Regulation of Human Hydrolases and Its Implications in Pharmacokinetics and Pharmacodynamics

Hydrolases represent an essential class of enzymes indispensable for the metabolism of various clinically essential medications. Individuals exhibit marked differences in the expression and activation of hydrolases, resulting in significant variability in the pharmacokinetics (PK) and pharmacodynamics (PD) of drugs metabolized by these enzymes. The regulation of hydrolase expression and activity involves both genetic polymorphisms and nongenetic factors. This review examines the current understanding of genetic and nongenetic regulators of six clinically significant hydrolases, including carboxylesterase (CES)-1 CES2, arylacetamide deacetylase (AADAC), paraoxonase (PON)-1 PON3, and cathepsin A (CTSA). We explore genetic variants linked to the expression and activity of the hydrolases and their effects on the PK and PD of their substrate drugs. Regarding nongenetic regulators, we focus on the inhibitors and inducers of these enzymes. Additionally, we examine the developmental expression patterns and gender differences in the hydrolases when pertinent information was available. Many genetic and nongenetic regulators were found to be associated with the expression and activity of the hydrolases and PK and PD. However, hydrolases remain generally understudied compared with other drug-metabolizing enzymes, such as cytochrome P450s. The clinical significance of genetic and nongenetic regulators has not yet been firmly established for the majority of hydrolases. Comprehending the mechanisms that underpin the regulation of these enzymes holds the potential to refine therapeutic regimens, thereby enhancing the efficacy and safety of drugs metabolized by the hydrolases. SIGNIFICANCE STATEMENT: Hydrolases play a crucial role in the metabolism of numerous clinically important medications. Genetic polymorphisms and nongenetic regulators can affect hydrolases' expression and activity, consequently influencing the exposure and clinical outcomes of hydrolase substrate drugs. A comprehensive understanding of hydrolase regulation can refine therapeutic regimens, ultimately enhancing the efficacy and safety of drugs metabolized by the enzymes.

Drug interaction with UDP-Glucuronosyltransferase (UGT) enzymes is a predictor of drug-induced liver injury

BACKGROUND AND AIMS

DILI frequently contributes to the attrition of new drug candidates and is a common cause for the withdrawal of approved drugs from the market. Although some noncytochrome P450 (non-CYP) metabolism enzymes have been implicated in DILI development, their association with DILI outcomes has not been systematically evaluated.

APPROACH AND RESULTS

In this study, we analyzed a large data set comprising 317 drugs and their interactions in vitro with 42 non-CYP enzymes as substrates, inducers, and/or inhibitors retrieved from historical regulatory documents using multivariate logistic regression. We examined how these in vitro drug-enzyme interactions are correlated with the drugs' potential for DILI concern, as classified in the Liver Toxicity Knowledge Base database. Our study revealed that drugs that inhibit non-CYP enzymes are significantly associated with high DILI concern. Particularly, interaction with UDP-glucuronosyltransferases (UGT) enzymes is an important predictor of DILI outcomes. Further analysis indicated that only pure UGT inhibitors and dual substrate inhibitors, but not pure UGT substrates, are significantly associated with high DILI concern.

CONCLUSIONS

Drug interactions with UGT enzymes may independently predict DILI, and their combined use with the rule-of-two model further improves overall predictive performance. These findings could expand the currently available tools for assessing the potential for DILI in humans.

Role of carboxylesterase and arylacetamide deacetylase in drug metabolism, physiology, and pathology

Carboxylesterases (CES1 and CES2) and arylacetamide deacetylase (AADAC), which are expressed primarily in the liver and/or gastrointestinal tract, hydrolyze drugs containing ester and amide bonds in their chemical structure. These enzymes often catalyze the conversion of prodrugs, including the COVID-19 drugs remdesivir and molnupiravir, to their pharmacologically active forms. Information on the substrate specificity and inhibitory properties of these enzymes, which would be useful for drug development and toxicity avoidance, has accumulated. Recently,in vitroandin vivostudies have shown that these enzymes are involved not only in drug hydrolysis but also in lipid metabolism. CES1 and CES2 are capable of hydrolyzing triacylglycerol, and the deletion of their orthologous genes in mice has been associated with impaired lipid metabolism and hepatic steatosis. Adeno-associated virus-mediated human CES overexpression decreases hepatic triacylglycerol levels and increases fatty acid oxidation in mice. It has also been shown that overexpression of CES enzymes or AADAC in cultured cells suppresses the intracellular accumulation of triacylglycerol. Recent reports indicate that AADAC can be up- or downregulated in tumors of various organs, and its varied expression is associated with poor prognosis in patients with cancer. Thus, CES and AADAC not only determine drug efficacy and toxicity but are also involved in pathophysiology. This review summarizes recent findings on the roles of CES and AADAC in drug metabolism, physiology, and pathology.

A novel system to determine activity of individual uridine 5'-diphospho-glucuronosyltransferase (UGT) isoforms: Recombinant UGT-beads

Previous work demonstrated that human liver microsomes (HLMs) can spontaneously bind to silica-coated magnetizable beads (HLM-beads) and that these HLM-beads retain uridine 5'-diphospho-glucuronosyltransferase (UGT) activity. However, the contributions of individual UGT isoforms are not directly assessable in this system except through use of model inhibitors. Thus, a preparation wherein recombinant UGT (rUGT) microsomes bound to these same beads to form rUGT-beads of individual UGT isoforms would provide a novel system for measuring the contribution of individual UGT isoforms in a direct manner. To this end, the enzyme activities and kinetic parameter estimates of various rUGT isoforms in rUGT-beads were investigated, as well as the impact of fatty acids (FAs) on enzyme activity. The catalytic efficiencies (Vmax/Km) of the tested rUGTs were twofold to sevenfold higher in rUGT-beads compared with rUGT microsomes, except for rUGT1A6, where Vmax is the maximum product formation rate normalized to milligram of microsomal protein (pmol/min/mg protein). Interestingly, in contrast to traditional rUGT preparations, the sequestration of UGT-inhibitory FA using bovine serum albumin did not alter the catalytic efficiency (Vmax/Km) of the rUGTs in rUGT-beads. Moreover, the increase in catalytic efficiency of rUGT-beads over rUGT microsomes was similar to increases in catalytic efficiency noted with rUGT microsomes (not bound to beads) incubated with bovine serum albumin, suggesting the beads in some way altered the potential for FAs to inhibit activity. The rUGT-bead system may serve as a useful albumin-free tool to determine kinetic constants for UGT substrates, particularly those that exhibit high binding to albumin.

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.

Improving In Vitro-In Vivo Extrapolation of Clearance Using Rat Liver Microsomes for Highly Plasma Protein-Bound Molecules

It is common practice in drug discovery and development to predict in vivo hepatic clearance from in vitro incubations with liver microsomes or hepatocytes using the well-stirred model (WSM). When applying the WSM to a set of approximately 3000 Novartis research compounds, 73% of neutral and basic compounds (extended clearance classification system [ECCS] class 2) were well-predicted within 3-fold. In contrast, only 44% (ECCS class 1A) or 34% (ECCS class 1B) of acids were predicted within 3-fold. To explore the hypothesis whether the higher degree of plasma protein binding for acids contributes to the in vitro-in vivo correlation (IVIVC) disconnect, 68 proprietary compounds were incubated with rat liver microsomes in the presence and absence of 5% plasma. A minor impact of plasma on clearance IVIVC was found for moderately bound compounds (fraction unbound in plasma [fup] ≥1%). However, addition of plasma significantly improved the IVIVC for highly bound compounds (fup <1%) as indicated by an increase of the average fold error from 0.10 to 0.36. Correlating fup with the scaled unbound intrinsic clearance ratio in the presence or absence of plasma allowed the establishment of an empirical, nonlinear correction equation that depends on fup Taken together, estimation of the metabolic clearance of highly bound compounds was enhanced by the addition of plasma to microsomal incubations. For standard incubations in buffer only, application of an empirical correction provided improved clearance predictions. SIGNIFICANCE STATEMENT: Application of the well-stirred liver model for clearance in vitro-in vivo extrapolation (IVIVE) in rat generally underpredicts the clearance of acids and the strong protein binding of acids is suspected to be one responsible factor. Unbound intrinsic in vitro clearance (CLint,u) determinations using rat liver microsomes supplemented with 5% plasma resulted in an improved IVIVE. An empirical equation was derived that can be applied to correct CLint,u-values in dependance of fraction unbound in plasma (fup) and measured CLint in buffer.

Ruminant metabolism of zygacine, the major toxic alkaloid in foothill death camas (Zigadenuspaniculatus)

Death Camas (Zigadenus spp.) are common poisonous plants distributed throughout North America. The toxic alkaloids in foothill death camas are zygadenine and a series of zygadenine esters, with zygacine, the 3-acetyl ester of zygadenine, being the most abundant. Both cattle and sheep can be poisoned by grazing death camas, however, sheep consume death camas more readily and are most often poisoned. We hypothesized that the presence of enzymes, including esterases present in the rumen, liver, and blood of livestock would metabolize zygacine. The objective of this study was to investigate the metabolism of zygacine in sheep and cattle using in-vitro and in-vivo systems. Results from experiments where zygacine was incubated in rumen culture, plasma, liver S9 fractions, and liver microsomes and from the analysis of rumen and sera from sheep and cattle dosed death camas plant material demonstrated that zygacine is metabolized to zygadenine in the rumen, liver and blood of sheep and cattle. The results from this study indicate that diagnosticians should analyze for zygadenine, and not zygacine, in the rumen and sera for the diagnosis of livestock suspected to have been poisoned by foothill death camas.

Acceleration of infectious disease drug discovery and development using a humanized model of drug metabolism

A key step in drug discovery, common to many disease areas, is preclinical demonstration of efficacy in a mouse model of disease. However, this demonstration and its translation to the clinic can be impeded by mouse-specific pathways of drug metabolism. Here, we show that a mouse line extensively humanized for the cytochrome P450 gene superfamily ("8HUM") can circumvent these problems. The pharmacokinetics, metabolite profiles, and magnitude of drug-drug interactions of a test set of approved medicines were in much closer alignment with clinical observations than in wild-type mice. Infection with Mycobacterium tuberculosis, Leishmania donovani, and Trypanosoma cruzi was well tolerated in 8HUM, permitting efficacy assessment. During such assessments, mouse-specific metabolic liabilities were bypassed while the impact of clinically relevant active metabolites and DDI on efficacy were well captured. Removal of species differences in metabolism by replacement of wild-type mice with 8HUM therefore reduces compound attrition while improving clinical translation, accelerating drug discovery.

A Review of CYP-Mediated Drug Interactions: Mechanisms and In Vitro Drug-Drug Interaction Assessment

Drug metabolism is a major determinant of drug concentrations in the body. Drug-drug interactions (DDIs) caused by the co-administration of multiple drugs can lead to alteration in the exposure of the victim drug, raising safety or effectiveness concerns. Assessment of the DDI potential starts with in vitro experiments to determine kinetic parameters and identify risks associated with the use of comedication that can inform future clinical studies. The diverse range of experimental models and techniques has significantly contributed to the examination of potential DDIs. Cytochrome P450 (CYP) enzymes are responsible for the biotransformation of many drugs on the market, making them frequently implicated in drug metabolism and DDIs. Consequently, there has been a growing focus on the assessment of DDI risk for CYPs. This review article provides mechanistic insights underlying CYP inhibition/induction and an overview of the in vitro assessment of CYP-mediated DDIs.

Quantitative Analysis of mRNA and Protein Expression Levels of Aldo-Keto Reductase and Short-Chain Dehydrogenase/Reductase Isoforms in the Human Intestine

Enzymes catalyzing the reduction reaction of xenobiotics are mainly members of the aldo-keto reductase (AKR) and short-chain dehydrogenase/reductase (SDR) superfamilies. The intestine, together with the liver, is responsible for first-pass effects and is an organ that determines the bioavailability of orally administered drugs. In this study, we evaluated the mRNA and protein expression levels of 12 AKR isoforms (AKR1A1, AKR1B1, AKR1B10, AKR1B15, AKR1C1, AKR1C2, AKR1C3, AKR1C4, AKR1D1, AKR1E2, AKR7A2, and AKR7A3) and 7 SDR isoforms (CBR1, CBR3, CBR4, DCXR, DHRS4, HSD11B1, and HSD17B12) in each region of the human intestine using next-generation sequencing and data-independent acquisition proteomics. At both the mRNA and protein levels, most AKR isoforms were highly expressed in the upper regions of the intestine, namely the duodenum and jejunum, and then declined toward the rectum. Among the members in the SDR superfamily, CBR1 and DHRS4 were highly expressed in the upper regions, whereas the expression levels of the other isoforms were almost uniform in all regions. Significant positive correlations between mRNA and protein levels were observed in AKR1A1, AKR1B1, AKR1B10, AKR1C3, AKR7A2, AKR7A3, CBR1, and CBR3. The mRNA level of AKR1B10 was highest, followed by AKR7A3 and CBR1, each accounting for more than 10% of the sum of all AKR and SDR levels in the small intestine. This expression profile in the human intestine was greatly different from that in the human liver, where AKR1C isoforms are predominantly expressed. SIGNIFICANCE STATEMENT: In this study comprehensively determined the mRNA and protein expression profiles of aldo-keto reductase (AKR) and short-chain dehydrogenase/reductase isoforms involved in xenobiotic metabolism in the human intestine and found that most of them are highly expressed in the upper region, where AKR1B10, AKR7A3, and CBR1 are predominantly expressed. Since the intestine is significantly involved in the metabolism of orally administered drugs, the information provided here is valuable for pharmacokinetic studies in drug development.

Ontogeny of Scaling Factors for Pediatric Physiologically Based Pharmacokinetic Modeling and Simulation: Cytosolic Protein Per Gram of Liver

Scaling factors are necessary for translating in vitro drug biotransformation data to in vivo clearance values in physiologically-based pharmacokinetic modeling and simulation. Values for microsomal protein per gram of liver are available from several sources for use as a scaling factor to estimate hepatic clearance from microsomal drug biotransformation data. However, data regarding the distribution of cytosolic protein per gram of liver (CPPGL) values across the lifespan are limited, and sparse pediatric data have been published to date. Thus, CPPGL was determined in 160 liver samples from pediatric (n = 129) and adult (n = 31) donors obtained from multiple sources: the University of Maryland Brain and Tissue Bank, tissue retrieval services at the University of Minnesota and University of Pittsburgh, and Sekisui-XenoTech. Tissues were homogenized and subjected to differential centrifugation to isolate cytosolic fractions. Cytosolic protein content was determined by BCA assay. CPPGL varied from two- to sixfold within each age group/developmental stage. Tissue source and sex did not contribute substantially to variability in protein content. Regression analyses revealed minimal change in CPPGL over the first two decades of life (logCPPGL increases 0.1 mg/g per decade). A mean ± S.D. CPPGL value of 44.4 ± 17.4 mg/g or median 41.0 mg/g is representative of values observed between birth and early adulthood (0-18 years, n = 129). SIGNIFICANCE STATEMENT: Cytosolic protein per gram of liver (CPPGL) is a scaling factor required for physiologically based pharmacokinetic modeling and simulation of drug biotransformation by cytosolic enzymes, but pediatric data are limited. Although CPPGL varies from two- to sixfold within developmental stages, a value of 44.4 ± 17.4 mg/g (mean ± S.D.) is representative of the pediatric period (0-18 years, n = 129).

Establishment of UGT1A1-knockout human iPS-derived hepatic organoids for UGT1A1-specific kinetics and toxicity evaluation

Uridine diphosphate glucuronosyltransferases (UGTs) are highly expressed in the liver and are involved in the metabolism of many drugs. In particular, UGT1A1 has a genetic polymorphism that causes decreased activity, leading to drug-induced hepatotoxicity. Therefore, an in vitro evaluation system that accurately predicts the kinetics of drugs involving UGT1A1 is required. However, there is no such evaluation system because of the absence of the UGT1A1-selective inhibitor. Here, using human induced pluripotent stem (iPS) cells, genome editing technology, and organoid technology, we generated UGT1A1-knockout human iPS hepatocyte-derived liver organoids (UGT1A1-KO i-HOs) as a model for UGT1A1-specific kinetics and toxicity evaluation. i-HOs showed higher gene expression of many drug-metabolizing enzymes including UGT1A1 than human iPS cell-derived hepatocyte-like cells (iPS-HLCs), suggesting that hepatic organoid technology improves liver functions. Wild-type (WT) i-HOs showed similar levels of UGT1A1 activity to primary human (cryopreserved) hepatocytes, while UGT1A1-KO i-HOs completely lost the activity. Additionally, to evaluate whether this model can be used to predict drug-induced hepatotoxicity, UGT1A1-KO i-HOs were exposed to SN-38, the active metabolite of irinotecan, an anticancer drug, and acetaminophen and confirmed that these cells could predict UGT1A1-mediated toxicity. Thus, we succeeded in generating model cells that enable evaluation of UGT1A1-specific kinetics and toxicity.

Scalable production of tissue-like vascularized liver organoids from human PSCs

The lack of physiological parity between 2D cell culture and in vivo culture has led to the development of more organotypic models, such as organoids. Organoid models have been developed for a number of tissues, including the liver. Current organoid protocols are characterized by a reliance on extracellular matrices (ECMs), patterning in 2D culture, costly growth factors and a lack of cellular diversity, structure, and organization. Current hepatic organoid models are generally simplistic and composed of hepatocytes or cholangiocytes, rendering them less physiologically relevant compared to native tissue. We have developed an approach that does not require 2D patterning, is ECM independent, and employs small molecules to mimic embryonic liver development that produces large quantities of liver-like organoids. Using single-cell RNA sequencing and immunofluorescence, we demonstrate a liver-like cellular repertoire, a higher order cellular complexity, presenting with vascular luminal structures, and a population of resident macrophages: Kupffer cells. The organoids exhibit key liver functions, including drug metabolism, serum protein production, urea synthesis and coagulation factor production, with preserved post-translational modifications such as N-glycosylation and functionality. The organoids can be transplanted and maintained long term in mice producing human albumin. The organoids exhibit a complex cellular repertoire reflective of the organ and have de novo vascularization and liver-like function. These characteristics are a prerequisite for many applications from cellular therapy, tissue engineering, drug toxicity assessment, and disease modeling to basic developmental biology.

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.

Synthesis and Characterization of Phenylalanine Amides Active against Mycobacterium abscessus and Other Mycobacteria

Nα-2-thiophenoyl-d-phenylalanine-2-morpholinoanilide [MMV688845, Pathogen Box; Medicines for Malaria Venture; IUPAC: (2R)-N-(1-((2-morpholinophenyl)amino)-1-oxo-3-phenylpropan-2-yl)thiophene-2-carboxamide)] is a hit compound, which shows activity against Mycobacterium abscessus (MIC90 6.25-12.5 μM) and other mycobacteria. This work describes derivatization of MMV688845 by introducing a thiomorpholine moiety and the preparation of the corresponding sulfones and sulfoxides. The molecular structures of three analogs are confirmed by X-ray crystallography. Conservation of the essential R configuration during synthesis is proven by chiral HPLC for an exemplary compound. All analogs were characterized in a MIC assay against M. abscessus, Mycobacterium intracellulare, Mycobacterium smegmatis, and Mycobacterium tuberculosis. The sulfone derivatives exhibit lower MIC90 values (M. abscessus: 0.78 μM), and the sulfoxides show higher aqueous solubility than the hit compound. The most potent derivatives possess bactericidal activity (99% inactivation of M. abscessus at 12.5 μM), while they are not cytotoxic against mammalian cell lines.

In Silico Prediction of Metabolic Reaction Catalyzed by Human Aldehyde Oxidase

Aldehyde oxidase (AOX) plays an important role in drug metabolism. Human AOX (hAOX) is widely distributed in the body, and there are some differences between species. Currently, animal models cannot accurately predict the metabolism of hAOX. Therefore, more and more in silico models have been constructed for the prediction of the hAOX metabolism. These models are based on molecular docking and quantum chemistry theory, which are time-consuming and difficult to automate. Therefore, in this study, we compared traditional machine learning methods, graph convolutional neural network methods, and sequence-based methods with limited data, and proposed a ligand-based model for the metabolism prediction catalyzed by hAOX. Compared with the published models, our model achieved better performance (ACC = 0.91, F1 = 0.77). What's more, we built a web server to predict the sites of metabolism (SOMs) for hAOX. In summary, this study provides a convenient and automatable model and builds a web server named Meta-hAOX for accelerating the drug design and optimization stage.

Evaluation of a Five-Probe Metabolic Control Cocktail in Long-Term Cocultured Human Hepatocytes

Hepatocyte cocultures like HepatoPac have become more frequently used for the assessment of the intrinsic clearance of slowly metabolised drugs during drug discovery due to a superiority in enzymatic activity over time compared to liver microsomal fractions and suspended primary hepatocytes. However, the relatively high cost and practical limitations prevent several quality control compounds to be included in studies and the activities of many important metabolic enzymes are consequently often not monitored. In this study, we have evaluated the possibility for a cocktail approach of quality control compounds in the human HepatoPac system to ensure adequate activity of the major metabolising enzymes. Five reference compounds were selected based on their known metabolic substrate profile in order to capture major CYP and non-CYP metabolic pathways in the incubation cocktail. The intrinsic clearance of the reference compounds when incubated as singlets or in a cocktail was compared and no considerable difference was observed. We show here that a cocktail approach of quality control compounds allows for easy and efficient evaluation of the metabolic competency of the hepatic coculture system over an extended incubation period.

Improved Predictability of Hepatic Clearance with Optimal pH for Acyl-Glucuronidation in Liver Microsomes

The purpose of this study was to investigate the optimal pH for acyl-glucuronidation formation with carboxylic acid-containing compounds in human and rat liver microsomes to improve the predictability of their hepatic clearance. The optimal pH for acyl-glucuronidation of all 17 compounds was around pH 6.0 in human and rat liver microsomes. Correlation analysis was done with the predicted in vitro intrinsic clearance (CL_{int,in vitro}) and in vivo intrinsic clearance (CL_{int,in vivo}) calculated from available reported data of total clearance (CL_tot) of 11 compounds in humans. For 8 of the 11 compounds, under the pH 6.0 condition, the CL_{int,in vitro} were within 1/3 to 3-fold error of the observed CL_{int,in vivo} whereas, the error was within 1/3 to 3-fold of the observed CL_{int,in vivo} for only 3 of the 11 under the pH 7.4 condition. The intracellular pH in human and rat hepatocytes decreased in the presence of a carboxylic acid-containing compound. These findings suggest that acyl-glucuronidation in liver microsomes at pH 6.0 is closer to physiological conditions in the presence of carboxylic acid compounds, and thus, use of this pH condition is important for physiological interpretation and predictability of intrinsic clearance.

Altered Bioavailability and Pharmacokinetics in Crohn's Disease: Capturing Systems Parameters for PBPK to Assist with Predicting the Fate of Orally Administered Drugs

Backgrond and Objective

Crohn’s disease (CD) is a chronic inflammatory bowel disease that affects a wide age range. Hence, CD patients receive a variety of drugs over their life beyond those used for CD itself. The changes to the integrity of the intestine and its drug metabolising enzymes and transporters (DMETs) can alter the oral bioavailability of drugs. However, there are other changes in systems parameters determining the fate of drugs in CD, and understanding these is essential for dose adjustment in patients with CD.

Methods

The current analysis gathered all the available clinical data on the kinetics of drugs in CD (by March 2021), focusing on orally administered small molecule drugs. A meta-analysis of the systems parameters affecting oral drug pharmacokinetics was conducted. The systems information gathered on intestine, liver and blood proteins and other physiological parameters was incorporated into a physiologically based pharmacokinetic (PBPK) platform to create a virtual population of CD patients, with a view for guiding dose adjustment in the absence of clinical data in CD.

Results

There were no uniform trends in the reported changes in reported oral bioavailability. The nature of the drug as well as the formulation affected the direction and magnitude of variation in kinetics in CD patients relative to healthy volunteers. Even for the same drug, the reported changes in exposure varied, possibly due to a lack of distinction between the activity states of CD. The highest alteration was seen with S-verapamil and midazolam, 8.7- and 5.3-fold greater exposure, respectively, in active CD patients relative to healthy volunteers. Only one report was available on liver DMETs in CD, and indicated reduced CYP3A4 activity. In a number of reports, mRNA expression of DMETs in the ileum and colon of CD patients was measured, focussing on P-glycoprotein (p-gp) transporter and CYP3A4 enzyme, and showed contradictory results. No data were available on protein expression in duodenum and jejunum despite their dominant role in oral drug absorption.

Conclusion

There are currently inadequate dedicated clinical or quantitative proteomic studies in CD to enable predictive PBPK models with high confidence and adequate verification. The PBPK models for CD with the available systems parameters were able to capture the major physiological influencers and the gaps to be filled by future research. Quantification of DMETs in the intestine and the liver in CD is warranted, alongside well-defined clinical drug disposition studies with a number of index drugs as biomarkers of changes in DMETs in these patients, to avoid large-scale dedicated studies for every drug to determine the effects of disease on the drug’s metabolism and disposition and the consequential safety and therapeutic concerns.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40262-022-01169-4.

High-Throughput Production of Diverse Xenobiotic Metabolites with Cytochrome P450-Transduced Huh7 Hepatoma Cell Lines

Precision medicine and exposomics require methods to assess xenobiotic metabolism in human metabolomic analyses, including the identification of known and undocumented drug and chemical exposures as well as their metabolites. Recent work demonstrated the use of high-throughput generation of xenobiotic metabolites with human liver S-9 fractions for their detection in human plasma and urine. Here, we tested whether a panel of lentivirally transduced human hepatoma cell lines (Huh7) that express individual cytochrome P450 (P450) enzymes could be used to generate P450-specific metabolites in a high-throughput manner, while simultaneously identifying the enzymes responsible. Cell-line activities were verified using P450-specific probe substrates. To increase analytical throughput, we used a pooling strategy where 36 chemicals were grouped into 12 unique mixtures, each mixture containing 6 randomly selected compounds, and each compound being present in two separate mixtures. Each mixture was incubated with 8 different P450 cell lines for 0 and 2 hours and extracts were analyzed using liquid chromatography-high-resolution mass spectrometry. Cell lines selectively metabolized test substrates, e.g., pazopanib, bupropion, and β-naphthoflavone with expected substrate-enzyme specificities. Predicted metabolites from the remaining 33 compounds as well as many unidentified m/z features were detected. We also showed that a specific bupropion metabolite generated by CYP2B6 cells, but not detected in the S9 system, was identified in human samples. Our data show that the chemical mixtures approach accelerated characterization of xenobiotic chemical space, while simultaneously identifying enzyme sources that can be used for scalable generation of metabolites for their identification in human metabolomic analyses. SIGNIFICANCE STATEMENT: High-resolution mass spectrometry (HRMS) enables the detection of exposures to drugs and other xenobiotics in human samples, but chemical identification can be difficult for several reasons. This paper demonstrates the utility of a panel of engineered cytochrome P450-expressing hepatoma cells in a scalable workflow for production of xenobiotic metabolites, which will facilitate their use as surrogate standards to validate xenobiotic detection by HRMS in human metabolomic studies.

Characterization of intravenous pharmacokinetics in Göttingen minipig and clearance prediction using established in vitro to in vivo extrapolation methodologies

1. The use of the Göttingen minipig as an animal model for drug safety testing and prediction of human pharmacokinetics (PK) continues to gain momentum in pharmaceutical research and development. The aim of this study was to evaluate in vitro to in vivo extrapolation (IVIVE) methodologies for prediction of hepatic, metabolic clearance (CL_hep,met) in Göttingen minipig, using a comprehensive set of compounds.2. In vivo clearance was determined in Göttingen minipig by intravenous cassette dosing and hepatocyte intrinsic clearance, plasma protein binding and non-specific incubation binding were determined in vitro. Prediction of CL_hep,met was performed by IVIVE using conventional and adapted formats of the well-stirred liver model.3. The best prediction of in vivo CL_hep,met from scaled in vitro kinetic data was achieved using an empirical correction factor based on a 'regression offset' of the IVIV relationship.4. In summary, these results expand the in vitro and in vivo PK knowledge in Göttingen minipig. We show regression corrected IVIVE provides superior prediction of in vivo CL_hep,met in minipig offering a practical, unified scaling approach to address systematic under-predictions. Finally, we propose a reference set for researchers to establish their own 'lab-specific' regression correction for IVIVE in minipig.

Use of selective substrates and inhibitors to rapidly characterise batches of cryopreserved primary human hepatocytes for assessment of active uptake liability in drug discovery and development

The use of hepatocytes to predict human hepatic metabolic clearance is the gold standard approach. However whilst enzymes are well characterised, knowledge gaps remain for transporters. Furthermore, methods to study specific transporter involvement are often complicated by overlapping substrate specificity. Selective substrates and inhibitors would aid investigations into clinically relevant pharmacokinetic effects. However, to date no consensus has been reached.This work defines selective hepatic uptake transporter substrates and inhibitors for the six main human hepatocyte transporters (OATP1B1, OATP1B3, OATP2B1, NTCP, OAT2 & OCT1), and demonstrates their use to rapidly characterise batches of human hepatocytes for uptake transporter activity. Hepatic uptake was determined across a range of substrate concentrations, allowing the definition of kinetic parameters and hence active and passive components. Systematic investigations identified a specific substrate and inhibitor for each transporter, with no overlap between the specificity of substrate and inhibitor for any given transporter.Early characterisation of compound interactions with uptake transporters will aid in early risk assessment and chemistry design. Hence, this work further highlights the feasibility of a refined methodology for rapid compound characterisation for the application of static and dynamic models, for early clinical risk assessment and guidance for the clinical development plan.

Defining the Selectivity of Chemical Inhibitors Used for Cytochrome P450 Reaction Phenotyping: Overcoming Selectivity Limitations with a Six-Parameter Inhibition Curve-Fitting Approach

The utility of chemical inhibitors in cytochrome P450 (CYP) reaction phenotyping is highly dependent on their selectivity and potency for their target CYP isoforms. In the present study, seventeen inhibitors of CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, and 3A4/5 commonly used in reaction phenotyping were evaluated for their cross-enzyme selectivity in pooled human liver microsomes. The data were evaluated using a statistical desirability analysis to identify (1) inhibitors of superior selectivity for reaction phenotyping and (2) optimal concentrations for each. Among the inhibitors evaluated, α-naphthoflavone, furafylline, sulfaphenazole, tienilic acid, N-benzylnirvanol, and quinidine were most selective, such that their respective target enzymes were inhibited by ~95% without inhibiting any other CYP enzyme by more than 10%. Other commonly employed inhibitors, such as ketoconazole and montelukast, among others, were of insufficient selectivity to yield a concentration that could adequately inhibit their target enzymes without affecting other CYP enzymes. To overcome these shortcomings, an experimental design was developed wherein dose response data from a densely sampled multi-concentration inhibition curve are analyzed by a six-parameter inhibition curve function, allowing accounting of the inhibition of off-target CYP isoforms inhibition and more reliable determination of maximum targeted enzyme inhibition. The approach was exemplified using rosiglitazone N-demethylation, catalyzed by both CYP2C8 and 3A4, and was able to discern the off-target inhibition by ketoconazole and montelukast from the inhibition of the targeted enzyme. This methodology yields more accurate estimates of CYP contributions in reaction phenotyping. Significance Statement Isoform-selective chemical inhibitors are important tools for identifying and quantifying enzyme contributions as part of a CYP reaction phenotyping assessment for projecting drug-drug interactions. However, currently employed practices fail to adequately compensate for shortcomings in inhibitor selectivity and the resulting confounding impact on estimates of the CYP enzyme contribution to drug clearance. In this report, we describe a detailed IC50 study design with 6-parameter modeling approach that yields more accurate estimates of enzyme contribution.

Ziritaxestat Drug-Drug Interaction with Oral Contraceptives: Role of SULT1E1 Inhibition

In vitro signals indicate that ziritaxestat is a weak cytochrome P450 (CYP) 3A4 inhibitor and inducer. Therefore, potential drug–drug interactions (DDIs) with oral contraceptives were examined at a time when ziritaxestat was under development for treatment of fibrotic diseases. This open‐label, crossover (fixed sequence) DDI study enrolled healthy, nonpregnant women aged 18–65 years (n = 15) who were using highly effective contraception, such as a nonhormonal intrauterine device, bilateral tubal occlusion, or sexual abstinence. A single dose of oral contraceptive (0.03 mg ethinyl estradiol (EE) and 3 mg drospirenone (DRSP)) was administered on days 1, 8, and 18, and ziritaxestat 600 mg once daily was administered from days 8 to 23. Co‐administration resulted in a 2.8‐fold and 2.4‐fold increase in EE maximum plasma concentration (C_max) and area under the plasma drug concentration–time curve from time zero to infinity (AUC_0–inf), respectively (day 18 vs. day 1). DRSP C_max and AUC_0–inf increased by 1.1‐fold and 1.2‐fold, respectively. DRSP is a CYP3A4 substrate, meaning increased EE exposure with ziritaxestat was not due to CYP3A4 inhibition. Ziritaxestat inhibition of EE glucuronidation and sulfation was quantified by liquid chromatography with tandem mass spectrometry in day 1 and day 18 plasma samples after EE conjugate hydrolysis. The ratio of EE AUC from time of administration up to the time of the last quantifiable concentration (AUC_last) with/without hydrolysis by arylsulfatase was substantially lower on day 18 vs. day 1, suggesting ziritaxestat is a potent inhibitor of sulfation; EE glucuronidation was largely unaffected by ziritaxestat. In vitro assessment confirmed ziritaxestat is a potent inhibitor of sulfotransferase family 1E member 1 (half‐maximal inhibitory concentration < 0.8 μM). These findings highlight the importance of assessing enzymes other than CYP3A4 when investigating potential DDIs with oral contraceptives.

Identification and Strategies to Mitigate High Total Clearance of Benzylamine-Substituted Biphenyl Ring Systems

For most oral small-molecule projects within drug discovery, the extent and duration of the effect are influenced by the total clearance of the compound; hence, designing compounds with low clearance remains a key focus to help enable sufficient protein target engagement. Comprehensive understanding and accurate prediction of animal clearance and pharmacokinetics provides confidence that the same can be observed for human. During a MERTK inhibitor lead optimization project, a series containing a biphenyl ring system with benzylamine meta-substitution on one phenyl and nitrogen inclusion as the meta atom on the other ring demonstrated multiple routes of compound elimination in rats. Here, we describe the identification of a structural pharmacophore involving two key interactions observed for both the MERTK program and an additional internal project. Four strategies to mitigate these clearance liabilities were identified and systematically investigated. We provide evidence that disruption of at least one of the interactions led to a significant reduction in CL that was subsequently predicted from rat hepatocytes using in vitro/in vivo extrapolation and the well-stirred scaling method. These tactics will likely be of general utility to the medicinal chemistry and DMPK community during compound optimization when similar issues are encountered for biphenyl benzylamines.

Energy Decomposition Analysis of the Nature of Coordination Bonding at the Heme Iron Center in Cytochrome P450 Inhibition

Drug compounds or their metabolic intermediates (MIs) sometimes inhibit the function of cytochrome P450 enzymes (P450s) by forming a coordination bond with the Fe(III) heme or Fe(II) heme of P450s. Such inhibition is one of the major causes of drug-drug interactions (DDIs), a subject of longstanding academic and practical interest. However, such coordination bonding is not fully understood at the quantum mechanical level, thus hampering rational improvement of the accuracy of DDI-related predictions. In this work, we employed density functional theory (DFT) and the generalized Kohn-Sham energy decomposition analysis (GKS-EDA) scheme to investigate the nature of the coordination bonding formed in the reversible and quasi-irreversible inhibition of P450s. The GKS-EDA results highlighted a previously unrecognized role of the electron correlation effect in P450 inhibition. The correlation effect tends to be larger in Fe(II) complexes of MI-type inhibitors and is particularly prominent for the nitrosoalkane ligand. An additional natural bond orbital (NBO) analysis provided insight into the relative significance of the σ donation and π backdonation effects in various heme-inhibitor complexes.

Prediction of In Vivo Pharmacokinetic Parameters and Time-Exposure Curves in Rats Using Machine Learning from the Chemical Structure

Animal pharmacokinetic (PK) data as well as human and animal in vitro systems are utilized in drug discovery to define the rate and route of drug elimination. Accurate prediction and mechanistic understanding of drug clearance and disposition in animals provide a degree of confidence for extrapolation to humans. In addition, prediction of in vivo properties can be used to improve design during drug discovery, help select compounds with better properties, and reduce the number of in vivo experiments. In this study, we generated machine learning models able to predict rat in vivo PK parameters and concentration-time PK profiles based on the molecular chemical structure and either measured or predicted in vitro parameters. The models were trained on internal in vivo rat PK data for over 3000 diverse compounds from multiple projects and therapeutic areas, and the predicted endpoints include clearance and oral bioavailability. We compared the performance of various traditional machine learning algorithms and deep learning approaches, including graph convolutional neural networks. The best models for PK parameters achieved R² = 0.63 [root mean squared error (RMSE) = 0.26] for clearance and R² = 0.55 (RMSE = 0.46) for bioavailability. The models provide a fast and cost-efficient way to guide the design of molecules with optimal PK profiles, to enable the prediction of virtual compounds at the point of design, and to drive prioritization of compounds for in vivo assays.

Induction by Phenobarbital of Phase I and II Xenobiotic-Metabolizing Enzymes in Bovine Liver: An Overall Catalytic and Immunochemical Characterization

In cattle, phenobarbital (PB) upregulates target drug-metabolizing enzyme (DME) mRNA levels. However, few data about PB's post-transcriptional effects are actually available. This work provides the first, and an almost complete, characterization of PB-dependent changes in DME catalytic activities in bovine liver using common probe substrates and confirmatory immunoblotting investigations. As expected, PB increased the total cytochrome P450 (CYP) content and the extent of metyrapone binding; moreover, an augmentation of protein amounts and related enzyme activities was observed for known PB targets such as CYP2B, 2C, and 3A, but also CYP2E1. However, contradictory results were obtained for CYP1A, while a decreased catalytic activity was observed for flavin-containing monooxygenases 1 and 3. The barbiturate had no effect on the chosen hydrolytic and conjugative DMEs. For the first time, we also measured the 26S proteasome activity, and the increase observed in PB-treated cattle would suggest this post-translational event might contribute to cattle DME regulation. Overall, this study increased the knowledge of cattle hepatic drug metabolism, and further confirmed the presence of species differences in DME expression and activity between cattle, humans, and rodents. This reinforced the need for an extensive characterization and understanding of comparative molecular mechanisms involved in expression, regulation, and function of DMEs.

Interindividual Variability and Differential Tissue Abundance of Mitochondrial Amidoxime Reducing Component Enzymes in Humans

Mitochondrial amidoxime-reducing component (mARC) enzymes are molybdenum-containing proteins that metabolize a number of endobiotics and xenobiotics. The interindividual variability and differential tissue abundance of mARC1 and mARC2 were quantified using targeted proteomics in three types of tissue fractions: 1) pediatric liver tissue homogenates, 2) total membrane fraction of the paired liver and kidney samples from pediatric and adult donors, and 3) pooled S9 fractions of the liver, intestine, kidney, lung, and heart. The absolute levels of mARC1 and mARC2 in the pediatric liver homogenate were 40.08 ± 4.26 and 24.58 ± 4.02 pmol/mg homogenate protein, respectively, and were independent of age and sex. In the total membrane fraction of the paired liver and kidney samples, the abundance of hepatic mARC1 and mARC2 was comparable, whereas mARC2 abundance in the kidney was approximately 9-fold higher in comparison with mARC1. The analysis of the third set of samples (i.e., S9 fraction) revealed that mARC1 abundance in the kidney, intestine, and lung was 5- to 13-fold lower than the liver S9 abundance, whereas mARC2 abundance was approximately 3- and 16-fold lower in the intestine and lung than the liver S9, respectively. In contrast, the kidney mARC2 abundance in the S9 fraction was approximately 2.5-fold higher as compared with the hepatic mARC2 abundance. The abundance of mARC enzymes in the heart was below the limit of quantification (∼0.6 pmol/mg protein). The mARC enzyme abundance data presented here can be used to develop physiologically based pharmacokinetic models for the prediction of in vivo pharmacokinetics of mARC substrates. SIGNIFICANCE STATEMENT: A precise targeted quantitative proteomics method was developed and applied to quantify newly discovered drug-metabolizing enzymes, mARC1 and mARC2, in pediatric and adult tissue samples. The data suggest that mARC enzymes are ubiquitously expressed in an isoform-specific manner in the human liver, kidney, intestine, and lung, and the enzyme abundance is not associated with age and sex. These data are important for developing physiologically based pharmacokinetic models for the prediction of in vivo pharmacokinetics of mARC substrates.

The Role of Uptake and Efflux Transporters in the Disposition of Glucuronide and Sulfate Conjugates

Glucuronidation and sulfation are the most typical phase II metabolic reactions of drugs. The resulting glucuronide and sulfate conjugates are generally considered inactive and safe. They may, however, be the most prominent drug-related material in the circulation and excreta of humans. The glucuronide and sulfate metabolites of drugs typically have limited cell membrane permeability and subsequently, their distribution and excretion from the human body requires transport proteins. Uptake transporters, such as organic anion transporters (OATs and OATPs), mediate the uptake of conjugates into the liver and kidney, while efflux transporters, such as multidrug resistance proteins (MRPs) and breast cancer resistance protein (BCRP), mediate expulsion of conjugates into bile, urine and the intestinal lumen. Understanding the active transport of conjugated drug metabolites is important for predicting the fate of a drug in the body and its safety and efficacy. The aim of this review is to compile the understanding of transporter-mediated disposition of phase II conjugates. We review the literature on hepatic, intestinal and renal uptake transporters participating in the transport of glucuronide and sulfate metabolites of drugs, other xenobiotics and endobiotics. In addition, we provide an update on the involvement of efflux transporters in the disposition of glucuronide and sulfate metabolites. Finally, we discuss the interplay between uptake and efflux transport in the intestine, liver and kidneys as well as the role of transporters in glucuronide and sulfate conjugate toxicity, drug interactions, pharmacogenetics and species differences.

Metopimazine is primarily metabolized by a liver amidase in humans

Metopimazine (MPZ) is a peripherally restricted, dopamine D2 receptor antagonist used for four decades to treat acute nausea and vomiting. MPZ is currently under clinical investigation for the treatment of gastroparesis (GP). MPZ undergoes high first-pass metabolism that produces metopimazine acid (MPZA), the major circulating metabolite in humans. Despite a long history of use, the enzymes involved in the metabolism of MPZ have not been identified. Here we report a series of studies designed to identify potential MPZ metabolites in vitro, determine their clinical relevance in humans, and elucidate the enzymes responsible for their formation. The findings demonstrated that the formation of MPZA was primarily catalyzed by human liver microsomal amidase. Additionally, human liver cytosolic aldehyde oxidase (AO) catalyzes the formation of MPZA, in vitro, although to a much lesser extent. Neither cytochrome P450 enzymes nor flavin-monooxygenases (FMO) were involved in the formation MPZA, although two minor oxidative pathways were catalyzed by CYP3A4 and CYP2D6 in vitro. Analysis of plasma samples from subjects dosed 60 mg of MPZ verified that these oxidative pathways are very minor and that CYP enzyme involvement was negligible compared to microsomal amidase/hydrolase in overall MPZ metabolism in humans. The metabolism by liver amidase, an enzyme family not well defined in small molecule drug metabolism, with minimal metabolism by CYPs, differentiates this drug from current D2 antagonists used or in development for the treatment of GP.

INTERSYSTEM EXTRAPOLATION FACTORS (ISEF) ARE SUBSTRATE-DEPENDENT FOR CYP3A4: IMPACT ON CYTOCHROME P450 REACTION PHENOTYPING

The use of intersystem extrapolation factors (ISEF) is required for the quantitative scaling of drug metabolism data generated in individually expressed cytochrome P450 enzymes when estimating fractional contribution to metabolism by P450 enzymes in vivo (f_m,_CYP). For successful prediction of f_m, ISEF values must be universal across all substrates for any individual enzyme. In this study, ISEF values were generated for ten CYP3A4 selective substrates using a common source of recombinant heterologously expressed CYP3A4 and a pool of human liver microsomes. The resulting ISEF values for CYP3A4 were substrate-dependent and ranged 8-fold, with the highest value generated from intrinsic clearance of midazolam depletion (0.36) and the lowest from quinidine depletion (0.044). Application of these ISEF values for estimation of the fractional contribution of CYP3A4 and CYP2C19 to omeprazole clearance yielded values that ranged from 0.21-0.63 and 0.37-0.79, respectively, as compared to back-extrapolated in vivo f_m values of 0.27 (CYP3A4) and 0.85 (CYP2C19) from clinical pharmacokinetic data. For risperidone, estimated f_m values for CYP3A4 and CYP2D6 ranged from 0.87-0.98 and 0.02-0.13, respectively, as compared to in vivo values of 0.36 (CYP3A4) and 0.63-0.88 (CYP2D6), showing that the importance of CYP3A4 was over-estimated and the importance of CYP2D6 under-estimated. Overall, these findings suggest that ISEF values for CYP3A4 can vary with the marker substrate used to derive them, thereby reducing the effectiveness of the approach of using metabolism data from rCYP3A4 with ISEF values for the prediction of f_m values in vivo. Significance Statement Intersystem extrapolation factors (ISEF) are utilized for assigning fractional contributions of individual enzymes to drug clearance (f_m) from drug metabolism data generated in recombinant P450s. The present data shows that ISEF values for cytochrome P4503A4 vary with the substrate. This can lead to variable and erroneous prediction of f_m.

Non-P450 Drug-Metabolizing Enzymes: Contribution to Drug Disposition, Toxicity, and Development

Most clinically used drugs are metabolized in the body via oxidation, reduction, or hydrolysis reactions, which are considered phase I reactions. Cytochrome P450 (P450) enzymes, which primarily catalyze oxidation reactions, contribute to the metabolism of over 50% of clinically used drugs. In the last few decades, the function and regulation of P450s have been extensively studied, whereas the characterization of non-P450 phase I enzymes is still incomplete. Recent studies suggest that approximately 30% of drug metabolism is carried out by non-P450 enzymes. This review summarizes current knowledge of non-P450 phase I enzymes, focusing on their roles in controlling drug efficacy and adverse reactions as an important aspect of drug development. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

How Science Is Driving Regulatory Guidances

This chapter provides regulatory perspectives on how to translate in vitro drug metabolism findings into in vivo drug-drug interaction (DDI) predictions and how this affects the decision of conducting in vivo DDI evaluation. The chapter delineates rationale and analyses that have supported the recommendations in the U.S. Food and Drug Administration (FDA) DDI guidances in terms of in vitro-in vivo extrapolation of cytochrome P450 (CYP) inhibition-mediated DDI potential for investigational new drugs and their metabolites as substrates or inhibitors. The chapter also describes the framework and considerations to assess UDP-glucuronosyltransferase (UGT) inhibition-mediated DDI potential for drugs as substrates or inhibitors. The limitations of decision criteria and further improvements needed are also discussed. Case examples are provided throughout the chapter to illustrate how decision criteria have been utilized to evaluate in vivo DDI potential from in vitro data.

Reaction Phenotyping of Low-Turnover Compounds in Long-Term Hepatocyte Cultures Through Persistent Selective Inhibition of Cytochromes P450

Recognizing the challenges of determining the relative contribution of different drug metabolizing enzymes to the metabolism of slowly metabolized compounds, a cytochrome P450 reaction phenotyping (CRP) method using cocultured human hepatocytes (HEPATOPAC) has been established. In this study, the emphasis on the relative contribution of different cytochrome P450 (P450) isoforms was assessed by persistently inhibiting P450 isoforms over 7 days with human HEPATOPAC. P450 isoform-selective inhibition was achieved with the chemical inhibitors furafylline (CYP1A2), tienilic acid (CYP2C9), (+)-N-3-benzylnirvanol (CYP2C19), paroxetine (CYP2D6), azamulin (CYP3A), and a combination of 1-aminobenzotriazole and tienilic acid (broad spectrum inhibition of P450s). We executed this CRP method using HEPATOPAC by optimizing for the choice of P450 inhibitors, their selectivity, and the temporal effect of inhibitor concentrations on maintaining selectivity of inhibition. In general, the established CRP method using potent and selective chemical inhibitors allows to measure the relative contribution of P450s and to calculate the fraction of metabolism (f _m) of low-turnover compounds. Several low-turnover compounds were used to validate this CRP method by determining their hepatic intrinsic clearance and f _m, with comparison with literature values. We established the foundation of a robust CRP for low-turnover compound test system which can be expanded to include inhibition of other drug metabolizing enzymes. This generic CRP assay, using human long-term hepatocyte cultures, will be an essential tool in drug development for new chemical entities in the quantitative assessment of the risk as a victim of drug-drug interactions. SIGNIFICANCE STATEMENT: An ongoing trend is to develop drug candidates which have limited metabolic clearance. The current studies report a generic approach to conducting reaction phenotyping studies with human HEPATOPAC, focusing on P450 metabolism of low-turnover compounds. Potent and selective chemical inhibitors were used to assess the relative contribution of the major human P450s. Validation was achieved by confirming hepatic intrinsic clearance and fraction of metabolism for previously reported low-turnover compounds. This approach is adaptable for assessment of all drug metabolizing enzymes.

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.

Differences in Hydrolase Activities in the Liver and Small Intestine between Marmosets and Humans

For drug development, species differences in drug-metabolism reactions present obstacles for predicting pharmacokinetics in humans. We characterized the species differences in hydrolases among humans and mice, rats, dogs, and cynomolgus monkeys. In this study, to expand the series of such studies, we attempted to characterize marmoset hydrolases. We measured hydrolase activities for 24 compounds using marmoset liver and intestinal microsomes, as well as recombinant marmoset carboxylesterase (CES) 1, CES2, and arylacetamide deacetylase (AADAC). The contributions of CES1, CES2, and AADAC to hydrolysis in marmoset liver microsomes were estimated by correcting the activities by using the ratios of hydrolase protein levels in the liver microsomes and those in recombinant systems. For six out of eight human CES1 substrates, the activities in marmoset liver microsomes were lower than those in human liver microsomes. For two human CES2 substrates and three out of seven human AADAC substrates, the activities in marmoset liver microsomes were higher than those in human liver microsomes. Notably, among the three rifamycins, only rifabutin was hydrolyzed by marmoset tissue microsomes and recombinant AADAC. The activities for all substrates in marmoset intestinal microsomes tended to be lower than those in liver microsomes, which suggests that the first-pass effects of the CES and AADAC substrates are due to hepatic hydrolysis. In most cases, the sums of the values of the contributions of CES1, CES2, and AADAC were below 100%, which indicated the involvement of other hydrolases in marmosets. In conclusion, we clarified the substrate preferences of hydrolases in marmosets. SIGNIFICANCE STATEMENT: This study confirmed that there are large differences in hydrolase activities between humans and marmosets by characterizing marmoset hydrolase activities for compounds that are substrates of human CES1, CES2, or arylacetamide deacetylase. The data obtained in this study may be useful for considering whether marmosets are appropriate for examining the pharmacokinetics and efficacies of new chemical entities in preclinical studies.

A comprehensive review of in silico approaches for the prediction and modulation of aldehyde oxidase-mediated drug metabolism: The current features, challenges and future perspectives

The importance of aldehyde oxidase (AOX) in drug metabolism necessitates the development and application of the in silico rational drug design methods as an integral part of drug discovery projects for the early prediction and modulation of AOX-mediated metabolism. The current study represents an up-to-date and thorough review of in silico studies of AOX-mediated metabolism and modulation methods. In addition, the challenges and the knowledge gap that should be covered have been discussed. The importance of aldehyde oxidase (AOX) in drug metabolism is a hot topic in drug discovery. Different strategies are available for the modulation of the AOX-mediated metabolism of drugs. Application of the rational drug design methods as an integral part of drug discovery projects is necessary for the early prediction of AOX-mediated metabolism. The current study represents a comprehensive review of AOX molecular structure, AOX-mediated reactions, AOX substrates, AOX inhibition, approaches to modify AOX-mediated metabolism, prediction of AOX metabolism/substrates/inhibitors, and the AOX related structure-activity relationship (SAR) studies. Furthermore, an up-to-date and thorough review of in silico studies of AOX metabolism has been carried out. In addition, the challenges and the knowledge gap that should be covered in the scientific literature have been discussed in the current review.

Recent developments in predicting CYP-independent metabolism

As lead optimization efforts have successfully reduced metabolic liabilities due to cytochrome P450 (CYP)-mediated metabolism, there has been an increase in the frequency of involvement of non-CYP enzymes in the metabolism of investigational compounds. Although there have been numerous notable advancements in the characterization of non-CYP enzymes with respect to their localization, reaction mechanisms, species differences and identification of typical substrates, accurate prediction of non-CYP-mediated clearance, with a particular emphasis with the difficulties in accounting for any extrahepatic contributions, remains a challenge. The current manuscript comprehensively summarizes the recent advancements in the prediction of drug metabolism and the in vitro to in vitro extrapolation of clearance for substrates of non-CYP drug metabolizing enzymes.

Recent developments in in vitro and in vivo models for improved translation of preclinical pharmacokinetics and pharmacodynamics data

Improved pharmacokinetics/pharmacodynamics (PK/PD) prediction in the early stages of drug development is essential to inform lead optimization strategies and reduce attrition rates. Recently, there have been significant advancements in the development of new in vitro and in vivo strategies to better characterize pharmacokinetic properties and efficacy of drug leads. Herein, we review advances in experimental and mathematical models for clearance predictions, advancements in developing novel tools to capture slowly metabolized drugs, in vivo model developments to capture human etiology for supporting drug development, limitations and gaps in these efforts, and a perspective on the future in the field.

Stability of Ketoprofen Methylester in Plasma of Different Species

BACKGROUND

Pharmacokinetic and pharmacodynamic assessment of ester-containing drugs can be impacted by hydrolysis of the drugs in plasma samples post blood collection. The impact is different in the plasma of different species.

OBJECTIVE

This study evaluated the stability of a prodrug, ketoprofen methylester (KME), in commercially purchased and freshly collected plasma of mouse, rat, dog, cat, pig, sheep, cattle and horse.

METHODS

KME hydrolysis was determined following its incubation in commercially purchased and freshly collected plasma of those species. Different esterase inhibitors were evaluated for prevention of the hydrolysis in rat, dog and pig plasma.

RESULTS

KME was rapidly hydrolyzed in both commercially purchased and freshly collected plasma of mouse, rat, and horse. The hydrolysis was initially quick and then limited in cat plasma. KME hydrolysis was minimum in commercially purchased plasma of dog, pig, sheep and cattle but substantial in freshly collected plasma of those species. Different esterase inhibitors showed different effects on the stability of KME in rat, dog and pig plasma.

CONCLUSION

These results indicate that plasma of different species has different hydrolytic activities to estercontaining drugs. The activities in commercially purchased and freshly collected plasma may be different and species-dependent. Esterase inhibitors have different effects on preventing hydrolysis of the ester-containing drugs in the plasma of different species.

Evaluation of Pharmacokinetic Drug-Drug Interactions: A Review of the Mechanisms, In Vitro and In Silico Approaches

Pharmacokinetic drug–drug interactions (DDIs) occur when a drug alters the absorption, transport, distribution, metabolism or excretion of a co-administered agent. The occurrence of pharmacokinetic DDIs may result in the increase or the decrease of drug concentrations, which can significantly affect the drug efficacy and safety in patients. Enzyme-mediated DDIs are of primary concern, while the transporter-mediated DDIs are less understood but also important. In this review, we presented an overview of the different mechanisms leading to DDIs, the in vitro experimental tools for capturing the factors affecting DDIs, and in silico methods for quantitative predictions of DDIs. We also emphasized the power and strategy of physiologically based pharmacokinetic (PBPK) models for the assessment of DDIs, which can integrate relevant in vitro data to simulate potential drug interaction in vivo. Lastly, we pointed out the future directions and challenges for the evaluation of pharmacokinetic DDIs.

Prediction of Total Drug Clearance in Humans Using Animal Data: Proposal of a Multimodal Learning Method Based on Deep Learning

Research into pharmacokinetics plays an important role in the development process of new drugs. Accurately predicting human pharmacokinetic parameters from preclinical data can increase the success rate of clinical trials. Since clearance (CL) which indicates the capacity of the entire body to process a drug is one of the most important parameters, many methods have been developed. However, there are still rooms to be improved for practical use in drug discovery research; "improving CL prediction accuracy" and "understanding the chemical structure of compounds in terms of pharmacokinetics". To improve those, this research proposes a multimodal learning method based on deep learning that takes not only the chemical structure of a drug but also rat CL as inputs. Good results were obtained compared with the conventional animal scale-up method; the geometric mean fold error was 2.68 and the proportion of compounds with prediction errors of 2-fold or less was 48.5%. Furthermore, it was found to be possible to infer the partial structure useful for CL prediction by a structure contributing factor inference method. The validity of these results of structural interpretation of metabolic stability was confirmed by chemists.

Case Study 10: A Case to Investigate Acetyl Transferase Kinetics

Major routes of metabolism for marketed drugs are predominately driven by enzyme families such as cytochromes P450 and UDP-glucuronosyltransferases. Less studied conjugative enzymes, like N-acetyltransferases (NATs), are commonly associated with detoxification pathways. However, in the clinic, the high occurrence of NAT polymorphism that leads to slow and fast acetylator phenotypes in patient populations has been linked to toxicity for a multitude of drugs. A key example of this is the observed clinical toxicity in patients who exhibit the slow acetylator phenotype and were treated with isoniazid. Toxicity in patients has led to detailed characterization of the two NAT isoforms and their polymorphic genotypes. Investigation in recombinant enzymes, genotyped hepatocytes, and in vivo transgenic models coupled with acetylator status-driven clinical studies have helped understand the role of NATs in drug development, clinical study design and outcomes, and potential roles in human disease models. The selected case studies herein document NAT enzyme kinetics to explore substrate overlap from two human isoforms, preclinical species considerations, and clinical genotype population concerns.

Reversible Mechanisms of Enzyme Inhibition and Resulting Clinical Significance

Inhibition of a drug-metabolizing enzyme by the reversible interaction of a drug with the enzyme, thus decreasing the metabolism of another drug, is a major cause of clinically significant drug-drug interactions. This chapter defines the four reversible mechanisms of inhibition exhibited by drugs: competitive, noncompetitive, uncompetitive, and mixed competitive/noncompetitive. An in vitro procedure to determine the potential of a drug to be a reversible inhibitor is also provided. Finally, a number of examples of clinically significant drug-drug interactions resulting from reversible inhibition are described.

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.