Bayesian Population Pharmacokinetic Modeling of Ondansetron for Neonatal Opioid Withdrawal Syndrome

Abstract

Ondansetron is an anti-emetic 5-HT3 receptor antagonist being investigated for treating neonatal opioid withdrawal syndrome (NOWS). Sparse PK data were analyzed from a multicenter, double-blind clinical trial with 98 mother/neonate dyads. Pregnant women with opioid use disorder were randomized to receive either placebo or ondansetron 8 mg intravenously within 4 h of delivery. Neonates born to mothers who were randomized to ondansetron received 0.07 mg/kg orally once every 24 h for up to five doses. Using current PK data, model parameters from a two-compartmental structural model from the literature (i.e., a priori model) were updated with the Metropolis-Hastings Markov-chain Monte Carlo estimation algorithm in NONMEM. The updated Bayesian model indicated a slower absorption rate (KA) but no differences in model parameters (CL, V, V2, Q) after including body weight and postmenstrual age. Sensitivity analyses on CL prior revealed statistical improvement favoring larger body weights, but not changes in postmenstrual age. However, further model development using larger body weights did not illustrate superior performance through visual inspection of diagnostic plots. Overall, a cumulative AUC of at least 1000 ng*h/mL appears to be the threshold for reductions in symptom severity. Exposure-response analyses suggest the total number of doses to be the primary driver for efficacy with respect to AUC, which reasonably aligns with the literature. Overall, it is suggested that at least three doses of the current oral ondansetron regimen are required to reduce symptom severity in neonates.