Clinical pharmacokinetics · 2025
Population Pharmacokinetics Model of Thioguanine in Patients with Inflammatory Bowel Disease.
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Bayoumy A B, de Boer N K H, Keizer R J, Derijks L J J
Аннотация
BACKGROUND: Thioguanine (TG) has recently been rediscovered as an immunosuppressive agent in the treatment of inflammatory bowel disease (IBD). This prodrug is directly converted into its active metabolites, 6-thioguanine nucleotides (6-TGNs), targeting the inhibition of RAC1 GTPase in inflammatory conditions, disrupting key cellular signaling pathways necessary for T-cell activation and survival, thereby contributing to its immunosuppressive action. In IBD, TG is used fixed dose and may benefit from model-informed precision dosing (MIPD) to optimize treatment efficacy and minimize toxicity. However, a population pharmacokinetic (PopPK) model to do so is lacking.
OBJECTIVE: To develop a PopPK model for TG in IBD patients, enhancing the understanding of TG's pharmacokinetics and supporting the implementation of model-informed precision dosing (MIPD).
METHODS: We employed a dataset comprising 131 6-TGN trough concentrations from 28 IBD patients treated with TG. The data were analyzed using nonlinear mixed-effects modeling (NONMEM) to estimate pharmacokinetic parameters and explore the influence of covariates such as weight and 5-ASA use on drug disposition. Model fit-for-purpose was evaluated through computation of the model's forecasting performance.
RESULTS: The developed PopPK model was a one-compartment model with first-order absorption. A one-compartment TG model was stable, and able to estimate pharmacokinetic parameters with good precision (relative standard error [RSE] 15%) with weight and aminosalicylic acid (5-ASA) use significantly affected TG clearance. Forecasting performance was also adequate with a relative root mean squared error (rRMSE) of 24.1% and practically no systematic bias (mean percentage error [MPE] 0.2%).
CONCLUSION: This study presents the first PopPK model of thioguanine for IBD, offering a novel tool for MIPD in clinical settings. Future studies should explore additional covariates such as TPMT genotype and drug interactions to further refine dosing recommendations for diverse patient populations.
OBJECTIVE: To develop a PopPK model for TG in IBD patients, enhancing the understanding of TG's pharmacokinetics and supporting the implementation of model-informed precision dosing (MIPD).
METHODS: We employed a dataset comprising 131 6-TGN trough concentrations from 28 IBD patients treated with TG. The data were analyzed using nonlinear mixed-effects modeling (NONMEM) to estimate pharmacokinetic parameters and explore the influence of covariates such as weight and 5-ASA use on drug disposition. Model fit-for-purpose was evaluated through computation of the model's forecasting performance.
RESULTS: The developed PopPK model was a one-compartment model with first-order absorption. A one-compartment TG model was stable, and able to estimate pharmacokinetic parameters with good precision (relative standard error [RSE] 15%) with weight and aminosalicylic acid (5-ASA) use significantly affected TG clearance. Forecasting performance was also adequate with a relative root mean squared error (rRMSE) of 24.1% and practically no systematic bias (mean percentage error [MPE] 0.2%).
CONCLUSION: This study presents the first PopPK model of thioguanine for IBD, offering a novel tool for MIPD in clinical settings. Future studies should explore additional covariates such as TPMT genotype and drug interactions to further refine dosing recommendations for diverse patient populations.