Liquid Biopsy for Patient Characterization in Cardiovascular Disease: Verification against Markers of Cytochrome P450 and P-Glycoprotein Activities

Proteomic profiling of paired human liver homogenate and tissue derived extracellular vesicles

Advances in technologies to isolate extracellular vesicles (EVs) and detect/quantify their cargo underpin the novel potential of these circulating particles as a liquid biopsy to understand physiology and disease. One organ of particular interest in terms of utilizing EVs as a liquid biopsy is the liver. The extent to which EVs originating from the liver reflect the functional status of this organ remains unknown. This is an important knowledge gap that underpins the utility of circulating liver derived EVs as a liquid biopsy. The primary objective of this study was to characterize the proteomic profile of EVs isolated from the extracellular space of liver tissue (LEV) and compare this profile to that of paired tissue (LH). LCMS analyses detected 2892 proteins in LEV and 2673 in LH. Of the 2673 proteins detected in LH, 1547 (58%) were also detected in LEV. Bioinformatic analyses demonstrated comparable representation of proteins in terms of biological functions and cellular compartments. Although, enriched representation of membrane proteins and associated functions was observed in LEV, while representation of nuclear proteins and associated functions was depleted in LEV. These data support the potential use of circulating liver derived EVs as a liquid biopsy for this organ.

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

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

Membrane transporters in drug development and as determinants of precision medicine

The effect of membrane transporters on drug disposition, efficacy and safety is now well recognized. Since the initial publication from the International Transporter Consortium, significant progress has been made in understanding the roles and functions of transporters, as well as in the development of tools and models to assess and predict transporter-mediated activity, toxicity and drug-drug interactions (DDIs). Notable advances include an increased understanding of the effects of intrinsic and extrinsic factors on transporter activity, the application of physiologically based pharmacokinetic modelling in predicting transporter-mediated drug disposition, the identification of endogenous biomarkers to assess transporter-mediated DDIs and the determination of the cryogenic electron microscopy structures of SLC and ABC transporters. This article provides an overview of these key developments, highlighting unanswered questions, regulatory considerations and future directions.

Therapeutic drug monitoring, liquid biopsies or pharmacogenomics for prediction of human drug metabolism and response

Pharmacokinetics plays a central role in understanding the significant interindividual differences that exist in drug metabolism and response. Effectively addressing these differences requires a multi-faceted approach that encompasses a variety of tools and methods. In this review, we examine three key strategies to achieve this goal, namely pharmacogenomics, therapeutic drug monitoring (TDM) and liquid biopsy-based monitoring of hepatic ADME gene expression and highlight their advantages and limitations. We note that larger cohort studies are needed to validate the utility of liquid biopsy-based assessment of hepatic ADME gene expression, which includes prediction of drug metabolism in the clinical setting. Modern mass spectrometers have improved traditional TDM methods, offering versatility and sensitivity. In addition, the identification of endogenous or dietary markers for CYP metabolic traits offers simpler and more cost-effective alternatives to determine the phenotype. We believe that future pharmacogenomic applications in clinical practice should prioritize the identification of missing heritable factors, using larger, well-characterized patient studies and controlling for confounding factors such as diet, concomitant medication and physical health. The intricate regulation of ADME gene expression implies that large-scale studies combining long-read next-generation sequencing (NGS) of complete genomes with phenotyping of patients taking different medications are essential to identify these missing heritabilities. The continuous integration of such data into AI-driven analytical systems could provide a comprehensive and useful framework. This could lead to the development of highly effective algorithms to improve genetics-based precision treatment by predicting drug metabolism and response, significantly improving clinical outcomes.

Development of an activity-based ratiometric electrochemical probe of the tumor biomarker γ-glutamyl transpeptidase: Rapid and convenient sensing in whole blood, urine and live-cell samples

γ-Glutamyl transpeptidase (GGT) is a key biomarker for cancer diagnosis and post-treatment surveillance. Currently available methods for sensing GGT show high potential, but face certain challenges including an inability to be used to directly sense analytes in turbid biofluid samples such as whole blood without tedious sample pretreatment. To overcome this issue, activity-based electrochemical probes (GTLP and GTLPOH) were herein developed for a convenient and specific direct targeting of GGT activity in turbid biosamples. Both probes were designed to have GGT catalyze the hydrolysis of the gamma-glutamyl amide moiety of the probe, and result in a self-immolative reaction and concomitant ejection of the masked amino ferrocene reporter. The GTLPOH probe, delivered distinctive key results including high sensitivity, high affinity, a wide detection range of 2-100 U/L, and low LOD of 0.38 U/L against GGT. This probe delivered a precise target for sensing GGT and was free of interference from other electroactive biological species. Furthermore, the GTLPOH probe was employed to monitor and quantify the activity of GGT on the surfaces of tumor cells. The designed sensing method was also validated by the direct quantitative measurement of GGT activity in whole blood and urine samples, and the results were found to be consistent with those of the standard fluorometric assay kit. Thus, GTLPOH is of great significance for its promise as a point-of-care tool for early-stage cancer diagnosis as well as a new drug screening method.

Pharmacogenomics - a minor rather than major force in clinical medicine

INTRODUCTION

Pharmacogenomics (PGx) is touted as essential for the future of precision medicine. But the opportunity cost of PGx from the prescribers' perspective is rarely considered. The aim of this article is to critique PGx-guided prescribing using clinical pharmacology principles so that important cases for PGx testing are not missed by doctors responsible for therapeutic decision making.

AREAS COVERED

Three categories of PGx and their limitations are outlined - exposure PGx, response PGx, and immune-mediated safety PGx. Clinical pharmacology reasons are given for the narrow scope of PGx-guided prescribing apart from a few medical specialties. Clinical problems for doctors that may arise from PGx are then explained, including mismatch between patients' expectations of PGx testing and the benefits or answers it provides.

EXPERT OPINION

Contrary to popular opinion, PGx is unlikely to become the cornerstone of precision medicine. Sound clinical pharmacology reasons explain why PGx-guided prescribing is unnecessary for most drugs. Pharmacogenomics is important for niche areas of prescribing but has limited clinical utility more broadly. The opportunity cost of PGx-guided prescribing is currently too great for most doctors.

Circulating Biomarkers Instead of Genotyping to Establish Metabolizer Phenotypes

Pharmacogenomics (PGx) enables personalized treatment for the prediction of drug response and to avoid adverse drug reactions. Currently, PGx mainly relies on the genetic information of absorption, distribution, metabolism, and excretion (ADME) targets such as drug-metabolizing enzymes or transporters to predict differences in the patient's phenotype. However, there is evidence that the phenotype-genotype concordance is limited. Thus, we discuss different phenotyping strategies using exogenous xenobiotics (e.g., drug cocktails) or endogenous compounds for phenotype prediction. In particular, minimally invasive approaches focusing on liquid biopsies offer great potential to preemptively determine metabolic and transport capacities. Early studies indicate that ADME phenotyping using exosomes released from the liver is reliable. In addition, pharmacometric modeling and artificial intelligence improve phenotype prediction. However, further prospective studies are needed to demonstrate the clinical utility of individualized treatment based on phenotyping strategies, not only relying on genetics. The present review summarizes current knowledge and limitations.

Novel Approaches to Characterize Individual Drug Metabolism and Advance Precision Medicine

Interindividual variability in drug metabolism can significantly affect drug concentrations in the body and subsequent drug response. Understanding an individual's drug metabolism capacity is important for predicting drug exposure and developing precision medicine strategies. The goal of precision medicine is to individualize drug treatment for patients to maximize efficacy and minimize drug toxicity. While advances in pharmacogenomics have improved our understanding of how genetic variations in drug-metabolizing enzymes (DMEs) affect drug response, nongenetic factors are also known to influence drug metabolism phenotypes. This minireview discusses approaches beyond pharmacogenetic testing to phenotype DMEs-particularly the cytochrome P450 enzymes-in clinical settings. Several phenotyping approaches have been proposed: traditional approaches include phenotyping with exogenous probe substrates and the use of endogenous biomarkers; newer approaches include evaluating circulating noncoding RNAs and liquid biopsy-derived markers relevant to DME expression and function. The goals of this minireview are to 1) provide a high-level overview of traditional and novel approaches to phenotype individual drug metabolism capacity, 2) describe how these approaches are being applied or can be applied to pharmacokinetic studies, and 3) discuss perspectives on future opportunities to advance precision medicine in diverse populations. SIGNIFICANCE STATEMENT: This minireview provides an overview of recent advances in approaches to characterize individual drug metabolism phenotypes in clinical settings. It highlights the integration of existing pharmacokinetic biomarkers with novel approaches; also discussed are current challenges and existing knowledge gaps. The article concludes with perspectives on the future deployment of a liquid biopsy-informed physiologically based pharmacokinetic strategy for patient characterization and precision dosing.

Virtual twin for healthcare management

Healthcare is increasingly fragmented, resulting in escalating costs, patient dissatisfaction, and sometimes adverse clinical outcomes. Strategies to decrease healthcare fragmentation are therefore attractive from payer and patient perspectives. In this commentary, a patient-centered smart phone application called Virtual Twin for Healthcare Management (VTHM) is proposed, including its organizational layout, basic functionality, and potential clinical applications. The platform features a virtual twin hub that displays the body and its health data. This is a physiologically based human model that is "virtualized" for the patient based on their unique genetic, molecular, physiological, and disease characteristics. The spokes of the system are a full service and interoperable electronic-health record, accessible to healthcare providers with permission on any device with internet access. Theoretical case studies based on real scenarios are presented to show how VTHM could potentially improve patient care and clinical efficiency. Challenges that must be overcome to turn VTHM into reality are also briefly outlined. Notably, the VTHM platform is designed to operationalize current and future precision medicine initiatives, such as access to molecular diagnostic results, pharmacogenomics-guided prescribing, and model-informed precision dosing.

Extracellular Vesicles as Surrogates for Drug Metabolism and Clearance: Promise vs. Reality

Drug-metabolizing enzymes (DMEs) and transporters play a major role in drug efficacy and safety. They are regulated at multiple levels and by multiple factors. Estimating their expression and activity could contribute to predicting drug pharmacokinetics and their regulation by drugs or pathophysiological situations. Determining the expression of these proteins in the liver, intestine, and kidney requires the collection of biopsy specimens. Instead, the isolation of extracellular vesicles (EVs), which are nanovesicles released by most cells and present in biological fluids, could deliver this information in a less invasive way. In this article, we review the use of EVs as surrogates for the expression and activity of DMEs, uptake, and efflux transporters. Preliminary evidence has been provided for a correlation between the expression of some enzymes and transporters in EVs and the tissue of origin. In some cases, data obtained in EVs reflect the induction of phase I-DMEs in the tissues. Further studies are required to elucidate to what extent the regulation of other DMEs and transporters in the tissues reflects in the EV cargo. If an association between tissues and their EVs is firmly established, EVs may represent a significant advancement toward precision therapy based on the biotransformation and excretion capacity of each individual.

Impact of Obesity and Bariatric Surgery on Metabolic Enzymes and P-Glycoprotein Activity Using the Geneva Cocktail Approach

The inter-individual variability of CYP450s enzyme activity may be reduced by comparing the effects of bariatric surgery on CYP-mediated drug elimination in comparable patients before and after surgery. The current research will use a low-dose phenotyping cocktail to simultaneously evaluate the activities of six CYP isoforms and P-gp. The results showed that following weight reduction after surgery, the activity of all enzymes increased compared to the obese period, which was statistically significant in the case of CYP3A, CYP2B6, CYP2C9, and CYP1A2. Furthermore, the activity of P-gp after surgery decreased without reaching a statistical significance (p-value > 0.05). Obese individuals had decreased CYP3A and CYP2D6 activity compared with the control group, although only CYP3A was statistically important. In addition, there was a trend toward increased activity for CYP1A2, CYP2B6, CYP2C9, and CYP2C19 in obese patients compared to the control group, without reaching statistical insignificance (p-value ≥ 0.05). After six months (at least), all enzymes and the P-gp pump activity were significantly higher than the control group except for CYP2D6. Ultimately, a greater comprehension of phenoconversion can aid in altering the patient's treatment. Further studies are required to confirm the changes in the metabolic ratios of probes after bariatric surgery to demonstrate the findings' clinical application. As a result, the effects of inflammation-induced phenoconversion on medication metabolism may differ greatly across persons and drug CYP pathways. It is essential to apply these results to the clinic to recommend dose adjustments.

The impact of CYP2C19 genotype on phenoconversion by concomitant medication

Introduction: Pharmacogenetics-informed drug prescribing is increasingly applied in clinical practice. Typically, drug metabolizing phenotypes are determined based on genetic test results, whereupon dosage or drugs are adjusted. Drug-drug-interactions (DDIs) caused by concomitant medication can however cause mismatches between predicted and observed phenotypes (phenoconversion). Here we investigated the impact of CYP2C19 genotype on the outcome of CYP2C19-dependent DDIs in human liver microsomes. Methods: Liver samples from 40 patients were included, and genotyped for CYP2C19*2, *3 and *17 variants. S-mephenytoin metabolism in microsomal fractions was used as proxy for CYP2C19 activity, and concordance between genotype-predicted and observed CYP2C19 phenotype was examined. Individual microsomes were subsequently co-exposed to fluvoxamine, voriconazole, omeprazole or pantoprazole to simulate DDIs. Results: Maximal CYP2C19 activity (V_max) in genotype-predicted intermediate metabolizers (IMs; *1/*2 or *2/*17), rapid metabolizers (RMs; *1/*17) and ultrarapid metabolizers (UMs; *17/*17) was not different from V_max of predicted normal metabolizers (NMs; *1/*1). Conversely, CYP2C19*2/*2 genotyped-donors exhibited V_max rates ∼9% of NMs, confirming the genotype-predicted poor metabolizer (PM) phenotype. Categorizing CYP2C19 activity, we found a 40% concordance between genetically-predicted CYP2C19 phenotypes and measured phenotypes, indicating substantial phenoconversion. Eight patients (20%) exhibited CYP2C19 IM/PM phenotypes that were not predicted by their CYP2C19 genotype, of which six could be linked to the presence of diabetes or liver disease. In subsequent DDI experiments, CYP2C19 activity was inhibited by omeprazole (-37% ± 8%), voriconazole (-59% ± 4%) and fluvoxamine (-85% ± 2%), but not by pantoprazole (-2 ± 4%). The strength of CYP2C19 inhibitors remained unaffected by CYP2C19 genotype, as similar percental declines in CYP2C19 activity and comparable metabolism-dependent inhibitory constants (K_inact/K_I) of omeprazole were observed between CYP2C19 genotypes. However, the consequences of CYP2C19 inhibitor-mediated phenoconversion were different between CYP2C19 genotypes. In example, voriconazole converted 50% of *1/*1 donors to a IM/PM phenotype, but only 14% of *1/*17 donors. Fluvoxamine converted all donors to phenotypic IMs/PMs, but *1/*17 (14%) were less likely to become PMs than *1/*1 (50%) or *1/*2 and *2/*17 (57%). Conclusion: This study suggests that the differential outcome of CYP2C19-mediated DDIs between genotypes are primarily dictated by basal CYP2C19 activity, that may in part be predicted by CYP2C19 genotype but likely also depends on disease-related factors.

A Physiologically Based Pharmacokinetic Model to Predict Determinants of Variability in Epirubicin Exposure and Tissue Distribution

BACKGROUND

Epirubicin is an anthracycline antineoplastic drug that is primarily used in combination therapies for the treatment of breast, gastric, lung and ovarian cancers and lymphomas. Epirubicin is administered intravenously (IV) over 3 to 5 min once every 21 days with dosing based on body surface area (BSA; mg/m²). Despite accounting for BSA, marked inter-subject variability in circulating epirubicin plasma concentration has been reported.

METHODS

In vitro experiments were conducted to determine the kinetics of epirubicin glucuronidation by human liver microsomes in the presence and absence of validated UGT2B7 inhibitors. A full physiologically based pharmacokinetic model was built and validated using Simcyp^® (version 19.1, Certara, Princeton, NJ, USA). The model was used to simulate epirubicin exposure in 2000 Sim-Cancer subjects over 158 h following a single intravenous dose of epirubicin. A multivariable linear regression model was built using simulated demographic and enzyme abundance data to determine the key drivers of variability in systemic epirubicin exposure.

RESULTS

Multivariable linear regression modelling demonstrated that variability in simulated systemic epirubicin exposure following intravenous injection was primarily driven by differences in hepatic and renal UGT2B7 expression, plasma albumin concentration, age, BSA, GFR, haematocrit and sex. By accounting for these factors, it was possible to explain 87% of the variability in epirubicin in a simulated cohort of 2000 oncology patients.

CONCLUSIONS

The present study describes the development and evaluation of a full-body PBPK model to assess systemic and individual organ exposure to epirubicin. Variability in epirubicin exposure was primarily driven by hepatic and renal UGT2B7 expression, plasma albumin concentration, age, BSA, GFR, haematocrit and sex.

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

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

Comparison of P-glycoprotein function in peripheral blood mononuclear cells ex vivo in stable Black and White male and female kidney transplant recipients

Kidney allograft survival remains poorer in Black compared to White recipients due to racial differences in calcineurin inhibitor (CNI) pharmacology. P-glycoprotein (P-gp), an ABC efflux transporter expressed in peripheral blood mononuclear cells (PBMCs), modulates CNI pharmacokinetics and intracellular pharmacology. This study investigated P-gp function in PBMC ex vivo at 0 (trough), 4, 8, and 12 h in stable Black and White male and female kidney transplant recipients (n = 67) receiving tacrolimus and mycophenolic acid. Tacrolimus doses were adjusted to troughs of 4-10 ng/ml. P-gp function was quantified with flow cytometric measurement of cyclosporine (CYA; 2.5 μM)-reversible efflux of P-gp substrate, 3,3'-Diethyloxacarbocyanine iodide by determining the percentage change of mean fluorescent intensity (MFI) with CYA (% ΔMFI). The composite parameter of area under the concentration versus time (AUC)0-12h % ΔMFI estimated P-gp function. Data analysis examined race, sex, and race-sex associations to P-gp function. A secondary aim analyzed ABCB1 genotypes: 1236C>T (rs1128503), 2677G>T/A (rs2032582), 3435C>T (rs1045642), and P-gp function. P-gp function (% ΔMFI) was higher in White patients at troughs (p = 0.031) compared to Black counterparts with similar trends at 4 and 8 h. Reduced AUC0-12h % ΔMFI was noted in Black recipients (N = 32) compared with Whites (N = 35, p = 0.029) with notable pairwise adjusted differences between Black and White women (p = 0.021). Higher AUC0-12h % ΔMFI was associated with ABCB1 2677 TT compared to GG variants (p = 0.035). The AUC0-12h % ΔMFI was greater in White than Black subjects. P-gp function was higher at troughs in White subjects and differed between race-sex groups. P-gp function in PBMC may influence intracellular tacrolimus exposure and inter-relating pharmacodynamic responses which may support race and sex pharmacologic differences.

Liquid Biopsies or Therapeutic Drug Monitoring for CYP Activity Profile Determination

During pharmacotherapy, knowledge about the actual drug and metabolite concentrations in plasma is often critical. Individual dose adjustments can be performed based on pre-emptive genotyping of certain absorption, distribution, metabolism, and excretion (ADME) genes but also using therapeutic drug monitoring (TDM). Analyses of liquid biopsies for tumor-derived components are well-established and have been found to be a good complement to biopsy examinations. Recently, liquid biopsy-based quantification of cell-free RNA (cfRNA) in plasma exosomes was proposed as a proxy measurement for the expression of different hepatic ADME genes and for the rate of drug metabolism, constituting an alternative to TDM. In this study, we validated these findings by examining the correlation between mRNA expression of eight different CYP genes in liver and the corresponding rate of enzyme-specific drug metabolism in 96 donor-matched liver samples. Analyses of CYP-dependent drug metabolism in liver microsomes in comparison to the level of mRNA expression for the different CYP genes revealed a mean Pearson correlation coefficient of 0.28. The highest correlations (0.33-0.34) were obtained for CYP2D6 and CYP3A4 and the weakest correlations were observed for CYP1A2 and CYP2B6 (0.18-0.21). In all cases, the correlations obtained were too weak to demonstrate a predictive relationship, likely due to different regulatory and post-translational events controlling the rate of enzyme activity. Our results reinforce the notion that, whilst liquid biopsy-based approaches might have utility for prediction of hepatic CYP protein expression, they are not currently an important substitute for TDM.

The impact of CYP2D6*41 on CYP2D6 enzyme activity using phenotyping methods in urine, plasma, and saliva

Aims: The CYP2D6*41 variant is the second or third frequent reduced function allele in Chinese with a frequency of around 3–4%, while it is the major reduced function allele in Indians, Saudi Arabians and Caucasians with frequencies of around 10–20%. The present study was designed to explore the impact of CYP2D6*41 on the metabolic activity of CYP2D6 using phenotyping methods in urine, plasma, and saliva.

Methods: We used dextromethorphan as the probe drug to analyze the phenotypes of 87 subjects with CYP2D6*1/*1 (n = 22), CYP2D6*1/*2 (n = 33), CYP2D6*2/*2 (n = 4), CYP2D6*1/*41 (n = 5), CYP2D6*2/*41 (n = 3), CYP2D6*10/*41 (n = 16), and CYP2D6*5/*41 (n = 4) for CYP2D6. The ratio of parent drug to metabolite in 3 h saliva, 3 h plasma, and in 0–3 h urine was considered the metabolic ratio (MR).

Results: The CYP2D6*41 allele had substantial impact on the metabolic activity of CYP2D6 regardless of the urinary, plasma, or salivary phenotyping method used. In subjects with CYP2D6*1(or *2)/*1(or *2), *1 (or *2)/*41, *10/*41 and *5/*41 (all p < 0.001), the salivary, plasma, or urinary MR value increased. The MRs in saliva, plasma, and urine displayed high correlations.

Conclusion: The activity score system or the consensus activity score system, instead of the traditional phenotype classification, could predict the CYP2D6 enzyme activity more accurately. CYP2D6*41 had similar or more impact on the CYP2D6 enzyme activity as compared with CYP2D6*10. Assigning *41 a score of 0.5 and assigning *10 a score of 0.25 according to the consensus AS system should be reconsidered.

Clinical Implications of Altered Drug Transporter Abundance/Function and PBPK Modeling in Specific Populations: An ITC Perspective

The role of membrane transporters on pharmacokinetics (PKs), drug-drug interactions (DDIs), pharmacodynamics (PDs), and toxicity of drugs has been broadly recognized. However, our knowledge of modulation of transporter expression and/or function in the diseased patient population or specific populations, such as pediatrics or pregnancy, is still emerging. This white paper highlights recent advances in studying the changes in transporter expression and activity in various diseases (i.e., renal and hepatic impairment and cancer) and some specific populations (i.e., pediatrics and pregnancy) with the focus on clinical implications. Proposed alterations in transporter abundance and/or activity in diseased and specific populations are based on (i) quantitative transporter proteomic data and relative abundance in specific populations vs. healthy adults, (ii) clinical PKs, and emerging transporter biomarker and/or pharmacogenomic data, and (iii) physiologically-based pharmacokinetic modeling and simulation. The potential for altered PK, PD, and toxicity in these populations needs to be considered for drugs and their active metabolites in which transporter-mediated uptake/efflux is a major contributor to their absorption, distribution, and elimination pathways and/or associated DDI risk. In addition to best practices, this white paper discusses current challenges and knowledge gaps to study and quantitatively predict the effects of modulation in transporter activity in these populations, together with the perspectives from the International Transporter Consortium (ITC) on future directions.