m-CL u,c,i ) were normalized for transplacental antipyrine clearance. At 5 μM THC, the m-f-CL u,c,i , 5.1 ± 2.1, was significantly lower than the f-m-CL u,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-CL u,c,i vs. f-m-CL u,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., (© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

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., (Copyright © 2023 by The American Society for Pharmacology and Experimental Therapeutics.)

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., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

(-)-Δ 9 -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., (Copyright © 2023 by The American Society for Pharmacology and Experimental Therapeutics.)

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., (© 2022 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

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 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., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest. R.E., P.P.C., O.J.E., X.L., and Y.L. are all employees of their respective companies and hold stock or stock options in the company., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Plasma proteins or human serum albumin (HSA) have been reported to increase the in vitro intrinsic uptake clearance (CL int,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 CL int,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 CL int,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 IC 50 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., (Copyright © 2022 by The American Society for Pharmacology and Experimental Therapeutics.)

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, K p,uu ). Second, the maximum unbound peak (C u,max,ss,f ) and trough (C u,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., (© 2022, The American College of Clinical Pharmacology.)

To assess efficacy and toxicity of a drug in humans, it is important to measure the tissue concentration of a drug at the target site. For a drug that is transported into or out of the tissue, the tissue unbound steady-state concentration can be dramatically different from its corresponding unbound steady-state plasma concentration. Because routine measurement of drug tissue concentrations is not possible, using rosuvastatin as a model transporter substrate drug, we compared the ability of the proteomics-informed relative expression factor (REF) approach and sandwich-cultured human hepatocytes (SCH) to accurately predict rosuvastatin human hepatobiliary clearances and hepatic concentrations. REF-predicted rosuvastatin biliary clearance (CL bile ), estimated using BCRP-overexpressing, MDR1-overexpressing, and MRP2-overexpressing vesicles, together with our previously published REF-predicted rosuvastatin hepatic sinusoidal uptake clearance (CL uptake ) and physiologically scaled sinusoidal passive uptake and efflux clearance (CL s,efflux ), were used to predict rosuvastatin hepatic concentrations. For SCH, the estimated rosuvastatin CL bile , CL uptake , and CL s,efflux were scaled using physiological scaling. The REF-predicted CL bile (6.39 ± 1.56 mL/minute) and hepatic rosuvastatin area under the concentration-time curve (AUC) fell within our a priori defined success criterion, i.e., within twofold of the observed positron emission tomography-imaged values. In contrast, as expected, SCH dramatically overpredicted (predicted/observed ratio P/O = 8.38-10.41) rosuvastatin CL bile , and underpredicted hepatic AUC (P/O = 0.08-0.14). For both approaches, predictions were improved by using the parallel tube model vs. well-stirred model. Overall, using rosuvastatin as a model drug, this study demonstrates the success of the REF approach in predicting in vivo CL bile and hepatic concentration of drugs, and highlights the shortcomings of the SCH approach in making such predictions., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

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., (© 2022. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

(-)-Δ 9 -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-Δ 9 -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 [V max : 1.1 ± 0.38 nmol/min/mg; Michaelis-Menten constant (K m ): 70 nM; intrinsic clearance (CL int ): 15 ± 5.4 ml/min/mg; fraction metabolized (fm): 0.89 ± 0.31 at concentration ≪ 70 nM] and CYP3A (CL int : 2.0 ± 0.86 ml/min/mg; fm: 0.11 ± 0.050). 11-OH-THC (50 nM) was metabolized by CYP3A (CL int : 0.26 ± 0.058 ml/min/mg; fm: 0.51 ± 0.11) and UGT2B7 (CL int : 0.13 ± 0.027 ml/min/mg; fm: 0.25 ± 0.053). THC at 500 nM (CL int : 4.7 ± 0.22 ml/min/mg) and 11-OH-THC at 50 nM (CL int : 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 (-)-Δ 9 -tetrahydrocannabinol (THC) and (±)-11-hydroxy-Δ 9 -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)., (Copyright © 2022 by The American Society for Pharmacology and Experimental Therapeutics.)

Pregnant women are frequently prescribed drugs to treat chronic diseases such as human immunodeficiency virus infection, but little is known about the benefits and risks of these drugs to the fetus that are driven by fetal drug exposure. The latter can be estimated by fetal-to-maternal unbound plasma concentration at steady state (K p,uu,fetal ). For drugs that are substrates of placental efflux transporters [i.e., P-glycoprotein (P-gp) or breast cancer resistance protein (BCRP)], K p,uu,fetal is expected to be <1. Here, we estimated the in vivo K p,uu,fetal of selective P-gp and BCRP substrate drugs by maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) modeling of umbilical vein (UV) plasma and maternal plasma (MP) concentrations obtained simultaneously at term from multiple maternal-fetal dyads. To do so, three drugs were selected: nelfinavir (P-gp substrate), efavirenz (BCRP substrate), and imatinib (P-gp/BCRP substrate). An m-f-PBPK model for each drug was developed and validated for the nonpregnant population and pregnant women using the Simcyp simulator (v20). Then, after incorporating placental passive diffusion clearance, the in vivo K p,uu,fetal of the drug was estimated by adjusting the placental efflux clearance until the predicted UV/MP values best matched the observed data (K p,uu,fetal ) of nelfinavir = 0.41, efavirenz = 0.39, and imatinib = 0.35. Furthermore, K p,uu,fetal of nelfinavir and efavirenz at gestational weeks (GWs) 25 and 15 were predicted to be 0.34 and 0.23 (GW25) and 0.33 and 0.27 (GW15). These K p,uu,fetal values can be used to adjust dosing regimens of these drugs to optimize maternal-fetal drug therapy throughout pregnancy, to assess fetal benefits and risks of these dosing regimens, and to determine if these estimated in vivo K p,uu,fetal values can be predicted from in vitro studies. SIGNIFICANCE STATEMENT: The in vivo fetal-to-maternal unbound steady-state plasma concentration ratio (K p,uu,fetal ) of nelfinavir [P-glycoprotein (P-gp) substrate], efavirenz [breast cancer resistance protein (BCRP) substrate], and imatinib (P-gp and BCRP substrate) was successfully estimated using maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) modeling. These K p,uu,fetal values can be used to adjust dosing regimens of these drugs to optimize maternal-fetal drug therapy throughout pregnancy, to assess fetal benefits and risks of these dosing regimens, and to determine if these estimated in vivo K p,uu,fetal values can be predicted from in vitro studies., (Copyright © 2022 The Author(s).)

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., (Copyright © 2022 by The American Society for Pharmacology and Experimental Therapeutics.)

We previously reported the unbound reversible (IC 50,u ) and time-dependent (K I,u ) inhibition potencies of cannabidiol (CBD), delta-9-tetrahydrocannabinol (THC), and THC metabolites 11-hydroxy THC (11-OH THC) and 11-nor-9-carboxy-delta-9-THC (11-COOH THC) against the major cytochrome P450 (P450) enzymes (1A2, 2C9, 2C19, 2D6, and 3A). Here, using human liver microsomes, we determined the CYP2A6, 2B6, and 2C8 IC 50,u values of the aforementioned cannabinoids and the IC 50,u and K I,u of the circulating CBD metabolites 7-hydroxy CBD (7-OH CBD) and 7-carboxy CBD (7-COOH CBD), against all the P450s listed above. The IC 50,u of CBD, 7-OH CBD, THC, and 11-OH THC against CYP2B6 was 0.05, 0.34, 0.40, and 0.32 μ M, respectively, and against CYP2C8 was 0.28, 1.02, 0.67, and 3.66 μ M, respectively. 7-COOH CBD, but not 11-COOH THC, was a weak inhibitor of CYP2B6 and 2C8. All tested cannabinoids except 11-COOH THC were weak inhibitors of CYP2A6. 7-OH CBD inhibited all P450s examined (IC 50,u <2.5 μ M) except CYP1A2 and inactivated CYP2C19 and CYP3A, with inactivation efficiencies (k inact /K I,u ) of 0.10 and 0.14 minutes -1 μ M -1 , respectively. Using several different static models, we predicted the following maximum pharmacokinetic interactions (affected P450 probe drug and area under the plasma concentration-time curve ratio) between oral CBD (700 mg) and drugs predominantly metabolized by CYP3A (midazolam, 14.8) > 2C9 (diclofenac, 9.6) > 2C19 (omeprazole, 7.3) > 1A2 (theophylline, 4.0) > 2B6 (ticlopidine, 2.2) > 2D6 (dextromethorphan, 2.1) > 2C8 (repaglinide, 1.6). Oral (130 mg) or inhaled (75 mg) THC was predicted to precipitate interactions with drugs predominately metabolized by CYP2C9 (diclofenac, 6.6 or 2.3, respectively) > 3A (midazolam, 1.8) > 1A2 (theophylline, 1.4). In vivo drug interaction studies are warranted to verify these predictions. SIGNIFICANCE STATEMENT: This study, combined with our previous findings, provides for the first time a comprehensive analysis of the potential for cannabidiol, delta-9-tetrahydrocannabinol, and their metabolites to inhibit cytochrome P450 enzymes in a reversible or time-dependent manner. These analyses enabled us to predict the potential of these cannabinoids to produce drug interactions in vivo at clinical or recreational doses., (Copyright © 2022 by The American Society for Pharmacology and Experimental Therapeutics.)

Pharmacokinetic drug interactions precipitated by botanical and other natural products (NPs) remain critically understudied. Investigating these complex interactions is fraught with difficulties due to the methodologic and technical challenges associated with the inherently complex chemistries and product variability of NPs. This knowledge gap is perpetuated by a continuing absence of a harmonized framework regarding the design of clinical pharmacokinetic studies of NPs and NP-drug interactions. Accordingly, this Recommended Approach, the fourth in a series of Recommended Approaches released by the Center of Excellence for Natural Product Drug Interaction Research (NaPDI Center), provides recommendations for the design of clinical pharmacokinetic studies involving NPs. Building on prior Recommended Approaches and data generated from the NaPDI Center, such a framework is presented for the design of (1) phase 0 studies to assess the pharmacokinetics of an NP and (2) clinical pharmacokinetic NP-drug interaction studies. Suggestions for NP sourcing, dosing, study design, participant selection, sampling periods, and data analysis are presented. With the intent to begin addressing the gap between regulatory agencies' guidance documents about drug-drug interactions and contemporary NPDI research, the objective of this Recommended Approach is to propose methods for the design of clinical pharmacokinetic studies of NPs and NP-drug interactions., (© 2021 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Pregnancy can significantly change the pharmacokinetics of drugs, including those renally secreted by organic anion transporters (OATs). Quantifying these changes in pregnant women is logistically and ethically challenging. Hence, predicting the in vivo plasma renal secretory clearance (CL sec ) and renal CL (CL renal ) of OAT drugs in pregnancy is important to design correct dosing regimens of OAT drugs. Here, we first quantified the fold-change in renal OAT activity in pregnant versus nonpregnant individual using available selective OAT probe drug CL renal data (training dataset; OAT1: tenofovir, OAT2: acyclovir, OAT3: oseltamivir carboxylate). The fold-change in OAT1 activity during the 2 nd and 3 rd trimester was 2.9 and 1.0 compared with nonpregnant individual, respectively. OAT2 activity increased 3.1-fold during the 3 rd trimester. OAT3 activity increased 2.2, 1.7 and 1.3-fold during the 1 st , 2 nd , and 3 rd trimester, respectively. Based on these data, we predicted the CL sec , CL renal and total clearance ((CL total ) of drugs in pregnancy, which are secreted by multiple OATs (verification dataset; amoxicillin, pravastatin, cefazolin and ketorolac, R -ketorolac, S -ketorolac). Then, the predicted clearances (CLs) were compared with the observed values. The predicted/observed CL sec , CL renal , and CL total of drugs in pregnancy of all verification drugs were within 0.80-1.25 fold except for CL sec of amoxicillin in the 3 rd trimester (0.76-fold) and cefazolin in the 2 nd trimester (1.27-fold). Overall, we successfully predicted the CL sec , CL renal , and CL total of drugs in pregnancy that are renally secreted by multiple OATs. This approach could be used in the future to adjust dosing regimens of renally secreted OAT drugs which are administered to pregnant women. SIGNIFICANCE STATEMENT: To the authors' knowledge, this is the first report to successfully predict renal secretory clearance and renal clearance of multiple OAT substrate drugs during pregnancy. The data presented here could be used in the future to adjust dosing regimens of renally secreted OAT drugs in pregnancy. In addition, the mechanistic approach used here could be extended to drugs transported by other renal transporters., Competing Interests: The authors have no conflicts of interest to declare., (Copyright © 2021 by The American Society for Pharmacology and Experimental Therapeutics.)

Many women take drugs during their pregnancy to treat a variety of clinical conditions. To optimize drug efficacy and reduce fetal toxicity, it is important to determine or predict fetal drug exposure throughout pregnancy. Previously, we developed and verified a maternal-fetal physiologically based pharmacokinetic (m-f PBPK) model to predict fetal K p,uu (unbound fetal plasma AUC/unbound maternal plasma AUC) of drugs that passively cross the placenta. Here, we used in vitro transport studies in Transwell, in combination with our m-f PBPK model, to predict fetal K p,uu of drugs that are effluxed by placental P-glycoprotein (P-gp)-namely, dexamethasone, betamethasone, darunavir, and lopinavir. Using Transwell, we determined the efflux ratio of these drugs in hMDR1-MDCK cP-gpKO cells, in which human P-gp was overexpressed and the endogenous P-gp was knocked out. Then, using the proteomics-informed efflux ratio-relative expressive factor approach, we predicted the fetal K p,uu of these drugs at term. Finally, to verify our predictions, we compared them with the observed in vivo fetal K p,uu at term. The latter was estimated using our m-f PBPK model and published fetal [umbilical vein (UV)]/maternal plasma drug concentrations obtained at term (UV/maternal plasma). Fetal K p,uu predictions for dexamethasone (0.63), betamethasone (0.59), darunavir (0.17), and lopinavir (0.08) were successful, as they fell within the 90% confidence interval of the corresponding in vivo fetal K p,uu (0.30-0.66, 0.29-0.71, 0.11-0.22, 0.04-0.19, respectively). This is the first demonstration of successful prediction of fetal K p,uu of P-gp drug substrates from in vitro studies. SIGNIFICANCE STATEMENT: For the first time, using in vitro studies in cells, this study successfully predicted human fetal K p,uu of P-gp substrate drugs. This success confirms that the m-f PBPK model, combined with the ER-REF approach, can successfully predict fetal drug exposure to P-gp substrates. This success provides increased confidence in the use of the ER-REF approach, combined with the m-f PBPK model, to predict fetal K p,uu of drugs (transported by P-gp or other transporters), both at term and at earlier gestational ages., (Copyright © 2021 The Author(s).)

(-)-Δ 9 -Tetrahydrocannabinol (THC) is the primary psychoactive constituent of cannabis. In humans, 11-hydroxy-THC (11-OH-THC) and 11-nor-9-carboxy-THC (THC-COOH) are psychoactive and nonpsychoactive circulating metabolites of THC, respectively. Whether these cannabinoids are substrates or inhibitors of human P-glycoprotein (P-gp) or breast cancer resistance protein (BCRP) is unknown. Previous animal studies suggest that THC and its metabolites could be substrates of these transporters. Therefore, we performed Transwell, cellular accumulation, and vesicular transport assays, at pharmacologically relevant concentrations of these cannabinoids, using Madin-Darby canine kidney (MDCK) II cells or plasma membrane vesicles overexpressing human P-gp or BCRP. Neither THC nor 11-OH-THC was found to be a substrate or inhibitor of P-gp or BCRP. The efflux ratio of THC-COOH in MDCKII-BCRP cells was 1.6, which was significantly decreased to 1.0 by the BCRP inhibitor Ko143. Likewise, cellular accumulation of THC-COOH was significantly increased 1.6-fold in the presence versus absence of Ko143. THC-COOH also significantly inhibited BCRP-mediated transport of Lucifer yellow, a BCRP substrate; however, THC-COOH was neither a substrate nor an inhibitor of P-gp. Collectively, these results indicate that THC and 11-OH-THC are not substrates or inhibitors (at pharmacologically relevant concentrations) of either P-gp or BCRP. THC-COOH is a weak substrate and inhibitor of BCRP, but not of P-gp. Accordingly, we predict that P-gp/BCRP will not modulate the disposition of these cannabinoids in humans. In addition, use of these cannabinoids will not result in P-gp- or BCRP-based drug interactions. SIGNIFICANCE STATEMENT: This study systematically investigated whether Δ 9 -tetrahydrocannabinol (THC) and its major metabolites, 11-hydroxy-THC and 11-nor-9-carboxy-THC, are substrates and/or inhibitors of human P-gp and BCRP at pharmacologically relevant concentrations. The results obtained are highly valuable for mechanistic understanding and prediction of the roles of P-gp and BCRP in determining the human pharmacokinetics, tissue distribution, and drug interactions of cannabinoids., (Copyright © 2021 by The American Society for Pharmacology and Experimental Therapeutics.)

We have previously developed a maternal-fetal physiologically-based pharmacokinetic (m-f PBPK) model to dynamically predict (and verify) fetal-maternal exposure to drugs that passively diffuse across the placenta. Here, we extended the application of this model to dynamically predict fetal exposure to drugs which are effluxed by placental P-glycoprotein, namely the antenatal corticosteroids (ACS; dexamethasone [DEX], and betamethasone [BET]). To do so, we estimated both the placental P-gp mediated efflux clearance (CL) and the passive diffusion CL of the ACS. The efficacy and toxicity of the currently used maternal ACS dosing regimens to prevent neonatal respiratory distress syndrome could be improved by altering their dosing regimens. Therefore, to illustrate the utility of our m-f PBPK model, we used it to design alternative dosing regimens of DEX and BET that could potentially improve their efficacy and reduce their toxicity. The redesigned dosing regimens are convenient to administer, maintain maternal-fetal exposure (area under the concentration-time curve [AUC]) or maximum plasma concentration (C max ) or both (DEX and BET) or minimize maternal exposure while maintaining fetal drug plasma concentrations above the minimum therapeutic threshold of 1 ng/ml for 48 h (BET only; based on efficacy data in sheep). To our knowledge, this is the first study to dynamically predict fetal plasma concentrations of placental P-gp effluxed drugs. Our approach and our m-f PBPK model could be used in the future to predict maternal-fetal exposure to any drug and to design alternative dosing regimens of the drug., (© 2021 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

In order to optimize central nervous system (CNS) drug development, accurate prediction of the drug's human steady-state unbound brain interstitial fluid-to-plasma concentration ratio (K p,uu,brain ) is critical, especially for drugs that are effluxed by the multiple drug resistance transporters (e.g., P-glycoprotein, P-gp). Due to lack of good in vitro human blood-brain barrier models, we and others have advocated the use of a proteomics-informed relative expressive factor (REF) approach to predict K p,uu,brain . Therefore, we tested the success of this approach in humans, with a focus on P-gp substrates, using brain positron emission tomography imaging data for verification. To do so, the efflux ratio (ER) of verapamil, N-desmethyl loperamide, and metoclopramide was determined in human P-gp-transfected MDCKII cells using the Transwell assay. Then, using the ER estimate, K p,uu,brain of the drug was predicted using REF (ER approach). Alternatively, in vitro passive and P-gp-mediated intrinsic clearances (CLs) of these drugs, estimated using a five-compartmental model, were extrapolated to in vivo using REF (active CL) and brain microvascular endothelial cells protein content (passive CL). The ER approach successfully predicted K p,uu,brain of all three drugs within twofold of observed data and within 95% confidence interval of the observed data for verapamil and N-desmethyl loperamide. Using the in vitro-to-in vivo extrapolated clearance approach, K p,uu,brain was reasonably well predicted but not the brain unbound interstitial fluid drug concentration-time profile. Therefore, we propose that the ER approach be used to predict K p,uu,brain of CNS candidate drugs to enhance their success in development., (© 2021 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Conducting clinical trials to understand the exposure risk/benefit relationship of cannabis use is not always feasible. Alternatively, physiologically based pharmacokinetic (PBPK) models can be used to predict exposure of the psychoactive cannabinoid (-)-Δ 9 -tetrahydrocannabinol (THC) and its active metabolite 11-hydroxy-Δ 9 -tetrahydrocannabinol (11-OH-THC). Here, we first extrapolated in vitro mechanistic pharmacokinetic information previously quantified to build a linked THC/11-OH-THC PBPK model and verified the model with observed data after intravenous and inhalation administration of THC in a healthy, nonpregnant population. The in vitro to in vivo extrapolation of both THC and 11-OH-THC disposition was successful. The inhalation bioavailability (F inh ) of THC after inhalation was higher in chronic versus casual cannabis users (F inh = 0.35 and 0.19, respectively). Sensitivity analysis demonstrated that 11-OH-THC but not THC exposure was sensitive to alterations in hepatic intrinsic clearance of the respective compound. Next, we extrapolated the linked THC/11-OH-THC PBPK model to pregnant women. Simulations showed that THC plasma area under the curve (AUC) does not change during pregnancy, but 11-OH-THC plasma AUC decreases by up to 41%. Using a maternal-fetal PBPK model, maternal and fetal THC serum concentrations were simulated and compared with the observed THC serum concentrations in pregnant women at term. To recapitulate the observed THC fetal serum concentrations, active placental efflux of THC needed to be invoked. In conclusion, we built and verified a linked THC/11-OH-THC PBPK model in healthy nonpregnant population and demonstrated how this mechanistic physiologic and pharmacokinetic platform can be extrapolated to a special population, such as pregnant women. SIGNIFICANCE STATEMENT: Although the pharmacokinetics of cannabinoids have been extensively studied clinically, limited mechanistic pharmacokinetic models exist. Here, we developed and verified a physiologically based pharmacokinetic (PBPK) model for (-)-Δ 9 -tetrahydrocannabinol (THC) and its active metabolite, 11-hydroxy-Δ 9 -tetrahydrocannabinol (11-OH-THC). The PBPK model was verified in healthy, nonpregnant population after intravenous and inhalation administration of THC, and then extrapolated to pregnant women. The THC/11-OH-THC PBPK model can be used to predict exposure in special populations, predict drug-drug interactions, or impact of genetic polymorphism., Competing Interests: The authors report no conflicts of interest., (Copyright © 2021 by The American Society for Pharmacology and Experimental Therapeutics.)

Our goal was to measure the absolute differential abundance of key drug transporters in human epileptogenic brain tissue and to compare them between patients and at various distances from the epileptogenic zone within the same patient. Transporter protein abundance was quantified in brain tissue homogenates from patients who underwent epilepsy surgery, using targeted proteomics, and correlations with clinical and tissue characteristics were assessed. Fourteen brain samples (including four epileptogenic hippocampal samples) were collected from nine patients. Among the quantifiable drug transporters, the abundance (median, range) ranked: breast cancer resistance protein (ABCG2/BCRP; 0.55, 0.01-3.26 pmol/g tissue) > P -glycoprotein (ABCB1/MDR1; 0.30, 0.02-1.15 pmol/g tissue) > equilibrative nucleoside transporter 1 (SLC29A1/ENT1; 0.06, 0.001-0.35 pmol/g tissue). The ABCB1/ABCG2 ratio (mean 0.27, range 0.08-0.47) was comparable with literature values from nonepileptogenic brain tissue (mean 0.5-0.8). Transporter abundance was lower in the hippocampi than in the less epileptogenic neocortex of the same patients. ABCG2/BCRP and ABCB1/MDR1 expression strongly correlated with that of glucose transporter 1 (SLC2A1/GLUT1) ( r = 0.97, p < 0.001; r = 0.90, p < 0.01, respectively). Low transporter abundance was found in patients with overt vascular pathology, whereas the highest abundance was seen in a sample with normally appearing blood vessels. In conclusion, drug transporter abundance highly varies across patients and between epileptogenic and less epileptogenic brain tissue of the same patient. The strong correlation in abundance of ABCB1/MDR1, ABCG2/BCRP, and SLC2A1/GLUT1 suggests variation in the content of the functional vasculature within the tissue samples. The epileptogenic tissue can be depleted of key drug transport mechanisms, warranting consideration when selecting treatments for patients with drug-resistant epilepsy.

The botanical natural product goldenseal can precipitate clinical drug interactions by inhibiting cytochrome P450 (CYP) 3A and CYP2D6. Besides P-glycoprotein, effects of goldenseal on other clinically relevant transporters remain unknown. Established transporter-expressing cell systems were used to determine the inhibitory effects of a goldenseal extract, standardized to the major alkaloid berberine, on transporter activity. Using recommended basic models, the extract was predicted to inhibit the efflux transporter BCRP and uptake transporters OATP1B1/3. Using a cocktail approach, effects of the goldenseal product on BCRP, OATP1B1/3, OATs, OCTs, MATEs, and CYP3A were next evaluated in 16 healthy volunteers. As expected, goldenseal increased the area under the plasma concentration-time curve (AUC 0-inf ) of midazolam (CYP3A; positive control), with a geometric mean ratio (GMR) (90% confidence interval (CI)) of 1.43 (1.35-1.53). However, goldenseal had no effects on the pharmacokinetics of rosuvastatin (BCRP and OATP1B1/3) and furosemide (OAT1/3); decreased metformin (OCT1/2, MATE1/2-K) AUC 0-inf (GMR, 0.77 (0.71-0.83)); and had no effect on metformin half-life and renal clearance. Results indicated that goldenseal altered intestinal permeability, transport, and/or other processes involved in metformin absorption, which may have unfavorable effects on glucose control. Inconsistencies between model predictions and pharmacokinetic outcomes prompt further refinement of current basic models to include differential transporter expression in relevant organs and intestinal degradation/metabolism of the precipitant(s). Such refinement should improve in vitro-in vivo prediction accuracy, contributing to a standard approach for studying transporter-mediated natural product-drug interactions., (© 2020 The Authors. Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.)

The popularity of botanical and other purported medicinal natural products (NPs) continues to grow, especially among patients with chronic illnesses and patients managed on complex prescription drug regimens. With few exceptions, the risk of a given NP to precipitate a clinically significant pharmacokinetic NP-drug interaction (NPDI) remains understudied or unknown. Application of static or dynamic mathematical models to predict and/or simulate NPDIs can provide critical information about the potential clinical significance of these complex interactions. However, methods used to conduct such predictions or simulations are highly variable. Additionally, published reports using mathematical models to interrogate NPDIs are not always sufficiently detailed to ensure reproducibility. Consequently, guidelines are needed to inform the conduct and reporting of these modeling efforts. This recommended approach from the Center of Excellence for Natural Product Drug Interaction Research describes a systematic method for using mathematical models to interpret the interaction risk of NPs as precipitants of potential clinically significant pharmacokinetic NPDIs. A framework for developing and applying pharmacokinetic NPDI models is presented with the aim of promoting accuracy, reproducibility, and generalizability in the literature. SIGNIFICANCE STATEMENT: Many natural products (NPs) contain phytoconstituents that can increase or decrease systemic or tissue exposure to, and potentially the efficacy of, a pharmaceutical drug; however, no regulatory agency guidelines exist to assist in predicting the risk of these complex interactions. This recommended approach from a multi-institutional consortium designated by National Institutes of Health as the Center of Excellence for Natural Product Drug Interaction Research provides a framework for modeling pharmacokinetic NP-drug interactions., Competing Interests: The authors have no financial conflicts of interest to disclose., (Copyright © 2021 by The American Society for Pharmacology and Experimental Therapeutics.)

The human blood-brain barrier (BBB) transporter P-gp can efflux amyloid-β (Aβ) out of the central nervous system (CNS). Aβ is thought to be the causative agent for Alzheimer's disease (AD). Using positron emission tomography imaging, we have shown that BBB P-gp activity is reduced in AD, as quantified by the in vivo brain distribution of the P-gp probe [ 11 C]-verapamil. Therefore, the aim of this study was to determine whether this reduced BBB P-gp activity in AD was due to decreased P-gp abundance at the BBB. Using targeted proteomics, we quantified the abundance of P-gp and other drug transporters in gray matter brain microvessels isolated from 43 subjects with AD and 38 age-matched controls (AMCs) from regions affected by AD (hippocampus and the parietal lobe of the brain cortex) and not affected by AD (cerebellum). First, P-gp abundance was decreased in the BBB of the hippocampus vs. the cerebellum in both subjects with AD and AMCs, and therefore was not AD-related. In addition, gray matter BBB abundance of P-gp (and of other transporters) in the hippocampus and the parietal lobe was not different between AD and AMC. The gray matter BBB abundance of all drug transporters decreased with age, likely due to age-dependent decrease in the density of brain microvessels. Collectively, the observed reduced in vivo cerebral BBB P-gp activity in AD cannot be explained by reduced abundance of P-gp at the BBB. Nevertheless, the drug transporter abundance at the human gray matter BBB data provided here can be used to predict brain distribution of drugs targeted to treat CNS diseases, including AD., (© 2020 The Authors Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.)