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

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

Ontogeny of Human Liver Aldehyde Oxidase: Developmental Changes and Implications for Drug Metabolism.

Despite the increasing importance of aldehyde oxidase (AO) in the drug metabolism of clinical candidates, ontogeny data for AO are limited. The objective of our study was to characterize the age-dependent AO content and activity in the human liver cytosolic fraction (HLC) and human hepatocytes (HH). HLC (n = 121 donors) and HH (n = 50 donors) were analyzed for (1) AO protein content by quantitative proteomics and (2) enzyme activity using carbazeran as a probe substrate. AO activity showed high technical variability and poor correlation with the content in HLC samples, whereas hepatocyte samples showed a strong correlation between the content and activity. Similarly, AO content and activity showed no significant age-dependent differences in HLC samples, whereas the average AO content and activity in hepatocytes increased significantly (∼20-40-fold) from the neonatal levels (0-28 days). Based on the hepatocyte data, the age at which 50% of the adult AO content is reached (age50) was 3.15 years (0.32-13.97 years, 95% CI). Metabolite profiling of carbazeran revealed age-dependent metabolic switching and the role of non-AO mechanisms (glucuronidation and desmethylation) in carbazeran elimination. The content-activity correlation in hepatocytes improved significantly (R2 = 0.95; p < 0.0001) in samples showing <10% contribution of glucuronidation toward the overall metabolism, confirming that AO-mediated oxidation and glucuronidation are the key routes of carbazeran metabolism. Considering the confounding effect of glucuronidation on AO activity, AO content-based ontogeny data are a more direct reflection of developmental changes in protein expression. The comprehensive ontogeny data of AO in HH samples are more reliable than HLC data, which are important for developing robust physiologically based pharmacokinetic models for predicting AO-mediated metabolism in children.

Influence of novel CYP2C-haplotype on proton pump inhibitor pharmacokinetics in children.

In this brief report, we provide an analysis of the influence of a novel CYP2C haplotype (CYP2C:TG) on proton pump inhibitor (PPI) pharmacokinetics (PK) in children. The CYP2C:TG haplotype has been proposed to be associated with increased CYP2C19 activity. We sought to determine if this CYP2C:TG haplotype resulted in similar alterations in metabolism for proton pump inhibitors, which are primarily metabolized by CYP2C19. In a cohort of 41 children aged 6-21 participating in a PPI pharmacokinetic study, effects of the CYP2C:TG allele were assessed by fitting two linear regression models for each of the six PK outcomes assessed, the second of which accounted for the presence of the CYP2C:TG allele. The difference in R2 values between the two models was computed to quantify the variability in the outcome that could be accounted for by the CYP2C:TG allele after adjustment for the CYP2C19 genotype. We found the CYP2C:TG haplotype to have no measurable additive impact on CYP2C19-mediated metabolism of PPIs in vivo in older children and adolescents. The findings of this study do not support the clinical utility of routine testing for the CYP2C:TG haplotype to guide PPI dose adjustments in children.

SLCO1B1 Genetic Variation Influence on Atorvastatin Systemic Exposure in Pediatric Hypercholesterolemia.

This clinical study examined the influence of SLCO1B1 c.521T>C (rs4149056) on plasma atorvastatin concentrations in pediatric hypercholesterolemia. The participants (8-21 years), including heterozygous (c.521T/C, n = 13), homozygous (c.521C/C, n = 2) and controls (c.521T/T, n = 13), completed a single-oral-dose pharmacokinetic study. Similar to in adults, the atorvastatin (AVA) area-under-concentration-time curve from 0 to 24 h (AUC0-24) was 1.7-fold and 2.8-fold higher in participants with c.521T/C and c.521C/C compared to the c.521T/T participants, respectively. The inter-individual variability in AVA exposure within these genotype groups ranged from 2.3 to 4.8-fold, indicating that additional factors contribute to the inter-individual variability in the AVA dose-exposure relationship. A multivariate model reinforced the SLCO1B1 c.521T>C variant as the central factor contributing to AVA systemic exposure in this pediatric cohort, accounting for ~65% of the variability in AVA AUC0-24. Furthermore, lower AVA lactone concentrations in participants with increased body mass index contributed to higher exposure within the c.521T/T and c.521T/C genotype groups. Collectively, these factors contributing to higher systemic exposure could increase the risk of toxicity and should be accounted for when individualizing the dosing of atorvastatin in eligible pediatric patients.

Population Pharmacokinetic Analysis of Atomoxetine and its Metabolites in Children and Adolescents with Attention-Deficit/Hyperactivity Disorder.

Atomoxetine (ATX) is a non-stimulant used to treat attention-deficit/hyperactivity disorder (ADHD) and systemic exposure is highly variable due to polymorphic cytochrome P450 2D6 (CYP2D6) activity. The objective of this study was to characterize the time course of ATX and metabolites (4-hydroxyatomoxetine (4-OH); N-desmethylatomoxetine (NDA); and 2-carboxymethylatomoxetine (2-COOH)) exposure following oral ATX dosing in children with ADHD to support individualized dosing. A nonlinear mixed-effect modeling approach was used to analyze ATX, 4-OH, and NDA plasma and urine, and 2-COOH urine profiles obtained over 24-72 hours from children with ADHD (n = 23) following a single oral ATX dose. Demographics and CYP2D6 activity score (AS) were evaluated as covariates. Simulations were performed to explore the ATX dosing in subjects with various CYP2D6 AS. A simultaneous pharmacokinetic modeling approach was used in which a model for ATX, 4-OH, and NDA in plasma and urine, and 2-COOH in urine was developed. Plasma ATX, 4-OH, and NDA were modeled using two-compartment models with first-order elimination. CYP2D6 AS was a significant determinant of ATX apparent oral clearance (CL/F), fraction metabolized to 4-OH, and systemic exposure of NDA. CL/F of ATX varied almost 7-fold across the CYP2D6 AS groups: AS 2: 20.02 L/hour; AS 1: 19.00 L/hour; AS 0.5: 7.47 L/hour; and AS 0: 3.10 L/hour. The developed model closely captures observed ATX, 4-OH, and NDA plasma and urine, and 2-COOH urine profiles. Application of the model shows the potential for AS-based dosing recommendations for improved individualized dosing.

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).

Impact of CYP2C:TG Haplotype on CYP2C19 Substrates Clearance In Vivo, Protein Content, and In Vitro Activity.

A novel haplotype composed of two non-coding variants, CYP2C18 NM_000772.3:c.*31T (rs2860840) and NM_000772.2:c.819+2182G (rs11188059), referred to as "CYP2C:TG," was recently associated with ultrarapid metabolism of various CYP2C19 substrates. As the underlying mechanism and clinical relevance of this effect remain uncertain, we analyzed existing in vivo and in vitro data to determine the magnitude of the CYP2C:TG haplotype effect. We assessed variability in pharmacokinetics of CYP2C19 substrates, including citalopram, sertraline, voriconazole, omeprazole, pantoprazole, and rabeprazole in 222 healthy volunteers receiving one of these six drugs. We also determined its impact on CYP2C8, CYP2C9, CYP2C18, and CYP2C19 protein abundance in 135 human liver tissue samples, and on CYP2C18/CYP2C19 activity in vitro using N-desmethyl atomoxetine formation. No effects were observed according to CYP2C:TG haplotype or to CYP2C19*1+TG alleles (i.e., CYP2C19 alleles containing the CYP2C:TG haplotype). In contrast, CYP2C19 intermediate (e.g., CYP2C19*1/*2) and poor metabolizers (e.g., CYP2C19*2/*2) showed significantly higher exposure in vivo, lower CYP2C19 protein abundance in human liver microsomes, and lower activity in vitro compared with normal, rapid (i.e., CYP2C19*1/*17), and ultrarapid metabolizers (i.e., CYP2C19*17/*17). Moreover, a tendency toward lower exposure was observed in ultrarapid metabolizers compared with rapid metabolizers and normal metabolizers. Furthermore, when the CYP2C19*17 allele was present, CYP2C18 protein abundance was increased suggesting that genetic variation in CYP2C19 may be relevant to the overall metabolism of certain drugs by regulating not only its expression levels, but also those of CYP2C18. Considering all available data, we conclude that there is insufficient evidence supporting clinical CYP2C:TG testing to inform drug therapy.

Identifying Effective Treatments for Dystonia in Patients With Cerebral Palsy: A Precision Therapeutics Approach.

Recent focus on improving the recognition of dystonia in cerebral palsy (DCP) has highlighted the need for more effective treatments. Evidence supports improved functional outcomes with early interventions for patients with cerebral palsy, but it is not known which interventions are most effective for DCP. Current pharmacologic recommendations for DCP are based largely on anecdotal evidence, with medications demonstrating minimal to moderate improvements in dystonia and variable efficacy between patients. Patients, families, and clinicians have identified the need for new and improved treatments in DCP, naming this as the top research theme in a recent Neurology® publication. Precision therapeutics focuses on providing early effective interventions that are individualized to every patient and can guide research priorities to improve treatments for DCP. This commentary outlines current obstacles to improving treatment of DCP and addresses how precision therapeutics can address each of these obstacles through 4 key components: (1) identification of predictive biomarkers to select patients likely to develop DCP in the future and for whom early intervention may be appropriate to delay or prevent full manifestation of dystonia, (2) stratification of patients with DCP into subgroups according to shared features (clinical, functional, biochemical, etc) to provide a targeted intervention based on those shared features, (3) administration of an individualized dose of an effective intervention to ensure adequate concentrations of the therapeutic entity at the site of action, and (4) monitoring of objective biomarkers of response to intervention. With implementation of each of these components of precision therapeutics, new and more effective treatments for every person with DCP can be realized.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A Genotypes and Serotonin Reuptake Inhibitor Antidepressants.

Serotonin reuptake inhibitor antidepressants, including selective serotonin reuptake inhibitors (SSRIs; i.e., citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, and sertraline), serotonin and norepinephrine reuptake inhibitors (i.e., desvenlafaxine, duloxetine, levomilnacipran, milnacipran, and venlafaxine), and serotonin modulators with SSRI-like properties (i.e., vilazodone and vortioxetine) are primary pharmacologic treatments for major depressive and anxiety disorders. Genetic variation in CYP2D6, CYP2C19, and CYP2B6 influences the metabolism of many of these antidepressants, which may potentially affect dosing, efficacy, and tolerability. In addition, the pharmacodynamic genes SLC6A4 (serotonin transporter) and HTR2A (serotonin-2A receptor) have been examined in relation to efficacy and side effect profiles of these drugs. This guideline updates and expands the 2015 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and SSRI dosing and summarizes the impact of CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes on antidepressant dosing, efficacy, and tolerability. We provide recommendations for using CYP2D6, CYP2C19, and CYP2B6 genotype results to help inform prescribing these antidepressants and describe the existing data for SLC6A4 and HTR2A, which do not support their clinical use in antidepressant prescribing.

Developmental pharmacokinetics of indomethacin in preterm neonates: Severely decreased drug clearance in the first week of life.

Indomethacin is used commonly in preterm neonates for the prevention of intracranial hemorrhage and closure of an abnormally open cardiac vessel. Due to biomedical advances, the infants who receive this drug in the neonatal intensive care unit setting have become younger, smaller, and less mature (more preterm) at the time of treatment. To develop a pharmacokinetics (PK) model to aid future dosing, we designed a prospective cohort study to characterize indomethacin PK in a dynamically changing patient population. A population PK base model was created using NONMEM, and a covariate model was developed in a primary development cohort and subsequently was tested for accuracy in a validation cohort. Postnatal age was a significant covariate for hepatic clearance (CLH ) and renal clearance (CLR ). The typical value of the total clearance (CL, the sum of CLR and CLH ) was 3.09 ml/h and expressed as CL/WTmedian  = 3.96 ml/h/kg, where WTmedian is the median body weight. The intersubject variability of CLR and CLH were 61% and 207%, respectively. The typical value of the volume of distribution Vp  = 366 ml (Vp /WTmedian  = 470 ml/kg), and its intersubject variability was 38.8%. Half-life was 82.1 h. Compared with more mature and older preterm populations studied previously, indomethacin CL is considerably lower in this contemporary population. Model-informed precision dosing incorporating important covariates other than weight alone offers an opportunity to individualize dosing in a susceptible patient undergoing rapid change.

A longitudinal study of cytochrome P450 2D6 (CYP2D6) activity during adolescence.

CYP2D6 substrates are among the most highly prescribed medications in teenagers and also commonly associated with serious adverse events. To investigate the relative contributions of genetic variation, growth, and development on CYP2D6 activity during puberty, healthy children and adolescents 7-15 years of age at enrollment participated in a longitudinal phenotyping study involving administration of 0.3 mg/kg dextromethorphan (DM) and 4-h urine collection every 6 months for 3 years (7 total visits). At each visit, height, weight, and sexual maturity were recorded, and CYP2D6 activity was determined as the urinary molar ratio of DM to its metabolite dextrorphan (DX). A total of 188 participants completed at least one visit, and 102 completed all seven study visits. Following univariate analysis, only CYP2D6 activity score (p < 0.001), urinary pH (p < 0.001), weight (p = 0.018), and attention-deficit/hyperactivity disorder (ADHD) diagnosis (p < 0.001) were significantly correlated with log(DM/DX). Results of linear mixed model analysis with random intercept, random slope covariance structure revealed that CYP2D6 activity score had the strongest effect on log(DM/DX), with model-estimated average log(DM/DX) being 3.8 SDs higher for poor metabolizers than for patients with activity score 3. A moderate effect on log(DM/DX) was observed for sex, and smaller effects were observed for ADHD diagnosis and urinary pH. The log(DM/DX) did not change meaningfully with age or pubertal development. CYP2D6 genotype remains the single, largest determinant of variability in CYP2D6 activity during puberty. Incorporation of genotype-based dosing guidelines should be considered for CYP2D6 substrates given the prevalent use of these agents in this pediatric age group.

Isolation and Identification of 3,4-Seco-Solanidine-3,4-dioic acid (SSDA) as a Urinary Biomarker of Cytochrome P450 2D6 (CYP2D6) Activity.

Cytochrome P450 2D6 (CYP2D6), is responsible for the metabolism and elimination of approximately 25% of clinically used drugs, including antidepressants and antipsychotics, and its activity varies considerably on a population basis primary due to genetic variation. CYP2D6 phenotype can be assessed in vivo following administration of an exogenous probe compound, such as dextromethorphan or debrisoquine, but use of a biomarker that does not require administration of an exogenous compound (i.e., drug) has considerable appeal for assessing CYP2D6 activity in vulnerable populations, such as children. The goal of this study was to isolate, purify and identify an "endogenous" urinary biomarker (M1; m/z 444.3102) of CYP2D6 activity reported previously. Several chromatographic separation techniques (reverse phase HPLC, cation exchange and analytical reverse phase UPLC) were used to isolate and purify 96 µg of M1 from 40 L of urine. Subsequently, 1D and 2D NMR, and functional group modification reactions were used to elucidate its structure. Analysis of mass spectrometry and NMR data revealed M1 to have similar spectroscopic features to the nitrogen-containing steroidal alkaloid, solanidine. 2D NMR characterization by HMBC, COSY, TOCSY, and HSQC-TOCSY proved to be invaluable in the structural elucidation of M1; derivatization of M1 revealed the presence of two carboxylic acid moieties. M1 was determined to be a steroidal alkaloid with a solanidine backbone that had undergone C-C bond scission to yield 3,4-seco-solanidine-3,4-dioic acid (SSDA). SSDA may have value as a dietary biomarker of CYP2D6 activity in populations where potato consumption is common. Significance Statement Endogenous biomarkers of processes involved in drug disposition and response may allow improved individualization of drug treatment, especially in vulnerable populations, such as children. Given that several CYP2D6 substrates are commonly used in pediatrics and the ubiquitous nature of potato consumption in western diets, SSDA has considerable appeal as non-invasive biomarker of CYP2D6 activity to guide treatment with CYP2D6 substrates in children and adults.

Pediatric growth patterns in youth-onset type 2 diabetes mellitus: Implications for physiologically-based pharmacokinetic models.

An accurate understanding of the changes in height and weight of children with age is critical to the development of models predicting drug concentrations in children (i.e., physiologically-based pharmacokinetic models). However, curves describing the growth of a typical population of children may not accurately characterize growth of children with various conditions, such as obesity. Therefore, to develop height and weight versus age growth curves for youth who were diagnosed with type 2 diabetes, we extracted data from electronic medical records. Robust nonlinear models were parameterized to the equations describing height and weight versus age as defined by the Centers for Disease Control and Prevention (CDC). CDC z-scores were calculated using an internal program. The growth curves and z-scores were compared to CDC norms. Youth with type 2 diabetes were increasingly heavier than CDC norms from early childhood. Except for a period around puberty, youth with type 2 diabetes were, on average, shorter than CDC norms, resulting in shorter average adult height. Deviations in growth were apparent in youth who develop type 2 diabetes; such deviations may be expected for other conditions as well, and disease-specific growth curves should be considered during development of model-informed drug development for pediatric conditions.

The Impact of Age and Genetics on Naltrexone Biotransformation.

Naltrexone, an opioid antagonist primarily metabolized by aldo-keto reductase 1C4 (AKR1C4), treats pediatric conditions involving compulsiveness (e.g., autism spectrum, Prader-Willi, eating disorders, non-suicidal self-injury). Pharmacokinetic variability is apparent in adults, yet no data are available for children. This study aimed to examine the impact of age and genetic variation on naltrexone biotransformation. Human liver cytosol (HLC) samples (n = 158) isolated from children and adult organ donors were incubated with therapeutically relevant concentrations of naltrexone (0.1, 1 µM). Naltrexone biotransformation was determined by ultraperformance mass spectrometry quantification of the primary metabolite, 6-beta-naltrexol (6ßN), and 6ßN formation rates (pmol/mg protein/min) were calculated. HLCs from organ donors, age range 0-79 y (mean 16.0 ± 18.2 y), 37% (n = 60) female, 20% (n = 33) heterozygous and 1.2% (n = 2) homozygous for co-occurring AKR1C4 variants (S145C/L311V) showed >200-fold range in 6ßN formation (0.37-76.5 pmol/mg protein/min). Source of donor samples was found to be a substantial contributor to variability. Model estimates for a trimmed data set of source-adjusted pediatric samples (aged 0-18 y) suggested that AKR1C4 genetic variation, age, and sex explained 36% of the variability in 6ßN formation. Although activity increased steadily from birth and peaked in middle childhood (2-5 years), genetic variation (S145C/L311V) demonstrated a greater effect on activity than did age. Naltrexone biotransformation is highly variable in pediatric and adult livers and can be partly accounted for by individual factors feasible to obtain (e.g., genetic variability, age, sex). These data may inform a precision therapeutics approach (e.g., exposure optimization) to further study Naltrexone responsiveness in children and adults. SIGNIFICANCE STATEMENT: Biotransformation of the commonly used opioid antagonist naltrexone is highly variable and may contribute to reduced therapeutic response. Age, sex, and genetic variation in the drug-metabolizing enzyme, AKR1C4, are potential factors contributing to this variability. In pediatric samples, genetic variation (S145C/L311V) demonstrates a greater impact on activity than age. Additionally, the source of donor samples was identified as an important contributor and must be accounted for to confidently elucidate the biological variables most impactful to drug biotransformation.

Ontogeny of Scaling Factors for Pediatric Physiology-Based Pharmacokinetic Modeling and Simulation: Microsomal Protein Per Gram of Liver.

Microsomal protein per gram of liver (MPPGL) is an important scaling factor for bottom-up physiology-based pharmacokinetic modeling and simulation, but data in pediatrics are limited. Therefore, MPPGL was determined in 160 liver samples from pediatric (n = 129) and adult (n = 31) donors obtained from four sources: the University of Maryland Brain and Tissue Bank (UMBTB), tissue retrieval services at the University of Minnesota and University of Pittsburgh, and Sekisui-Xenotech. Tissues were homogenized and subjected to differential centrifugation to prepare microsomes, and cytochrome c reductase activities in tissue homogenates and microsomes were used to estimate cytochrome P450 reductase (POR) activity as a marker of microsomal recovery; microsomal POR content was also assessed by quantitative proteomics. MPPGL values varied 5- to 10-fold within various age groups/developmental stages, and tissue source was identified as a contributing factor. Using a "trimmed" dataset comprised of samples ranging from 3 to 18 years of age common to the four sources, POR protein abundance and activity in microsomes and POR activity in homogenates was lower in UMBTB samples (autopsy) compared with other sources (perfused/flash-frozen). Regression analyses revealed that the UMBTB samples were driving an apparent age effect as no effect of age on log-transformed MPPGL values was observed when the UMBTB samples were excluded. We conclude that a mean±SD MPPGL value of 30.4±1.7 mg/g is representative between one month postnatal age and early adulthood. Potential source effects should be considered for studies involving tissue samples from multiple sources with different procurement and processing procedures. SIGNIFICANCE STATEMENT: Microsomal protein per gram of liver (MPPGL) is an important scaling factor for bottom up PBPK modeling and simulation, but data in pediatrics are limited. Although MPPGL varies 5- to 10-fold at a given developmental stage, a value of 30.4 ± 1.7 mg/g (mean ± SD) is representative between one month postnatal age and early adulthood. However, when tissue samples are obtained from multiple sources, different procurement and processing procedures may influence the results and should be taken into consideration.

Recent advances in the ontogeny of drug disposition.

Developmental changes that occur throughout childhood have long been known to impact drug disposition. However, pharmacokinetic studies in the paediatric population have historically been limited due to ethical concerns arising from incorporating children into clinical trials. As such, much of the early work in the field of developmental pharmacology was reliant on difficult-to-interpret in vitro and in vivo animal studies. Over the last 2 decades, our understanding of the mechanistic processes underlying age-related changes in drug disposition has advanced considerably. Progress has largely been driven by technological advances in mass spectrometry-based methods for quantifying proteins implicated in drug disposition, and in silico tools that leverage these data to predict age-related changes in pharmacokinetics. This review summarizes our current understanding of the impact of childhood development on drug disposition, particularly focusing on research of the past 20 years, but also highlighting select examples of earlier foundational research. Equally important to the studies reviewed herein are the areas that we cannot currently describe due to the lack of research evidence; these gaps provide a map of drug disposition pathways for which developmental trends still need to be characterized.

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

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

Ontogeny of Drug-Metabolizing Enzymes.

Almost 50% of prescription drugs lack age-appropriate dosing guidelines and therefore are used "off-label." Only ~10% drugs prescribed to neonates and infants have been studied for safety or efficacy. Immaturity of drug metabolism in children is often associated with drug toxicity. This chapter summarizes data on the ontogeny of major human metabolizing enzymes involved in oxidation, reduction, hydrolysis, and conjugation of drugs. The ontogeny data of individual drug-metabolizing enzymes are important for accurate prediction of drug pharmacokinetics and toxicity in children. This information is critical for designing clinical studies to appropriately test pharmacological hypotheses and develop safer pediatric drugs, and to replace the long-standing practice of body weight- or surface area-normalized drug dosing. The application of ontogeny data in physiologically based pharmacokinetic model and regulatory submission are discussed.