Therapeutic drug monitoring is essential with tacrolimus, which is one of the key immunosuppressive agents used after solid organ transplant.
Solid organ transplantation of the lungs, heart, liver, intestines, or kidney offers life-saving treatment for patients living with end-organ dysfunction. During transplantation, various immunosuppressive medications are used at different times to prevent the patient’s body from rejecting the transplanted organ.
Administering these medications requires a delicate balance. The drugs must suppress the patient’s immune system enough to prevent rejection of the transplanted organ, but not so much that the patient develops opportunistic infections.
Tacrolimus, which is frequently administered in both the inpatient and outpatient setting, is one of the key immunosuppressive agents used after solid organ transplant. Therapeutic drug monitoring (TDM) is essential, and the patient’s serum level must be closely monitored throughout the course of treatment.
In 2020, a new consensus guideline for the therapeutic monitoring of vancomycin firmly recommended Bayesian forecasting software as the preferred method of dosage calculation, citing its clinical benefit and widespread availability.3 A MAP-Bayesian analysis uses the maximum a posteriori estimate, or the most probable model parameters, to interpret the patient’s levels in the context of the PK model.
Although the 2019 tacrolimus guideline stops just short of recommending Bayesian analysis as the preferred methodology, it does promote population PK model-based Bayesian estimators as improving target achievement compared with standard TDM. Although most transplant centers rely on trough concentrations drawn immediately before the dose, as these have historically been easier to obtain than area under the curve (AUC) values, the consensus notes that evidence shows a poor correlation between tacrolimus trough concentrations and outcome.4
The 2019 tacrolimus consensus frames Bayesian estimation software as the clear path for the future, stating that the use of population PK model-based Bayesian estimators provide AUC predictions with minimal bias (<5%) and imprecision (<20%).5 The authors conclude that Bayesian estimation, rather than standard trough concentration-based TDM, seems to be a better way to improve future tacrolimus TDM.
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