Knowledge is limited regarding how ontogeny and genetic variation influence the expression of drug targets and thereby contribute to variability in drug response in children. One challenge in designing studies to acquire this knowledge is the extensive variability in drug exposure that occurs in vivo, especially when drug clearance is dependent on a polymorphically expressed pathway. For example, recently published data by our group demonstrated a 30-fold difference in systemic exposure between CYP2D6 poor and ultrarapid metabolizers administered the same weight-based dose (0.5 mg/kg) of atomoxetine (ATX), a medication used to treat ADHD. Therefore, we propose that by eliminating inter-individual differences in dose-exposure we can identify patient-specific characteristics that are predictive of response thereby creating a foundation for personalized drug dosing guidelines.
The aims of this project are to 1) identify the inherent characteristics of children that segregate with ATX clinical response phenotypes, and 2) translate our understanding of the individual characteristics that drive the ATX dose-exposure relationship to target therapeutic exposures prior to a child's first dose.
These aims will be accomplished by an investigation that employs an individual genome-ontogeny informed pharmacokinetic (iGO-PK) model to control ATX exposure between patients with state-of-the-art measures of outcome including pharmaco metabolomic signatures, biomarkers of neurotransmitter activity, such as plasma dihydroxyphenylglycol (DHPG) and change in pupil diameter as an indicator of central norepinephrine transport (NET) inhibition by ATX, as well as comprehensive clinical assessment. The proposed study will establish a new investigational paradigm that can be generally applied to medications used for a diverse array of pediatric indications, and that allows physicians to choose the safest and most effective dose of any drug that they prescribe for children.