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

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

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

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

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

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

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).

Abundance of P-Glycoprotein and Other Drug Transporters at the Human Blood-Brain Barrier in Alzheimer's Disease: A Quantitative Targeted Proteomic Study.

The human blood-brain barrier (BBB) transporter P-gp can efflux amyloid-ß (Aß) out of the central nervous system (CNS). Aß 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.

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.

Pharmacokinetics of dacarbazine (DTIC) in pregnancy.

PURPOSE: The purpose of this report is to describe, for the first time, the pharmacokinetics of dacarbazine (DTIC) and its metabolites [5-[3-methyl-triazen-1-yl]-imidazole-4-carboxamide (MTIC), 5-[3-hydroxymethyl-3-methyl-triazen-1-yl]-imidazole-4-carboxamide (HMMTIC) and 5-aminoimidazole-4-carboxamide (AIC)] during pregnancy (n = 2) and postpartum (n = 1). METHODS: Non-compartmental DTIC, MTIC, HMMTIC, and AIC pharmacokinetics (PK) were estimated in one case at 29 week gestation and 18 day postpartum and a second case at 32 week gestation, in women receiving DTIC in combination with doxorubicin, bleomycin, and vinblastine for treatment of Hodgkin's lymphoma. Drug concentrations were measured by HPLC. RESULTS: In the subject who completed both pregnancy and postpartum study days, DTIC area under the concentration-time curve (AUC) was 27% higher and metabolite AUCs were lower by 27% for HMMTIC, 38% for MTIC, and 83% of AIC during pregnancy compared to postpartum. At 7 and 9 year follow-up, both subjects were in remission of their Hodgkin's lymphoma. CONCLUSIONS: Based on these two case reports, pregnancy appears to decrease the metabolism of the pro-drug dacarbazine, likely through inhibition of CYP1A2 activity. Lower concentrations of active metabolites and decreased efficacy may result, although both these subjects experienced long-term remission of their Hodgkin's lymphoma.