Physicochemical Properties, Biotransformation, and Transport Pathways of Established and Newly Approved Medications: A Systematic Review of the Top 200 Most Prescribed Drugs vs. the FDA-Approved Drugs Between 2005 and 2016

CYP2D6 copy number determination using digital PCR

Background

CYP2D6 testing is increasingly used to guide drug therapy and thus, reliable methods are needed to test this complex and polymorphic gene locus. A particular challenge arises from the detection and interpretation of structural variants (SVs) including gene deletions, duplications, and hybrids with the CYP2D7 pseudogene. This study validated the Absolute Q™ platform for digital PCR-based CYP2D6 copy number variation (CNV) determination by comparing results to those obtained with a previously established method using the QX200 platform. In addition, protocols for streamlining CYP2D6 CNV testing were established and validated including the "One-pot" single-step restriction enzyme digestion and a multiplex assay simultaneously targeting the CYP2D6 5'UTR, intron 6, and exon 9 regions.

Methods

Genomic DNA (gDNA) samples from Coriell (n = 13) and from blood, saliva, and liver tissue (n = 17) representing 0-6 copies were tested on the Absolute Q and QX200 platforms. Custom TaqMan™ copy number (CN) assays targeting CYP2D6 the 5'UTR, intron 6, and exon 9 regions and a reference gene assay (TERT or RNaseP) were combined for multiplexing by optical channel. In addition, two digestion methods (One-pot digestion and traditional) were assessed. Inconclusive CN values on the Absolute Q were resolved using an alternate reference gene and/or diluting gDNA.

Results

Overall, results between the two platforms and digestions methods were consistent. The "One-pot" digestion method and optically multiplexing up to three CYP2D6 regions yielded consistent result across DNA sample types and diverse SVs, reliably detecting up to 6 gene copies. Rare variation in reference genes were found to interfere with results and interpretation, which were resolved by using a different reference.

Conclusion

The Absolute Q produced accurate and reliable CYP2D6 copy number results allowing for a streamlined and economical protocol using One-pot digestion and multiplexing three target regions. Protocols are currently being expanded to other pharmacogenes presenting with SVs/CNVs.

Qualitative and quantitative status of cytochrome P450s after the administration of a liposomal platelet substitute in rat liver

In the process of the drug development, studies on the cytochrome P450 (CYP) profiles after its administration provided fundamental information regarding drug interactions with concomitantly administered drugs. Here, we evaluated the influence of the administration of H12-(ADP)-liposomes, a platelet substitute, on the mRNA and protein expression, and metabolic activity of CYPs, with focus on the CYP1A2, CYP2C11 and CYP3A2, in rat liver.At 24 h after administering saline or H12-(ADP)-liposomes (10 mg of lipids/kg), a quantitative RT-PCR and western blot analysis revealed that the mRNA and proteins expression of all of the target hepatic CYP isoforms were not different between the saline and H12-(ADP)-liposome groups. Furthermore, an ex vivo CYP metabolic activity assay showed that hepatic CYP metabolic activities in the H12-(ADP)-liposome group were comparable to the corresponding saline group. On the other hand, the area under the blood concentration-time curve for substitutes for CYP1A2 and CYP2C11 was higher in H12-(ADP)-liposome group than in saline group, but the degree of elevations was negligible levels.At a minimum, based on these results, we conclude that H12-(ADP)-liposomes have no quantitative and qualitative effect on the hepatic CYP isoforms, indicating that the drug interactions of H12-(ADP)-liposomes with CYP-metabolizing drugs would be negligible.

Pregnane X receptor activation induces liver enlargement and regeneration and simultaneously promotes the metabolic activity of CYP3A1/2 and CYP2C6/11 in rats

Human pregnane X receptor (PXR) is critical for regulating the expression of key drug-metabolizing enzymes such as CYP3A and CYP2C. Our recent study revealed that treatment with rodent-specific PXR agonist pregnenolone-16α-carbonitrile (PCN) significantly induced hepatomegaly and promoted liver regeneration after two-thirds partial hepatectomy (PHx) in mice. However, it remains unclear whether PXR activation induces hepatomegaly and liver regeneration and simultaneously promotes metabolic function of the liver. Here, we investigated the metabolism activity of CYP1A2, CYP3A1/2 and CYP2C6/11 during PXR activation-induced liver enlargement and regeneration in rats after cocktail dosing of CYP probe drugs. For PCN-induced hepatomegaly, a notable increase in the metabolic activity of CYP3A1/2 and CYP2C6/11, as evidenced by the plasma exposure of probe substrates and the AUC ratios of the characteristic metabolites to its corresponding probe substrates. The metabolic activity of CYP1A2, CYP3A1/2 and CYP2C6/11 decreased significantly after PHx. However, PCN treatment obviously enhanced the metabolic activity of CYP2C6/11 and CYP3A1/2 in PHx rats. Furthermore, the protein expression levels of CYP3A1/2 and CYP2C6/11 in liver were up-regulated. Taken together, this study demonstrates that PXR activation not only induces hepatomegaly and liver regeneration in rats, but also promotes the protein expression and metabolic activity of the PXR downstream metabolizing enzymes such as CYP3A1/2 and CYP2C6/11 in the body.

Comparison of Relative Activity versus Relative Expression Factors (RAF versus REF) in Predicting Glucuronidation Mediated Drug Clearance Using Recombinant UGTs

PURPOSE

Predicting the quantitative fraction of glucuronidation (fgluc) by individual UDP-glucuronosyltransferase enzymes (UGTs) is challenging due to the lack of selective inhibitors and inconsistent activity of recombinant UGT systems (rUGTs). Our study compares the relative expression versus activity factors (REF versus RAF) to predict fgluc based on rUGT data to human liver and intestinal microsomes (HLM and HIM).

METHODS

REF scalars were derived from a previous in-house proteomics study for eleven UGT enzymes (UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A9, UGT1A10, UGT2B4, UGT2B7, UGT2B10, UGT2B15, and UGT2B17), whereas RAF was calculated by measuring activities in rUGTs to microsomes of selective UGT probe substrates. Protein-normalized activity factor (pnAF) values were generated after correcting activity of individual UGTs to their corresponding protein abundance. The utility of REF and RAF in predicting fgluc was assessed for three UGT substrates-diclofenac, vorinostat, and raltegravir.

RESULTS

The REF values ranged from 0.02 to 1.75, RAF based on activity obtained in rUGTs to HLM/HIM were from 0.1 to 274. pnAF values were ~ 5 to 80-fold, except for UGT2B4 and UGT2B15, where pnAF was ~ 180 and > 1000, respectively. The results revealed confounding effect of differential specific activities (per pmol) of rUGTs in fgluc prediction.

CONCLUSION

The data suggest that the activity of UGT enzymes was significantly lower when compared to their activity in microsomes at the same absolute protein amount (pmol). Collectively, results of this study demonstrate poor and variable specific activity of different rUGTs (per pmol protein), as determined by pnAF values, which should be considered in fgluc scaling.

Beyond Cytotoxic Potency: Disposition Features Required to Design ADC Payload

Antibody-drug conjugates (ADCs) have demonstrated impressive clinical usefulness in treating several types of cancer, with the notion of widening of the therapeutic index of the cytotoxic payload through the minimization of the systemic toxicity. Therefore, choosing the most appropriate payload molecule is a particularly important part of the early design phase of ADC development, especially given the highly competitive environment ADCs find themselves in today. The focus of the current review is to describe critical attributes/considerations needed in the discovery and ultimately development of cytotoxic payloads in support of ADC design. In addition to potency, several key dispositional characteristics including solubility, permeability and bystander effect, pharmacokinetics, metabolism, and drug-drug interactions, are described as being an integral part of the integrated activities required in the design of clinically safe and useful ADC therapeutic agents.

Predicting routes of phase I and II metabolism based on quantum mechanics and machine learning

Unexpected metabolism could lead to the failure of many late-stage drug candidates or even the withdrawal of approved drugs. Thus, it is critical to predict and study the dominant routes of metabolism in the early stages of research.We describe the development and validation of a 'WhichEnzyme' model that accurately predicts the enzyme families most likely to be responsible for a drug-like molecule's metabolism. Furthermore, we combine this model with our previously published regioselectivity models for Cytochromes P450, Aldehyde Oxidases, Flavin-containing Monooxygenases, UDP-glucuronosyltransferases and Sulfotransferases - the most important Phase I and Phase II drug metabolising enzymes - and a 'WhichP450' model that predicts the Cytochrome P450 isoform(s) responsible for a compound's metabolism.The regioselectivity models are based on a mechanistic understanding of these enzymes' actions and use quantum mechanical simulations with machine learning methods to accurately predict sites of metabolism and the resulting metabolites. We train heuristics based on the outputs of the 'WhichEnzyme', 'WhichP450', and regioselectivity models to determine the most likely routes of metabolism and metabolites to be observed experimentally.Finally, we demonstrate that this combination delivers high sensitivity in identifying experimentally reported metabolites and higher precision than other methods for predicting in vivo metabolite profiles.

Prediction of drug-drug interaction risk of P-glycoprotein substrate in drug discovery

We aimed at predicting the drug-drug interaction (DDI) risk of P-glycoprotein (P-gp) substrates by using P-gp expressing LLC-PK1 cells and its knockout mice (KO). The area under the curve (AUC) of 16 marketed drugs and plasma concentration (Cplasma) of 207 screening compounds, with corrected efflux ratio (CER) ≥ 2, were compared between P-gp KO mice and wild type mice (WT). At permeability (Papp) ≥ 10 × 10-6 cm/s in parent LLC-PK1 cells, AUC ratios (KO/WT) and Cplasma ratios (KO/WT) of these compounds were within 3-fold. AUC ratios (KO/WT) of clinical P-gp substrates, with human AUC ratios with and without P-gp inhibitor administration ≥2, were higher than 8.7. These observations led us to establish a work-flow of P-gp substrate assessment with the threshold AUC ratio (KO/WT) ≥ 9 leading to a DDI risk of AUC ratio (human) ≥ 2. A screening compound showing high CER (=57.6) was found, but its AUC ratio (KO/WT) was 3.7, had been presumed to be a weak risk and its AUC ratio (human) was 1.2 in a later clinical DDI study. Our proposed workflow should be useful for predicting the DDI risk of P-gp substrates in drug discovery.

Small molecule drug metabolite synthesis and identification: why, when and how?

The drug discovery and development process encompasses the interrogation of metabolites arising from the biotransformation of drugs. Here we look at why, when and how metabolites of small-molecule drugs are synthesised from the perspective of a specialist contract research organisation, with particular attention paid to projects for which regulatory oversight is relevant during this journey. To illustrate important aspects, we look at recent case studies, trends and learnings from our experience of making and identifying metabolites over the past ten years, along with with selected examples from the literature.

A review on mycogenic metallic nanoparticles and their potential role as antioxidant, antibiofilm and quorum quenching agents

The emergence of antimicrobial resistance among biofilm forming pathogens aimed to search for the efficient and novel alternative strategies. Metallic nanoparticles have drawn a considerable attention because of their significant applications in various fields. Numerous methods are developed for the generation of these nanoparticles however, mycogenic (fungal-mediated) synthesis is attractive due to high yields, easier handling, eco-friendly and being energy efficient when compared with conventional physico-chemical methods. Moreover, mycogenic synthesis provides fungal derived biomolecules that coat the nanoparticles thus improving their stability. The process of mycogenic synthesis can be extracellular or intracellular depending on the fungal genera used and various factors such as temperature, pH, biomass concentration and cultivation time may influence the synthesis process. This review focuses on the synthesis of metallic nanoparticles by using fungal mycelium, mechanism of synthesis, factors affecting the mycosynthesis and also describes their potential applications as antioxidants and antibiofilm agents. Moreover, the utilization of mycogenic nanoparticles as quorum quenching agent in hampering the bacterial cell-cell communication (quorum sensing) has also been discussed.

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.

Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent Inhibition

Most drugs are mainly metabolized by cytochrome P450 (CYP450), which can lead to drug-drug interactions (DDI). Specifically, time-dependent inhibition (TDI) of CYP3A4 isoenzyme has been associated with clinically relevant DDI. To overcome potential DDI issues, high-throughput in vitro assays were established to assess the TDI of CYP3A4 during the discovery and lead optimization phases. However, in silico machine learning models would enable an earlier and larger-scale assessment of TDI potential liabilities. For CYP inhibition, most modeling efforts have focused on highly imbalanced and small data sets. Moreover, assay variability is rarely considered, which is key to understand the model's quality and suitability for decision-making. In this work, machine learning models were built for the prediction of TDI of CYP3A4, evaluated prospectively, and compared to the variability of the experimental assay. Different modeling strategies were investigated to assess their influence on the model's performance. Through multitask learning, additional data sets were leveraged for model building, coming from public databases, in-house CYP-related assays, or other pharmaceutical companies (federated learning). Apart from the numerical prediction of inactivation rates of CYP3A4 TDI, three-class predictions were carried out, giving a negative (inactivation rate kobs < 0.01 min-1), weak positive (0.01 ≤ kobs ≤ 0.025 min-1), or positive (kobs > 0.025 min-1) output. The final multitask graph neural network model achieved misclassification rates of 8 and 7% for positive and negative TDI, respectively. Importantly, the presented deep learning-based predictions had a similar precision to the reproducibility of in vitro experiments and thus offered great opportunities for drug design, early derisk of DDI potential, and selection of experiments. To facilitate CYP inhibition modeling efforts in the public domain, the developed model was used to annotate ∼16 000 publicly available structures, and a surrogate data set is shared as Supporting Information.

Comparison of brexpiprazole, aripiprazole, and placebo for Japanese major depressive disorder: A systematic review and network meta-analysis

AIM

This systematic review and frequentist network meta-analysis used random-effects models is conducted to determine whether there are differences in the efficacy, acceptability, tolerability, and safety profiles of brexpiprazole (BRE) and aripiprazole (ARI) for Japanese with major depressive disorder (MDD) who were inadequately responsive to antidepressants.

METHODS

Outcome measures were scores on the Montgomery Åsberg Depression Rating Scale (primary), the Clinical Global Impression severity scale, and social functioning scale; the non-response rate; the non-remission rate; all-cause discontinuation; discontinuation due to adverse events (DAE); at least one adverse event (1AE); serious adverse event, akathisia; tremor; weight gain.

RESULTS

A literature search identified three double-blind, randomized, placebo-controlled trials. These comprised one BRE study (with a 1 mg/day [BRE1] and a 2 mg/day [BRE2]) and two ARI studies (with a 3 mg/day arm and a flexible-dose arm[within the dosage range approved in Japan]) (n = 1736). Both BRE and ARI demonstrated better efficacy than the placebo. BRE but not ARI had a higher DAE than the placebo. ARI but not BRE had a higher 1AE than the placebo. BRE and ARI had a higher risk of akathisia and weight gain than the placebo. There were no significant differences between BRE and ARI for any of the outcomes. Although BRE1 had good efficacy, it carried risk of weight gain. Although BRE2 also had efficacy, it carried risks of DAE, akathisia, and weight gain. However, the risk of akathisia in BRE2 was reduced by an initial dose of 0.5 mg/day rather than 1.0 mg/day.

CONCLUSIONS

Overall BRE showed similar utility to ARI and a good risk-benefit balance.

Characterization of CYP3A5 Selective Inhibitors for Reaction Phenotyping of Drug Candidates

CYP3A is one of the most important classes of enzymes and is involved in the metabolism of over 70% drugs. While several selective CYP3A4 inhibitors have been identified, the search for a selective CYP3A5 inhibitor has turned out to be rather challenging. Recently, several selective CYP3A5 inhibitors have been identified through high-throughput screening of ~ 11,000 compounds and hit expansion using human recombinant enzymes. We set forth to characterize the three most selective CYP3A5 inhibitors in a more physiologically relevant system of human liver microsomes to understand if these inhibitors can be used for reaction phenotyping studies in drug discovery settings. Gomisin A and T-5 were used as selective substrate reactions for CYP3A4 and CYP3A5 to determine IC50 values of the two enzymes. The results showed that clobetasol propionate and loteprednol etabonate were potent and selective CYP3A5 reversible inhibitors with selectivity of 24-fold against CYP3A4 and 39-fold or more against the other major CYPs. The selectivity of difluprednate in HLM is much weaker than that in the recombinant enzymes due to hydrolysis of the acetate group in HLM. Based on the selectivity data, loteprednol etabonate can be utilized as an orthogonal approach, when experimental fraction metabolized of CYP3A5 is greater than 0.5, to understand CYP3A5 contribution to drug metabolism and its clinical significance. Future endeavors to identify even more selective CYP3A5 inhibitors are warranted to enable accurate determination of CYP3A5 contribution to metabolism versus CYP3A4.

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.

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).

PharmVar Tutorial on CYP2D6 Structural Variation Testing and Recommendations on Reporting

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus and a comprehensive summary of structural variation. CYP2D6 contributes to the metabolism of numerous drugs and, thus, genetic variation in its gene impacts drug efficacy and safety. To accurately predict a patient's CYP2D6 phenotype, testing must include structural variants including gene deletions, duplications, hybrid genes, and combinations thereof. This tutorial offers a comprehensive overview of CYP2D6 structural variation, terms, and definitions, a review of methods suitable for their detection and characterization, and practical examples to address the lack of standards to describe CYP2D6 structural variants or any other pharmacogene. This PharmVar tutorial offers practical guidance on how to detect the many, often complex, structural variants, as well as recommends terms and definitions for clinical and research reporting. Uniform reporting is not only essential for electronic health record-keeping but also for accurate translation of a patient's genotype into phenotype which is typically utilized to guide drug therapy.

Delivery and Transcriptome Assessment of an In Vitro Three-Dimensional Proximal Tubule Model Established by Human Kidney 2 Cells in Clinical Gelatin Sponges

The high prevalence of kidney diseases and the low identification rate of drug nephrotoxicity in preclinical studies reinforce the need for representative yet feasible renal models. Although in vitro cell-based models utilizing renal proximal tubules are widely used for kidney research, many proximal tubule cell (PTC) lines have been indicated to be less sensitive to nephrotoxins, mainly due to altered expression of transporters under a two-dimensional culture (2D) environment. Here, we selected HK-2 cells to establish a simplified three-dimensional (3D) model using gelatin sponges as scaffolds. In addition to cell viability and morphology, we conducted a comprehensive transcriptome comparison and correlation analysis of 2D and 3D cultured HK-2 cells to native human PTCs. Our 3D model displayed stable and long-term growth with a tubule-like morphology and demonstrated a more comparable gene expression profile to native human PTCs compared to the 2D model. Many missing or low expressions of major genes involved in PTC transport and metabolic processes were restored, which is crucial for successful nephrotoxicity prediction. Consequently, we established a cost-effective yet more representative model for in vivo PTC studies and presented a comprehensive transcriptome analysis for the systematic characterization of PTC lines.

Quantitative Translation of Substrate Intrinsic Clearance from Recombinant CYP1A1 to Humans

CYP1A1 is a cytochrome P450 family 1 enzyme that is mostly expressed in the extrahepatic tissues. To understand the CYP1A1 contribution to drug clearance in humans, we examined the in vitro-in vivo extrapolation (IVIVE) of intrinsic clearance (CLint) for a set of drugs that are in vitro CYP1A1 substrates. Despite being strong in vitro CYP1A1 substrates, 82% of drugs gave good IVIVE with predicted CLint within 2-3-fold of the observed values using human liver microsomes and hepatocytes, suggesting they were not in vivo CYP1A1 substrates due to the lack of extrahepatic contribution to CLint. Only three drugs (riluzole, melatonin and ramelteon) that are CYP1A2 substrates yielded significant underprediction of in vivo CLint up to 11-fold. The fold of CLint underprediction was linearly proportional to human recombinant CYP1A1 (rCYP1A1) CLint, indicating they were likely to be in vivo CYP1A1 substrates. Using these three substrates, a calibration curve can be developed to enable direct translation from in vitro rCYP1A1 CLint to in vivo extrahepatic contributions in humans. In vivo CYP1A1 substrates are planar and small, which is consistent with the structure of the active site. This is in contrast to the in vitro substrates, which include large and nonplanar molecules, suggesting rCYP1A1 is more accessible than what is in vivo. The impact of CYP1A1 on first-pass intestinal metabolism was also evaluated and shown to be minimal. This is the first study providing new insights on in vivo translation of CYP1A1 contributions to human clearance using in vitro rCYP1A1 data.

Development and Verification of a Japanese Pediatric Physiologically Based Pharmacokinetic Model with Emphasis on Drugs Eliminated by Cytochrome P450 or Renal Excretion

Physiologically based pharmacokinetic (PBPK) models are useful in bridging drug exposure in different ethnic groups, and there is increasing regulatory application of this approach in adults. Reported pediatric PBPK models tend to focus on the North European population, with few examples in other ethnic groups. This study describes the development and verification of a Japanese pediatric PBPK population. The development of the model was based on the existing North European pediatric population. Japanese systems and clinical data were collated from public databases and the literature, and the underlying demographics and equations were optimized so that physiological outputs represented the Japanese pediatric population. The model was tested using 14 different small molecule drugs, eliminated by a variety of pathways, including cytochrome P450 3A4 (CYP3A4) metabolism and renal excretion. Given the limitations of the clinical data, the overall performance of the model was good, with 44/62 predictions for PK parameters (area under the plasma drug concentration-time curve, AUC; maximum serum concentration, Cmax ; clearance, CL) being within 0.8- to 1.25-fold, 56/62 within 0.67- to 1.5-fold, and 61/62 within 0.5- to 2.0-fold of the observed values. Specific results for the 5 CYP3A4 substrates showed 20/31 cases were predicted within 0.8- to 1.25-fold, 27/31 within 0.67- to 1.5-fold, and all were within 0.5- to 2.0-fold of the observed values. Given the increased regulatory use of pediatric PBPK in drug development, expanding these models to other ethnic groups are important. Considering qualifying these models based on the context of use, there is a need to expand on the current research to include a larger range of drugs with different elimination pathways. Collaboration among academic, industry, model providers, and regulators will facilitate further development.

CYP3A4 and CYP3A5 Genotyping Recommendations: A Joint Consensus Recommendation of the Association for Molecular Pathology, Clinical Pharmacogenetics Implementation Consortium, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, European Society for Pharmacogenomics and Personalized Therapy, and Pharmacogenomics Knowledgebase

The goals of the Association for Molecular Pathology Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations for a minimum panel of variant alleles (tier 1) and an extended panel of variant alleles (tier 2) that will aid clinical laboratories when designing assays for PGx testing. The Association for Molecular Pathology PGx Working Group considered functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. The goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This document will focus on clinical CYP3A4 and CYP3A5 PGx testing that may be applied to all CYP3A4- and CYP3A5-related medications. These recommendations are not to be interpreted as prescriptive but to provide a reference guide.

Characterization of Reference Materials for CYP3A4 and CYP3A5: A (GeT-RM) Collaborative Project

Pharmacogenetic testing for CYP3A4 is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the CYP3A4 variants included in clinical tests. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program (GeT-RM), in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 30 DNA samples derived from Coriell cell lines for CYP3A4. Samples were distributed to five volunteer laboratories for genotyping using a variety of commercially available and laboratory-developed tests. Sanger and next-generation sequencing were also utilized by some of the laboratories. Whole-genome sequencing data from the 1000 Genomes Projects were utilized to inform genotype. Twenty CYP3A4 alleles were identified in the 30 samples characterized for CYP3A4: CYP3A4∗4, ∗5, ∗6, ∗7, ∗8, ∗9, ∗10, ∗11, ∗12, ∗15, ∗16, ∗18, ∗19, ∗20, ∗21, ∗22, ∗23, ∗24, ∗35, and a novel allele, CYP3A4∗38. Nineteen additional samples with preexisting data for CYP3A4 or CYP3A5 were re-analyzed to generate comprehensive reference material panels for these genes. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

Genetic polymorphisms are associated with individual susceptibility to dexmedetomidine

Introduction: Dexmedetomidine (DXM) is widely used as an adjuvant to anesthesia or a sedative medicine, and differences in individual sensitivity to the drug exist. This study aimed to investigate the effect of genetic polymorphisms on these differences. Methods: A total of 112 patients undergoing hand surgery were recruited. DXM 0.5 μg/kg was administered within 10 min and then continuously injected (0.4 μg/kg/h). Narcotrend index, effective dose and onset time of sedation, MAP, and HR were measured. Forty-five single nucleotide polymorphisms (SNPs) were selected for genotype. Results: We observed individual differences in the sedation and hemodynamics induced by DXM. ABCG2 rs2231142, CYP2D6 rs16947, WBP2NL rs5758550, KATP rs141294036, KCNMB1 rs11739136, KCNMA1 rs16934182, ABCC9 rs11046209, ADRA2A rs1800544, and ADRB2 rs1042713 were shown to cause statistically significant (p < 0.05) influence on the individual variation of DXM on sedation and hemodynamics. Moreover, the multiple linear regression analysis indicated sex, BMI, and ADRA2A rs1800544 are statistically related to the effective dose of DXM sedation. Discussion: The evidence suggests that the nine SNPs involved in transport proteins, metabolic enzymes, and target proteins of DXM could explain the individual variability in the sedative and hemodynamic effects of DXM. Therefore, with SNP genotyping, these results could guide personalized medication and promote clinical and surgical management.

Recent advances in measurement of metabolic clearance, metabolite profile and reaction phenotyping of low clearance compounds

INTRODUCTION

Low metabolic clearance is usually a highly desirable property of drug candidates in order to reduce dose and dosing frequency. However, measurement of low clearance can be challenging in drug discovery. A number of new tools have recently been developed to address the gaps in the measurement of intrinsic clearance, identification of metabolites, and reaction phenotyping of low clearance compounds.

AREAS COVERED

The new methodologies of low clearance measurements are discussed, including the hepatocyte relay, HepatoPac®, HμREL®, and spheroid systems. In addition, metabolite formation rate determination and in vivo allometric scaling approaches are covered as alternative methods for low clearance measurements. With these new methods, measurement of ~ 20-fold lower limit of intrinsic clearance can be achieved. The advantages and limitations of each approach are highlighted.

EXPERT OPINION

Although several novel methods have been developed in recent years to address the challenges of low clearance, these assays tend to be time and labor intensive and costly. Future innovations focusing on developing systems with high enzymatic activities, ultra-sensitive universal quantifiable detectors, and artificial intelligence will further enhance our ability to explore the low clearance space.

Intraindividual Variability in Absolute Bioavailability and Clearance of Midazolam in Healthy Individuals

BACKGROUND AND OBJECTIVE

Midazolam is the preferred clinical probe drug for assessing CYP3A activity. We have previously shown substantial intraindividual variability in midazolam absolute bioavailability and clearance in patients with obesity before and after weight loss induced by gastric bypass or a strict diet. The objective was to describe intraindividual variability in absolute bioavailability and clearance of midazolam in healthy individuals without obesity.

METHODS

This study included 33 healthy volunteers [28 ± 8 years, 21% males, body mass index (BMI) 23 ± 2.5 kg/m2] subjected to four pharmacokinetic investigations over a 2-month period (weeks 0, 2, 4, and 8). Semi-simultaneous oral (0 h) and intravenous (2 h later) midazolam dosing was used to assess absolute bioavailability and clearance of midazolam.

RESULTS

At baseline, mean absolute bioavailability and clearance were 46 ± 18% and 31 ± 10 L/h, respectively. The mean coefficient of variation (CV, %) for absolute bioavailability and clearance of midazolam was 26 ± 15% and 20 ± 10%, respectively. Approximately one-third had a CV > 30% for absolute bioavailability, while 13% had a CV > 30% for clearance.

CONCLUSIONS

On average, intraindividual variability in absolute bioavailability and clearance of midazolam was low to moderate; however, especially absolute bioavailability showed considerable variability in a relatively large proportion of the individuals.

Transcriptional changes in specific subsets of Drosophila neurons following inhibition of the serotonin transporter

The transcriptional effects of SSRIs and other serotonergic drugs remain unclear, in part due to the heterogeneity of postsynaptic cells, which may respond differently to changes in serotonergic signaling. Relatively simple model systems such as Drosophila afford more tractable microcircuits in which to investigate these changes in specific cell types. Here, we focus on the mushroom body, an insect brain structure heavily innervated by serotonin and comprised of multiple different but related subtypes of Kenyon cells. We use fluorescence-activated cell sorting of Kenyon cells, followed by either bulk or single-cell RNA sequencing to explore the transcriptomic response of these cells to SERT inhibition. We compared the effects of two different Drosophila Serotonin Transporter (dSERT) mutant alleles as well as feeding the SSRI citalopram to adult flies. We find that the genetic architecture associated with one of the mutants contributed to significant artefactual changes in expression. Comparison of differential expression caused by loss of SERT during development versus aged, adult flies, suggests that changes in serotonergic signaling may have relatively stronger effects during development, consistent with behavioral studies in mice. Overall, our experiments revealed limited transcriptomic changes in Kenyon cells, but suggest that different subtypes may respond differently to SERT loss-of-function. Further work exploring the effects of SERT loss-of-function in other circuits may be used help to elucidate how SSRIs differentially affect a variety of different neuronal subtypes both during development and in adults.

Characterization of complex structural variation in the CYP2D6-CYP2D7-CYP2D8 gene loci using single-molecule long-read sequencing

Complex regions in the human genome such as repeat motifs, pseudogenes and structural (SVs) and copy number variations (CNVs) present ongoing challenges to accurate genetic analysis, particularly for short-read Next-Generation-Sequencing (NGS) technologies. One such region is the highly polymorphic CYP2D loci, containing CYP2D6, a clinically relevant pharmacogene contributing to the metabolism of >20% of common drugs, and two highly similar pseudogenes, CYP2D7 and CYP2D8. Multiple complex SVs, including CYP2D6/CYP2D7-derived hybrid genes are known to occur in different configurations and frequencies across populations and are difficult to detect and characterize accurately. This can lead to incorrect enzyme activity assignment and impact drug dosing recommendations, often disproportionally affecting underrepresented populations. To improve CYP2D6 genotyping accuracy, we developed a PCR-free CRISPR-Cas9 based enrichment method for targeted long-read sequencing that fully characterizes the entire CYP2D6-CYP2D7-CYP2D8 loci. Clinically relevant sample types, including blood, saliva, and liver tissue were sequenced, generating high coverage sets of continuous single molecule reads spanning the entire targeted region of up to 52 kb, regardless of SV present (n = 9). This allowed for fully phased dissection of the entire loci structure, including breakpoints, to accurately resolve complex CYP2D6 diplotypes with a single assay. Additionally, we identified three novel CYP2D6 suballeles, and fully characterized 17 CYP2D7 and 18 CYP2D8 unique haplotypes. This method for CYP2D6 genotyping has the potential to significantly improve accurate clinical phenotyping to inform drug therapy and can be adapted to overcome testing limitations of other clinically challenging genomic regions.

Prediction of Sites of Metabolism of CYP3A4 Substrates Utilizing Docking-Derived Geometric Features

Cytochrome P450 3A4 (CYP3A4) is one of the major drug-metabolizing enzymes in the human body and is responsible for the metabolism of ∼50% of clinically used drugs. Therefore, the identification of the compound's sites of metabolism (SOMs) mediated by CYP3A4 is of utmost importance in the early stage of drug discovery and development. Herein, docking-based approaches incorporating geometric features were used for SOMs prediction of CYP3A4 substrates. The cross-docking poses of a relatively large data set containing 474 substrates were analyzed in depth, and a widely observed geometric pattern called the close proximity of SOMs was derived from the poses. On the basis of the close proximity, several structure-based models have been constructed, which demonstrated better performance than those structure-based models using the criterion of Fe-SOM distance. For further improving the prediction performance, the structure-based models were also combined with the well-known ligand-based model SMARTCyp. One combined model exhibited good performance on the SOMs prediction of an external substrate set containing kinase inhibitors, PROTACs, approved drugs, and some lead compounds.

Determination of the Duplicated CYP2D6 Allele Using Real-Time PCR Signal: An Alternative Approach

CYP2D6 duplication has important pharmacogenomic implications. Reflex testing with long-range PCR (LR-PCR) can resolve the genotype when a duplication and alleles with differing activity scores are detected. We evaluated whether visual inspection of plots from real-time-PCR-based targeted genotyping with copy number variation (CNV) detection could reliably determine the duplicated CYP2D6 allele. Six reviewers evaluated QuantStudio OpenArray CYP2D6 genotyping results and the TaqMan Genotyper plots for seventy-three well-characterized cases with three copies of CYP2D6 and two different alleles. Reviewers blinded to the final genotype visually assessed the plots to determine the duplicated allele or opt for reflex sequencing. Reviewers achieved 100% accuracy for cases with three CYP2D6 copies that they opted to report. Reviewers did not request reflex sequencing in 49-67 (67-92%) cases (and correctly identified the duplicated allele in each case); all remaining cases (6-24) were marked by at least one reviewer for reflex sequencing. In most cases with three copies of CYP2D6, the duplicated allele can be determined using a combination of targeted genotyping using real-time PCR with CNV detection without need for reflex sequencing. In ambiguous cases and those with >3 copies, LR-PCR and Sanger sequencing may still be necessary for determination of the duplicated allele.

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

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

Unusual Biotransformation Reactions of Drugs and Drug Candidates

Detailed assessment of the fate of drugs in nonclinical test species and humans is essential to ensure the safety and efficacy of medicines in patients. In this context, biotransformation of drugs and drug candidates has been an area of keen interest over many decades in the pharmaceutical industry as well as academia. Although many of the enzymes and biotransformation pathways involved in the metabolism of xenobiotics and more specifically drugs have been well characterized, each drug molecule is unique and constitutes specific challenges for the biotransformation scientist. In this mini-review written for the special issue on the occasion of the 50th Anniversary celebration of Drug Metabolism and Disposition and to celebrate contributions of F. Peter Guengerich, one of the pioneers of the drug metabolism field, recently reported "unusual" biotransformation reactions are presented. Scientific and technological advances in the "toolbox" of the biotransformation scientists are summarized. As the pharmaceutical industry continues to explore therapeutic modalities different from the traditional small molecule drugs, the new challenges confronting the biotransformation scientist as well as future opportunities are discussed. SIGNIFICANCE STATEMENT: For the biotransformation scientists, it is essential to share and be aware of unexpected biotransformation reactions so that they can increase their confidence in predicting metabolites of drugs in humans to ensure the safety and efficacy of these metabolites before the medicines reach large numbers of patients. The purpose of this review is to highlight recent observations of "unusual" metabolites so that the scientists working in the area of drug metabolism can strengthen their readiness in expecting the unexpected.

Transcriptional changes in specific subsets of Drosophila neurons following inhibition of the serotonin transporter

The transcriptional effects of SSRIs and other serotonergic drugs remain unclear, in part due to the heterogeneity of postsynaptic cells, which may respond differently to changes in serotonergic signaling. Relatively simple model systems such as Drosophila afford more tractable microcircuits in which to investigate these changes in specific cell types. Here, we focus on the mushroom body, an insect brain structure heavily innervated by serotonin and comprised of multiple different but related subtypes of Kenyon cells. We use fluorescence activated cell sorting of Kenyon cells, followed by either or bulk or single cell RNA sequencing to explore the transcriptomic response of these cells to SERT inhibition. We compared the effects of two different Drosophila Serotonin Transporter (dSERT) mutant alleles as well as feeding the SSRI citalapram to adult flies. We find that the genetic architecture associated with one of the mutants contributed to significant artefactual changes in expression. Comparison of differential expression caused by loss of SERT during development versus aged, adult flies, suggests that changes in serotonergic signaling may have relatively stronger effects during development, consistent with behavioral studies in mice. Overall, our experiments revealed limited transcriptomic changes in Kenyon cells, but suggest that different subtypes may respond differently to SERT loss-of-function. Further work exploring the effects of SERT loss-of-function in other Drosophila circuits may be used help to elucidate how SSRIs differentially affect a variety of different neuronal subtypes both during development and in adults.

Opportunities for Accelerating Drug Discovery and Development by Using Engineered Drug-Metabolizing Enzymes

The study of drug metabolism is fundamental to drug discovery and development (DDD) since by mediating the clearance of most drugs, metabolic enzymes influence their bioavailability and duration of action. Biotransformation can also produce pharmacologically active or toxic products, which complicates the evaluation of the therapeutic benefit versus liability of potential drugs but also provides opportunities to explore the chemical space around a lead. The structures and relative abundance of metabolites are determined by the substrate and reaction specificity of biotransformation enzymes and their catalytic efficiency. Preclinical drug biotransformation studies are done to quantify in vitro intrinsic clearance to estimate likely in vivo pharmacokinetic parameters, to predict an appropriate dose, and to anticipate interindividual variability in response, including from drug-drug interactions. Such studies need to be done rapidly and cheaply, but native enzymes, especially in microsomes or hepatocytes, do not always produce the full complement of metabolites seen in extrahepatic tissues or preclinical test species. Furthermore, yields of metabolites are usually limiting. Engineered recombinant enzymes can make DDD more comprehensive and systematic. Additionally, as renewable, sustainable, and scalable resources, they can also be used for elegant chemoenzymatic, synthetic approaches to optimize or synthesize candidates as well as metabolites. Here, we will explore how these new tools can be used to enhance the speed and efficiency of DDD pipelines and provide a perspective on what will be possible in the future. The focus will be on cytochrome P450 enzymes to illustrate paradigms that can be extended in due course to other drug-metabolizing enzymes. SIGNIFICANCE STATEMENT: Protein engineering can generate enhanced versions of drug-metabolizing enzymes that are more stable, better suited to industrial conditions, and have altered catalytic activities, including catalyzing non-natural reactions on structurally complex lead candidates. When applied to drugs in development, libraries of engineered cytochrome P450 enzymes can accelerate the identification of active or toxic metabolites, help elucidate structure activity relationships, and, when combined with other synthetic approaches, provide access to novel structures by regio- and stereoselective functionalization of lead compounds.

Estimating the In Vivo Function of CYP2D6 Alleles through Population Pharmacokinetic Modeling of Brexpiprazole

Accurate prediction of CYP2D6 phenotype from genotype information is important to support safe and efficacious pharmacotherapy with CYP2D6 substrates. To facilitate accurate CYP2D6 genotype-phenotype translation, there remains a need to investigate the enzyme activity associated with individual CYP2D6 alleles using large clinical data sets. This study aimed to quantify and compare the in vivo function of different CYP2D6 alleles through population pharmacokinetic (PopPK) modeling of brexpiprazole using data from 13 clinical studies. A PopPK model of brexpiprazole and its two metabolites, DM-3411 and DM-3412, was developed based on plasma concentration samples from 826 individuals. As the minor metabolite, DM-3412, is formed via CYP2D6, the metabolic ratio of DM-3412:brexpiprazole calculated from the PopPK parameter estimates was used as a surrogate measure of CYP2D6 activity. A CYP2D6 genotype-phenotype analysis based on 496 subjects showed that the CYP2D6*2 allele (n = 183) was associated with only 10% enzyme activity relative to the wild-type allele (CYP2D6*1) and a low enzyme activity was consistently observed across genotypes containing CYP2D6*2. Among the decreased function alleles, the following enzyme activities relative to CYP2D6*1 were estimated: 23% for CYP2D6*9 (n = 20), 32% for CYP2D6*10 (n = 62), 64% for CYP2D6*14 (n = 1), 4% for CYP2D6*17 (n = 37), 4% for CYP2D6*29 (n = 13), and 9% for CYP2D6*41 (n = 64). These findings imply that a lower functional value would more accurately reflect the in vivo function of many reduced function CYP2D6 alleles in the metabolism of brexpiprazole. The low enzyme activity observed for CYP2D6*2, which has also been reported by others, suggests that the allele exhibits substrate-specific enzyme activity.

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.

Physiologically based pharmacokinetic (PBPK) modeling of the role of CYP2D6 polymorphism for metabolic phenotyping with dextromethorphan

The cytochrome P450 2D6 (CYP2D6) is a key xenobiotic-metabolizing enzyme involved in the clearance of many drugs. Genetic polymorphisms in CYP2D6 contribute to the large inter-individual variability in drug metabolism and could affect metabolic phenotyping of CYP2D6 probe substances such as dextromethorphan (DXM). To study this question, we (i) established an extensive pharmacokinetics dataset for DXM; and (ii) developed and validated a physiologically based pharmacokinetic (PBPK) model of DXM and its metabolites dextrorphan (DXO) and dextrorphan O-glucuronide (DXO-Glu) based on the data. Drug-gene interactions (DGI) were introduced by accounting for changes in CYP2D6 enzyme kinetics depending on activity score (AS), which in combination with AS for individual polymorphisms allowed us to model CYP2D6 gene variants. Variability in CYP3A4 and CYP2D6 activity was modeled based on in vitro data from human liver microsomes. Model predictions are in very good agreement with pharmacokinetics data for CYP2D6 polymorphisms, CYP2D6 activity as described by the AS system, and CYP2D6 metabolic phenotypes (UM, EM, IM, PM). The model was applied to investigate the genotype-phenotype association and the role of CYP2D6 polymorphisms for metabolic phenotyping using the urinary cumulative metabolic ratio (UCMR), DXM/(DXO + DXO-Glu). The effect of parameters on UCMR was studied via sensitivity analysis. Model predictions indicate very good robustness against the intervention protocol (i.e. application form, dosing amount, dissolution rate, and sampling time) and good robustness against physiological variation. The model is capable of estimating the UCMR dispersion within and across populations depending on activity scores. Moreover, the distribution of UCMR and the risk of genotype-phenotype mismatch could be estimated for populations with known CYP2D6 genotype frequencies. The model can be applied for individual prediction of UCMR and metabolic phenotype based on CYP2D6 genotype. Both, model and database are freely available for reuse.

Characterization of Novel CYP2D6 Alleles across Sub-Saharan African Populations

The CYP2D6 gene has been widely studied to characterize variants and/or star alleles, which account for a significant portion of variability in drug responses observed within and between populations. However, African populations remain under-represented in these studies. The increasing availability of high coverage genomes from African populations has provided the opportunity to fill this knowledge gap. In this study, we characterized computationally predicted novel CYP2D6 star alleles in 30 African subjects for whom DNA samples were available from the Coriell Institute. CYP2D6 genotyping and resequencing was performed using a variety of commercially available and laboratory-developed tests in a collaborative effort involving three laboratories. Fourteen novel CYP2D6 alleles and multiple novel suballeles were identified. This work adds to the growing catalogue of validated African ancestry CYP2D6 allelic variation in pharmacogenomic databases, thus laying the foundation for future functional studies and improving the accuracy of CYP2D6 genotyping, phenotype prediction, and the refinement of clinical pharmacogenomic implementation guidelines in African and global settings.

From Croatian Roma to 1000 Genomes: The Story of the CYP2D6 Gene Promoter and Enhancer SNPs

The CYP2D6 gene encodes an enzyme responsible for the metabolism of ~20% of clinically prescribed drugs. In this study, 18 SNPs from the enhancer and promoter regions of CYP2D6 in 323 Roma from Croatia were genotyped, to find out whether the demographic history of Roma affected the distribution of the studied SNPs and their linkage disequilibrium (LD) values, with the major SNPs defining the CYP2D6 star alleles. No differences were found between the three Roma groups in allele and genotype frequencies. The distribution of LD values of Roma was compared with LD values of European and Asian populations. Regulatory CYP2D6 SNPs (rs5758550, rs28624811, rs1080985 and rs1080983) showed similar distribution and the highest LDs with rs16947 from the gene-coding region in all populations. In the promoter region, a complete LD between rs1080989 and rs28588594, and between rs1080983 and rs28624811, was found in Croatian Roma and investigated populations from 1000 genomes. A high LD was also found between rs1080985 from the promoter and rs5758550 from the enhancer region. SNP rs28735595 from the gene promoter region had the highest LD, with two gene region SNPs, rs1058164 and rs1135840. To conclude, the Croatian Roma population shows an LD pattern of the CYP2D6 gene region similar to the 1000 Genomes European and Asian populations.

Cytochrome P450 enzymes in the pediatric population: Connecting knowledge on P450 expression with pediatric pharmacokinetics

Cytochrome P450 enzymes play an important role in the pharmacokinetics, efficacy, and toxicity of drugs. Age-dependent changes in P450 enzyme expression have been studied based on several detection systems, as well as by deconvolution of in vivo pharmacokinetic data observed in pediatric populations. The age-dependent changes in P450 enzyme expression can be important determinants of drug disposition in childhood, in addition to the changes in body size and the other physiological parameters, and effects of pharmacogenetics and disease on organ functions. As a tool incorporating drug-specific and body-specific factors, physiologically-based pharmacokinetic (PBPK) models have become increasingly used to characterize and explore mechanistic insights into drug disposition. Thus, PBPK models can be a bridge between findings from basic science and utilization in predictive science. Pediatric PBPK models incorporate additional system specific information on developmental physiology and ontogeny and have been used to predict pharmacokinetic parameters from preterm neonates onwards. These models have been advocated by regulatory authorities in order to support pediatric clinical trials. The purpose of this chapter is to highlight accumulated knowledge and findings from basic research focusing on P450 enzymes, as well as the current status and future challenges of expanding the utilization of pediatric PBPK modeling.

LEGO-Lipophosphonoxins: A Novel Approach in Designing Membrane Targeting Antimicrobials

The alarming rise of bacterial antibiotic resistance requires the development of new compounds. Such compounds, lipophosphonoxins (LPPOs), were previously reported to be active against numerous bacterial species, but serum albumins abolished their activity. Here we describe the synthesis and evaluation of novel antibacterial compounds termed LEGO-LPPOs, loosely based on LPPOs, consisting of a central linker module with two attached connector modules on either side. The connector modules are then decorated with polar and hydrophobic modules. We performed an extensive structure–activity relationship study by varying the length of the linker and hydrophobic modules. The best compounds were active against both Gram-negative and Gram-positive species including multiresistant strains and persisters. LEGO-LPPOs act by first depleting the membrane potential and then creating pores in the cytoplasmic membrane. Importantly, their efficacy is not affected by the presence of serum albumins. Low cytotoxicity and low propensity for resistance development demonstrate their potential for therapeutic use.

Plasma exchange treats severe intrahepatic cholestasis caused by dacomitinib: A case report

RATIONALE

Dacomitinib-induced liver injury is often manifested by mild elevations of transaminases and bilirubin, and severe intrahepatic cholestasis caused by dacomitinib for simultaneous taking orally cytochrome P450 2D6 (CYP2D6) competitive substrates has been rarely reported.

PATIENT CONCERNS

The patient was a 69-year-old woman with non-small cell lung cancer (NSCLC) who was prescribed oral dacomitinib for a month; she was given oral loratadine due to "allergic rhinitis" and metoprolol extended action tablets due to "tachycardia" separately for a few days during the course of dacomitinib treatment. The patient developed liver damage, increased fatigue, yellow urine, and pruritus, with significantly elevated serum levels of bilirubin and glutamyltranspetidase.

DIAGNOSIS

Intrahepatic cholestasis, drug-induced liver injury, and NSCLC.

INTERVENTIONS

After admission, the patient was prescribed adenosylmethionine, acetylcysteine, ursodeoxycholic acid capsule, methylprednisolone and fenofibrate for a month, with progressive elevation of liver biochemical parameters. Through drug enzyme gene assays in the liver tissue after percutaneous liver biopsy, we found both CYP2D6*10/*10 and ATP-binding cassette subfamily B member 1 GG variants (rs1045642) positive. After the poor response to the conventional medication, the patient underwent plasma exchange.

OUTCOMES

The patient was discharged after her liver parameters improved; the parameters remained normal at several follow-up visits, and she renewed the NSCLC regimens without dacomitinib after being evaluated by oncologists.

LESSONS

Dacomitinib can induce severe intrahepatic cholestasis. It is considered that patients with intermediate metabolic CYP2D6 are susceptible to drug-induced liver injury caused by dacomitinib; plasma exchange may be an effective treatment.

The frequency of major CYP2C19 genetic polymorphisms in women of Asian, Native Hawaiian and Pacific Islander subgroups

Aim: Prevalence of clinically actionable genetic variants of CYP2C19 is lacking in specific population subgroups. This study aims to assess the frequencies of CYP2C19*2, *3, and *17 in Asian, Native Hawaiian and Pacific Islander (NHPI) population subgroups compared with Europeans. Patients & methods: The study included repository DNA samples of 1064 women, 18 years or older, who self-reported as Filipino, Korean, Japanese, Native Hawaiian, Marshallese and Samoan. Results: The overall frequencies of CYP2C19*2 (25-36%) and CYP2C19*3 (2.5-10%) were significantly higher in all our subgroups than in Europeans (15 and 0.02%, respectively). The overall frequency of CYP2C19*17 was significantly lower in all our subgroups (1-6%) than in Europeans (21.7%). Conclusion: This is the first report on the frequencies of CYP2C19*2, *3, and *17 in women of Asian and NHPI descent with distinct population subgroup differences. Differential allele frequencies of CYP2C19 among population subgroups underscore the importance of increasing racial and ethnic diversity in pharmacogenetic research.

Novel Insights in Drug Transporter Sciences: the Year 2021 in Review

On behalf of the team I am pleased to present the second annual 'novel insights into drug transporter sciences review' focused on peer-reviewed articles that were published in the year 2021. In compiling the articles for inclusion, preprints available in 2021 but officially published in 2022 were considered to be in scope. To support this review the contributing authors independently selected one or two articles that were thought to be impactful and of interest to the broader research community. A similar approach as published last year was adopted whereby key observations, methods and analysis of each paper is concisely summarized in the synopsis followed by a commentary highlighting the impact of the paper in understanding of drug transporters' role in drug disposition.As the goal of this review is not to provide a comprehensive overview of each paper but rather highlight important findings that are well supported by the data, the reader is encouraged to consult the original articles for additional information. Further, and keeping in line with the goals of this review, it should be noted that all authors actively contributed by writing synopsis and commentary for individual papers and no attempt was made to standardize language or writing styles. In this way, the review article is reflective of not only the diversity of the articles but also that of the contributors. I extend my thanks to the authors for their continued support and also welcome Diane Ramsden and Pallabi Mitra as contributing authors for this issue.

Recent advances in the translation of drug metabolism and pharmacokinetics science for drug discovery and development

Drug metabolism and pharmacokinetics (DMPK) is an important branch of pharmaceutical sciences. The nature of ADME (absorption, distribution, metabolism, excretion) and PK (pharmacokinetics) inquiries during drug discovery and development has evolved in recent years from being largely descriptive to seeking a more quantitative and mechanistic understanding of the fate of drug candidates in biological systems. Tremendous progress has been made in the past decade, not only in the characterization of physiochemical properties of drugs that influence their ADME, target organ exposure, and toxicity, but also in the identification of design principles that can minimize drug-drug interaction (DDI) potentials and reduce the attritions. The importance of membrane transporters in drug disposition, efficacy, and safety, as well as the interplay with metabolic processes, has been increasingly recognized. Dramatic increases in investments on new modalities beyond traditional small and large molecule drugs, such as peptides, oligonucleotides, and antibody-drug conjugates, necessitated further innovations in bioanalytical and experimental tools for the characterization of their ADME properties. In this review, we highlight some of the most notable advances in the last decade, and provide future perspectives on potential major breakthroughs and innovations in the translation of DMPK science in various stages of drug discovery and development.

Artificial intelligence-assisted development of in situ forming nanoparticles for arthritis therapy via intra-articular delivery

Intra-articular (IA) injection is grasping much interest due to the poor drug bioavailability at the targeted site of action which minimizes the effect of the orally administered moiety. Based on the integral role of non-steroidal anti-inflammatory drugs (NSAIDs) in the treatment of Rheumatoid Arthritis (RA), much effort is exerted to develop novel localized drug delivery systems to increase their bioavailability and minimize their side effects. Artificial intelligence (AI) is acquiring an increasing role in the design of experiments being an effective tool for saving both time and resources. Hence, the aim of this work was to develop, characterize and optimize targeted in-situ forming nano particles (ISNs) for IA delivery of piroxicam using Design^® Expert as an AI-based application where a 3³ full factorial experimental design was adopted. Morphological investigation, injectability, rheological studies, Fourier Transform Infrared Radiation (FTIR) as well as biological, histopathological, and biochemical examinations were performed to evaluate the optimized-ISNs. The optimized formulation, exhibiting a nano-sized particle size with a dense core, showed significant improvement in the histopathological findings compared to both the oral solution and the placebo. Additionally, the once-a-week IA administration of the optimized-ISNs proved a significant reduction in the protein expression of both STAT-3 and RANKL and the levels of anti-CCP and MCP-1 by almost 54 and 73%, respectively, coupled with a marked decline in the content of IL-17, MMP-3, NF-κB and TNF-α as compared to the positive control. In conclusion, the use of ISNs for intra-articular injection has demonstrated their effectiveness in piroxicam delivery for RA treatment.

An Overview of the Evidence and Mechanism of Drug-Herb Interactions Between Propolis and Pharmaceutical Drugs

With the growing interest in the medicinal use of propolis, numerous studies have reported significant interactions between propolis extract and pharmaceutical drugs which may result in great clinical benefits or risks. The present study aims to review the drug-herb interactions of the full-spectrum propolis extract and main pharmaceutical drugs from the pharmacodynamic and pharmacokinetic aspects and elucidate the underlying pharmacological mechanisms. A literature search was conducted between June 2021 and February 2022 in Google Scholar, PubMed, MEDLINE, and EMBASE databases to include English studies from years 2000 to 2022 that evaluated the interaction of full-spectrum propolis extract and standard pharmaceutical drugs/cytochromes P450s. Studies that looked into geopropolis, propolis fractions, and isolated compounds, or interaction of propolis with foods, bioactive molecules, or receptors other than standard pharmaceutical drugs were excluded. From a pharmacodynamic perspective, propolis extract exhibited positive or synergistic interaction with several chemotherapeutic drugs by enhancing antitumor activity, sensitizing the chemoresistance cell lines, and attenuating multi-organ toxicity. The molecular mechanisms were associated with upregulating the apoptotic signal and immunomodulatory activity and attenuating oxidative damage. Propolis extract also enhanced the anti-bacterial and antifungal activities of many antimicrobial drugs against sensitive and resistant organisms, with an effect against the gram-positive bacteria stronger than that of the gram-negative bacteria. The synergistic action was related to strengthened action on interfering cell wall integrity and protein synthesis. The strong antioxidant activity of propolis also strengthened the therapeutic effect of metformin in attenuating hyperglycemia and pancreatic damage, as well as mitigating oxidative stress in the liver, kidney, and testis. In addition, propolis showed a potential capacity to enhance short-term and long-term memory function together with donepezil and improve motor function with levodopa and parasite killing activity with praziquantel. Pharmacokinetic studies showed inhibitory activities of propolis extracts on several CYP450 enzymes in vitro and in vivo. However, the effects on those CYP450 were deemed insignificant in humans, which may be attributed to the low bioavailability of the contributing bioactive compounds when administered in the body. The enhanced bioactivities of propolis and main pharmaceutical drugs support using propolis in integrative medicine in anti-cancer, anti-microbial, antidiabetic, and neurological disorders, with a low risk of altered pharmacokinetic activities.

The Identification of Novel CYP2D6 Variants in US Hmong: Results From Genome Sequencing and Clinical Genotyping

Objective: Hmong individuals represent a unique East Asian subpopulation in whom limited information concerning pharmacogenetic variation exists. The objectives of this study were to comprehensively characterize the highly polymorphic CYP2D6 gene in Hmong, estimate allele and phenotype frequencies and to compare results between two testing platforms. Methods: DNA from 48 self-identified Hmong participants were sequenced using a targeted next-generation sequencing (NGS) panel. Star allele calls were made using Astrolabe, manual inspection of NGS variant calls and confirmatory Sanger sequencing. Structural variation was determined by long-range (XL)-PCR and digital droplet PCR (ddPCR). The consensus diplotypes were subsequently translated into phenotype utilizing the activity score system. Clinical grade pharmacogenetic testing was obtained for 12 of the 48 samples enabling an assessment of concordance between the consensus calls and those determined by clinical testing platforms. Results: A total of 13 CYP2D6 alleles were identified. The most common alleles were CYP2D6*10 and its structural arrangements (37.5%, 36/96) and the *5 gene deletion (13.5%, 13/96). Three novel suballeles (*10.007, *36.004, and *75.002) were also identified. Phenotype frequencies were as follows: ultrarapid metabolizers (4.2%, 2/48), normal metabolizers (41.7%, 20/48) and intermediate metabolizers (52.1%, 25/48); none of the 48 participants were predicted to be poor metabolizers. Concordance of diplotype and phenotype calls between the consensus and clinical testing were 66.7 and 50%, respectively. Conclusion: Our study to explore CYP2D6 genotypes in the Hmong population suggests that this subpopulation is unique regarding CYP2D6 allelic variants; also, a higher portion of Hmong participants (50%) are predicted to have an intermediate metabolizer phenotype for CYP2D6 compared to other East Asians which range between 27 and 44%. Results from different testing methods varied considerably. These preliminary findings underscore the importance of thoroughly interrogating unique subpopulations to accurately predict a patient's CYP2D6 metabolizer status.

CYP2C8, CYP2C9, and CYP2C19 Characterization Using Next-Generation Sequencing and Haplotype Analysis: A GeT-RM Collaborative Project

Pharmacogenetic tests typically target selected sequence variants to identify haplotypes that are often defined by star (∗) allele nomenclature. Due to their design, these targeted genotyping assays are unable to detect novel variants that may change the function of the gene product and thereby affect phenotype prediction and patient care. In the current study, 137 DNA samples that were previously characterized by the Genetic Testing Reference Material (GeT-RM) program using a variety of targeted genotyping methods were recharacterized using targeted and whole genome sequencing analysis. Sequence data were analyzed using three genotype calling tools to identify star allele diplotypes for CYP2C8, CYP2C9, and CYP2C19. The genotype calls from next-generation sequencing (NGS) correlated well to those previously reported, except when novel alleles were present in a sample. Six novel alleles and 38 novel suballeles were identified in the three genes due to identification of variants not covered by targeted genotyping assays. In addition, several ambiguous genotype calls from a previous study were resolved using the NGS and/or long-read NGS data. Diplotype calls were mostly consistent between the calling algorithms, although several discrepancies were noted. This study highlights the utility of NGS for pharmacogenetic testing and demonstrates that there are many novel alleles that are yet to be discovered, even in highly characterized genes such as CYP2C9 and CYP2C19.

A Potential In Vitro 3D Cell Model to Study Vascular Diseases by Simulating the Vascular Wall Microenvironment and Its Application

BACKGROUND

Current in vitro vascular models are too simple compared with the real vascular environment. In this research, a novel in vitro 3D vascular disease model that simulated the vascular microenvironment was introduced.

METHODS

This model was mainly established by low shear stress and co-culture of endothelial cells and smooth muscle cells. Characterization and reproduction of the pathological state of the 3D model were determined. The effect of two clinical drugs was verified in this model. The difference of drug screening between a traditional oxidative-damaged cell model and this 3D model was determined by HPLC.

RESULTS

This model presented many disease markers of vascular diseases: abnormal cellular shape, higher endothelial cell apoptotic rate and smooth muscle cell migration rate, decreased superoxide dismutase level, and increased malondialdehyde and platelet-derived growth factor level. The drugs effectively reduced the disease indices and relieved the damage caused by low shear stress. Compared to the traditional oxidative-damaged cell model, this 3D model screened different active components of Salviae Miltiorrhizae extract, and it is closer to clinical studies.

CONCLUSIONS

These results suggest that the 3D vascular disease model is a more efficient and selective in vitro study and drug screening platform for vascular diseases than previously reported in vitro vascular disease models.

The Impact of the CYP2D6 "Enhancer" Single Nucleotide Polymorphism on CYP2D6 Activity

rs5758550 has been associated with enhanced transcription and suggested to be a useful marker of CYP2D6 activity. As there are limited and inconsistent data regarding the utility of this distant "enhancer" single nucleotide polymorphism (SNP), our goal was to further assess the impact of rs5758550 on CYP2D6 activity toward two probe substrates, atomoxetine (ATX) and dextromethorphan (DM), using in vivo urinary metabolite (DM; n = 188) and pharmacokinetic (ATX; n = 70) and in vitro metabolite formation (ATX and DM; n = 166) data. All subjects and tissues were extensively genotyped, the "enhancer" SNP phased with established CYP2D6 haplotypes either computationally or experimentally, and the impact on CYP2D6 activity investigated using several linear models of varying complexity to determine the proportion of variability in CYP2D6 activity captured by each model. For all datasets and models, the "enhancer" SNP had no or only a modest impact on CYP2D6 activity prediction. An increased effect, when present, was more pronounced for ATX than DM suggesting potential substate-dependency. In addition, CYP2D6*2 alleles with the "enhancer" SNP were associated with modestly higher metabolite formation rates in vitro, but not in vivo; no effect was detected for CYP2D6*1 alleles with "enhancer" SNP. In summary, it remains inconclusive whether the small effects detected in this investigation are indeed caused by the "enhancer" SNP or are rather due to its incomplete linkage with other variants within the gene. Taken together, there does not appear to be sufficient evidence to warrant the "enhancer" SNP be included in clinical CYP2D6 pharmacogenetic testing.