MATERIALS AND METHODS: Five Malay patients receiving warfarin maintenance therapy were investigated for their CYP2C9*2, CYP2C9*3, and VKORC1-1639G>A genotypes and their vitamin K-dependent (VKD) clotting factor activities. The records of their daily warfarin doses and international normalized ratio (INR) 2 years prior to and after the measurement of VKD clotting factors activities were acquired. The mean warfarin doses were compared with predicted warfarin doses calculated from a genotypic-based dosing model developed for Asians.
RESULTS: A patient with the VKORC1-1639 GA genotype, who was supposed to have higher dose requirements, had a lower mean warfarin dose similar to those having the VKORC1-1639 AA genotype. This discrepancy may be due to the coadministration of celecoxib, which has the potential to decrease warfarins metabolism. Not all patients' predicted mean warfarin doses based on a previously developed dosing algorithm for Asians were similar to the actual mean warfarin dose, with the worst predicted dose being 54.34% higher than the required warfarin dose.
CONCLUSION: Multiple clinical factors can significantly change the actual required dose from the predicted dose from time to time. The additions of other dynamic variables, especially INR, VKD clotting factors, and concomitant drug use, into the dosing model are important in order to improve its accuracy.
METHODS: A retrospective audit of heart transplant recipients (n = 87) treated with tacrolimus was performed. Relevant data were collected from the time of transplant to discharge. The concordance of tacrolimus dosing and monitoring according to hospital guidelines was assessed. The observed and software-predicted tacrolimus concentrations (n = 931) were compared for the first 3 weeks of oral immediate-release tacrolimus (Prograf) therapy, and the predictive performance (bias and imprecision) of the software was evaluated.
RESULTS: The majority (96%) of initial oral tacrolimus doses were guideline concordant. Most initial intravenous doses (93%) were lower than the guideline recommendations. Overall, 36% of initial tacrolimus doses were administered to transplant recipients with an estimated glomerular filtration rate of <60 mL/min/1.73 m despite recommendations to delay the commencement of therapy. Of the tacrolimus concentrations collected during oral therapy (n = 1498), 25% were trough concentrations obtained at steady-state. The software displayed acceptable predictions of tacrolimus concentration from day 12 (bias: -6%; 95%confidence interval, -11.8 to 2.5; imprecision: 16%; 95% confidence interval, 8.7-24.3) of therapy.
CONCLUSIONS: Tacrolimus dosing and monitoring were discordant with the guidelines. The Bayesian forecasting software was suitable for guiding tacrolimus dosing after 11 days of therapy in heart transplant recipients. Understanding the factors contributing to the variability in tacrolimus pharmacokinetics immediately after transplant may help improve software predictions.
METHODS: Medical records of renal transplant patients at Penang General Hospital were retrospectively analyzed. A time-dissociated PKPD model with covariate effects was developed using NONMEM to evaluate renal graft function response, quantified as estimated glomerular filtration rate (eGFR), toward the cyclosporine cumulative exposure (area under the concentration-time curve). The final model was integrated into a tool to predict the potential outcome. Individual eGFR predictions were evaluated based on the clinical response recorded as acute rejection/nephrotoxicity events.
RESULTS: A total of 1256 eGFR readings with 2473 drug concentrations were obtained from 107 renal transplant patients receiving cyclosporine. An Emax drug effect with a linear drug toxicity model best described the data. The baseline renal graft level (E0), maximum effect (Emax), area under the concentration-time curve achieving 50% of the maximum effect, and nephrotoxicity slope were estimated as 12.9 mL·min-1·1.73 m-2, 50.7 mL·min-1·1.73 m-2, 1740 ng·h·mL-1, and 0.00033, respectively. The hemoglobin level was identified as a significant covariate affecting the E0. The model discerned acute rejection from nephrotoxicity in 19/24 cases.
CONCLUSIONS: A time-dissociated PKPD model successfully described a large number of observations and was used to develop an online tool to predict renal graft response. This may help discern early rejection from nephrotoxicity, especially for patients unwilling to undergo a biopsy or those waiting for biopsy results.