The Ontogeny of UDP-glucuronosyltransferase Enzymes, Recommendations for Future Profiling Studies and Application Through Physiologically Based Pharmacokinetic Modelling

Abstract

Limited understanding of drug pharmacokinetics in children is one of the major challenges in paediatric drug development. This is most critical in neonates and infants owing to rapid changes in physiological functions, especially in the activity of drug-metabolising enzymes. Paediatric physiologically based pharmacokinetic models that integrate ontogeny functions for cytochrome P450 enzymes have aided our understanding of drug exposure in children, including those under the age of 2 years. Paediatric physiologically based pharmacokinetic models have consequently been recognised by the European Medicines Agency and the US Food and Drug Administration as innovative tools in paediatric drug development and regulatory decision making. However, little is currently known about age-related changes in UDP-glucuronosyltransferase-mediated metabolism, which represents the most important conjugation reaction for xenobiotics. Therefore, the objective of the review was to conduct a thorough literature survey to summarise our current understanding of age-related changes in UDP-glucuronosyltransferases as well as associated clinical and experimental sources of variance. Our findings indicate that there are distinct differences in UDP-glucuronosyltransferase expression and activity between isoforms for different age groups. In addition, there is substantial variability between individuals and laboratories reported for human liver microsomes, which results in part from a lack of standardised experimental conditions. Therefore, we provide a number of best practice recommendations for experimental conditions, which ultimately may help improve the quality of data used for quantitative clinical pharmacology approaches, and thus for safe and effective pharmacotherapy in children.

Characterization of the Ontogeny of Hepatic UDP‐Glucuronosyltransferase Enzymes Based on Glucuronidation Activity Measured in Human Liver Microsomes

“…Several drugs are mainly metabolized via UGT enzymes, for example, raltegravir (UGT1A1), lamotrigine (UGT1A4), propofol (UGT1A9), zidovudine, and morphine (UGT2B7) . Associations between increased plasma exposure and serious adverse events for UGT‐metabolized drugs were reported in our previous work and can be from immature or reduced UGT catalytic efficiency. Changes in maturation processes, distinct pathological mechanisms, and low sample size and limited sample volumes may limit the evaluation of drug PK in neonates and infants and require adaptively designed clinical trials.…”

“…The UGT1A (UGT1A1, UGT1A3, UGT1A4, UGT1A6, and UGT1A9), UGT2B (UGT2B4, UGT2B7, UGT2B10, UGT2B15, and UGT2B17), UGT3A (UGT3A1 and UGT3A2), and UGT8 subfamily isoforms, expressed in the liver. However, only the UGT1A and UGT2B subfamilies are extensively involved in drug metabolism …”

“…UGT enzymes are key determinants of pharmacokinetic (PK), toxicity and the safety of many pediatric drugs . Several drugs are mainly metabolized via UGT enzymes, for example, raltegravir (UGT1A1), lamotrigine (UGT1A4), propofol (UGT1A9), zidovudine, and morphine (UGT2B7) .…”

“…Several factors may limit our ability to determine the age‐related changes in UGT activity and the contribution of UGTs to metabolism of existing and new drug molecules. These include the partial selectivity of in vitro UGT probe substrates, the lack of clinically used drugs as selective probe substrates, and variations in experimental conditions across in vitro studies . To minimize experimental variability, we recently optimized the experimental conditions of an in vitro automated glucuronidation assay and discussed the selectivity of UGT probe substrates as functional markers of UGT activity in HLMs of UGT phenotyping and screening assays .…”

Predictive Pediatric Modeling and Simulation Using Ontogeny Information

“…In order to adequately apply PBPK modeling to children for drugs eliminated through specific elimination pathways, a proper implementation of the ontogeny of these pathways in the model is needed. Several articles have been published identifying the ontogeny of active processes such as phase 1 and phase 2 metabolizing enzymes and, to a lesser extent, transporters as well as passive processes such as glomerular filtration rate (GFR) and plasma proteins . Ontogeny information can originate from various sources such as in the form of (semi)quantitative mRNA expression or in vitro activity data .…”