Influence of OCT1 Ontogeny and Genetic Variation on Morphine Disposition in Critically Ill Neonates: Lessons From PBPK Modeling and Clinical Study

Abstract

Morphine is commonly used for analgesia in the neonatal intensive care unit (NICU) despite having highly variable pharmacokinetics (PKs) between individual patients. The pharmacogenetic (PG) effect of variants at the loci of organic cation transporter 1 (OCT1) and UDP-glucuronosyltransferase 2B7 (UGT 2B7) on age-dependent morphine clearance were evaluated in a cohort of critically ill neonatal patients using an opportunistic sampling design. Our primary results demonstrate the significant influence of OCT1 genotype (P < 0.05) and gestational age (P ≤ 0.005) on morphine PKs. A physiologically based pharmacokinetic (PBPK) model for morphine that accounted for OCT1 ontogeny and PG effect in post-term neonates adequately described the clinically observed variability in morphine PKs. This study serves as a proof of concept for genotype-dependent drug transporter ontogeny in neonates.Morphine is widely used for management of perioperative pain and/or neonatal abstinence syndrome in the neonatal intensive care unit (NICU) of many hospitals. Wide interpatient variability in morphine exposure and response among neonates and small infants is a major limitation to morphine pharmacotherapy within these younger populations, making it difficult for clinicians to determine appropriate individualized dosage. Suboptimal dose titration is associated with both inadequate pain control in the case of underexposure, and often life-threatening side effects (primarily excessive sedation and respiratory depression) in the case of overexposure. 1,2 The variability in exposure and response to morphine observed in patients has been presumed to correlate with differences in morphine pharmacokinetics (PKs). 3,4 In young patients, the factors underlying morphine PKs are complex due to increase in body size (growth), pharmacogenetic (PG) effects, age-related physiological differences, and/or disease condition/progress. Especially in neonatal and small infant patients, the ontogeny of metabolic enzyme and drug transporter expression should

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 .…”

Virtual Twins: Understanding the Data Required for Model‐Informed Precision Dosing

“…To date, VTs have been generated by individualizing a limited number of systems parameters in established PBPK platforms. [1][2][3][4] Which data are required routinely, how these data are generated and stored, how models are best individualized and updated, and whether VTs can be deployed clinically for accurate dosing decisions, are all areas of uncertainties that require addressing (e.g., prediction of complex drug-drug-genedisease interactions). Much data for VTs is readily available but underutilized, and validated biomarkers of ADME processes from "liquid biopsies" are currently driving superior model individualization.…”

“…Fixed parameters in the VT publications to date include age, gender, kidney function, and DME genotype and/ or phenotype. [1][2][3][4] Monte Carlo simulation then allows sensible variability in PK for the VTs to be estimated from covariates of the "nonfixed" default system parameters, i.e., similar to population level PBPK M&S. Figure 2 illustrates this workflow using the example of a patient starting olanzapine for schizophrenia. 1…”

“…The approach has four published reports to date, two of which have pharmacodynamic predictions via linked quantitative systems pharmacology (QSP) models. [1][2][3][4] Importantly, VTs are patient focused rather than drug focused. Predictions of drug behavior depend on the interactions of certain elements of VTs pertinent to a specific drug (e.g., eliminating pathways), some of which may or may not be relevant to the other drugs taken.…”

Incorporating Ontogeny in Physiologically Based Pharmacokinetic Modeling to Improve Pediatric Drug Development: What We Know About Developmental Changes in Membrane Transporters

“…33,34,37 This was supported by a recently published clinical study in neonates who were admitted to the neonatal intensive care unit where postmenstrual age as well as OCT1 genotype impacted the PK of the OCT1 substrate morphine. 38 Further, the age at which half of adult level is reached (TM 50 ) was also estimated using a sigmoidal maximum effect (E max ) model and was reported to be about 6 months. r OATP1B1: mRNA expression of OATP1B1 in fetal liver was 20-fold lower than that in adults, and that in neonates and infants was even lower (500-fold and 90-fold, respectively).…”