Impact of Obesity on Hepatic Drug Clearance: What are the Influential Variables?

Drug clearance in obese subjects varies widely among different drugs and across subjects with different severity of obesity. This study investigates correlations between plasma clearance (CLp) and drug- and patient-related characteristics in obese subjects, and evaluates the systematic accuracy of common weight-based dosing methods. A physiologically-based pharmacokinetic (PBPK) modeling approach that uses recent information on obesity-related changes in physiology was used to simulate CLp for a normal-weight subject (body mass index [BMI] = 20) and subjects with various severities of obesity (BMI 25-60) for hypothetical hepatically cleared drugs with a wide range of properties. Influential variables for CLp change were investigated. For each drug and obese subject, the exponent that yields perfect allometric scaling of CLp from normal-weight subjects was assessed. Among all variables, BMI and relative changes in enzyme activity resulting from obesity proved highly correlated with obesity-related CLp changes. Drugs bound to α1-acid glycoprotein (AAG) had lower CLp changes compared to drugs bound to human serum albumin (HSA). Lower extraction ratios (ER) corresponded to higher CLp changes compared to higher ER. The allometric exponent for perfect scaling ranged from -3.84 to 3.34 illustrating that none of the scaling methods performed well in all situations. While all three dosing methods are generally systematically accurate for drugs with unchanged or up to 50% increased enzyme activity in subjects with a BMI below 30 kg/m2, in any of the other cases, information on the different drug properties and severity of obesity is required to select an appropriate dosing method for individuals with obesity.

In Vitro-In Vivo Extrapolation and Scaling Factors for Clearance of Human and Preclinical Species with Liver Microsomes and Hepatocytes.

In vitro-in vivo extrapolation ((IVIVE) and empirical scaling factors (SF) of human intrinsic clearance (CLint) were developed using one of the largest dataset of 455 compounds with data from human liver microsomes (HLM) and human hepatocytes (HHEP). For extended clearance classification system (ECCS) class 2/4 compounds, linear SFs (SFlin) are approximately 1, suggesting enzyme activities in HLM and HHEP are similar to those in vivo under physiological conditions. For ECCS class 1A/1B compounds, a unified set of SFs was developed for CLint. These SFs contain both SFlin and an exponential SF (SFß) of fraction unbound in plasma (fu,p). The unified SFs for class 1A/1B eliminate the need to identify the transporters involved prior to clearance prediction. The underlying mechanisms of these SFs are not entirely clear at this point, but they serve practical purposes to reduce biases and increase prediction accuracy. Similar SFs have also been developed for preclinical species. For HLM-HHEP disconnect (HLM > HHEP) ECCS class 2/4 compounds that are mainly metabolized by cytochrome P450s/FMO, HLM significantly overpredicted in vivo CLint, while HHEP slightly underpredicted and geometric mean of HLM and HHEP slightly overpredicted in vivo CLint. This observation is different than in rats, where rat liver microsomal CLint correlates well with in vivo CLint for compounds demonstrating permeability-limited metabolism. The good CLint IVIVE developed using HLM and HHEP helps build confidence for prospective predictions of human clearance and supports the continued utilization of these assays to guide structure-activity relationships to improve metabolic stability.

Evaluation of the Success of High-Throughput Physiologically Based Pharmacokinetic (HT-PBPK) Modeling Predictions to Inform Early Drug Discovery.

Minimizing in vitro and in vivo testing in early drug discovery with the use of physiologically based pharmacokinetic (PBPK) modeling and machine learning (ML) approaches has the potential to reduce discovery cycle times and animal experimentation. However, the prediction success of such an approach has not been shown for a larger and diverse set of compounds representative of a lead optimization pipeline. In this study, the prediction success of the oral (PO) and intravenous (IV) pharmacokinetics (PK) parameters in rats was assessed using a "bottom-up" approach, combining in vitro and ML inputs with a PBPK model. More than 240 compounds for which all of the necessary inputs and PK data were available were used for this assessment. Different clearance scaling approaches were assessed, using hepatocyte intrinsic clearance and protein binding as inputs. In addition, a novel high-throughput PBPK (HT-PBPK) approach was evaluated to assess the scalability of PBPK predictions for a larger number of compounds in drug discovery. The results showed that bottom-up PBPK modeling was able to predict the rat IV and PO PK parameters for the majority of compounds within a 2- to 3-fold error range, using both direct scaling and dilution methods for clearance predictions. The use of only ML-predicted inputs from the structure did not perform well when using in vitro inputs, likely due to clearance miss predictions. The HT-PBPK approach produced comparable results to the full PBPK modeling approach but reduced the simulation time from hours to seconds. In conclusion, a bottom-up PBPK and HT-PBPK approach can successfully predict the PK parameters and guide early discovery by informing compound prioritization, provided that good in vitro assays are in place for key parameters such as clearance.

Exploration and application of a liver-on-a-chip device in combination with modelling and simulation for quantitative drug metabolism studies.

Microphysiological systems (MPS) are complex and more physiologically realistic cellular in vitro tools that aim to provide more relevant human in vitro data for quantitative prediction of clinical pharmacokinetics while also reducing the need for animal testing. The PhysioMimix liver-on-a-chip integrates medium flow with hepatocyte culture and has the potential to be adopted for in vitro studies investigating the hepatic disposition characteristics of drug candidates. The current study focusses on liver-on-a-chip system exploration for multiple drug metabolism applications. Characterization of cytochrome P450 (CYP), UDP-glucuronosyl transferase (UGT) and aldehyde oxidase (AO) activities was performed using 15 drugs and in vitro to in vivo extrapolation (IVIVE) was assessed for 12 of them. Next, the utility of the liver-on-a-chip for estimation of the fraction metabolized (fm) via specific biotransformation pathways of quinidine and diclofenac was established. Finally, the metabolite identification opportunities were also explored using efavirenz as an example drug with complex primary and secondary metabolism involving a combination of CYP, UGT and sulfotransferase enzymes. A key aspect of these investigations was the application of mathematical modelling for improved parameter calculation. Such approaches will be required for quantitative assessment of metabolism and/or transporter processes in systems where medium flow and system compartments result in non-homogeneous drug concentrations. In particular, modelling was used to explore the effect of evaporation from the medium and it was found that the intrinsic clearance (CLint) might be underestimated by up to 40% for low clearance compounds if evaporation is not accounted for. Modelling of liver-on-a-chip in vitro data also enhanced the approach to fm estimation allowing objective assessment of metabolism models of different complexity. The resultant diclofenac fm,UGT of 0.64 was highly comparable with values reported previously in the literature. The current study demonstrates the integration of mathematical modelling with experimental liver-on-a-chip studies and illustrates how this approach supports generation of high quality of data from complex in vitro cellular systems.

Piecing together human adult comparative pharmacokinetic trials and rodent studies: What happens to drug clearance in obesity?

In many comparative trials examining the effects of adult obesity on pharmacokinetics of drugs, conclusions were made based on values that were either not adjusted to total body weight or adjusted to non-obese body mass (e.g., ideal or lean body weight). In many cases these values were higher in the obese subjects. We have reviewed the data from comparative human trials, and it is apparent that in examining clearance normalization to total body weight (as typically done in studies involving pediatric obese patients), the clearances are often reduced in the obese. We have also reviewed the results of experimental obese versus non-obese rodent models. Those studies have mostly found that the systemic exposures to the same dose per body weight are increased, with obesity-related decreases in clearance. Furthermore, the expression of a number of important drug metabolizing enzymes are reduced in the experimental obese state. There is also evidence that obesity causes increases in the measured mass of eliminating organs such as liver and kidney. Human clearance normalized to total body weight appears to better reflect the underlying changes reported in the expression of protein and functional activity of drug clearance mechanisms.

Dexmedetomidine Clearance Decreases with Increasing Drug Exposure: Implications for Current Dosing Regimens and Target-controlled Infusion Models Assuming Linear Pharmacokinetics.

BACKGROUND: Numerous pharmacokinetic models have been published aiming at more accurate and safer dosing of dexmedetomidine. The vast majority of the developed models underpredict the measured plasma concentrations with respect to the target concentration, especially at plasma concentrations higher than those used in the original studies. The aim of this article was to develop a dexmedetomidine pharmacokinetic model in healthy adults emphasizing linear versus nonlinear kinetics. METHODS: The data of two previously published clinical trials with stepwise increasing dexmedetomidine target-controlled infusion were pooled to build a pharmacokinetic model using the NONMEM software package (ICON Development Solutions, USA). Data from 48 healthy subjects, included in a stratified manner, were utilized to build the model. RESULTS: A three-compartment mamillary model with nonlinear elimination from the central compartment was superior to a model assuming linear pharmacokinetics. Covariates included in the final model were age, sex, and total body weight. Cardiac output did not explain between-subject or within-subject variability in dexmedetomidine clearance. The results of a simulation study based on the final model showed that at concentrations up to 2 ng · ml-1, the predicted dexmedetomidine plasma concentrations were similar between the currently available Hannivoort model assuming linear pharmacokinetics and the nonlinear model developed in this study. At higher simulated plasma concentrations, exposure increased nonlinearly with target concentration due to the decreasing dexmedetomidine clearance with increasing plasma concentrations. Simulations also show that currently approved dosing regimens in the intensive care unit may potentially lead to higher-than-expected dexmedetomidine plasma concentrations. CONCLUSIONS: This study developed a nonlinear three-compartment pharmacokinetic model that accurately described dexmedetomidine plasma concentrations. Dexmedetomidine may be safely administered up to target-controlled infusion targets under 2 ng · ml-1 using the Hannivoort model, which assumed linear pharmacokinetics. Consideration should be taken during long-term administration and during an initial loading dose when following the dosing strategies of the current guidelines.

Characterization of Metabolites of α-mangostin in Bio-samples from SD Rats by UHPLC-Q-exactive Orbitrap MS.

BACKGROUND: α-mangostin, a typical xanthone, often exists in Garcinia mangostana L. (Clusiaceae). α-mangostin was found to have a wide range of pharmacological properties. However, its specific metabolic route in vivo remains unclear, while these metabolites may accumulate to exert pharmacological effects, too. OBJECTIVE: This study aimed to clarify the metabolic pathways of α-mangostin after oral administration to the rats. METHODS: Here, an UHPLC-Q-Exactive Orbitrap MS was used for the detection of potential metabolites formed in vivo. A new strategy for the identification of unknown metabolites based on typical fragmentation routes was implemented. RESULTS: A total of 42 metabolites were detected, and their structures were tentatively identified in this study. The results showed that major in vivo metabolic pathways of α-mangostin in rats included methylation, demethylation, methoxylation, hydrogenation, dehydrogenation, hydroxylation, dehydroxylation, glucuronidation, and sulfation. CONCLUSIONS: This study is significant to expand our knowledge of the in vivo metabolism of α-mangostin and to understand the mechanism of action of α-mangostin in rats in vivo.

Complex Cytochrome P450 Kinetics Due to Multisubstrate Binding and Sequential Metabolism. Part 1. Theoretical Considerations.

Complexities in P450-mediated metabolism kinetics include multisubstrate binding, multiple-product formation, and sequential metabolism. Saturation curves and intrinsic clearances were simulated for single-substrate and multisubstrate models using derived velocity equations and numerical solutions of ordinary differential equations (ODEs). Multisubstrate models focused on sigmoidal kinetics because of their dramatic impact on clearance predictions. These models were combined with multiple-product formation and sequential metabolism, and simulations were performed with random error. Use of single-substrate models to characterize multisubstrate data can result in inaccurate kinetic parameters and poor clearance predictions. Comparing results for use of standard velocity equations with ODEs clearly shows that ODEs are more versatile and provide better parameter estimates. It would be difficult to derive concentration-velocity relationships for complex models, but these relationships can be easily modeled using numerical methods and ODEs. SIGNIFICANCE STATEMENT: The impact of multisubstrate binding, multiple-product formation, and sequential metabolism on the P450 kinetics was investigated. Numerical methods are capable of characterizing complicated P450 kinetics.

A Drug-Drug Interaction Study Evaluating the Effect of Givosiran, a Small Interfering Ribonucleic Acid, on Cytochrome P450 Activity in the Liver.

Givosiran (trade name GIVLAARI) is a small interfering ribonucleic acid that targets hepatic delta-aminolevulinic acid synthase 1 (ALAS1) messenger RNA for degradation through RNA interference (RNAi) that has been approved for the treatment of acute hepatic porphyria (AHP). RNAi therapeutics, such as givosiran, have a low liability for drug-drug interactions (DDIs) because they are not metabolized by cytochrome 450 (CYP) enzymes, and do not directly inhibit or induce CYP enzymes in the liver. The pharmacodynamic effect of givosiran (lowering of hepatic ALAS1, the first and rate limiting enzyme in the heme biosynthesis pathway) presents a unique scenario where givosiran could potentially impact heme-dependent activities in the liver, such as CYP enzyme activity. This study assessed the impact of givosiran on the pharmacokinetics of substrates of 5 major CYP450 enzymes in subjects with acute intermittent porphyria (AIP), the most common type of AHP, by using the validated "Inje cocktail," comprised of caffeine (CYP1A2), losartan (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and midazolam (CYP3A4). We show that givosiran treatment had a differential inhibitory effect on CYP450 enzymes in the liver, resulting in a moderate reduction in activity of CYP1A2 and CYP2D6, a minor effect on CYP3A4 and CYP2C19, and a similar weak effect on CYP2C9. To date, this is the first study evaluating the DDI for an oligonucleotide therapeutic and highlights an atypical drug interaction due to the pharmacological effect of givosiran. The results of this study suggest that givosiran does not have a large effect on heme-dependent CYP enzyme activity in the liver.

Spreadsheet-Based Minimal Physiological Models for the Prediction of Clearance of Therapeutic Proteins in Pediatric Patients.

There is a growing interest in the use of physiologically based pharmacokinetic (PBPK) models as clinical pharmacology drug development tools. In PBPK modeling, not every organ or physiological parameter is required, leading to the development of a minimal PBPK (mPBPK) model, which is simple and efficient. The objective of this study was to streamline mPBPK modeling approaches and enable straightforward prediction of clearance of protein-based products in children. Four mPBPK models for scaling clearance from adult to children were developed and evaluated on Excel spreadsheets using (1) liver and kidneys; (2) liver, kidneys, and skin; (3) liver, kidneys, skin, and lymph; and (4) interstitial, lymph, and plasma volume. There were 35 therapeutic proteins with a total of 113 observations across different age groups (premature neonates to adolescents). For monoclonal and polyclonal antibodies, more than 90% of observations were within a 0.5- to 2-fold prediction error for all 4 methods. For nonantibodies, 79% to 100% of observations were within the 0.5- to 2-fold prediction error for the 4 different methods. Methods 1 and 4 provided the best results, >90% of the total observations were within the 0.5- to 2-fold prediction error for all 3 classes of protein-based products across a wide age range. The precision of clearance prediction was comparatively lower in children ≤2 years of age vs older children (>2 years of age) with methods 1 and 4 predicting 80% to 100% and 75% to 90% of observations within the 0.5- to 2-fold prediction error, respectively. The results of the study indicated that mPBPK models can be developed on spreadsheets, with acceptable performance for prediction of clearance.

Evaluation and comparison of in vitro intrinsic clearance rates measured using cryopreserved hepatocytes from humans, rats, and rainbow trout.

In vitro and in silico methods that can reduce the need for animal testing are being used with increasing frequency to assess chemical risks to human health and the environment. The rate of hepatic biotransformation is an important species-specific parameter for determining bioaccumulation potential and extrapolating in vitro bioactivity to in vivo effects. One approach to estimating hepatic biotransformation is to employ in vitro systems derived from liver tissue to measure chemical (substrate) depletion over time which can then be translated to a rate of intrinsic clearance (CLint). In the present study, cryopreserved hepatocytes from humans, rats, and rainbow trout were used to measure CLint values for 54 industrial and pesticidal chemicals at starting test concentrations of 0.1 and 1 µM. A data evaluation framework that emphasizes the behavior of Heat-Treated Controls (HTC) was developed to identify datasets suitable for rate reporting. Measured or estimated ("greater than" or "less than") CLint values were determined for 124 of 226 (55 %) species-chemical-substrate concentration datasets with acceptable analytical chemistry. A large percentage of tested chemicals exhibited low HTC recovery values, indicating a substantial abiotic loss of test chemical over time. An evaluation of KOW values for individual chemicals suggested that in vitro test performance declined with increasing chemical hydrophobicity, although differences in testing devices for mammals and fish also likely played a role. The current findings emphasize the value of negative controls as part of a rigorous approach to data quality assessment for in vitro substrate depletion studies. Changes in current testing protocols can be expected to result in the collection of higher quality data. However, poorly soluble chemicals are likely to remain a challenge for CLint determination.

Factors associated with reduced infliximab exposure in the treatment of pediatric autoimmune disorders: a cross-sectional prospective convenience sampling study.

BACKGROUND: Inadequate systemic exposure to infliximab (IFX) is associated with treatment failure. This work evaluated factors associated with reduced IFX exposure in children with autoimmune disorders requiring IFX therapy. METHODS: In this single-center cross-sectional prospective study IFX trough concentrations and anti-drug antibodies (ADAs) were measured in serum from children diagnosed with inflammatory bowel disease (IBD) (n = 73), juvenile idiopathic arthritis (JIA) (n = 16), or uveitis (n = 8) receiving maintenance IFX infusions at an outpatient infusion clinic in a tertiary academic pediatric hospital. IFX concentrations in combination with population pharmacokinetic modeling were used to estimate IFX clearance. Patient demographic and clinical data were collected by chart review and evaluated for their relationship with IFX clearance. RESULTS: IFX trough concentrations ranged from 0 to > 40 µg/mL and were 3-fold lower in children with IBD compared to children with JIA (p = 0.0002) or uveitis (p = 0.001). Children with IBD were found to receive lower IFX doses with longer dosing intervals, resulting in dose intensities (mg/kg/day) that were 2-fold lower compared to children with JIA (p = 0.0002) or uveitis (p = 0.02). Use of population pharmacokinetic analysis to normalize for variation in dosing practices demonstrated that increased IFX clearance was associated with ADA positivity (p = 0.004), male gender (p = 0.02), elevated erythrocyte sedimentation rate (ESR) (p = 0.02), elevated c-reactive protein (CRP) (p = 0.001), reduced serum albumin concentrations (p = 0.0005), and increased disease activity in JIA (p = 0.009) and IBD (p ≤ 0.08). No significant relationship between diagnosis and underlying differences in IFX clearance was observed. Multivariable analysis by covariate population pharmacokinetic modeling confirmed increased IFX clearance to be associated with anti-IFX antibody positivity, increased ESR, and reduced serum albumin concentrations. CONCLUSIONS: Enhanced IFX clearance is associated with immunogenicity and inflammatory burden across autoimmune disorders. Higher systemic IFX exposures observed in children with rheumatologic disorders are driven primarily by provider drug dose and interval selection, rather than differences in IFX pharmacokinetics across diagnoses. Despite maintenance IFX dosing at or above the standard recommended range for IBD (i.e., 5 mg/kg every 8 weeks), the dosing intensity used in the treatment of IBD is notably lower than dosing intensities used to treat JIA and uveitis, and may place some children with IBD at risk for suboptimal maintenance IFX exposures necessary for treatment response.

Predicting drug metabolism and pharmacokinetics features of in-house compounds by a hybrid machine-learning model.

We constructed machine learning-based pharmacokinetic prediction models with very high performance. The models were trained on 26138 and 16613 compounds involved in metabolic stability and cytochrome P450 inhibition, respectively. Because the compound features largely differed between the publicly available and in-house compounds, the models learned on the public data could not predict the in-house compounds, suggesting that outside of a certain applicability domain (AD), the prediction results are unreliable and can mislead the design of novel compounds. To exclude the uncertain prediction results, we constructed another machine learning model that determines whether the newly designed compound is inside or outside the AD. The AD was evaluated multi-dimensionally with some explanatory variables: The structural similarities and the probability obtained from the pharmacokinetic prediction model. The accuracy of predicting metabolic stability was 79.9% on the test set, increasing significantly to 93.6% after excluding the low-reliability compounds. The model properly classified the reliability of the compounds. After learning on the in-house compounds, the reliability model classified almost all (90%) of the public compounds as low reliability, indicating that the AD was properly determined by the model.

Feasibility of physiologically based pharmacokinetic simulations for assessing pediatric patients after accidental drug ingestion: A case study of a 1.4-year-old girl who ingested alprazolam.

The accidental ingestion of drugs is a common concern, especially in the case of young children. A physiologically based pharmacokinetic (PBPK) model that implements the age-dependent size growth and ontogeny of organ functions can be used to predict the concentration-time profiles of drugs in the pediatric population. In this study, the feasibility of using a PBPK model for predicting the amount of drug accidentally swallowed by a child was assessed based on a case study in an infant. Alprazolam was the drug involved in the current case. The developed PBPK model of alprazolam was first evaluated using pharmacokinetic data obtained in healthy adult male volunteers. Then, it was adapted for application to virtual Japanese pediatric subjects having the same demographic information as the infant of interest. The pharmacokinetic data observed in the infant fell within the range of the 5th and 95th percentiles of the pharmacokinetic simulations after administration of 0.4 mg alprazolam (equivalent to one tablet) in the panel of virtual infants. PBPK simulations could provide estimates of the amount accidentally ingested by a child and also give mechanistic insights into the observed drug concentrations. The current study demonstrates the potential clinical utility of PBPK modeling.

The fructose-dependent acceleration of ethanol metabolism.

The aim of the present study was to elucidate how fructose is able to increase the rate of ethanol metabolism in the liver, an observation previously termed the fructose effect. Previous studies suggest that an increase in ATP consumption driven by glucose synthesis from fructose stimulates the oxidation of NADH in the mitochondrial respiratory chain, allowing faster oxidation of ethanol by alcohol dehydrogenase; however, this idea has been frequently challenged. We tested the effects of fructose, sorbose and tagatose both in vitro and in vivo. Both ethanol and each sugar were either added to isolated hepatocytes or injected intraperitoneally in the rat. In the in vitro experiments, samples were taken from the hepatocyte suspension in a time-dependent manner and deproteinized with perchloric acid. In the in vivo experiments, blood samples were taken every 15 min and the metabolites were determined in the plasma. These metabolites include ethanol, glucose, glycerol, sorbitol, lactate, fructose and sorbose. Ethanol oxidation by rat hepatocytes was increased by more than 50% with the addition of fructose. The stimulation was accompanied by increased glucose, glycerol, lactate and sorbitol production. A similar effect was observed with sorbose, while tagatose had no effect. The same pattern was observed in the in vivo experiments. This effect was abolished by inhibiting alcohol dehydrogenase with 4-methylpyrazole, whereas inhibition of the respiratory chain with cyanide did not affect the fructose effect. In conclusion, present results provide evidence that, by reducing glyceraldehyde and glycerol and fructose to sorbitol, respectively, NADH is consumed, allowing an increase in the elimination of ethanol. Hence, this effect is not linked to a stimulation of mitochondrial re-oxidation of NADH driven by ATP consumption.

Clinical Investigation of Metabolic and Renal Clearance Pathways Contributing to the Elimination of Fevipiprant Using Probenecid as Perpetrator.

Fevipiprant, an oral, nonsteroidal, highly selective, reversible, and competitive prostaglandin D2 receptor 2 antagonist, is eliminated by glucuronidation and by direct renal excretion predominantly via organic anion transporter (OAT) 3. This study aimed to assess the effect of simultaneous UDP-glucuronosyltransferase (UGT) and OAT3 inhibition by probenecid on the pharmacokinetics of fevipiprant and its acyl glucuronide (AG) metabolite to support the dosing recommendation of fevipiprant in the presence of drugs inhibiting these pathways; however, phase III clinical trial results did not support its submission. This was a single-center, open-label, single-sequence, two-period crossover study in healthy subjects. Liquid chromatography with tandem mass spectrometry was used to measure concentrations of fevipiprant and its AG metabolite in plasma and urine. In the presence of probenecid, the mean maximum concentrations of fevipiprant increased approximately 1.7-fold, and the area under the concentration-time curve in plasma increased approximately 2.5-fold, whereas the mean apparent volume of distribution and the AG metabolite:fevipiprant ratio decreased. The apparent systemic clearance decreased by approximately 60% and the renal clearance decreased by approximately 88% in the presence of probenecid. Using these data and those from previous studies, the relative contribution of OAT and UGT inhibition to the overall effect of probenecid was estimated. Furthermore, a general disposition scheme for fevipiprant was developed, showing how a perpetrator drug such as probenecid, which interferes with two key elimination pathways of fevipiprant, causes only a moderate increase in exposure and allows estimation of the drug-drug inhibition when only one of the two pathways is inhibited. SIGNIFICANCE STATEMENT: In this drug-drug interaction (DDI) study, probenecid was used as a tool to inhibit both glucuronidation and active renal secretion of fevipiprant. The combination of plasma and urine pharmacokinetic data from this study with available data allowed the development of a quantitative scheme to describe the fate of fevipiprant in the body, illustrating why the DDI effect on fevipiprant is weak-to-moderate even if a perpetrator drug inhibits several elimination pathways.

Biopharmaceutics Applications of Physiologically Based Pharmacokinetic Absorption Modeling and Simulation in Regulatory Submissions to the U.S. Food and Drug Administration for New Drugs.

Physiologically based pharmacokinetic (PBPK) absorption modeling and simulation is increasingly used as a tool in drug product development, not only in support of clinical pharmacology applications (e.g., drug-drug interaction, dose selection) but also from quality perspective, enhancing drug product understanding. This report provides a summary of the status and the application of PBPK absorption modeling and simulation in new drug application (NDA) submissions to the U.S. Food and Drug Administration to support drug product quality (e.g., clinically relevant dissolution specifications, active pharmaceutical ingredient (API) particle size distribution specifications). During the 10 years from 2008 to 2018, a total of 24 NDA submissions included the use of PBPK absorption modeling and simulations for biopharmaceutics-related assessment. In these submissions, PBPK absorption modeling and simulation served as an impactful tool in establishing the relationship of critical quality attributes (CQAs) including formulation variables, specifically in vitro dissolution, to the in vivo performance. This article also summarizes common practices in PBPK approaches and proposes future directions for the use of PBPK absorption modeling and simulation in drug product quality assessment.Graphical abstract.

Functional Proliferating Human Hepatocytes: In Vitro Hepatocyte Model for Drug Metabolism, Excretion, and Toxicity.

To develop a functional alternative hepatocyte model for primary human hepatocytes (PHHs) with proliferative property, essential drug metabolic, and transporter functions, proliferating human hepatocytes (ProliHHs) expanded from PHHs were fully characterized in vitro. Herein, ProliHHs generated from multiple PHHs donors could be expanded more than 200-fold within four passages and maintained their metabolic or transporter capacities partially. Furthermore, ProliHHs were able to regain the mature hepatic property after three-dimensional (3D) culture. Particularly, the downregulated mRNA expression and function of three major cytochrome P450 (P450) enzymes (CYP1A2, CYP2B6, and CYP3A4) in the proliferating process (ProliHHs-P) could be recovered by 3D culture. The metabolic variabilities across different PHHs donors could be inherited to their matured ProliHHs (ProliHHs-M). The intrinsic clearances of seven major P450 enzymes in ProliHHs-M correlated well (r = 0.87) with those in PHHs. Also, bile canaliculi structures could be observed in sandwich-cultured ProliHHs (SC-ProliHHs), and the biliary excretion index of four probe compounds [cholyl-lys-fluorescein, 5-(and-6)-carboxy-2', 7'-dichlorofluorescein diacetate (CDF), deuterium-labeled sodium taurocholate acid, and rosuvastatin] in SC-ProliHHs (>10%) were close to sandwich-cultured PHHs. More importantly, both ProliHHs-P and ProliHHs-M could be used to evaluate hepatotoxicity. Therefore, these findings demonstrated that the 3D and sandwich culture system could be used to recover the metabolic and transporter functions in ProliHHs for clearance prediction and cholestasis risk assessment, respectively. Together, ProliHHs could be a promising substitute for PHHs in drug metabolism, transport, and hepatotoxicity screening. SIGNIFICANCE STATEMENT: This report describes the study of drug metabolic capacities, efflux transporter functions, and toxicity assessments of proliferating human hepatocytes (ProliHHs). The metabolic variability in different primary human hepatocyte donors could be inherited by their matured ProliHHs derivatives. Also, ProliHHs could form canalicular networks in sandwich culture and display biliary excretion capacities. More importantly, both the proliferative and maturation statuses of ProliHHs could be used to evaluate hepatotoxicity. Together, ProliHHs were feasible to support drug candidate screening in hepatic metabolism, disposition, and toxicity.

In Vivo Gene Expression Profile of Human Intestinal Epithelial Cells: From the Viewpoint of Drug Metabolism and Pharmacokinetics.

Orally administered drugs are absorbed and metabolized in the intestine. To accurately predict pharmacokinetics in the intestine, it is essential to understand the intestinal expression profiles of the genes related to drug absorption, distribution, metabolism, and excretion (ADME). However, in many previous studies, gene expression analysis in the intestine has been carried out using specimens from patients with cancer. In this study, to obtain more accurate gene expression profiles, biopsy samples were collected under endoscopic observation from the noninflammatory regions of 14 patients with inflammatory bowel disease, and RNA-seq analysis was performed. Gene expression analysis of drug-metabolizing enzymes (cytochromes P450), non-cytochrome P450 enzymes, nuclear receptors, drug-conjugating enzymes (UDP-glucuronosyltransferases and sulfotransferases), and apical and basolateral drug transporters was performed in biopsy samples from the duodenum, ileum, colon, and rectum. The proportions of the cytochromes P450 expressed in the ileum were 25% (CYP3A4), 19% (CYP2C18), and 14% (CYP3A5). CYP3A4 and CYP2C19 were highly expressed in the duodenum and ileum, but not in the colon and rectum. In the ileum, apical transporters such as P-gp, peptide transporter 1, breast cancer resistance protein, MRP2, and ASBT were strongly expressed, and the expression levels of P-gp and ASBT in the ileum were higher than those in other regions. In the ileum, basolateral transporters such as OSTα, OSTß, and MRP3 were strongly expressed. We succeeded in obtaining gene expression profiles of ADME-related genes in human intestinal epithelial cells in vivo. We expect that this information would be useful for accurate prediction of the pharmacokinetics of oral drugs. SIGNIFICANCE STATEMENT: To obtain gene expression profiles of ADME-related genes in human intestinal epithelial cells in vivo, biopsy samples were collected under endoscopic observation from the noninflammatory regions of 14 patients with inflammatory bowel disease, and RNA-seq analysis was performed. Gene expression profiles of drug-metabolizing enzymes (cytochromes P450), non-cytochrome P450 enzymes, nuclear receptors, drug-conjugating enzymes (UDP-glucuronosyltransferases and sulfotransferases), and apical and basolateral drug transporters in biopsy samples from the duodenum, ileum, colon, and rectum were obtained in this study.

Changes of blood-brain-barrier function and transfer of amyloid beta in rats with collagen-induced arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is characterized by synovial inflammation, cartilage damage, and systemic inflammation. RA is also associated with the occurrence of neuroinflammation and neurodegenerative diseases. In this study, the impacts of RA on the function of the blood-brain barrier (BBB) and the disposition of amyloid beta (Aß), including BBB transport and peripheral clearance of Aß, were investigated in rats with collagen-induced arthritis (CIA), an animal model with similarity to clinical and pathological features of human RA. METHODS: CIA was induced in female Lewis rats. In addition to neuroinflammation, the integrity and function of the BBB were examined. The expression of Aß-transporting proteins at brain blood vessels was measured. Blood-to-brain influx and plasma clearance of Aß were determined. RESULTS: Both microgliosis and astrogliosis were significantly increased in the brain of CIA rats, compared with controls. In terms of BBB function, the BBB permeability of sodium fluorescein, a marker compound for BBB integrity, was significantly increased in CIA rats. Moreover, increased expression of matrix metalloproteinase-3 (MMP-3) and MMP-9 and decreased expression of tight junction proteins, zonula occludens-1 (ZO-1) and occludin, were observed in brain microvessels of CIA rats. In related to BBB transport of Aß, protein expression of the receptor of advanced glycation end product (RAGE) and P-glycoprotein (P-gp) was significantly increased in brain microvessels of CIA rats. Notably, much higher expression of RAGE was identified at the arterioles of the hippocampus of CIA rats. Following an intravenous injection of human Aß, significant higher brain influx of Aß was observed in the hippocampus of CIA rats. CONCLUSIONS: Neuroinflammation and the changes of BBB function were observed in CIA rats. The increased RAGE expression at cerebral blood vessels and enhanced blood-to-brain influx of Aß indicate the imbalanced BBB clearance of Aß in RA.