Background Inter-patient variation in the pharmacokinetics of drugs can result in unpredictable variability in occurrence of adverse events and toxicity as well as variation in therapeutic efficacy. Although a multitude of factors contribute to this observed variation, inherited variation in genes involved in drug metabolism and transport has been shown to play a significant role. Genetic polymorphisms can influence the gene expression and/or activity, thereby impacting drug pharmacokinetics and causing inter-individual variation in drug levels which can alter risk of toxicity or therapeutic efficacy. The goal of this study is to identify pharmacogenomic biomarkers predicting drug response and toxicity in children receiving chemotherapy for acute hematologic malignancies. Identification of such biomarkers will establish relevant biomarkers for allowing for personalizing therapy to achieve maximum benefit and minimal side effects in future studies. Study Design and Methods: Study Population Male and female participants are included with no restrictions based on racial and/or ethnic origin. All patients aged 26 years of younger who have received at least one year of treatment for acute lymphoblastic leukemia (ALL) or acute myeloid leukemia (AML) and have experienced organ toxicity CTCAE v5.0 Grade 3 or higher at the University of Florida are offered participation. Subjects meeting eligibility criteria are excluded if they cannot provide a blood specimen. Study Design This pilot study proposes to identify and characterize pharmacogenomic variations that lead to different systemic toxicity profiles in pediatric patients receiving commonly used chemotherapy agents for ALL and AML. Agents of interest include drugs used during induction chemotherapy cycles which include Vincristine, Methotrexate, Cytarabine, Daunorubicin, Prednisone, Dexamethasone, 6-thioguanine, Cyclophosphamide, 6-mercaptopurine, and Etoposide. A single-nucleotide polymorphism (SNP) panel to evaluate SNPs in pharmacokinetic pathway genes of the selected drugs has been created. Genotyping is performed using Taqman genotyping assays and the Quant studio real time PCR system. We are investigating genes involved in the pharmacokinetics of the selected chemotherapy agents such as ABCB1, GSTM1, GSTT1, BCL2, MCL1, BCL2L11, MTHFR, SLC29A1, FMO3, DYNC2H1, TPMT, NUDT15, GSTP1, SOD2, and TP53. Toxicities that are correlated to SNP genotypes include the following: renal injury defined as creatinine clearance 29-15 ml/min/1.73 m2 or less; hepatic injury defined by increase in serum total bilirubin > 3.0 times the upper normal limit; hematological impairment including severe neutropenia, thrombocytopenia, and anemia leading to treatment delays; number of neutropenic fever hospitalizations; thromboembolic events; pancreatitis; cardiotoxicity defined by decline in ejection fraction by > 20% of baseline; neurotoxicity defined by examination and alterations in function; and insulin-dependent glucose resistance. The relationship and prevalence of SNP variations to the defined toxicities is analyzed. Statistical Considerations and Study Endpoint Complete case analysis will be performed. Toxicities per CTCAE v5.0 are graded by ordinal statistics. We aim to describe rates of pharmacogenomic SNP variants and the prevalence of specific toxicities related to these variants. The sample size of 100 patients was selected because this number should allow us to be relatively precise in our conclusions while still allowing for estimates of variability. Factors such as the rarity of pediatric cancer and the numbers of patients treated at our institution were considered in selecting this sample size. A chi-square test is used to evaluate for an association between SNP variants and toxicity grading. To quantify identified associations, multinomial logistic regression analysis will be performed. A P-value <0.05 is considered statistically significant. Study Endpoints: The study endpoint is to identify pharmacogenomic SNP variants of children undergoing treatment for acute hematologic malignancies and to provide an analysis of the relationship between these variants and clinically graded toxicities. Identification of these biomarkers would help guide subsequent validation in a larger cohort and establish clinically relevant biomarkers for personalization of acute leukemia therapy. Disclosures No relevant conflicts of interest to declare.