Population Pharmacokinetics Model of Thioguanine in Patients with Inflammatory Bowel Disease

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.

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).

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.

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%).

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.