Simultaneous quantification of the abundance of several cytochrome P450 and uridine 5'-diphospho-glucuronosyltransferase enzymes in human liver microsomes using multiplexed targeted proteomics

In vitro-in vivo scaling of cytochrome P450-mediated metabolic clearance using a relative activity factor approach

Quantitative prediction of hepatic clearance is a key element in predicting the human pharmacokinetic profile in the nonclinical stages. In the present study, we focused on the major cytochrome P450 (P450) isoforms (CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4) and tested a relative activity factor (RAF) method to quantitatively predict in vivo hepatic intrinsic clearance (CLh,int,vivo) and fraction metabolized (fm) by the P450 isoforms directly from an in vitro recombinant P450 system. We selected multiple probe substrates for CYP1A2 (caffeine, tizanidine, phenacetin), CYP2C9 ((S)-acenocoumarol, glimepiride, lornoxicam, tolbutamide, (S)-warfarin), CYP2C19 ((S)-lansoprazole, omeprazole, pantoprazole), CYP2D6 (desipramine, metoprolol, nebivolol, tolterodine), and CYP3A4 (alprazolam, felodipine, midazolam, nisoldipine, sildenafil, triazolam) to calculate the representative RAF value for each P450 isoform based on the in vivo-to-in vitro clearance ratio of the multiple probe substrates. The most pronounced substrate dependency of the RAF values was noted for CYP3A4 (2698 [alprazolam] to 19073 [nisoldipine] pmol P450/kg). Using the geometric mean of the RAF values for each isoform, a within 3-fold prediction of the CLh,int,vivo was obtained for all the 11 test drugs, except glibenclamide, which is a known substrate of hepatic uptake transporters. The fm values of the responsible P450 isoform(s) could be well predicted for mexiletine, tamsulosin, risperidone, celecoxib, and glibenclamide. This simple, practical RAF method can be one of the useful nonclinical methods to estimate the CLh,int,vivo and fm mediated by the major P450 isoforms, which would promote earlier understanding of the impact of genetic polymorphisms and drug-drug interactions on the human pharmacokinetics of the substrate compounds. SIGNIFICANCE STATEMENT: The relative activity factor method has been used for extrapolating in vitro clearance from recombinant systems to liver microsomes, but this study utilized this method to predict in vivo hepatic clearance and fraction metabolized values. By applying relative activity factor values obtained from multiple probe substrates, this study was able to quantitatively predict the in vivo clearances mediated by CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4. This simple, practical method will help optimize metabolic clearances via the major cytochrome P450 isoforms in the nonclinical stages.

Efficient protein quantification in drug metabolism and pharmacokinetics with an accelerated proteomic workflow

Quantifying proteins involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs is essential to improve understanding of their disposition and pharmacokinetics. Proteomics, because of its great versatility, is a widely used approach for protein analysis. However, existing protocols face challenges, such as poor peptide identification in liquid chromatography with tandem mass spectrometry under multiple reaction monitoring mode as well as the time- and labor-intensive nature of detergent-engaged workflows. In this study, we compared and evaluated several targeted ADME proteomic methods, including a novel approach called Fast Surfactant-Treated (FAST). Using FAST in ADME proteome analysis of primary human hepatocytes revealed that most proteins, especially membrane proteins, were efficiently solubilized and digested, with the ionic detergent sodium deoxycholate and rapidly removed during preparation by the incorporation of a centrifugation step following acetonitrile precipitation. Compared with the traditional proteomic workflow involving dithiothreitol reduction and iodoacetamide alkylation, FAST achieved an approximately 4-fold increase in cytochrome P450 and UDP-glucuronosyltransferases quantification and 5-fold increase in transporters, based on endogenous tryptic peptide signals. For specific proteins such as CYP2J2, organic anion transporter, and organic anion transporting polypeptide 1B1, FAST generated peptide quantification peaks with significantly higher signal-to-noise ratios and in a shorter amount of sample processing time. We then further validated the FAST proteomics workflow using the pregnane X receptor agonist rifampicin in human hepatocytes, which revealed that CYP3A4 protein levels were induced to a similar extent as observed in the CYP3A midazolam-1'-hydroxylase activity assay. Altogether, these results suggest that FAST proteomics is a robust, efficient, and versatile method for ADME bioanalysis. SIGNIFICANCE STATEMENT: Quantifying absorption, distribution, metabolism, and excretion (ADME) proteins from in vitro matrices remains a challenge, particularly when speed and efficiency are critical. By incorporating sodium deoxycholate detergent into the ADME proteome sample preparation workflow, we developed a methodology called Fast Surfactant-Treated proteomics. This approach enabled more efficient quantification of drug-metabolizing enzymes and membrane transporters, offering a streamlined protocol with reduced bench time.

PBPK modeling: What is the role of CYP3A4 expression in the gastrointestinal tract to accurately predict first-pass metabolism?

Gastrointestinal first-pass metabolism plays an important role in bioavailability and in drug-drug interactions. Physiologically-based pharmacokinetic (PBPK) modeling is a powerful tool to integrate these processes mechanistically. However, a correct bottom-up prediction of GI first-pass metabolism is challenging and depends on various model parameters like the level of enzyme expression and the basolateral intestinal mucosa permeability (Pmucosa). This work aimed to investigate if cytochrome P450 (CYP) 3A4 expression could help predict the first-pass effect using PBPK modeling or whether additional factors like Pmucosa do play additional roles using PBPK modeling. To this end, a systematic review of the absolute CYP3A expression in the human gastrointestinal tract and liver was conducted. The resulting CYP3A4 expression profile and two previously published profiles were applied to PBPK models of seven CYP3A4 substrates (alfentanil, alprazolam, felodipine, midazolam, sildenafil, triazolam, and verapamil) built-in PK-Sim®. For each compound, it was assessed whether first-pass metabolism could be adequately predicted based on the integrated CYP3A4 expression profile alone or whether an optimization of Pmucosa was required. Evaluation criteria were the precision of the predicted interstudy bioavailabilities and area under the concentration-time curves. It was found that none of the expression profiles provided upfront an adequate description of the extent of GI metabolism and that optimization of Pmucosa as a compound-specific parameter improved the prediction of most models. Our findings indicate that a pure bottom-up prediction of gastrointestinal first-pass metabolism is currently not possible and that compound-specific features like Pmucosa must be considered as well.

Understanding Voriconazole Metabolism: A Middle-Out Physiologically-Based Pharmacokinetic Modelling Framework Integrating In Vitro and Clinical Insights

BACKGROUND AND OBJECTIVE

Voriconazole (VRC), a broad-spectrum antifungal drug, exhibits nonlinear pharmacokinetics (PK) due to saturable metabolic processes, autoinhibition and metabolite-mediated inhibition on their own formation. VRC PK is also characterised by high inter- and intraindividual variability, primarily associated with cytochrome P450 (CYP) 2C19 genetic polymorphism. Additionally, recent in vitro findings indicate that VRC main metabolites, voriconazole N-oxide (NO) and hydroxyvoriconazole (OHVRC), inhibit CYP enzymes responsible for VRC metabolism, adding to its PK variability. This variability poses a significant risk of therapeutic failure or adverse events, which are major challenges in VRC therapy. Understanding the underlying processes and sources of these variabilities is essential for safe and effective therapy. This work aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) modelling framework that elucidates the complex metabolism of VRC and the impact of its metabolites, NO and OHVRC, on the PK of the parent, leveraging both in vitro and in vivo clinical data in a middle-out approach.

METHODS

A coupled parent-metabolite PBPK model for VRC, NO and OHVRC was developed in a stepwise manner using PK-Sim® and MoBi®. Based on available in vitro data, NO formation was assumed to be mediated by CYP2C19, CYP3A4, and CYP2C9, while OHVRC formation was attributed solely to CYP3A4. Both metabolites were assumed to be excreted via renal clearance, with hepatic elimination also considered for NO. Inhibition functions were implemented to describe the complex interaction network of VRC autoinhibition and metabolite-mediated inhibition on each CYP enzyme.

RESULTS

Using a combined bottom-up and middle-out approach, incorporating data from multiple clinical studies and existing literature, the model accurately predicted plasma concentration-time profiles across various intravenous dosing regimens in healthy adults, of different CYP2C19 genotype-predicted phenotypes. All (100%) of the predicted area under the concentration-time curve (AUC) and 94% of maximum concentration (Cmax) values of VRC met the 1.25-fold acceptance criterion, with overall absolute average fold errors of 1.12 and 1.14, respectively. Furthermore, all predicted AUC and Cmax values of NO and OHVRC met the twofold acceptance criterion.

CONCLUSION

This comprehensive parent-metabolite PBPK model of VRC quantitatively elucidated the complex metabolism of the drug and emphasised the substantial impact of the primary metabolites on VRC PK. The comprehensive approach combining bottom-up and middle-out modelling, thereby accounting for VRC autoinhibition, metabolite-mediated inhibition, and the impact of CYP2C19 genetic polymorphisms, enhances our understanding of VRC PK. Moreover, the model can be pivotal in designing further in vitro experiments, ultimately allowing for extrapolation to paediatric populations, enhance treatment individualisation and improve clinical outcomes.

Roles of Individual Human Cytochrome P450 Enzymes in Drug Metabolism

Our knowledge of the roles of individual cytochrome P450 (P450) enzymes in drug metabolism has developed considerably in the past 30 years, and this base has been of considerable use in avoiding serious issues with drug interactions and issues due to variations. Some newer approaches are being considered for "phenotyping" metabolism reactions with new drug candidates. Endogenous biomarkers are being used for noninvasive estimation of levels of individual P450 enzymes. There is also the matter of some remaining "orphan" P450s, which have yet to be assigned reactions. Practical problems that continue in drug development include predicting drug-drug interactions, predicting the effects of polymorphic and other P450 variations, and evaluating interspecies differences in drug metabolism, particularly in the context of "metabolism in safety testing" regulatory issues ["disproportionate (human) metabolites"]. SIGNIFICANCE STATEMENT: Cytochrome P450 enzymes are the major catalysts involved in drug metabolism. The characterization of their individual roles has major implications in drug development and clinical practice.

Physiologically-Based Pharmacokinetic Modeling of Total and Unbound Valproic Acid to Evaluate Dosing in Children With and Without Hypoalbuminemia

BACKGROUND AND OBJECTIVE

Valproic acid (VPA) demonstrates nonlinear pharmacokinetics (PK) due to a capacity-limited protein binding, which has potential implications on its total and unbound plasma concentrations, especially during hypoalbuminemia. A physiologically based pharmacokinetic (PBPK) model was developed to assess the nonlinear dose-exposure relationship of VPA with special emphasis on pediatric patients with hypoalbuminemia.

METHODS

A PBPK model was first developed and evaluated in adults using PK-Sim® and MoBi® (v.11) and the scaled to children 1 year and older. The capacity-limited protein binding was characterized by second-order kinetics between VPA and albumin with a 2:1 molar ratio. All drug-specific parameters were informed by literature and optimized using published PK data of VPA. PK simulations were performed in virtual populations with normal and low albumin levels.

RESULTS

The reported concentration-time profiles of total and unbound VPA were adequately predicted by the PBPK model across the age and dose range (3-120 mg/kg). The model was able to characterize the nonlinear PK, as the concentration-dependent fraction unbound (fu) and the related dose-dependent clearance values were well predicted. Simulated steady-state trough concentrations of total VPA were less than dose-proportional and were within the therapeutic drug monitoring range of 50-100 mg/L for doses between 30 and 45 mg/kg per day in children with normal albumin concentrations. However, virtual children with hypoalbuminemia largely failed to achieve the target exposure.

CONCLUSION

The PBPK model helped assess the nonlinear dose-exposure relationship of VPA and the impact of albumin concentrations on the achievement of target exposure.

Dealing With Variable Drug Exposure Due to Variable Hepatic Metabolism: A Proof-of-Concept Application of Liquid Biopsy in Renal Impairment

Precision dosing strategies require accounting for between-patient variability in pharmacokinetics (PK), affecting drug exposure, and in pharmacodynamics (PD), affecting response achieved at the same drug concentration at the site of action. Although liquid biopsy for assessing different levels of molecular drug targets has yet to be established, individual characterization of drug elimination pathways using liquid biopsy has recently been demonstrated. The feasibility of applying this approach in conjunction with modeling tools to guide individual dosing remains unexplored. In this study, we aimed to individualize physiologically-based pharmacokinetic (PBPK) models based on liquid biopsy measurements in plasma from 25 donors with different grades of renal function who were previously administered oral midazolam as part of a microdose cocktail. Virtual twin models were constructed based on demographics, renal function, and hepatic expression of relevant pharmacokinetic pathways projected from liquid biopsy output. Simulated exposure (AUC) to midazolam was in agreement with observed data (AFE = 1.38, AAFE = 1.78). Simulated AUC variability with three dosing approaches indicated higher variability with uniform dosing (14-fold) and stratified dosing (13-fold) compared with individualized dosing informed by liquid biopsy (fivefold). Further, exosome screening revealed mRNA expression of 532 targets relevant to drug metabolism and disposition (169 enzymes and 361 transporters). Data related to these targets can be used to further individualize PBPK models for pathways relevant to PK of other drugs. This study provides additional verification of liquid biopsy-informed PBPK modeling approaches, necessary to advance strategies that seek to achieve precise dosing from the start of treatment.

Investigating the Correlation between Genotypes and Hepatic Protein Expression of CYP2C9, CYP2C19, CYP2D6, and CYP3A5 Using Postmortem Tissue from a Danish Population

The cytochrome P450 (CYP) family of enzymes plays a central role in the metabolism of many drugs. CYP genes are highly polymorphic, which is known to affect protein levels, but for some low frequent CYP genotypes the correlation between genotype and CYP protein expression is less established. In this study, we determined the CYP2C9, CYP2C19, CYP2D6, and CYP3A5 genotypes of 250 Danish individuals included in a postmortem study. For 116 of the individuals, the hepatic CYP protein levels were investigated by a proteomics approach. Overall, we found the postmortem genetic and proteomic data to be in agreement with those of other studies performed on fresh hepatic tissue, showing the usability of postmortem hepatic tissue for this type of investigation. For less investigated genotypes, we could corroborate previously found results: 1) statistically significantly lower levels of hepatic CYP2C9 protein in individuals carrying the CYP2C9*3 variant compared with individuals with two wild type (wt) alleles; 2) comparable levels of CYP2C19 in CYP2C19*2/*17 and CYP2C19*1/*2 individuals; 3) reduced CYP2D6 protein levels in heterozygous individuals with the CYP2D6*3, CYP2D6*4, and CYP2D6*5 gene deletion variants; and 4) significantly lower levels of CYP3A5 protein in CYP3A5*3 homozygous individuals compared with individuals who were heterozygous for the CYP3A5*3 allele or homozygous individuals for the wt alleles. In conclusion, the use of postmortem tissue significantly increases the access to human specimens for research purposes, and postmortem proteomics can be used to investigate the link between CYP genotypes and hepatic protein expression. SIGNIFICANCE STATEMENT: In tissue samples from a large postmortem cohort (n = 250) we determined the CYP2C9, CYP2C19, CYP2D6, and CYP3A5 genotypes. Hepatic CYP protein levels were investigated in 116 individuals using a proteomics approach. For common genotypes, we found results similar to previous knowledge, pointing toward the usability of postmortem tissue. For the less investigated genotypes, we were able to corroborate genotype/protein expression correlations. It is a novel approach to use a large postmortem cohort to investigate genetic/protein expression correlations.

Morphine concentrations in fatalities after palliative treatment of acute burn injury

The evaluation of a morphine concentration in postmortem blood is routine for a forensic toxicologist. We here report three fatal cases where we found high morphine concentrations with 7.96, 4.30, and 5.82 mg/l in femoral blood that have to be estimated as unusually high. All these individuals died due to severe burn injuries and obtained morphine in the context of their palliative care in the last hours of their lives. According to the autopsy results, the cause of death in case 1 was burn disease with burns of about 90% of the body surface area (BSA), case 2 burn trauma, and case 3 burn shock. Besides morphine, propofol, fentanyl, sufentanil, midazolam, diazepam, lorazepam, cefazolin, and rocuronium were detected in femoral blood. The findings fitted well with the detailed clinical documentation. Further evidence of therapeutic concentrations of quetiapine, duloxetine, and melperone could be matched to preexisting medication of the individuals. Physiologically based pharmacokinetic modelling (PBPK) was applied, developed for the intravenous administration of morphine, to find an explanation for the high morphine concentrations in femoral blood. Quantification of morphine in body fluids and tissue was performed to calculate morphine tissue concentration ratios to the morphine concentration in femoral blood. The presented cases show that pharmacokinetic simulations can reflect decreased renal clearance and decreased hepatic metabolism in general. However, this prediction is not sufficient to explain the high morphine concentrations in femoral blood measured here. It can be assumed that burn shock in particular leads to altered pharmacokinetics, namely decreased distribution of morphine.

Uridine 5'-Diphospho-glucuronosyltransferase 1A3 (UGT1A3) Prediction of Hepatic Clearance of Organic Anion Transporting Polypeptide 1B3 (OATP1B3) Substrate Telmisartan by Glucuronidation Using In Vitro-In Vivo Extrapolation (IVIVE)

BACKGROUND AND OBJECTIVE

The prediction of pharmacokinetic parameters for drugs metabolised by cytochrome P450 enzymes has been the subject of active research for many years, while the application of in vitro-in vivo extrapolation (IVIVE) techniques for non-cytochrome P450 enzymes has not been thoroughly evaluated. There is still no established quantitative method for predicting hepatic clearance of drugs metabolised by uridine 5'-diphospho-glucuronosyltransferases (UGTs), not to mention those which undergo hepatic uptake. The objective of the study was to predict the human hepatic clearance for telmisartan based on in vitro metabolic stability and hepatic uptake results.

METHODS

Telmisartan was examined in liver systems, allowing to estimate intrinsic clearance (CLint, in vitro) based on the substrate disappearance rate with the use of liquid chromatography tandem mass spectrometry (LC-MS/MS) technique. Obtained CLint, in vitro values were corrected for corresponding unbound fractions. Prediction of human hepatic clearance was made from scaled unbound CLint, in vitro data with the use of the well-stirred model, and finally referenced to the literature value of observed clearance in humans, allowing determination of the essential scaling factors.

RESULTS

The in vitro scaled CLint, in vitro by UGT1A3 was assessed using three systems, human hepatocytes, liver microsomes, and recombinant enzymes. Obtained values were scaled and hepatic metabolism clearance was predicted, resulting in significant clearance underprediction. Utilization of the extended clearance concept (ECC) and hepatic uptake improved prediction of hepatic metabolism clearance. The scaling factors for hepatocytes, assessing the in vitro-in vivo difference, changed from sixfold difference to only twofold difference with the application of the ECC.

CONCLUSIONS

The study showed that taking into consideration hepatic uptake of a drug allows us to obtain satisfactory scaling factors, hence enabling the prediction of in vivo hepatic glucuronidation from in vitro data.

Complementarity of two proteomic data analysis tools in the identification of drug-metabolising enzymes and transporters in human liver

Several software packages are available for the analysis of proteomic LC-MS/MS data, including commercial (e.g. Mascot/Progenesis LC-MS) and open access software (e.g. MaxQuant). In this study, Progenesis and MaxQuant were used to analyse the same data set from human liver microsomes (n = 23). Comparison focussed on the total number of peptides and proteins identified by the two packages. For the peptides exclusively identified by each software package, distribution of peptide length, hydrophobicity, molecular weight, isoelectric point and score were compared. Using standard cut-off peptide scores, we found an average of only 65% overlap in detected peptides, with surprisingly little consistency in the characteristics of peptides exclusively detected by each package. Generally, MaxQuant detected more peptides than Progenesis, and the additional peptides were longer and had relatively lower scores. Progenesis-specific peptides tended to be more hydrophilic and basic relative to peptides detected only by MaxQuant. At the protein level, we focussed on drug-metabolising enzymes (DMEs) and transporters, by comparing the number of unique peptides detected by the two packages for these specific proteins of interest, and their abundance. The abundance of DMEs and SLC transporters showed good correlation between the two software tools, but ABC showed less consistency. In conclusion, in order to maximise the use of MS datasets, we recommend processing with more than one software package. Together, Progenesis and MaxQuant provided excellent coverage, with a core of common peptides identified in a very robust way.

Comparative Intra-Subject Analysis of Gene Expression and Protein Abundance of Major and Minor Drug Metabolizing Enzymes in Healthy Human Jejunum and Liver

First pass metabolism by phase I and phase II enzymes in the intestines and liver is a major determinant of the oral bioavailability of many drugs. Several studies analyzed expressions of major drug-metabolizing enzymes (DMEs), such as CYP3A4 and UGT1A1 in the human gut and liver. However, there is still a lack of knowledge regarding other DMEs (i.e., "minor" DMEs), although several clinically relevant drugs are affected by those enzymes. Moreover, there is very limited intra-subject data on hepatic and intestinal expression levels of minor DMEs. To fill this gap of knowledge, we analyzed gene expression (quantitative real-time polymerase chain reaction) and protein abundance (targeted proteomics) of 24 clinically relevant DMEs, that is, carboxylesterases (CES), UDP-glucuronosyltransferases (UGT), and cytochrome P450 (CYP)-enzymes. We performed our analysis using jejunum and liver tissue specimens from the same 11 healthy organ donors (8 men and 3 women, aged 19-60 years). Protein amounts of all investigated DMEs, with the exception of CYP4A11, were detected in human liver samples. CES2, CYP2C18, CYP3A4, and UGT2B17 protein abundance was similar or even higher in the jejunum, and all other DMEs were found in higher amounts in the liver. Significant correlations between gene expression and protein levels were observed only for 2 of 15 jejunal, but 13 of 23 hepatic DMEs. Intestinal and hepatic protein amounts only significantly correlated for CYP3A4 and UGT1A3. Our results demonstrated a notable variability between the individuals, which was even higher in the intestines than in the liver. Our intrasubject analysis of DMEs in the jejunum and liver from healthy donors, may be useful for physiologically-based pharmacokinetic-based modeling and prediction in order to improve efficacy and safety of oral drug therapy.

Recent findings and advancements in the detection of designer benzodiazepines: a brief review

This review article takes a closer look at a new class of psychoactive substances called designer benzodiazepines (DBZs) and the challenges of their detection. These are adinazolam, clonazolam, deschloroetizolam, diclazepam, etizolam, flualprazolam, flubromazepam, flubromazolam, phenazepam, and pyrazolam. They are central nervous system depressants and sedatives that can cause psychomotor impairment and increase the overdose risk when combined with other sedatives. DBZs undergo phase I and II metabolism similar to traditional benzodiazepines, but their specific metabolic pathways and the influence of genetic polymorphisms are yet to be clarified. Advances in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enhanced the method's sensitivity for DBZs and their metabolites in biological samples and coupled with improved blood sampling methods require less blood for drug monitoring. Further research should focus on elucidating their pharmacokinetic properties and metabolism in humans, especially in view of genetic polymorphisms and drug interactions that could inform clinical treatment choices. Even though we have witnessed important advances in DBZ detection and measurement, further refinements are needed to expand the scope of detectable DBZs and their metabolites. All this should help toxicological research to better identify and characterise the risks of chronic and polydrug abuse and facilitate clinical, forensic, and regulatory responses to this growing issue.

Quantitative analysis of the UDP-glucuronosyltransferase transcriptome in human tissues

UDP-glucuronosyltransferases (UGTs) are phase II drug metabolizing enzymes that play important roles in the detoxification of endogenous and exogenous substrates. The 22 human UGTs belong to four families (UGT1, UGT2, UGT3, and UGT8) and differ in their expression, substrate specificity, UDP-sugar preference, and physiological functions. Differential expression/activity of the UGTs contributes to interperson variability in drug responses and toxicity, hormone homeostasis, and disease/cancer risks. However, in normal tissues, the tissue-specific expression profiles and transcriptional regulation of the UGTs are still not fully understood. In this study, we comprehensively analyzed the transcriptome of 22 UGTs in 54 human tissues/regions using RNAseq data from GTEx. We then validated the findings in the liver and small intestine samples using real-time PCR. Our results showed large interindividual variability across tissues in the expression of each UGT and the overall composition of UGT pools, consisting of different UGTs and their splice isoforms. Our results also revealed coexpression of the UGTs, Cytochrome P450s, and many transcription factors in the liver, suggesting potential coregulation or functional coordination. Our results provide the groundwork for future studies to detail further the regulation of the expression and activity of the UGTs.

Quantification of drug metabolising enzymes and transporter proteins in the paediatric duodenum via LC-MS/MS proteomics using a QconCAT technique

Characterising the small intestine absorptive membrane is essential to enable prediction of the systemic exposure of oral formulations. In particular, the ontogeny of key intestinal Drug Metabolising Enzymes and Transporter (DMET) proteins involved in drug disposition needs to be elucidated to allow for accurate prediction of the PK profile of drugs in the paediatric cohort. Using pinch biopsies from the paediatric duodenum (n = 36; aged 11 months to 15 years), the abundance of 21 DMET proteins and two enterocyte markers were quantified via LC-MS/MS. An established LCMS nanoflow method was translated to enable analysis on a microflow LC system, and a new stable-isotope-labelled QconCAT standard developed to enable quantification of these proteins. Villin-1 was used to standardise abundancy values. The observed abundancies and ontogeny profiles, agreed with adult LC-MS/MS-based data, and historic paediatric data obtained via western blotting. A linear trend with age was observed for duodenal CYP3A4 and CES2 only. As this work quantified peptides on a pinch biopsy coupled with a microflow method, future studies using a wider population range are very feasible. Furthermore, this DMET ontogeny data can be used to inform paediatric PBPK modelling and to enhance the understanding of oral drug absorption and gut bioavailability in paediatric populations.

Sex- and Lifestyle-Related Factors are Associated with Altered Hepatic CYP Protein Levels in People Diagnosed with Mental Disorders

In this study, we used human postmortem tissue to investigate hepatic protein expression levels of cytochrome P450 (CYP) 1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4 by LC-MS/MS in a population of people suffering from mental disorders (n = 171). We report hepatic protein levels of these six CYP isoforms in 171 individuals in total, and define a focused population dataset of 116 individuals after excluding 55 samples due to low microsomal protein per gram of liver (MPPGL) yield. Postmortem decay was most likely the reason for the low MPPGL yield in the 55 samples. In the focused population, we found women to have significantly higher protein levels of CYP3A4 than men in addition to decreased CYP3A4 protein levels among obese individuals. Furthermore, MPPGL was negatively correlated with body mass index (BMI). An increase in CYP1A2 protein levels was observed among smokers, and increased CYP2E1 protein levels were observed among individuals with a history of alcohol abuse. Finally, individuals who received phenobarbital (CYP3A4 inducer) had significantly higher CYP3A4 levels. In conclusion, lifestyle-related factors prevalent among people suffering from mental disorders are associated with altered CYP protein levels, which may alter drug metabolism and affect the efficacy of commonly prescribed drugs. Furthermore, this investigation demonstrates that postmortem hepatic tissue can be used to study how lifestyle and effectors affect hepatic CYP-levels in a large cohort of patients. SIGNIFICANCE STATEMENT: Using a large number of postmortem hepatic tissue specimens (n=116) originating from the autopsy of individuals diagnosed with mental disorders, we were able to show that hepatic CYP-levels were affected by alcohol, smoking, BMI, and sex and that MPPGL was affected by BMI. These lifestyle-related changes may alter drug metabolism and affect the efficacy of commonly prescribed drugs. It is a novel approach to use a large postmortem cohort to investigate how lifestyle and effectors affect hepatic CYP-levels.

Development and Validation of a Proteomic Correlation Profiling Technique to Detect and Identify Enzymes Involved in Metabolism of Drugs of Concern

To predict the variation of pharmacological or toxicological effect caused by pharmacokinetic variance, it is important to be able to detect previously unknown and unsuspected enzymes involved in drug metabolism. We investigated the use of proteomic correlation profiling (PCP) as a technique to identify the enzymes involved in metabolism of drugs of concern. By evaluating the metabolic activities of each enzyme (including isoforms of cytochrome P450, uridine 5' diphospho-glucuronosyltransferase, and hydrolases, plus aldehyde oxidase and carbonyl reductase) on their typical substrates using a panel of human liver samples, we were able to show the validity of PCP for this purpose. R or Rs and P values were calculated for the association between the protein abundance profile of each protein and the metabolic rate profile of each typical substrate. For the 18 enzymatic activities examined, 13 of the enzymes reported to be responsible for the reactions had correlation coefficients higher than 0.7 and were ranked first to third. For the remaining five activities, the responsible enzymes had correlation coefficients lower than 0.7 and lower rankings. The reasons for this were diverse, including confounding resulting from low protein abundance ratios, artificially high correlations of other enzymes due to limited sample numbers, the presence of inactive enzyme forms, and genetic polymorphisms. Overall, PCP was able to identify the majority of responsible drug-metabolizing enzymes across several enzyme classes (oxidoreductase, transferase, hydrolase); use of this methodology could allow more timely and accurate identification of unknown drug-metabolizing enzymes. SIGNIFICANCE STATEMENT: Proteomic correlation profiling using samples from individual human donors was proven to be a useful methodology for the identification of enzymes responsible for drug-metabolism. This methodology could accelerate the identification of unknown drug-metabolizing enzymes in the future.

Potential herb‒drug interactions between anti-COVID-19 drugs and traditional Chinese medicine

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread worldwide. Effective treatments against COVID-19 remain urgently in need although vaccination significantly reduces the incidence, hospitalization, and mortality. At present, antiviral drugs including Nirmatrelvir/Ritonavir (PaxlovidTM), Remdesivir, and Molnupiravir have been authorized to treat COVID-19 and become more globally available. On the other hand, traditional Chinese medicine (TCM) has been used for the treatment of epidemic diseases for a long history. Currently, various TCM formulae against COVID-19 such as Qingfei Paidu decoction, Xuanfei Baidu granule, Huashi Baidu granule, Jinhua Qinggan granule, Lianhua Qingwen capsule, and Xuebijing injection have been widely used in clinical practice in China, which may cause potential herb-drug interactions (HDIs) in patients under treatment with antiviral drugs and affect the efficacy and safety of medicines. However, information on potential HDIs between the above anti-COVID-19 drugs and TCM formulae is lacking, and thus this work seeks to summarize and highlight potential HDIs between antiviral drugs and TCM formulae against COVID-19, and especially pharmacokinetic HDIs mediated by metabolizing enzymes and/or transporters. These well-characterized HDIs could provide useful information on clinical concomitant medicine use to maximize clinical outcomes and minimize adverse and toxic effects.

Rationally Engineered CYP3A4 Fluorogenic Substrates for Functional Imaging Analysis and Drug-Drug Interaction Studies

Cytochrome P450 3A4 (CYP3A4) is a key xenobiotic-metabolizing enzyme-mediated drug metabolism and drug-drug interaction (DDI). Herein, an effective strategy was used to rationally construct a practical two-photon fluorogenic substrate for hCYP3A4. Following two-round structure-based substrate discovery and optimization, we have successfully constructed a hCYP3A4 fluorogenic substrate (F8) with desirable features, including high binding affinity, rapid response, excellent isoform specificity, and low cytotoxicity. Under physiological conditions, F8 is readily metabolized by hCYP3A4 to form a brightly fluorescent product (4-OH F8) that can be easily detected by various fluorescence devices. The practicality of F8 for real-time sensing and functional imaging of hCYP3A4 has been examined in tissue preparations, living cells, and organ slices. F8 also demonstrates good performance for high-throughput screening of hCYP3A4 inhibitors and assessing DDI potentials in vivo. Collectively, this study develops an advanced molecular tool for sensing CYP3A4 activities in biological systems, which strongly facilitates CYP3A4-associated fundamental and applied research studies.

Pharmacokinetics of N,N-dimethyltryptamine in Humans

BACKGROUND AND OBJECTIVE

N,N-dimethyltryptamine (DMT) is a psychedelic compound under development for the treatment of major depressive disorder (MDD). This study evaluated the preclinical and clinical pharmacokinetics and metabolism of DMT in healthy subjects.

METHODS

The physiochemical properties of DMT were determined using a series of in vitro experiments and its metabolic profile was assessed using monoamine oxidase (MAO) and cytochrome P450 (CYP) inhibitors in hepatocyte and mitochondrial fractions. Clinical pharmacokinetics results are from the phase I component of a phase I/IIa randomised, double-blind, placebo-controlled, parallel-group, dose-escalation trial (NCT04673383). Healthy adults received single escalating doses of DMT fumarate (SPL026) via a two-phase intravenous (IV) infusion. Dosing regimens were calculated based on pharmacokinetic modelling and predictions with progression to each subsequent dose level contingent upon safety and tolerability.

RESULTS

In vitro clearance of DMT was reduced through the inhibition of MAO-A, CYP2D6 and to a lesser extent CYP2C19. Determination of lipophilicity and plasma protein binding was low, indicating that a high proportion of DMT is available for distribution and metabolism, consistent with the very rapid clinical pharmacokinetics. Twenty-four healthy subjects received escalating doses of DMT administered as a 10-min infusion over the dose range of 9-21.5 mg (DMT freebase). DMT was rapidly cleared for all doses: mean elimination half-life was 9-12 min. All doses were safe and well tolerated and there was no relationship between peak DMT plasma concentrations and body mass index (BMI) or weight.

CONCLUSION

This is the first study to determine, in detail, the full pharmacokinetics profile of DMT following a slow IV infusion in humans, confirming rapid attainment of peak plasma concentrations followed by rapid clearance. These findings provide evidence which supports the development of novel DMT infusion regimens for the treatment of MDD.

CLINICAL TRIAL REGISTRATION

Registered on ClinicalTrials.gov (NCT04673383).

Quantification of Accurate Composition and Total Abundance of Homologous Proteins by Conserved-Plus-Surrogate Peptide Approach: Quantification of UDP Glucuronosyltransferases in Human Tissues

Characterization of accurate compositions and total abundance of homologous drug-metabolizing enzymes, such as UDP glucuronosyltransferases (UGTs), is important for predicting the fractional contribution of individual isoforms involved in the metabolism of a drug for applications in physiologically based pharmacokinetic (PBPK) modeling. Conventional targeted proteomics utilizes surrogate peptides, which often results in high technical and interlaboratory variability due to peptide-specific digestion leading to data inconsistencies. To address this problem, we developed a novel conserved-plus-surrogate peptide (CPSP) approach for determining the accurate compositions and total or cumulative abundance of homologous UGTs in commercially available pooled human liver microsomes (HLM), human intestinal microsomes (HIM), human kidney microsomes (HKM), and human liver S9 (HLS9) fraction. The relative percent composition of UGT1A and UGT2B isoforms in the human liver was 35:5:36:11:13 for UGT1A1:1A3:1A4:1A6:1A9 and 20:32:22:21:5 for UGT2B4:2B7:2B10:2B15:2B17. The human kidney and intestine also showed unique compositions of UGT1As and UGT2Bs. The reproducibility of the approach was validated by assessing correlations of UGT compositions between HLM and HLS9 (R2> 0.91). The analysis of the conserved peptides also provided the abundance for individual UGT isoforms included in this investigation as well as the total abundance (pmol/mg protein) of UGT1As and UGT2Bs across tissues, i.e., 268 and 342 (HLM), 21 and 92 (HIM), and 138 and 99 (HKM), respectively. The CPSP approach could be used for applications in the in-vitro-to-in-vivo extrapolation of drug metabolism and PBPK modeling. SIGNIFICANCE STATEMENT: We quantified the absolute compositions and total abundance of UDP glucuronosyltransferases (UGTs) in pooled human liver, intestine, and kidney microsomes using a novel conserved-plus-surrogate peptide (CPSP) approach. The CPSP approach addresses the surrogate peptide-specific variability in the determination of the absolute composition of UGTs. The data presented in this manuscript are applicable for the estimation of the fraction metabolized by individual UGTs towards better in vitro-to-in vivo extrapolation of UGT-mediated drug metabolism.

Proteomic quantification of receptor tyrosine kinases involved in the development and progression of colorectal cancer liver metastasis

Introduction

Alterations in expression and activity of human receptor tyrosine kinases (RTKs) are associated with cancer progression and in response to therapeutic intervention.

Methods

Thus, protein abundance of 21 RTKs was assessed in 15 healthy and 18 cancerous liver samples [2 primary and 16 colorectal cancer liver metastasis (CRLM)] matched with non-tumorous (histologically normal) tissue, by a validated QconCAT-based targeted proteomic approach.

Results

It was demonstrated, for the first time, that the abundance of EGFR, INSR, VGFR3 and AXL, is lower in tumours relative to livers from healthy individuals whilst the opposite is true for IGF1R. EPHA2 was upregulated in tumour compared with histologically normal tissue surrounding it. PGFRB levels were higher in tumours relative to both histologically normal tissue surrounding tumour and tissues taken from healthy individuals. The abundances of VGFR1/2, PGFRA, KIT, CSF1R, FLT3, FGFR1/3, ERBB2, NTRK2, TIE2, RET, and MET were, however, comparable in all samples. Statistically significant, but moderate correlations were observed (Rs > 0.50, p < 0.05) for EGFR with INSR and KIT. FGFR2 correlated with PGFRA and VGFR1 with NTRK2 in healthy livers. In non-tumorous (histologically normal) tissues from cancer patients, there were correlations between TIE2 and FGFR1, EPHA2 and VGFR3, FGFR3 and PGFRA (p < 0.05). EGFR correlated with INSR, ERBB2, KIT and EGFR, and KIT with AXL and FGFR2. In tumours, CSF1R correlated with AXL, EPHA2 with PGFRA, and NTRK2 with PGFRB and AXL. Sex, liver lobe and body mass index of donors had no impact on the abundance of RTKs, although donor age showed some correlations. RET was the most abundant of these kinases in non-tumorous tissues (~35%), while PGFRB was the most abundant RTK in tumours (~47%). Several correlations were also observed between the abundance of RTKs and proteins relevant to drug pharmacokinetics (enzymes and transporters).

Discussion

DiscussionThis study quantified perturbation to the abundance of several RTKs in cancer and the value generated in this study can be used as input to systems biology models defining liver cancer metastases and biomarkers of its progression.

A simple LC-MS/MS method for the simultaneous quantification of drug metabolic enzymes

OBJECTIVE

The aim of this study is to develop a LC-MS/MS method for the quantitation of seven cytochrome P450 (CYP450) enzymes.

METHODS

A high-performance liquid chromatography-tandem mass spectrometry method was developed using multiple reaction monitoring mode with positive electrospray ionization. The method was validated with selectivity, linearity, stability, accuracy and precious. In addition, the abundance of seven CYP450 enzymes in human liver microsomes and CYP3A4 in placenta were determined using the current method.

RESULTS

The linear range for CYP1A2, CYP2B6 and CYP2C8 was 0.036-3.6 nM and for CYP2C9, CYP2C19, CYP2D6 and CYP3A4 was 0.090-9.0 nM. No interference was found between the blank matrix and each specific peptides. The accuracy and precious results were in accord with the requirement of analytical methods for biological samples in Chinese Pharmacopoeia. In addition, the peptides were stable under current stability conditions. The content of CYP3A4 in placenta and the seven CYP450 enzymes in human liver microsomes were accurately quantified.

CONCLUSION

The developed method is sensitive and specific and can be applied to the quantification of enzymes abundance in different human derived samples like placenta and liver microsomes.

Optimising Fluvoxamine Maternal/Fetal Exposure during Gestation: A Pharmacokinetic Virtual Clinical Trials Study

Fluvoxamine plasma concentrations have been shown to decrease throughout pregnancy. CYP2D6 polymorphisms significantly influence these changes. However, knowledge of an optimum dose adjustment according to the CYP2D6 phenotype is still limited. This study implemented a physiologically based pharmacokinetic modelling approach to assess the gestational changes in fluvoxamine maternal and umbilical cord concentrations. The optimal dosing strategies during pregnancy were simulated, and the impact of CYP2D6 phenotypes on fluvoxamine maternal and fetal concentrations was considered. A significant decrease in fluvoxamine maternal plasma concentrations was noted during gestation. As for the fetal concentration, a substantial increase was noted for the poor metabolisers (PM), with a constant level in the ultrarapid (UM) and extensive (EM) metabolisers commencing from gestation week 20 to term. The optimum dosing regimen suggested for UM and EM reached a maximum dose of 300 mg daily at gestational weeks (GW) 15 and 35, respectively. In contrast, a stable dose of 100 mg daily throughout gestation for the PM is sufficient to maintain the fluvoxamine plasma concentration within the therapeutic window (60-230 ng/mL). Dose adjustment during pregnancy is required for fluvoxamine, particularly for UM and EM, to maintain efficacy throughout the gestational period.

Roles of cytochrome P450 enzymes in pharmacology and toxicology: Past, present, and future

The development of the cytochrome P450 (P450) field has been remarkable in the areas of pharmacology and toxicology, particularly in drug development. Today it is possible to use the knowledge base and relatively straightforward assays to make intelligent predictions about drug disposition prior to human dosing. Much is known about the structures, regulation, chemistry of catalysis, and the substrate and inhibitor specificity of human P450s. Many aspects of drug-drug interactions and side effects can be understood in terms of P450s. This knowledge has also been useful in pharmacy practice, as well as in the pharmaceutical industry and medical practice. However, there are still basic and practical questions to address regarding P450s and their roles in pharmacology and toxicology. Another aspect is the discovery of drugs that inhibit P450 to treat diseases.

Label-Free but Still Constrained: Assessment of Global Proteomic Strategies for the Quantification of Hepatic Enzymes and Transporters

Building and refining pharmacology models require "system" data derived from tissues and in vitro systems analyzed by quantitative proteomics. Label-free global proteomics offers a wide scope of analysis, allowing simultaneous quantification of thousands of proteins per sample. The data generated from such analysis offer comprehensive protein expression profiles that can address existing gaps in models. In this study, we assessed the performance of three widely used label-free proteomic methods, "high N" ion intensity approach (HiN), intensity-based absolute quantification (iBAQ) and total protein approach (TPA), in relation to the quantification of enzymes and transporters in 27 human liver microsomal samples. Global correlations between the three methods were highly significant (R2 > 0.70, P < 0.001, n = 2232 proteins). Absolute abundances of 57 pharmacokinetic targets measured by standard-based label-free methods (HiN and iBAQ) showed good agreement, whereas the TPA overestimated abundances by two- to threefold. Relative abundance distribution of enzymes was similar for the three methods, while differences were observed with TPA in the case of transporters. Variability (CV) was similar across methods, with consistent between-sample relative quantification. The back-calculated amount of protein in the samples based on each method was compared with the nominal protein amount analyzed in the proteomic workflow, revealing overall agreement with data from the HiN method with bovine serum albumin as standard. The findings herein present a critique of label-free proteomic data relevant to pharmacokinetics and evaluate the possibility of retrospective analysis of historic datasets. SIGNIFICANCE STATEMENT: This study provides useful insights for using label-free methods to generate abundance data applicable for populating pharmacokinetic models. The data demonstrated overall correlation between intensity-based label-free proteomic methods (HiN, iBAQ and TPA), whereas iBAQ and TPA overestimated the total amount of protein in the samples. The extent of overestimation can provide a means of normalization to support absolute quantification. Importantly, between-sample relative quantification was consistent (similar variability) across methods.

Quantitative Proteomics of Hepatic Drug-Metabolizing Enzymes and Transporters in Patients with Colorectal Cancer Metastasis

The impact of liver cancer metastasis on protein abundance of 22 drug‐metabolizing enzymes (DMEs) and 25 transporters was investigated using liquid chromatography‐tandem accurate mass spectrometry targeted proteomics. Microsomes were prepared from liver tissue taken from 15 healthy individuals and 18 patients with cancer (2 primary and 16 metastatic). Patient samples included tumors and matching histologically normal tissue. The levels of cytochrome P450 (CYPs 2B6, 2D6, 2E1, 3A4, and 3A5) and uridine 5′‐diphospho‐glucuronosyltransferases (UGTs 1A1, 1A6, 1A9, 2B15, 2B4, and 2B7) were lower in histologically normal tissue from patients relative to healthy controls (up to 6.6‐fold) and decreased further in tumors (up to 21‐fold for CYPs and 58‐fold for UGTs). BSEP and MRPs were also suppressed in histologically normal (up to 3.1‐fold) and tumorous tissue (up to 6.3‐fold) relative to healthy individuals. Abundance of OCT3, OAT2, OAT7, and OATPs followed similar trends (up to 2.9‐fold lower in histologically normal tissue and up to 16‐fold lower in tumors). Abundance of NTCP and OCT1 was also lower (up to 9‐fold). Interestingly, monocarboxylate transporter MCT1 was more abundant (3.3‐fold) in tumors, the only protein target to show this pattern. These perturbations could be attributed to inflammation. Interindividual variability was substantially higher in patients with cancer. Proteomics‐informed physiologically‐based pharmacokinetic (PBPK) models of 50 drugs with different attributes and hepatic extraction ratios (Simcyp) showed substantially lower drug clearance with cancer‐specific parameters compared with default parameters. In conclusion, this study provides values for decreased abundance of DMEs and transporters in liver cancer, which enables using population‐specific abundance for these patients in PBPK modeling.

Optical substrates for drug-metabolizing enzymes: Recent advances and future perspectives

Drug-metabolizing enzymes (DMEs), a diverse group of enzymes responsible for the metabolic elimination of drugs and other xenobiotics, have been recognized as the critical determinants to drug safety and efficacy. Deciphering and understanding the key roles of individual DMEs in drug metabolism and toxicity, as well as characterizing the interactions of central DMEs with xenobiotics require reliable, practical and highly specific tools for sensing the activities of these enzymes in biological systems. In the last few decades, the scientists have developed a variety of optical substrates for sensing human DMEs, parts of them have been successfully used for studying target enzyme(s) in tissue preparations and living systems. Herein, molecular design principals and recent advances in the development and applications of optical substrates for human DMEs have been reviewed systematically. Furthermore, the challenges and future perspectives in this field are also highlighted. The presented information offers a group of practical approaches and imaging tools for sensing DMEs activities in complex biological systems, which strongly facilitates high-throughput screening the modulators of target DMEs and studies on drug/herb‒drug interactions, as well as promotes the fundamental researches for exploring the relevance of DMEs to human diseases and drug treatment outcomes.

PBPK Modelling of Dexamethasone in Patients With COVID-19 and Liver Disease

The aim of the study was to apply Physiologically-Based Pharmacokinetic (PBPK) modelling to predict the effect of liver disease (LD) on the pharmacokinetics (PK) of dexamethasone (DEX) in the treatment of COVID-19. A whole-body PBPK model was created to simulate 100 adult individuals aged 18–60 years. Physiological changes (e.g., plasma protein concentration, liver size, CP450 expression, hepatic blood flow) and portal vein shunt were incorporated into the LD model. The changes were implemented by using the Child-Pugh (CP) classification system. DEX was qualified using clinical data in healthy adults for both oral (PO) and intravenous (IV) administrations and similarly propranolol (PRO) and midazolam (MDZ) were qualified with PO and IV clinical data in healthy and LD adults. The qualified model was subsequently used to simulate a 6 mg PO and 20 mg IV dose of DEX in patients with varying degrees of LD, with and without shunting. The PBPK model was successfully qualified across DEX, MDZ and PRO. In contrast to healthy adults, the simulated systemic clearance of DEX decreased (35%–60%) and the plasma concentrations increased (170%–400%) in patients with LD. Moreover, at higher doses of DEX, the AUC ratio between healthy/LD individuals remained comparable to lower doses. The exposure of DEX in different stages of LD was predicted through PBPK modelling, providing a rational framework to predict PK in complex clinical scenarios related to COVID-19. Model simulations suggest dose adjustments of DEX in LD patients are not necessary considering the low dose administered in the COVID-19 protocol.

Age-Related Change in Hepatic Clearance Inferred from Multiple Population Pharmacokinetic Studies: Comparison with Renal Clearance and Their Associations with Organ Weight and Blood Flow

OBJECTIVE

This study aimed to examine the magnitude of age-related change in hepatic clearance by integrating the data of multiple drugs and to compare this with renal clearance, considering associations with age-related changes in organ weight and blood flow.

METHODS

The results of multiple population pharmacokinetic analyses that detected age-related clearance changes in hepatically eliminated drugs were collected. The relationship between hepatic clearance of the unbound drug and age was then analyzed using the nonlinear least-squares method, adjusting for interdrug differences. The obtained change in hepatic clearance was compared with age-related changes in liver weight and hepatic blood flow in Japanese and Westerners. For comparison, the changes in renal clearance were analyzed similarly.

RESULTS

In total, 18 drugs were analyzed. The hepatic unbound clearance decreased by 32% at age 80 years and by 40% at age 90 years, compared with age 40 years, suggesting that it decreased by 0.80% per year with aging. The rate of the decrease was consistent with decreases in hepatic weight per person or blood flow per person, regardless of ethnicity and sex. Since age-related change in body weight varied somewhat by sex or ethnicity, hepatic weight per body weight was less consistent to account for age-related change in hepatic clearance. As for an index of renal clearance, the changes in inulin clearance with age were similar to those in renal blood flow, with a decrease of 0.97% per year from the age of 40 years.

CONCLUSIONS

Hepatic clearance consistently decreased by 0.80% per year from the age of 40 years, with aging for multiple drugs analyzed in this study. Changes in organ weight and blood flow are considered to be primarily responsible for the age-related changes in hepatic and renal clearance.

The Expression Profiles and Deregulation of UDP-Glycosyltransferase (UGT) Genes in Human Cancers and Their Association with Clinical Outcomes

The human UDP-glycosyltransferase (UGTs) superfamily has 22 functional enzymes that play a critical role in the metabolism of small lipophilic compounds, including carcinogens, drugs, steroids, lipids, fatty acids, and bile acids. The expression profiles of UGT genes in human cancers and their impact on cancer patient survival remains to be systematically investigated. In the present study, a comprehensive analysis of the RNAseq and clinical datasets of 9514 patients from 33 different TCGA (the Genome Cancer Atlas) cancers demonstrated cancer-specific UGT expression profiles with high interindividual variability among and within individual cancers. Notably, cancers derived from drug metabolizing tissues (liver, kidney, gut, pancreas) expressed the largest number of UGT genes (COAD, KIRC, KIRP, LIHC, PAAD); six UGT genes (1A6, 1A9, 1A10, 2A3, 2B7, UGT8) showed high expression in five or more different cancers. Kaplan-Meier plots and logrank tests revealed that six UGT genes were significantly associated with increased overall survival (OS) rates [UGT1A1 (LUSC), UGT1A6 (ACC), UGT1A7 (ACC), UGT2A3 (KIRC), UGT2B15 (BLCA, SKCM)] or decreased OS rates [UGT2B15 (LGG), UGT8 (UVM)] in specific cancers. Finally, differential expression analysis of 611 patients from 12 TCGA cancers identified 16 UGT genes (1A1, 1A3, 1A6, 1A7, 1A8, 1A9, 1A10, 2A1, 2A3, 2B4, 2B7, 2B11, 2B15, 3A1, 3A2, UGT8) that were up/downregulated in at least one cancer relative to normal tissues. In conclusion, our data show widespread expression of UGT genes in cancers, highlighting the capacity for intratumoural drug metabolism through the UGT conjugation pathway. The data also suggests the potentials for specific UGT genes to serve as prognostic biomarkers or therapeutic targets in cancers.

Comparison on Metabolism of Estradiol and Its 17-Sulfate by Recombinant Human CYP Isoforms

To identify the CYP isoforms involved in the production of 2-hydroxyestradiol 17-sulfate (2-OH-ES), which we assume to be an antioxidant in vivo, the 2-hydroxylation reaction of estradiol 17-sulfate (ES) by human liver microsome was investigated. As a result, it was estimated that CYP2C8 and 2C9 were largely involved in the production of 2-OH-ES. Therefore, the 2-hydroxylation kinetic analysis of ES was performed for both CYPs, and the metabolic clearance V_max/K_m (µL/nmol CYP/min) was determined. On comparing the results of ES with those of estradiol (E2), it was found that CYP2C8 was about 2.5 times higher and CYP2C9 was about 3 times higher, and ES was more likely to be a substrate for the 2-hydroxylation reaction by both CYPs. The CYP isoforms involved in A-ring hydroxylation of E2 and ES differed. From this, it was speculated that 2-OH-ES plays a different role to 2-hydroxyestradiol (2-OH-E2), which is recognized as an antioxidant in the body.

Characterization of Hepatic UDP-Glucuronosyltransferase Enzyme Abundance-Activity Correlations and Population Variability Using a Proteomics Approach and Comparison with Cytochrome P450 Enzymes

The expression of ten major drug-metabolizing UDP-glucuronosyltransferase (UGT) enzymes in a panel of 130 human hepatic microsomal samples was measured using a liquid chromatography-tandem mass spectrometry-based approach. Simultaneously, ten cytochromes P450 and P450 reductase were also measured, and activity-expression relationships were assessed for comparison. The resulting data sets demonstrated that, with the exception of UGT2B17, 10th to 90th percentiles of UGT expression spanned 3- to 8-fold ranges. These ranges were small relative to ranges of reported mean UGT enzyme expression across different laboratories. We tested correlation of UGT expression with enzymatic activities using selective probe substrates. A high degree of abundance-activity correlation (Spearman's rank correlation coefficient > 0.6) was observed for UGT1As (1A1, 3, 4, 6) and cytochromes P450. In contrast, protein abundance and activity did not correlate strongly for UGT1A9 and UGT2B enzymes (2B4, 7, 10, 15, and 17). Protein abundance was strongly correlated for UGTs 2B7, 2B10, and 2B15. We suggest a number of factors may contribute to these differences including incomplete selectivity of probe substrates, correlated expression of these UGT2B isoforms, and the impact of splice and polymorphic variants on the peptides used in proteomics analysis, and exemplify this in the case of UGT2B10. Extensive correlation analyses identified important criteria for validating the fidelity of proteomics and enzymatic activity approaches for assessing UGT variability, population differences, and ontogenetic changes. SIGNIFICANCE STATEMENT: Protein expression data allow detailed assessment of interindividual variability and enzyme ontogeny. This study has observed that expression and enzyme activity are well correlated for hepatic UGT1A enzymes and cytochromes P450. However, for the UGT2B family, caution is advised when assuming correlation of expression and activity as is often done in physiologically based pharmacokinetic modeling. This can be due to incomplete probe substrate specificities, but may also be related to presence of inactive UGT protein materials and the effect of splicing variations.

Gene Expression and Protein Abundance of Hepatic Drug Metabolizing Enzymes in Liver Pathology

Hepatic drug metabolizing enzymes (DMEs) markedly affect drug pharmacokinetics. Because liver diseases may alter enzymatic function and in turn drug handling and clinical efficacy, we investigated DMEs expression in dependence on liver pathology and liver failure state. In 5 liver pathologies (hepatitis C, alcoholic liver disease, autoimmune hepatitis, primary biliary cholangitis and primary sclerosing cholangitis) and for the first time stratified according to the Child–Pugh score, 10 CYPs (CYP1A1, CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4 and CYP3A5) and 4 UGTs (UGT1A1, UGT1A3, UGT2B7 and UGT2B) enzymes were quantified for protein abundance (LC-MS/MS) and gene expression (qRT-PCR). CYP2E1 was the most vulnerable enzyme, and its protein levels were significantly reduced just in Child–Pugh class A livers. The protein abundance of CYP1A1, CYP2B6, CYP2C19, CYP2D6 as well as UGT1A1, UGT1A3 and UGT2B15 was relatively stable in the course of progression of liver function deterioration. Alcoholic liver disease and primary biliary cholangitis were involved in the most prominent changes in the protein abundances, with downregulation of 6 (CYP1A2, CYP2C8, CYP2D6, CYP2E1, CYP3A4, UGT2B7) and 5 (CYP1A1, CYP2B6, CYP2C8, CYP2E1, CYP3A4) significantly downregulated enzymes, respectively. The results of the study demonstrate that DMEs protein abundance is affected both by the type of liver pathology as well as functional state of the organ.

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

The applications of translational modeling of local drug concentrations in various organs had a sharp increase over the last decade. These are part of the model-informed drug development initiative, adopted by the pharmaceutical industry and promoted by drug regulatory agencies. With respect to the kidney, the models serve as a bridge for understanding animal vs. human observations related to renal drug disposition and any consequential adverse effects. However, quantitative data on key drug-metabolizing enzymes and transporters relevant for predicting renal drug disposition are limited. Using targeted and global quantitative proteomics, we determined the abundance of multiple enzymes and transporters in 20 human kidney cortex samples. Nine enzymes and 22 transporters were quantified (8 for the first time in the kidneys). In addition, > 4,000 proteins were identified and used to form an open database. CYP2B6, CYP3A5, and CYP4F2 showed comparable, but generally low expression, whereas UGT1A9 and UGT2B7 levels were the highest. Significant correlation between abundance and activity (measured by mycophenolic acid clearance) was observed for UGT1A9 (Rs = 0.65, P = 0.004) and UGT2B7 (Rs = 0.70, P = 0.023). Expression of P-gp ≈ MATE-1 and OATP4C1 transporters were high. Strong intercorrelations were observed between several transporters (P-gp/MRP4, MRP2/OAT3, and OAT3/OAT4); no correlation in expression was apparent for functionally related transporters (OCT2/MATEs). This study extends our knowledge of pharmacologically relevant proteins in the kidney cortex, with implications on more prudent use of mechanistic kidney models under the general framework of quantitative systems pharmacology and toxicology.

Evaluation of the effect of Bovis Calculus Artifactus on eight rat liver cytochrome P450 isozymes using LC-MS/MS and cocktail approach

Bovis Calculus Artifactus (BCA) is the main substitute for natural Calculus bovis, a traditional drug in China used to treat high fever, convulsion, and sore throat. The effect of BCA on cytochrome P450 (CYP) activities is unknown. This study was to investigate the effect of BCA on eight rat hepatic microsomal CYPisozymes to evaluate the potential drug interactions using the cocktail approach.Metabolites of the eight isoform probe substrates of CYP isozymes were quantified by LC-MS/MS. The method was validated by incubating known CYP inhibitors α-naphthoflavone (CYP1A2), thiotepa (CYP2B1), quercetin (CYP2C7), sulfaphenazole (CYP2C6), ticlopidine (CYP2C11), quinidine (CYP2D1), ketoconazole (CYP3A1),4-methylpyrazole (CYP2E1) with individual probe substrate and rat liver microsomes. The formation rates of the corresponding metabolites of the eight probe substrates were determined to evaluate the activity of each isozyme.The results showed that BCA has different degrees of inhibitory effect on four CYP450 isoforms (CYP2C6, CYP2C11, CYP2D1, CYP3A1) (p < 0.05), but no significant influence on CYP1A2, 2B1, 2C7 or 2E1 (p > 0.05). Attention should be paid to the BCA-drug interactions by careful monitoring and appropriate dosage adjustments in the concurrent use of the drugs which are metabolized by CYP1A2, CYP2C19, and CYP3A4. Abbreviations: BCA, bovis calculus artifactus; CYP, cytochrome P450; DDIs, drug-drug interactions; ESI, electrospray ionization; MRM, multiple reaction monitoring; NBC, Natural Bovis Calculus; QC, quality control; T CM, traditional Chinese medicine.

Mass spectrometry-based targeted proteomics method for the quantification of clinically relevant drug metabolizing enzymes in human specimens

Biotransformation by phase I and II metabolizing enzymes represents the major determinant for the oral bioavailability of many drugs. To estimate the pharmacokinetics, data on protein abundance of hepatic and extrahepatic tissues, such as the small intestine, are required. Targeted proteomics assays are nowadays state-of-the-art for absolute protein quantification and several methods for quantification of drug metabolizing enzymes have been published. However, some enzymes remain still uncovered by the analytical spectra of those methods. Therefore, we developed and validated a quantification assay for two carboxylesterases (CES-1, CES-2), 17 cytochrome P450 enzymes (CYP) (CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C18, CYP2C19, CYP2D6, CYP2E1, CYP2J2, CYP3A4, CYP3A5, CYP3A7, CYP4F2, CYP4F12, CYP4A11) and five UDP-glucuronosyltransferases (UGTs) (UGT1A1, UGT1A3, UGT2B7, UGT2B15, UGT2B17). Protein quantification was performed by analyzing proteospecific surrogate peptides after tryptic digestion with stable isotope-labelled standards. Chromatographic separation was performed on a Kinetex® 2.6 µm C18 100 Å core-shell column (100 × 2.1 mm) with a gradient elution using 0.1% formic acid and acetonitrile containing 0.1% formic acid with a flow rate of 200 µl/min. Three mass transitions were simultaneously monitored with a scheduled multiple reaction monitoring (sMRM) method for each analyte and standard. The method was partly validated according to current bioanalytical guidelines and met the criteria regarding linearity (0.1-25 nmol/L), within-day and between-day accuracy and precision as well as multiple stability criteria. Finally, the developed method was successfully applied to determine the abundance of the aforementioned enzymes in human intestinal und liver microsomes. Our work offers a new fit for purpose method for the absolute quantification of CES, CYPs and UGTs in various human tissues and can be used for the acquisition of data for physiologically based pharmacokinetic modelling.

Physiologically Based Pharmacokinetic Modelling to Identify Pharmacokinetic Parameters Driving Drug Exposure Changes in the Elderly

BACKGROUND

Medication use is highly prevalent with advanced age, but clinical studies are rarely conducted in the elderly, leading to limited knowledge regarding age-related pharmacokinetic changes.

OBJECTIVE

The objective of this study was to investigate which pharmacokinetic parameters determine drug exposure changes in the elderly by conducting virtual clinical trials for ten drugs (midazolam, metoprolol, lisinopril, amlodipine, rivaroxaban, repaglinide, atorvastatin, rosuvastatin, clarithromycin and rifampicin) using our physiologically based pharmacokinetic (PBPK) framework.

METHODS

PBPK models for all ten drugs were developed in young adults (20-50 years) following the best practice approach, before predicting pharmacokinetics in the elderly (≥ 65 years) without any modification of drug parameters. A descriptive relationship between age and each investigated pharmacokinetic parameter (peak concentration [C_max], time to C_max [t_max], area under the curve [AUC], clearance, volume of distribution, elimination-half-life) was derived using the final PBPK models, and verified with independent clinically observed data from 52 drugs.

RESULTS

The age-related changes in drug exposure were successfully simulated for all ten drugs. Pharmacokinetic parameters were predicted within 1.25-fold (70%), 1.5-fold (86%) and 2-fold (100%) of clinical data. AUC increased progressively by 0.9% per year throughout adulthood from the age of 20 years, which was explained by decreased clearance, while C_max, t_max and volume of distribution were not affected by human aging. Additional clinical data of 52 drugs were contained within the estimated variability of the established age-dependent correlations for each pharmacokinetic parameter.

CONCLUSION

The progressive decrease in hepatic and renal blood flow, as well as glomerular filtration, rate led to a reduced clearance driving exposure changes in the healthy elderly, independent of the drug.

A latent variable approach to account for correlated inputs in global sensitivity analysis

In drug development decision-making is often supported through model-based methods, such as physiologically-based pharmacokinetics (PBPK). Global sensitivity analysis (GSA) is gaining use for quality assessment of model-informed inference. However, the inclusion and interpretation of correlated factors in GSA has proven an issue. Here we developed and evaluated a latent variable approach for dealing with correlated factors in GSA. An approach was developed that describes the correlation between two model inputs through the causal relationship of three independent factors: the latent variable and the unique variances of the two correlated parameters. The latent variable approach was applied to a set of algebraic models and a case from PBPK. Then, this method was compared to Sobol’s GSA assuming no correlations, Sobol’s GSA with groups and the Kucherenko approach. For the latent variable approach, GSA was performed with Sobol’s method. By using the latent variable approach, it is possible to devise a unique and easy interpretation of the sensitivity indices while maintaining the correlation between the factors. Compared methods either consider the parameters independent, group the dependent variables into one unique factor or present difficulties in the interpretation of the sensitivity indices. In situations where GSA is called upon to support model-informed decision-making, the latent variable approach offers a practical method, in terms of ease of implementation and interpretability, for applying GSA to models with correlated inputs that does not violate the independence assumption. Prerequisites and limitations of the approach are discussed.

Pharmacokinetics of the CYP3A4 and CYP2B6 Inducer Carbamazepine and Its Drug-Drug Interaction Potential: A Physiologically Based Pharmacokinetic Modeling Approach

The anticonvulsant carbamazepine is frequently used in the long-term therapy of epilepsy and is a known substrate and inducer of cytochrome P450 (CYP) 3A4 and CYP2B6. Carbamazepine induces the metabolism of various drugs (including its own); on the other hand, its metabolism can be affected by various CYP inhibitors and inducers. The aim of this work was to develop a physiologically based pharmacokinetic (PBPK) parent-metabolite model of carbamazepine and its metabolite carbamazepine-10,11-epoxide, including carbamazepine autoinduction, to be applied for drug-drug interaction (DDI) prediction. The model was developed in PK-Sim, using a total of 92 plasma concentration-time profiles (dosing range 50-800 mg), as well as fractions excreted unchanged in urine measurements. The carbamazepine model applies metabolism by CYP3A4 and CYP2C8 to produce carbamazepine-10,11-epoxide, metabolism by CYP2B6 and UDP-glucuronosyltransferase (UGT) 2B7 and glomerular filtration. The carbamazepine-10,11-epoxide model applies metabolism by epoxide hydroxylase 1 (EPHX1) and glomerular filtration. Good DDI performance was demonstrated by the prediction of carbamazepine DDIs with alprazolam, bupropion, erythromycin, efavirenz and simvastatin, where 14/15 DDI AUClast ratios and 11/15 DDI Cmax ratios were within the prediction success limits proposed by Guest et al. The thoroughly evaluated model will be freely available in the Open Systems Pharmacology model repository.

Enzyme Kinetics of Uridine Diphosphate Glucuronosyltransferases (UGTs)

Glucuronidation, catalyzed by uridine diphosphate glucuronosyltransferases (UGTs), is an important process for the metabolism and clearance of many lipophilic chemicals, including drugs, environmental chemicals, and endogenous compounds. Glucuronidation is a bisubstrate reaction that requires the aglycone and the cofactor, UDP-GlcUA. Accumulating evidence suggests that the bisubstrate reaction follows a compulsory-order ternary mechanism. To simplify the kinetic modeling of glucuronidation reactions in vitro, UDP-GlcUA is usually added to incubations in large excess. Many factors have been shown to influence UGT activity and kinetics in vitro, and these must be accounted for during experimental design and data interpretation. While the assessment of drug-drug interactions resulting from UGT inhibition has been challenging in the past, the increasing availability of UGT enzyme-selective substrate and inhibitor "probes" provides the prospect for more reliable reaction phenotyping and assessment of drug-drug interaction potential. Although extrapolation of the in vitro intrinsic clearance of a glucuronidated drug often underpredicts in vivo clearance, careful selection of in vitro experimental conditions and inclusion of extrahepatic glucuronidation may improve the predictivity of in vitro-in vivo extrapolation. Physiologically based pharmacokinetic (PBPK) modeling has also shown to be of value for predicting PK of drugs eliminated by glucuronidation.

Liquid Biopsy Enables Quantification of the Abundance and Interindividual Variability of Hepatic Enzymes and Transporters

Variability in individual capacity for hepatic elimination of therapeutic drugs is well recognized and is associated with variable expression and activity of liver enzymes and transporters. Although genotyping offers some degree of stratification, there is often large variability within the same genotype. Direct measurement of protein expression is impractical due to limited access to tissue biopsies. Hence, determination of variability in hepatic drug metabolism and disposition using liquid biopsy (blood samples) is an attractive proposition during drug development and in clinical practice. This study used a multi-"omic" strategy to establish a liquid biopsy technology intended to assess hepatic capacity for metabolism and disposition in individual patients. Plasma exosomal analysis (n = 29) revealed expression of 533 pharmacologically relevant genes at the RNA level, with 147 genes showing evidence of expression at the protein level in matching liver tissue. Correction of exosomal RNA expression using a novel shedding factor improved correlation against liver protein expression for 97 liver-enriched genes. Strong correlation was demonstrated for 12 key drug-metabolizing enzymes and 4 drug transporters. The developed test allowed reliable patient stratification, and in silico trials demonstrated utility in adjusting drug dose to achieve similar drug exposure between patients with variable hepatic elimination. Accordingly, this approach can be applied in characterization of volunteers prior to enrollment in clinical trials and for patient stratification in clinical practice to achieve more precise individual dosing.

The N6-methyladenosine modification posttranscriptionally regulates hepatic UGT2B7 expression

UDP-glucuronosyltransferases (UGTs) are enzymes catalyzing the glucuronidation of various endogenous and exogenous compounds. In this study, we examined the possibility that N⁶-methyladenosine (m⁶A) modification affects hepatic UGT expression. Treatment of HepaRG cells with 3-deazaadenosine, an inhibitor of RNA methylation, significantly increased UGT1A1, UGT1A3, UGT1A4, UGT1A9, UGT2B7, UGT2B10, and UGT2B15 mRNA levels (1.3- to 2.6-fold). Among them, we focused on UGT2B7 because it most highly contributes to glucuronidation of clinically used drugs. Methylated RNA immunoprecipitation assays revealed that UGT2B7 mRNA in HepaRG cells and human livers is subjected to m⁶A modification mainly at the 5' untranslated region (UTR) and secondarily at the 3'UTR. UGT2B7 mRNA and protein levels in Huh-7 cells were significantly increased by double knockdown of methyltransferase-like 3 (METTL3) and METTL14, whereas those were decreased by knockdown of fat mass and obesity-associated protein (FTO) or alkB homolog 5, RNA demethylase (ALKBH5), suggesting that m⁶A modification downregulates UGT2B7 expression. By experiments using actinomycin D, an inhibitor of transcription, it was demonstrated that ALKBH5-mediated demethylation would attenuate UGT2B7 mRNA degradation, whereas METTL3/METTL14 or FTO-mediated m⁶A modification would alter the transactivity of UGT2B7. Luciferase assays revealed that the promoter region at -118 to -106 has a key role in the decrease in transactivity of UGT2B7 by FTO knockdown. We found that hepatocyte nuclear factor 4α (HNF4α) expression was significantly decreased by knockdown of FTO, indicating that this would be the underlying mechanism of the decreased transactivity of UGT2B7 by knockdown of FTO. Interestingly, treatment with entacapone, which is used for the treatment of Parkinson's disease and is an inhibitor of FTO, decreased HNF4α and UGT2B7 expression. In conclusion, this study clarified that RNA methylation posttranscriptionally controls hepatic UGT2B7 expression.

Expression of cytochrome P450 isozyme transcripts and activities in human livers

Individual differences in cytochrome P450 (CYP) enzymes contribute to responses to drugs and environmental chemicals. The expression of CYPs is influenced by sex, age, and ethnicity. Human CYP studies are often conducted with human liver microsomes and liver cells to evaluate chemical induction and drug interactions. However, the basal or constitutive expression of CYP transcripts and enzyme activities in the intact liver are also important in our understanding of individual variation in CYPs. This study utilised 100 human liver samples to profile the constitutive expression of CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 3A4, and 4A11 enzyme activity and transcript levels. The mRNA expression of the CYPs and xenobiotic receptors AhR, CAR, and PXR was examined via qPCR. Results showed that there was greater inter-individual variation in mRNA expression than in enzyme activities, except for CYP2C19. Females had higher CYP3A4 activity than males. Children had lower CYP4A14 activity, while elderly had lower P450 oxidoreductase activity. Compared to Caucasians, Hispanics had higher CYP2C8 activity and higher CYP2B6, CYP2C9, and CYP2C19 mRNA expression, whereas African Americans had lower CYP2D6 mRNA expression. These results add to our understanding of individual variations in xenobiotic metabolism and toxicology.

Drug-Drug Interactions Involving Intestinal and Hepatic CYP1A Enzymes

Cytochrome P450 (CYP) 1A enzymes are considerably expressed in the human intestine and liver and involved in the biotransformation of about 10% of marketed drugs. Despite this doubtless clinical relevance, CYP1A1 and CYP1A2 are still somewhat underestimated in terms of unwanted side effects and drug–drug interactions of their respective substrates. In contrast to this, many frequently prescribed drugs that are subjected to extensive CYP1A-mediated metabolism show a narrow therapeutic index and serious adverse drug reactions. Consequently, those drugs are vulnerable to any kind of inhibition or induction in the expression and function of CYP1A. However, available in vitro data are not necessarily predictive for the occurrence of clinically relevant drug–drug interactions. Thus, this review aims to provide an up-to-date summary on the expression, regulation, function, and drug–drug interactions of CYP1A enzymes in humans.

Quantification of Proteins Involved in Intestinal Epithelial Handling of Xenobiotics

The intestinal epithelium represents a natural barrier against harmful xenobiotics, while facilitating the uptake of nutrients and other substances. Understanding the interaction of chemicals with constituents of the intestinal epithelium and their fate in the body requires quantitative measurement of relevant proteins in in vitro systems and intestinal epithelium. Recent studies have highlighted the mismatch between messenger RNA (mRNA) and protein abundance for several drug‐metabolizing enzymes and transporters in the highly dynamic environment of the intestinal epithelium; mRNA abundances cannot therefore be used as a proxy for protein abundances in the gut, necessitating direct measurements. The objective was to determine the expression of a wide range proteins pertinent to metabolism and disposition of chemicals and nutrients in the intestinal epithelium. Ileum and jejunum biopsy specimens were obtained from 16 patients undergoing gastrointestinal elective surgery. Mucosal fractions were prepared and analyzed using targeted and global proteomic approaches. A total of 29 enzymes, 32 transporters, 6 tight junction proteins, 2 adhesion proteins, 1 alkaline phosphatase, 1 thioredoxin, 5 markers, and 1 regulatory protein were quantified—60 for the first time. The global proteomic method identified a further 5,222 proteins, which are retained as an open database for interested parties to explore. This study significantly expands our knowledge of a wide array of proteins important for xenobiotic handling in the intestinal epithelium. Quantitative systems biology models will benefit from the novel systems data generated in the present study and the translation path offered for in vitro to in vivo translation.

Characterization of Differential Tissue Abundance of Major Non-CYP Enzymes in Human

The availability of assays that predict the contribution of cytochrome P450 (CYP) metabolism allows for the design of new chemical entities (NCEs) with minimal oxidative metabolism. These NCEs are often substrates of non-CYP drug-metabolizing enzymes (DMEs), such as UDP-glucuronosyltransferases (UGTs), sulfotransferases (SULTs), carboxylesterases (CESs), and aldehyde oxidase (AO). Nearly 30% of clinically approved drugs are metabolized by non-CYP enzymes. However, knowledge about the differential hepatic versus extrahepatic abundance of non-CYP DMEs is limited. In this study, we detected and quantified the protein abundance of eighteen non-CYP DMEs (AO, CES1 and 2, ten UGTs, and five SULTs) across five different human tissues. AO was most abundantly expressed in the liver and to a lesser extent in the kidney; however, it was not detected in the intestine, heart, or lung. CESs were ubiquitously expressed with CES1 being predominant in the liver, while CES2 was enriched in the small intestine. Consistent with the literature, UGT1A4, UGT2B4, and UGT2B15 demonstrated liver-specific expression, whereas UGT1A10 expression was specific to the intestine. UGT1A1 and UGT1A3 were expressed in both the liver and intestine; UGT1A9 was expressed in the liver and kidney; and UGT2B17 levels were significantly higher in the intestine than in the liver. All five SULTs were detected in the liver and intestine, and SULT1A1 and 1A3 were detected in the lung. Kidney abundance was the most variable among the studied tissues, and overall, high interindividual variability (>15-fold) was observed for UGT2B17, CES2 (intestine), SULT1A1 (liver), UGT1A9, UGT2B7, and CES1 (kidney). These differential tissue abundance data can be integrated into physiologically based pharmacokinetic (PBPK) models for the prediction of non-CYP drug metabolism and toxicity in hepatic and extrahepatic tissues.

Evidence-based strategies for the characterisation of human drug and chemical glucuronidation in vitro and UDP-glucuronosyltransferase reaction phenotyping

Enzymes of the UDP-glucuronosyltransferase (UGT) superfamily contribute to the elimination of drugs from almost all therapeutic classes. Awareness of the importance of glucuronidation as a drug clearance mechanism along with increased knowledge of the enzymology of drug and chemical metabolism has stimulated interest in the development and application of approaches for the characterisation of human drug glucuronidation in vitro, in particular reaction phenotyping (the fractional contribution of the individual UGT enzymes responsible for the glucuronidation of a given drug), assessment of metabolic stability, and UGT enzyme inhibition by drugs and other xenobiotics. In turn, this has permitted the implementation of in vitro - in vivo extrapolation approaches for the prediction of drug metabolic clearance, intestinal availability, and drug-drug interaction liability, all of which are of considerable importance in pre-clinical drug development. Indeed, regulatory agencies (FDA and EMA) require UGT reaction phenotyping for new chemical entities if glucuronidation accounts for ≥25% of total metabolism. In vitro studies are most commonly performed with recombinant UGT enzymes and human liver microsomes (HLM) as the enzyme sources. Despite the widespread use of in vitro approaches for the characterisation of drug and chemical glucuronidation by HLM and recombinant enzymes, evidence-based guidelines relating to experimental approaches are lacking. Here we present evidence-based strategies for the characterisation of drug and chemical glucuronidation in vitro, and for UGT reaction phenotyping. We anticipate that the strategies will inform practice, encourage development of standardised experimental procedures where feasible, and guide ongoing research in the field.