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The expression of cytochrome P450 (CYP) enzymes is highly variable and associated with factors, such as age, genotype, sex, and disease states. In this study, quantification of metronidazole metabolizing CYP isoforms (CYP2A6, CYP2E1, CYP3A4, CYP3A5, and CYP3A7) in human liver microsomes from 115 children and 35 adults was performed using a quantitative proteomics method. The data confirmed age‐dependent increase in CYP2A6, CYP2E1, and CYP3A4 abundance, whereas, as expected, CYP3A7 abundance showed postnatal decrease with age. In particular, the fold difference (neonatal to adulthood levels) in the protein abundance of CYP2A6, CYP2E1, and CYP3A4 was 14, 11, and 20, respectively. In contrast, protein abundance of CYP3A7 was > 125‐fold higher in the liver microsomes of neonates than of adults. The abundance of CYP2A6 and CYP3A5 was associated with genotypes, rs4803381 and rs776746, respectively. A proteomics‐informed physiologically based pharmacokinetic (PBPK) model was developed to describe the pharmacokinetics of metronidazole and its primary metabolite, 2‐hydroxymethylmetronidazole. The model revealed an increase in the metabolite‐to‐parent ratio with age and showed a strong correlation between CYP2A6 abundance and metabolite formation (r2 = 0.75). Notably, the estimated contribution of CYP3A7 was ~ 75% in metronidazole clearance in neonates. These data suggest that variability in CYP2A6 and CYP3A7 in younger children poses the risk of variable pharmacokinetics of metronidazole and its active metabolite with a potential impact on drug efficacy and safety. No sex‐dependent difference was observed in the protein abundance of the studied CYPs. The successful integration of hepatic CYP ontogeny data derived from a large liver bank into the pediatric PBPK model of metronidazole can be extended to other drugs metabolized by the studied CYPs. [ABSTRACT FROM AUTHOR]

Around 50% of the drugs used in children have never been tested for safety and efficacy in this vulnerable population. Immature drug elimination pathways can lead to drug toxicity when pediatric doses are determined using empirical methods such as body‐surface area or body‐weight‐normalized adult dosing. In the absence of clinical data, physiologically‐based pharmacokinetic (PBPK) modeling has emerged as a useful tool to predict drug pharmacokinetics in children. These models utilize developmental physiological data, including age‐dependent differences in the abundance of drug‐metabolizing enzymes and transporters (DMET), to mechanistically extrapolate adult pharmacokinetic data to children. The reported abundance data of hepatic DMET proteins in subcellular fractions isolated from frozen tissue are prone to high technical variability. Therefore, we carried out the proteomics‐based quantification of hepatic drug transporters and conjugating enzymes in 50 pediatric and 8 adult human hepatocyte samples. Out of the 34 studied proteins, 28 showed a significant increase or decrease with age. While MRP6, OAT7, and SULT1E1 were highest in < 1‐year‐old samples, the abundance of P‐gp and UGT1A4 was negligible in < 1‐year‐old samples and increased significantly after 1 year of age. Incorporation of the age‐dependent abundance data in PBPK models can help improve pediatric dose prediction, leading to safer drug pharmacotherapy in children. [ABSTRACT FROM AUTHOR]

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., (© 2021. Springer Science+Business Media, LLC, part of Springer Nature.)