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Dose optimization of sirolimus may further improve outcomes in allogeneic hematopoietic cell transplant (HCT) patients receiving post‐transplantation cyclophosphamide (PTCy) to prevent graft‐versus‐host disease (GVHD). Sirolimus exposure–response association studies in HCT patients (i.e., the association of trough concentration with clinical outcomes) have been conflicting. Sirolimus has important effects on T‐cells, including conventional (Tcons) and regulatory T‐cells (Tregs), both of which have been implicated in the mechanisms by which PTCy prevents GVHD, but there is an absence of validated biomarkers of sirolimus effects on these cell subsets. Considering the paucity of existing biomarkers and the complexities of the immune system, we conducted a literature review to inform a quantitative systems pharmacology (QSP) model of GVHD. The published literature presented multiple challenges. The sirolimus pharmacokinetic models insufficiently describe sirolimus distribution to relevant physiological compartments. Despite multiple publications describing sirolimus effects on Tcons and Tregs in preclinical and human ex vivo models, consistent parameters relating sirolimus concentrations to circulating Tcons and Tregs could not be found. Each aspect presents a challenge in building a QSP model of sirolimus and its temporal effects on T‐cell subsets and GVHD prevention. To optimize GVHD prevention regimens, phase I studies and systematic studies of immunosuppressant concentration–effect association are needed for QSP modeling. [ABSTRACT FROM AUTHOR]

Biomarker‐guided dosing may improve the efficacy and toxicity of cyclophosphamide (CY); however, clinical studies evaluating their association with the area under the plasma concentration–time curve (AUC) of CY and its metabolites are time‐ and resource‐intensive. Therefore, we sought to identify lipidomic biomarkers associated with the time‐varying differences in CY formation clearance to 4‐hydroxycyclophosphamide (4HCY), the principal precursor to CY's cytotoxic metabolite. Hematopoietic cell transplant (HCT) patients receiving post‐transplant CY (PT‐CY) were enrolled, cohort 1 (n = 25) and cohort 2 (n = 26) donating longitudinal blood samples before they started HCT (pre‐HCT), before infusion of the donor allograft (pre‐graft), before the first dose of PT‐CY (pre‐CY) and 24 h after the first dose of PT‐CY (24‐h post‐CY) which is also immediately before the second dose of CY. A total of 409 and 387 lipids were quantitated in the two cohorts, respectively. Associations between lipids, individually and at a class level, and the ratio of 4HCY/CY AUC (i.e., 4HCY formation clearance) were evaluated using linear regression with a false discovery rate <0.05. There were no individual lipids that passed control for false discovery at any time point. These results demonstrate the feasibility of lipidomics, but future studies in larger samples with multiple omic tools are warranted to optimize CY dosing in HCT. [ABSTRACT FROM AUTHOR]

The widely used alkylating agent cyclophosphamide (CY) has substantive interpatient variability in the area under the curve (AUC) of it and its metabolites. Numerous factors may influence the drug‐metabolizing enzymes that metabolize CY to 4‐hydroxycyclophosphamide (4HCY), the principal precursor to CY's cytotoxic metabolite. We sought to identify endogenous metabolomics compounds (EMCs) associated with 4HCY formation clearance (ratio of 4HCY/CY AUC) using global metabolomics. Patients who undergo hematopoietic cell transplantation receiving post‐transplant CY (PT‐CY) were enrolled, cohort 1 (n = 26) and cohort 2 (n = 25) donating longitudinal blood samples before they started HCT (pre‐HCT), before infusion of the donor allograft (pre‐graft), before the first dose of PT‐CY (pre‐CY), and 24 h after the first dose of PT‐CY (24‐h post‐CY), which is also immediately before the second dose of CY. A total of 512 and 498 EMCs were quantitated in two cohorts, respectively. Both univariate linear regression with false discovery rate (FDR), and pathway enrichment analyses using a global association test were performed. At the pre‐CY time point, no EMCs were associated at FDR less than 0.1. At pre‐HCT, cohort 1 had one EMC (levoglucosan) survive the FDR threshold. At pre‐graft, cohort 1 and cohort 2 had 20 and 13 EMCs, respectively, exhibiting unadjusted p values less than 0.05, with the only EMCs having an FDR less than 0.1 being two unknown EMCs. At 24‐h post‐CY, there were three EMCs, two ketones, and threitol, at FDR less than 0.1 in cohort 2. These results demonstrate the potential of pharmacometabonomics, but future studies in larger samples are needed to optimize CY. [ABSTRACT FROM AUTHOR]