454 Factors influencing pharmacokinetics of tacrolimus in hematopoietic stem cell transplantation: The integration of microbiome and pharmacogenomics

Objectives/Goals: Tacrolimus (TAC) is an immunosuppressant used after hematopoietic stem cell transplant (HSCT). Recently, TAC was found to be metabolized to a novel, less active metabolite by common gut microbiota. Our objective is to determine a microbiome signature that influences oral TAC pharmacokinetic (PK) and to develop a clinical tool to select the TAC dose. Methods/Study Population: This is an observational IRB approved microbiome-pharmacogenomic study using banked biospecimens and clinical data, TAC dose, and PK information from the electronic health record. Adult HSCT patients with pre-transplant DNA and stool specimens were included in this analysis if they received TAC in the first 100 days post-HSCT. A global diversity array was used for DNA pharmacogenomic (PGx) genotyping, and metagenomic shotgun sequencing was used for stool microbiome analysis. Spearman correlation will be used to identify potential stool microbiota associated with TAC PK. TAC trough concentrations at steady state will be modeled using nonlinear mixed effects (NLME) modeling to identify potential genetic and microbiota covariates that influence TAC clearance. Results/Anticipated Results: We identified 53 eligible patients who had available DNA and 90 stool samples. The majority (n = 49, 92.5%) were of European ancestry. These patients had 920 (oral = 622, IV infusion = 298) TAC trough blood concentrations. We expect that patients who have high abundance of bacteria that metabolize or reduce the absorption of TAC will have lower blood concentrations and will require a higher IV to oral dose conversion ratio than those with lower abundance. Those patients will also require higher oral TAC daily doses. Low stool microbial diversity is expected to be associated with high oral TAC trough intra-patient variability in the first 100 days post-transplant. In the NLME model, PGx when combined with potential bacterial signature will better explain variability in TAC clearance. Discussion/Significance of Impact: Combining PGx and microbiome biomarkers will provide a better understanding of the factors influencing TAC PK and lead to models for individualized dosing. To our knowledge, this is the first study to investigate the combined influence of microbiome and PGx on drug PK. The study is limited to the availability of samples in the biobank.