Quantitative Proteomic Map of Enzymes and Transporters in the Human Kidney: Stepping Closer to Mechanistic Kidney Models to Define Local Kinetics

Transporter Expressions as Part of Required Scaling Factor to Support In vitro In vivo Extrapolation for Blood-Brain Barrier Drug Permeability

Access of drugs to the central nervous system is limited by the blood-brain barrier, and this in turn affects drug efficacy/toxicity. To date, most drug discovery optimization paradigms have relied heavily on in vitro transporter assays and preclinical species pharmacokinetic evaluation to provide a qualitative assessment of human brain penetration. Because of the lack of human brain pharmacokinetic data, mechanistic models for preclinical species, combined with in vitro and in silico data, are useful for translation to human. These models require transporter expression data to be measured in both in vitro and in vivo systems. The purpose of this work was to quantify transporter expression and generate scaling factors (SFs) to enable in vitro in vivo extrapolation (IVIVE) of transporter-mediated processes and to support the development of a PBPK model of the brain in rats. SF represents the ratio of abundance of the relevant transporters in the tissue relative to transporter expressing cells. Using quantitative proteomics with QconCAT technology, the expression of human and rat P-gp (ABCB1/Abcb1) and BCRP/Bcrp (ABCG2/Abcg2) was measured in rat brain microvessels, mock and transfected cell lines including, (Madin-Darby canine kidney I (MDCK I), Madin-Darby canine kidney II (MDCK II) and pig kidney epithelial cells (LLC-PK1). P-gp expression ranged from 32 to 71 pmol/mg in rat brain microvessels, exceeding literature values of 14.1-25.2 pmol/mg microvessels proteins. Conversely, Bcrp expression ranged between 0.02-0.27 pmol/mg,proteinslower than the literature range (2-6.2 pmol/mg of proteins). P-gp expression in MDCK I and LLC-PK1 cells transfected with rat Mdr1a was similar (within 1.5-fold) as was human P-gp expression in MDR1 transfected LLC-PK1 and MDCK II cells. The generated SFs were 34.4 and 50.4 for brain P-gp (depending on the cell line used) and 0.53 for brain Bcrp. Endogenous P-gp transporter was detected in MDCK II cell lines when protein expression was measured using a surrogate peptide that was shared across species. The current work provides a framework for proteomics-informed translation of in vitro P-gp and BCRP-related kinetics of drugs and supports the development of PBPK models to predict drug disposition in the brain.

[Precision Medicine for Patients with Renal Cell Carcinoma Based on Drug-metabolizing Enzyme Expression Levels]

Notable advances have recently been achieved in drug therapies for renal cell carcinoma (RCC). Several tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) have been approved for metastatic RCC (mRCC). The current first-line treatment for mRCC involves combination therapies using TKIs and ICIs. However, there is no consensus on which TKI+ICI therapy is best or how to select the appropriate therapy for individual patients with RCC. The kidney expresses various metabolic enzymes, including CYP and uridine diphosphate glucose (UDP)-glucuronosyltransferase (UGT). Although information on CYP and UGT expression in the kidney is limited compared to our understanding of liver expression, the main CYP and UGT subtypes expressed at high levels in the kidney are estimated to be CYP2B6, CYP3A5, CYP4A11, CYP4F2, UGT1A6, UGT1A9, and UGT2B7. In RCC, the expression profiles and levels of these enzymes are somewhat altered compared with normal kidney. The main known subtypes of CYP and UGT in RCC are CYP1B1, CYP3A5, CYP4A11, UGT1A6, UGT1A9, UGT1A10, and UGT2B7. High CYP expression has been reported in several cancers, possibly conferring resistance to anti-cancer drugs including TKIs, due to extensive drug metabolism. Additionally, CYP and UGT expression levels may possibly affect cancer prognosis by metabolizing endogenous substrates, regardless of their role in anti-cancer drug metabolism. In this review, I discuss CYP and UGT expression level profiles in RCC based on previously published papers, including ours, and examine possible relationships between these enzyme expression profiles and treatment outcomes for patients with RCC.

Absolute Membrane Protein Abundance of P-gp, BCRP and MRPs in Term Human Placenta Tissue and Commonly Used Cell Systems: Application in PBPK Modeling of Placental Drug Disposition

The placenta acts as a barrier, excluding noxious substances whilst actively transferring nutrients to the fetus, mediated by various transporters. This study quantified the expression of key placental transporters in term human placenta (n=5) and BeWo, BeWo b30, and JEG-3 placenta cell lines. Combining these results with pregnancy physiologically-based pharmacokinetic (PBPK) modeling, we demonstrate the utility of proteomic analysis for predicting placental drug disposition and fetal exposure. Using targeted proteomics with QconCAT standards, we found significant expression of P-gp, BCRP, MRP2, MRP4, and MRP6 in the human placenta (0.05 - 0.25 pmol/mg membrane protein) with only regional differences observed for P-gp. Unexpectedly, both P-gp and BCRP were below the limit of quantification in the regularly used BeWo cells, indicating that this cell line may not be suitable for the study of placental P-gp and BCRP-mediated transport. In cellular and vesicular overexpression systems, P-gp and BCRP were detectable as expected. Vesicle batches showed consistent P-gp expression correlating with functional activity (N-methyl-quinidine (NMQ) transport). However, BCRP activity (Estrone 3-sulfate (E1S) transport) did not consistently align with expression levels. Incorporating in vitro transporter kinetic data, along with placental transporter abundance, into a PBPK model enabled the evaluation of fetal exposure. Simulation with a hypothetical drug indicated that estimating fetal exposure relies on the intrinsic clearances of relevant transporters. To minimize interlaboratory discrepancies, expression data was generated using consistent proteomic methodologies in the same lab. Integration of this data in pregnancy-PBPK modeling offers a promising tool to investigate maternal, placental and fetal drug exposure. Significance Statement This study quantified the expression of key transporters in human placenta and various placental cell lines, revealing significant expression variations. By integrating these data with PBPK modeling, the study highlights the importance of transporter abundance data in understanding and predicting placental drug disposition.

PharmVar GeneFocus: CYP4F2

The Pharmacogene Variation Consortium (PharmVar) serves as a global repository providing star (*) allele nomenclature for the polymorphic human CYP4F2 gene. CYP4F2 genetic variation impacts the metabolism of vitamin K, which is associated with warfarin dose requirements, and the metabolism of drugs, such as imatinib or fingolimod, and certain endogenous compounds including vitamin E and eicosanoids. This GeneFocus provides a comprehensive overview and summary of CYP4F2 genetic variation including the characterization of 14 novel star alleles, CYP4F2*4 through *17. A description of how haplotype information cataloged by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC) is also provided.

Albumin-Mediated Drug Uptake by Organic Anion Transporter 1/3 Is Real: Implications for the Prediction of Active Renal Secretion Clearance

Modulation of the transport-mediated active uptake by human serum albumin (HSA) for highly protein-bound substrates has been reported and improved the in vitro-to-in vivo extrapolation (IVIVE) of hepatic clearance. However, evidence for the relevance of such a phenomenon in the case of renal transporters is sparse. In this study, transport of renal organic anion transporter 1 or 3 (OAT1/3) substrates into conditionally immortalized proximal tubular epithelial cells transduced with OAT1/3 was measured in the presence and absence of 1 and 4% HSA while keeping the unbound substrate concentration constant (based on measured fraction unbound, fu,inc). In the presence of 4% HSA, the unbound intrinsic active uptake clearance (CLint,u,active) of six highly protein-bound substrates increased substantially relative to the HSA-free control (3.5- to 122-fold for the OAT1 CLint,u,active, and up to 28-fold for the OAT3 CLint,u,active). The albumin-mediated uptake effect (fold increase in CLint,u,active) was more pronounced with highly bound substrates compared to no effect seen for weakly protein-bound substrates adefovir (OAT1-specific) and oseltamivir carboxylate (OAT3-specific). The relationship between OAT1/3 CLint,u,active and fu,inc agreed with the facilitated-dissociation model; a relationship was established between the albumin-mediated fold change in CLint,u,active and fu,inc for both the OAT1 and OAT3, with implications for IVIVE modeling. The relative activity factor and the relative expression factor based on global proteomic quantification of in vitro OAT1/3 expression were applied for IVIVE of renal clearance. The inclusion of HSA improved the bottom-up prediction of the level of OAT1/3-mediated secretion and renal clearance (CLsec and CLr), in contrast to the underprediction observed with the control (HSA-free) scenario. For the first time, this study confirmed the presence of the albumin-mediated uptake effect with renal OAT1/3 transporters; the extent of the effect was more pronounced for highly protein-bound substrates. We recommend the inclusion of HSA in routine in vitro OAT1/3 assays due to considerable improvements in the IVIVE of CLsec and CLr.

Physiologically-Based Pharmacokinetic Modeling and Dosing Optimization of Cefotaxime in Preterm and Term Neonates

BACKGROUND

Cefotaxime is commonly used in treating bacterial infections in neonates. To characterize the pharmacokinetic process in neonates and evaluate different recommended dosing schedules of cefotaxime, a physiologically-based pharmacokinetic (PBPK) model of cefotaxime was established in adults and scaled to neonates.

METHODS

A whole-body PBPK model was built in PK-SIM® software. Three elimination pathways are composed of enzymatic metabolism in the liver, passive filtration through glomerulus, and active tubular secretion mediated by renal transporters. The ontogeny information was applied to account for age-related changes in cefotaxime pharmacokinetics. The established models were verified with realistic clinical data in adults and pediatric populations. Simulations in neonates were conducted and 100 % of the dosing interval where the unbound concentration in plasma was above the minimum inhibitory concentration (fT>MIC) was selected as the target index for dosing regimen evaluation.

RESULTS

The developed PBPK models successfully described the pharmacokinetic process of cefotaxime in adults and were scaled to the pediatric population. Good verification results were achieved in both adults' and neonates' PBPK models, indicating a good predictive performance. The optimal dosage regimen of cefotaxime was proposed according to the postnatal age (PNA) and gestational age (GA) of neonates. For preterm neonates (GA < 36 weeks), dosages of 25 mg/kg every 8 h in PNA 0-6 days and 25 mg/kg every 6 h in PNA 7-28 days were suggested. For term neonates (GA ≥ 36 weeks), dosages of 33 mg/kg every 8 h in PNA 0-6 days and 33 mg/kg every 6 h in PNA 7-28 days were recommended.

CONCLUSIONS

Our study may provide useful experience in practicing PBPK model-informed precision dosing in the pediatric population.

Sex and the Kidney Drug-Metabolizing Enzymes and Transporters: Are Preclinical Drug Disposition Data Translatable to Humans?

Cross-species differences in drug transport and metabolism are linked to poor translation of preclinical pharmacokinetic and toxicology data to humans, often resulting in the failure of new chemical entities (NCEs) during clinical drug development. Specifically, inaccurate prediction of renal clearance and renal accumulation of NCEs due to differential abundance of enzymes and transporters in kidneys can lead to differences in pharmacokinetics and toxicity between experimental animals and humans. We carried out liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based protein quantification of 78 membrane drug-metabolizing enzymes and transporters (DMETs) in the kidney membrane fractions of humans, rats, and mice for characterization of cross-species and sex-dependent differences. In general, majority of DMET proteins were higher in rodents than in humans. Significant cross-species differences were observed in 30 out of 33 membrane DMET proteins quantified in all three species. Although no significant sex-dependent differences were observed in humans, the abundance of 28 and 46 membrane proteins showed significant sex dependence in rats and mice, respectively. These cross-species and sex-dependent quantitative abundance data are valuable for gaining a mechanistic understanding of drug renal disposition and accumulation. Further, these data can also be integrated into systems pharmacology tools, such as physiologically based pharmacokinetic models, to enhance the interpretation of preclinical pharmacokinetic and toxicological data.

Drug-drug interactions that alter the exposure of glucuronidated drugs: Scope, UDP-glucuronosyltransferase (UGT) enzyme selectivity, mechanisms (inhibition and induction), and clinical significance

Drug-drug interactions (DDIs) arising from the perturbation of drug metabolising enzyme activities represent both a clinical problem and a potential economic loss for the pharmaceutical industry. DDIs involving glucuronidated drugs have historically attracted little attention and there is a perception that interactions are of minor clinical relevance. This review critically examines the scope and aetiology of DDIs that result in altered exposure of glucuronidated drugs. Interaction mechanisms, namely inhibition and induction of UDP-glucuronosyltransferase (UGT) enzymes and the potential interplay with drug transporters, are reviewed in detail, as is the clinical significance of known DDIs. Altered victim drug exposure arising from modulation of UGT enzyme activities is relatively common and, notably, the incidence and importance of UGT induction as a DDI mechanism is greater than generally believed. Numerous DDIs are clinically relevant, resulting in either loss of efficacy or an increased risk of adverse effects, necessitating dose individualisation. Several generalisations relating to the likelihood of DDIs can be drawn from the known substrate and inhibitor selectivities of UGT enzymes, highlighting the importance of comprehensive reaction phenotyping studies at an early stage of drug development. Further, rigorous assessment of the DDI liability of new chemical entities that undergo glucuronidation to a significant extent has been recommended recently by regulatory guidance. Although evidence-based approaches exist for the in vitro characterisation of UGT enzyme inhibition and induction, the availability of drugs considered appropriate for use as 'probe' substrates in clinical DDI studies is limited and this should be research priority.

Quantitative Characterization of Clinically Relevant Drug-Metabolizing Enzymes and Transporters in Rat Liver and Intestinal Segments for Applications in PBPK Modeling

Rats are extensively used as a preclinical model for assessing drug pharmacokinetics (PK) and tissue distribution; however, successful translation of the rat data requires information on the differences in drug metabolism and transport mechanisms between rats and humans. To partly fill this knowledge gap, we quantified clinically relevant drug-metabolizing enzymes and transporters (DMETs) in the liver and different intestinal segments of Sprague-Dawley rats. The levels of DMET proteins in rats were quantified using the global proteomics-based total protein approach (TPA) and targeted proteomics. The abundance of the major DMET proteins was largely comparable using quantitative global and targeted proteomics. However, global proteomics-based TPA was able to detect and quantify a comprehensive list of 66 DMET proteins in the liver and 37 DMET proteins in the intestinal segments of SD rats without the need for peptide standards. Cytochrome P450 (Cyp) and UDP-glycosyltransferase (Ugt) enzymes were mainly detected in the liver with the abundance ranging from 8 to 6502 and 74 to 2558 pmol/g tissue. P-gp abundance was higher in the intestine (124.1 pmol/g) as compared to that in the liver (26.6 pmol/g) using the targeted analysis. Breast cancer resistance protein (Bcrp) was most abundant in the intestinal segments, whereas organic anion transporting polypeptides (Oatp) 1a1, 1a4, 1b2, and 2a1 and multidrug resistance proteins (Mrp) 2 and 6 were predominantly detected in the liver. To demonstrate the utility of these data, we modeled digoxin PK by integrating protein abundance of P-gp and Cyp3a2 into a physiologically based PK (PBPK) model constructed using PK-Sim software. The model was able to reliably predict the systemic as well as tissue concentrations of digoxin in rats. These findings suggest that proteomics-informed PBPK models in preclinical species can allow mechanistic PK predictions in animal models including tissue drug concentrations.

Toward systems-informed models for biologics disposition: covariates of the abundance of the neonatal Fc Receptor (FcRn) in human tissues and implications for pharmacokinetic modelling

Biologics are a fast-growing therapeutic class, with intertwined pharmacokinetics and pharmacodynamics, affected by the abundance and function of the FcRn receptor. While many investigators assume adequacy of classical models, such as allometry, for pharmacokinetic characterization of biologics, advocates of physiologically-based pharmacokinetics (PBPK) propose consideration of known systems parameters that affect the fate of biologics to enable a priori predictions, which go beyond allometry. The aim of this study was to deploy a systems-informed modelling approach to predict the disposition of Fc-containing biologics. We used global proteomics to quantify the FcRn receptor [p51 and β₂-microglobulin (B2M) subunits] in 167 samples of human tissue (liver, intestine, kidney and skin) and assessed covariates of its expression. FcRn p51 subunit was highest in liver relative to other tissues, and B2M was 1-2 orders of magnitude more abundant than FcRn p51 across all sets. There were no sex-related differences, while higher expression was confirmed in neonate liver compared with adult liver. Trends of expression in liver and kidney indicated a moderate effect of body mass index, which should be confirmed in a larger sample size. Expression of FcRn p51 subunit was approximately 2-fold lower in histologically normal liver tissue adjacent to cancer compared with healthy liver. FcRn mRNA in plasma-derived exosomes correlated moderately with protein abundance in matching liver tissue, opening the possibility of use as a potential clinical tool. Predicted effects of trends in FcRn abundance in healthy and disease (cancer and psoriasis) populations using trastuzumab and efalizumab PBPK models were in line with clinical observations, and global sensitivity analysis revealed endogenous IgG plasma concentration and tissue FcRn abundance as key systems parameters influencing exposure to Fc-conjugated biologics.

Interplay of Breast Cancer Resistance Protein (Bcrp/Abcg2), Sex, and Fed State in Oral Pharmacokinetic Variability of Furosemide in Rats

Poor and variable oral bioavailability of furosemide (FUR) presents critical challenges in pharmacotherapy. We investigated the interplay of breast cancer resistance protein (Bcrp)-mediated transport, sex, and fed state on FUR pharmacokinetics (PK) in rats. A crossover PK study of FUR (5 mg/kg, oral) was performed in Sprague-Dawley rats (3 males and 3 females), alone or with a Bcrp inhibitor, novobiocin (NOV) (20 mg/kg, oral), in both fed and fasted states. Co-administration of NOV significantly increased FUR extent (AUC) and rate (C_max) of exposure by more than two-fold, which indicates efficient Bcrp inhibition in the intestine. The female rats showed two-fold higher AUC and C_max, and two-fold lower renal clearance of FUR compared to the male rats. The latter was correlated with higher renal abundance of Bcrp and organic anion transporters (Oats) in the male rats compared to age-matched female rats. These findings suggest that the PK of Bcrp and/or Oat substrates could be sex-dependent in rats. Moreover, allometric scaling of rat PK and toxicological data of Bcrp substrates should consider species and sex differences in Bcrp and Oat abundance in the kidney. Considering that Bcrp is abundant in the intestine of rats and humans, a prospective clinical study is warranted to evaluate the effect of Bcrp inhibition on FUR PK. The potential confounding effect of the Bcrp transporter should be considered when FUR is used as a clinical probe of renal organic anion transporter-mediated drug-drug interactions. Unlike human data, no food-effect was observed on FUR PK in rats.

Effect of polyethylene glycol 400 on the pharmacokinetics and tissue distribution of baicalin by intravenous injection based on the enzyme activity of UGT1A8/1A9

Baicalin (BG) is a bioactive flavonoid extracted from the dried root of the medicinal plant, Scutellaria radix (SR) (dicotyledonous family, Labiatae), and has several biological activities. Polyethylene glycol 400 (PEG400) has been used as a suitable solvent for several traditional Chinese medicines (TCM) and is often used as an excipient for the compound preparation of SR. However, the drug-excipient interactions between BG and PEG400 are still unknown. Herein, we evaluated the effect of a single intravenous PEG400 administration on the BG levels of rats using pharmacokinetic and tissue distribution studies. A liver microsome and recombinant enzyme incubation system were used to further confirm the interaction mechanism between PEG400 and UDP-glucuronosyltransferases (UGTs) (UGT1A8 and UGT1A9). The pharmacokinetic study demonstrated that following the co-intravenous administration of PEG400 and BG, the total clearance (CL_z) of BG in the rat plasma decreased by 101.60% (p < 0.05), whereas the area under the plasma concentration-time curve (AUC)_0-t and AUC_0-inf increased by 144.59% (p < 0.05) and 140.05% (p < 0.05), respectively. Additionally, the tissue distribution study showed that the concentration of BG and baicalein-6-O-β-D-glucuronide (B6G) in the tissues increased, whereas baicalein (B) in the tissues decreased, and the total amount of BG and its metabolites in tissues altered following the intravenous administration of PEG400. We further found that PEG400 induced the UGT1A8 and UGT1A9 enzyme activities by affecting the maximum enzymatic velocity (V_max) and Michaelis-Menten constant (K_m) values of UGT1A8 and UGT1A9. In conclusion, our results demonstrated that PEG400 interaction with UGTs altered the pharmacokinetic behaviors and tissue distribution characteristics of BG and its metabolites in rats.

Using a Mathematical Modeling To Simulate Pharmacokinetics and Urinary Glucose Excretion of Luseogliflozin and Explore the Role of SGLT1/2 in Renal Glucose Reabsorption

(1) Purpose: To develop a mathematical model combining physiologically based pharmacokinetic and urinary glucose excretion (PBPK-UGE) to simultaneously predict pharmacokinetic (PK) and UGE changes of luseogliflozin (LUS) as well as to explore the role of sodium-glucose cotransporters (SGLT1 and SGLT2) in renal glucose reabsorption (RGR) in humans. (2) Methods: The PBPK-UGE model was built using physicochemical and biochemical properties, binding kinetics data, affinity to SGLTs for glucose, and physiological parameters of renal tubules. (3) Results: The simulations using this model clarified that SGLT1/2 contributed 15 and 85%, respectively, to RGR in the absence of LUS. However, in the presence of LUS, the contribution proportion of SGLT1 rose to 52-76% in healthy individuals and 55-83% in T2DM patients, and that of SGLT2 reduced to 24-48 and 17-45%, respectively. Furthermore, this model supported the underlying mechanism that only 23-40% inhibition of the total RGR with 5 mg of LUS is resulted from SGLT1's compensatory effect and the reabsorption activity of unbound SGLT2. (4) Conclusion: This PBPK-UGE model can predict PK and UGE in healthy individuals and T2DM patients and can also analyze the contribution of SGLT1/2 to RGR with and without LUS.

Challenges and Opportunities for Improved Drug-Drug Interaction Predictions for Renal OCT2 and MATE1/2-K Transporters

Transporters contribute to renal elimination of drugs; therefore drug disposition can be impacted if transporters are inhibited by comedicant drugs. Regulatory agencies have provided guidelines to assess potential drug-drug interaction (DDI) risk for renal organic cation transporter 2 (OCT2) and multidrug and toxin extrusion 1 and 2-K (MATE1/2-K) transporters. Despite this, there are challenges with translating in vitro data using currently available tools to obtain a quantitative assessment of DDI risk in the clinic. Given the high number of drugs and new molecular entities showing in vitro inhibition toward OCT2 and/or MATE1/2-K and the lack of translation to clinically significant effects, it is reasonable to question whether the current in vitro assay design and modeling practice has led to unnecessary clinical evaluation. The aim of this review is to assess and discuss available in vitro and clinical data along with prediction models intended to provide clinical context of risk, including static models proposed by regulatory agencies and physiologically-based pharmacokinetic models, in order to identify best practices and areas of future opportunity. This analysis highlights that different in vitro assay designs, including substrate and cell systems used, strongly influence the derived concentration of drug producing 50% inhibition values and contribute to high variability observed across laboratories. Furthermore, the lack of sensitive index substrates coupled with specific inhibitors for individual transporters necessitates the use of complex models to evaluate clinical DDI risk.