Modeling Pharmacokinetic Natural Product-Drug Interactions for Decision-Making: A NaPDI Center Recommended Approach.

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.

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.

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.

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.

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.

Estimation of Fetal-to-Maternal Unbound Steady-State Plasma Concentration Ratio of P-Glycoprotein and/or Breast Cancer Resistance Protein Substrate Drugs Using a Maternal-Fetal Physiologically Based Pharmacokinetic Model.

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 (Kp,uu,fetal). For drugs that are substrates of placental efflux transporters [i.e., P-glycoprotein (P-gp) or breast cancer resistance protein (BCRP)], Kp,uu,fetal is expected to be <1. Here, we estimated the in vivo Kp,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 Kp,uu,fetal of the drug was estimated by adjusting the placental efflux clearance until the predicted UV/MP values best matched the observed data (Kp,uu,fetal) of nelfinavir = 0.41, efavirenz = 0.39, and imatinib = 0.35. Furthermore, Kp,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 Kp,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 Kp,uu,fetal values can be predicted from in vitro studies. SIGNIFICANCE STATEMENT: The in vivo fetal-to-maternal unbound steady-state plasma concentration ratio (Kp,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 Kp,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 Kp,uu,fetal values can be predicted from in vitro studies.

Comprehensive Predictions of Cytochrome P450 (P450)-Mediated In Vivo Cannabinoid-Drug Interactions Based on Reversible and Time-Dependent P450 Inhibition in Human Liver Microsomes.

We previously reported the unbound reversible (IC50,u) and time-dependent (KI,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 IC50,u values of the aforementioned cannabinoids and the IC50,u and KI,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 IC50,u of CBD, 7-OH CBD, THC, and 11-OH THC against CYP2B6 was 0.05, 0.34, 0.40, and 0.32 µM, respectively, and against CYP2C8 was 0.28, 1.02, 0.67, and 3.66 µM, 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 (IC50,u<2.5 µM) except CYP1A2 and inactivated CYP2C19 and CYP3A, with inactivation efficiencies (kinact/KI,u) of 0.10 and 0.14 minutes-1 µM-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.

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.

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).

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.

Prediction of Pregnancy-Induced Changes in Secretory and Total Renal Clearance of Drugs Transported by Organic Anion Transporters.

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 (CLsec) and renal CL (CLrenal) 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 CLrenal data (training dataset; OAT1: tenofovir, OAT2: acyclovir, OAT3: oseltamivir carboxylate). The fold-change in OAT1 activity during the 2nd and 3rd trimester was 2.9 and 1.0 compared with nonpregnant individual, respectively. OAT2 activity increased 3.1-fold during the 3rd trimester. OAT3 activity increased 2.2, 1.7 and 1.3-fold during the 1st, 2nd, and 3rd trimester, respectively. Based on these data, we predicted the CLsec, CLrenal and total clearance ((CLtotal) 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 CLsec, CLrenal, and CLtotal of drugs in pregnancy of all verification drugs were within 0.80-1.25 fold except for CLsec of amoxicillin in the 3rd trimester (0.76-fold) and cefazolin in the 2nd trimester (1.27-fold). Overall, we successfully predicted the CLsec, CLrenal, and CLtotal 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.

Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation.

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 Kp,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 Kp,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-MDCKcP-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 Kp,uu of these drugs at term. Finally, to verify our predictions, we compared them with the observed in vivo fetal Kp,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 Kp,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 Kp,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 Kp,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 Kp,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 Kp,uu of drugs (transported by P-gp or other transporters), both at term and at earlier gestational ages.

Tetrahydrocannabinol and Its Major Metabolites Are Not (or Are Poor) Substrates or Inhibitors of Human P-Glycoprotein [ATP-Binding Cassette (ABC) B1] and Breast Cancer Resistance Protein (ABCG2).

(-)-Δ9-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 Δ9-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.

Development and Verification of a Linked Δ 9-THC/11-OH-THC Physiologically Based Pharmacokinetic Model in Healthy, Nonpregnant Population and Extrapolation to Pregnant Women.

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 (-)-Δ9-tetrahydrocannabinol (THC) and its active metabolite 11-hydroxy-Δ9-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 (Finh) of THC after inhalation was higher in chronic versus casual cannabis users (Finh = 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 (-)-Δ9-tetrahydrocannabinol (THC) and its active metabolite, 11-hydroxy-Δ9-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.

Prediction of Transporter-Mediated Rosuvastatin Hepatic Uptake Clearance and Drug Interaction in Humans Using Proteomics-Informed REF Approach.

Suspended, plated, or sandwich-cultured human hepatocytes are routinely used for in vitro to in vivo extrapolation (IVIVE) of transporter-mediated hepatic clearance (CL) of drugs. However, these hepatocyte models have been reported to underpredict transporter-mediated in vivo hepatic uptake CL (CL uptake,in vivo ) of some drugs. Therefore, we determined whether transporter-expressing cells (TECs) can accurately predict the CL uptake,in vivo of drugs. To do so, we determined the uptake CL (CL int,uptake,cells ) of rosuvastatin (RSV) by TECs (organic anion transporting polypeptides/Na+-taurocholate cotransporting polypeptide) and then scaled it to that in vivo by relative expression factor (REF) (the ratio of transporter abundance in human livers and TEC) determined by liquid chromatography tandem mass spectrometry-based quantitative proteomics. Both the TEC and hepatocyte models did not meet our predefined success criteria of predicting within 2-fold the RSV CL uptake,in vivo value obtained from our positron emission tomography (PET) imaging. However, the TEC performed better than the hepatocyte models. Interestingly, using REF, TECs successfully predicted RSV CL int,uptake,hep obtained by the hepatocyte models, suggesting that the underprediction of RSV CL uptake,in vivo by TECs and hepatocytes is due to endogenous factor(s) not present in these in vitro models. Therefore, we determined whether inclusion of plasma (or albumin) in TEC uptake studies improved IVIVE of RSV CL uptake,in vivo It did, and our predictions were close to or just fell above our lower 2-fold acceptance boundary. Despite this success, additional studies are needed to improve transporter-mediated IVIVE of hepatic uptake CL of drugs. However, using REF and TEC, we successfully predicted the magnitude of PET-imaged inhibition of RSV CL uptake,in vivo by cyclosporine A. SIGNIFICANCE STATEMENT: We showed that the in vivo transporter-mediated hepatic uptake CL of rosuvastatin, determined by PET imaging, can be predicted (within 2-fold) from in vitro studies in transporter-expressing cells (TECs) (scaled using REF), but only when plasma proteins were included in the in vitro studies. This conclusion did not hold when plasma proteins were absent in the TEC or human hepatocyte studies. Thus, additional studies are needed to improve in vitro to in vivo extrapolation of transporter-mediated drug CL.

Abundance of P-glycoprotein and Breast Cancer Resistance Protein Measured by Targeted Proteomics in Human Epileptogenic Brain Tissue.

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.

Predicting the Potential for Cannabinoids to Precipitate Pharmacokinetic Drug Interactions via Reversible Inhibition or Inactivation of Major Cytochromes P450.

Cannabis is used for both recreational and medicinal purposes. The most abundant constituents are the cannabinoids - cannabidiol (CBD, nonpsychoactive) and (-)-trans-Δ9-tetrahydrocannabinol (THC, psychoactive). Both have been reported to reversibly inhibit or inactivate cytochrome P450 (CYPs) enzymes. However, the low aqueous solubility, microsomal protein binding, and nonspecific binding to labware were not considered, potentially leading to an underestimation of CYPs inhibition potency. Therefore, the binding-corrected reversible (IC50,u) and irreversible (K I,u ) inhibition potency of each cannabinoid toward major CYPs were determined. The fraction unbound of CBD and THC in the incubation mixture was 0.12 ± 0.04 and 0.05 ± 0.02, respectively. The IC50,u for CBD toward CYP1A2, 2C9, 2C19, 2D6, and 3A was 0.45 ± 0.17, 0.17 ± 0.03, 0.30 ± 0.06, 0.95 ± 0.50, and 0.38 ± 0.11 µM, respectively; the IC50,u for THC was 0.06 ± 0.02, 0.012 ± 0.001, 0.57 ± 0.22, 1.28 ± 0.25, and 1.30 ± 0.34 µM, respectively. Only CBD showed time-dependent inactivation (TDI) of CYP1A2, 2C19, and CYP3A, with inactivation efficiencies (k inact/K I,u) of 0.70 ± 0.34, 0.11 ± 0.06, and 0.14 ± 0.04 minutes-1 µM-1, respectively. A combined (reversible inhibition and TDI) mechanistic static model populated with these data predicted a moderate to strong pharmacokinetic interaction risk between orally administered CBD and drugs extensively metabolized by CYP1A2/2C9/2C19/2D6/3A and between orally administered THC and drugs extensively metabolized by CYP1A2/2C9/3A. These predictions will be extended to a dynamic model using physiologically based pharmacokinetic modeling and simulation and verified with a well-designed clinical cannabinoid-drug interaction study. SIGNIFICANCE STATEMENT: This study is the first to consider the impact of limited aqueous solubility, nonspecific binding to labware, or extensive binding to incubation protein shown by cannabidiol (CBD) and delta-9-tetrahydrocannabinol (THC) on their true cytochrome P450 inhibitory potency. A combined mechanistic static model predicted a moderate to strong pharmacokinetic interaction risk between orally administered CBD and drugs extensively metabolized by CYP1A2, 2C9, 2C19, 2D6, or 3A and between orally administered THC and drugs extensively metabolized by CYP1A2, 2C9, or 3A.

Successful Prediction of Positron Emission Tomography-Imaged Metformin Hepatic Uptake Clearance in Humans Using the Quantitative Proteomics-Informed Relative Expression Factor Approach.

Predicting transporter-mediated in vivo hepatic drug clearance (CL) from in vitro data (IVIVE) is important in drug development to estimate first-in-human dose and the impact of drug interactions and pharmacogenetics on hepatic drug CL. For IVIVE, one can use human hepatocytes and the traditional milligrams of protein content per gram of liver tissue (MGPGL) approach. However, this approach has been found to consistently underpredict the observed in vivo hepatic drug CL. Therefore, we hypothesized that using transporter-expressing cells and the relative expression factor (REF), determined using targeted quantitative proteomics, will accurately predict in vivo hepatic CL of drugs. We have successfully tested this hypothesis in rats with rosuvastatin, which is transported by hepatic Organic anion transporting polypeptides (OATPs). Here, we tested this hypothesis for another drug and another transporter; namely, organic cation transporter (OCT)1-mediated hepatic distributional CL of metformin. First, we estimated the in vivo metformin hepatic sinusoidal uptake CL (CLh,s,in) of metformin by reanalysis of previously published human positron emission tomography imaging data. Next, using the REF approach, we predicted the in vivo metformin CLh,s,in using OCT1-transporter-expressing HEK293 cells or plated human hepatocytes. Finally, we compared this REF-based prediction with that using the MGPGL approach. The REF approach accurately predicted the in vivo metformin hepatic CLh,s,in, whereas the MGPGL approach considerably underpredicted the in vivo metformin CLh,s,in Based on these and previously published data, the REF approach appears to be superior to the MGPGL approach for a diverse set of drugs transported by different transporters. SIGNIFICANCE STATEMENT: This study is the first to use organic cation transporter 1-expressing cells and plated hepatocytes to compare proteomics-informed REF approach with the traditional MGPGL approach to predict hepatic uptake CL of metformin in humans. The proteomics-informed REF approach, which corrected for plasma membrane abundance, accurately predicted the positron emission tomography-imaged metformin hepatic uptake CL, whereas the MGPGL approach consistently underpredicted this CL.

Gestational Age-Dependent Abundance of Human Placental Transporters as Determined by Quantitative Targeted Proteomics.

Some women take medication during pregnancy to address a variety of clinical conditions. Because of ethical and logistical concerns, it is impossible to determine fetal drug exposure, and therefore fetal risk, during pregnancy. Hence, alternative approaches need to be developed to predict maternal-fetal drug exposure throughout pregnancy. To do so, we previously developed and verified a maternal-fetal physiologically based pharmacokinetic model, which can predict fetal exposure to drugs that passively cross the placenta. However, many drugs are actively transported by the placenta (e.g., human immunodeficiency virus protease inhibitors). To extend our maternal-fetal physiologically based pharmacokinetic model to these actively transported drugs, we determined the gestational age-dependent changes in the protein abundance of placental transporters. Total cellular membrane fractions from first trimester (T1; n = 15), second trimester (T2; n = 19), and term (n = 15) human placentae obtained from uncomplicated pregnancies were isolated by ultracentrifugation. Transporter protein abundance was determined by targeted quantitative proteomics using liquid chromatography tandem mass specrometry. We observed that breast cancer resistance protein and P-glycoprotein abundance significantly decreased from T1 to term by 55% and 69%, respectively (per gram of tissue). Organic anion-transporting polypeptide (OATP) 2B1 abundance significantly decreased from T1 to T2 by 32%. In contrast, organic cation transporter (OCT) 3 and organic anion transporter 4 abundance significantly increased with gestational age (2-fold from T1 to term, 1.6-fold from T2 to term). Serotonin transporter and norepinephrine transporter did not change with gestational age. The abundance of bile salt export pump, multidrug resistance-associated protein 1-5, Na+-taurocholate cotransporting polypeptide, OATP1B1, OATP1B3, OCTN1-2, concentrative nucleoside transporter 1-3, equilibrative nucleoside transporter 2, and multidrug and toxin extrusion 1 could not be quantified. These data can be incorporated into our maternal-fetal physiologically based pharmacokinetic model to predict fetal exposure to drugs that are actively transported across the placenta. SIGNIFICANCE STATEMENT: We quantified the protein abundance of key placental uptake and efflux transporters [organic cation transporter (OCT) 3, P-glycoprotein (P-gp), breast cancer resistance protein (BCRP)] across gestational ages (first trimester, second trimester, and term) using quantitative targeted proteomics. We observed that the protein abundance of P-gp and BCRP decreased, whereas that of OCT3 increased with gestational age. Incorporating the protein abundance determined in this study into maternal-fetal physiologically based pharmacokinetic model can help us better predict fetal drug exposure to substrates of these transporters.

In Vivo-to-In Vitro Extrapolation of Transporter-Mediated Renal Clearance: Relative Expression Factor Versus Relative Activity Factor Approach.

About 30% of approved drugs are cleared predominantly by renal clearance (CLr). Of these, many are secreted by transporters. For these drugs, in vitro-to-in vivo extrapolation of transporter-mediated renal secretory clearance (CLsec,plasma) is important to prospectively predict their renal clearance and to assess the impact of drug-drug interactions and pharmacogenetics on their pharmacokinetics. Here we compared the ability of the relative expression factor (REF) and the relative activity factor (RAF) approaches to quantitatively predict the in vivo CLsec,plasma of 26 organic anion transporter (OAT) substrates assuming that OAT-mediated uptake is the rate-determining step in the CLsec,plasma of the drugs. The REF approach requires protein quantification of each transporter in the tissue (e.g., kidney) and transporter-expressing cells, whereas the RAF approach requires the use of a transporter-selective probe substrate (both in vitro and in vivo) for each transporter of interest. For the REF approach, 50% and 69% of the CLsec,plasma predictions were within 2- and 3-fold of the observed values, respectively; the corresponding values for the RAF approach were 65% and 81%. We found no significant difference between the two approaches in their predictive capability (as measured by accuracy and bias) of the CLsec,plasma or CLr of OAT drugs. We recommend that the REF and RAF approaches can be used interchangeably to predict OAT-mediated CLsec,plasma Further research is warranted to evaluate the ability of the REF or RAF approach to predict CLsec,plasma of drugs when uptake is not the rate-determining step. SIGNIFICANCE STATEMENT: This is the first direct comparison of the relative expression factor (REF) and relative activity factor (RAF) approaches to predict transporter-mediated renal clearance (CLr). The RAF, but not REF, approach requires transporter-selective probes and that the basolateral uptake is the rate-determining step in the CLr of drugs. Given that there is no difference in predictive capability of the REF and RAF approach for organic anion transporter-mediated CLr, the REF approach should be explored further to assess its ability to predict CLr when basolateral uptake is not the sole rate-determining step.