Intravenous busulfan doses are often personalized to a target plasma exposure (targeted busulfan) using an individual's busulfan clearance (BuCL). We evaluated whether BuCL could be predicted by a predose plasma panel of 841 endogenous metabolomic compounds (EMCs). In this prospective cohort of 132 hematopoietic cell transplantation (HCT) patients, all had samples collected immediately before busulfan administration (preBU) and 96 had samples collected 2 weeks before busulfan (2-week-preBU). BuCL was significantly associated with 37 EMCs after univariate linear regression analysis and controlling for false discovery (< 0.05) in the 132 preBU samples. In parallel, with preBU samples, we included all 841 EMCs in a least absolute shrinkage and selection operator-penalized regression which selected 13 EMCs as predominantly associated with BuCL. Then, we constructed a prediction model by estimating coefficients for these 13 EMCs, along with sex, using ordinary least-squares. When the resulting linear prediction model was applied to the 2-week-preBU samples, it explained 40% of the variation in BuCL (adjusted R2  = 0.40). Pathway enrichment analysis revealed 18 pathways associated with BuCL. Lysine degradation followed by steroid biosynthesis, which aligned with the univariate analysis, were the top two pathways. BuCL can be predicted before busulfan administration with a linear regression model of 13 EMCs. This pharmacometabolomics method should be prioritized over use of a busulfan test dose or pharmacogenomics to guide busulfan dosing. These results highlight the potential of pharmacometabolomics as a precision medicine tool to improve or replace pharmacokinetics to personalize busulfan doses.

Drug dosing in encephalopathic neonates treated with therapeutic hypothermia is challenging; exposure is dependent on body size and maturation but can also be influenced by factors related to disease and treatment. A better understanding of underlying pharmacokinetic principles is essential to guide drug dosing in this population. The prospective multicenter cohort study PharmaCool was designed to investigate the pharmacokinetics of commonly used drugs in neonatal encephalopathy. In the present study, all data obtained in the PharmaCool study were combined to study the structural system specific effects of body size, maturation, recovery of organ function, and temperature on drug clearance using nonlinear mixed effects modeling. Data collected during the first 5 days of life from 192 neonates treated with therapeutic hypothermia were included. An integrated population pharmacokinetic model of seven drugs (morphine, midazolam, lidocaine, phenobarbital, amoxicillin, gentamicin, and benzylpenicillin) and five metabolites (morphine-3-glucuronide, morphine-6-glucuronide, 1-hydroxymidazolam, hydroxymidazolam glucuronide, and monoethylglycylxylidide) was successfully developed based on previously developed models for the individual drugs. For all compounds, body size was related to clearance using allometric relationships and maturation was described with gestational age in a fixed sigmoidal Hill equation. Organ recovery after birth was incorporated using postnatal age. Clearance increased by 1.23%/hours of life (95% confidence interval (CI) 1.03-1.43) and by 0.54%/hours of life (95% CI 0.371-0.750) for high and intermediate clearance compounds, respectively. Therapeutic hypothermia reduced clearance of intermediate clearance compounds only, by 6.83%/°C (95% CI 5.16%/°C-8.34%/°C). This integrated model can be used to facilitate drug dosing and future pharmacokinetic studies in this population.