Objective: The aim of the study was to evaluate the ability of a combinatorial pharmacogenomic test to predict medication blood levels and relative clinical improvements in a selected pediatric population.

Methods: This study enrolled patients between ages 3 to 18 years who presented to a pediatric emergency department with acute psychiatric, behavioral, or mental health crisis and/or concerns, and had previously been prescribed psychotropic medications. Patients received combinatorial pharmacogenomic testing with medications categorized according to gene-drug interactions (GDIs); medications with a GDI were considered "incongruent," and medications without a GDI were considered "congruent." Blood levels for escitalopram, fluoxetine, aripiprazole, and clonidine were evaluated according to level of GDI. Relative clinical improvements in response to the prescribed psychotropic medications were measured using a parent-rated Clinical Global Impression of Improvement (CGI-I) assessment, where lower scores corresponded with greater improvement.

Results: Of the 100 patients enrolled, 73% reported taking ≥1 incongruent medication. There was no significant difference in CGI-I scores between patients prescribed congruent versus incongruent medications (3.37 vs 3.68, P = 0.343). Among patients who presented for depression or suicidal ideation, those prescribed congruent medications had significantly lower CGI-I scores compared with those taking incongruent medications ( P = 0.036 for depression, P = 0.018 for suicidal ideation). There was a significant association between medication GDI and blood levels for aripiprazole (n = 15, P = 0.01) and escitalopram (n = 10, P = 0.01).

Conclusions: Our preliminary findings suggest that combinatorial pharmacogenomic testing can predict medication blood levels and relative outcomes based on medication congruency in children presenting to an emergency department with acute psychiatric/behavioral crises. Additional studies will be needed to confirm these findings.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815804PMC
http://dx.doi.org/10.1097/PEC.0000000000002871DOI Listing

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