External validation of population pharmacokinetic models of tacrolimus in Thai adult liver transplant recipients.

OBJECTIVE: Several population pharmacokinetic models of tacrolimus in liver transplant patients were built, and their predictability was evaluated in their settings. However, the extrapolation in the prediction was unclear. This study aimed to evaluate the predictive performance of published tacrolimus models in adult liver transplant recipients using data from the Thai population as an external dataset. METHODS: The selected published models were systematically searched and evaluated for their quality. The external dataset of patients who underwent the first liver transplant and received immediate-release tacrolimus was used to assess the predictive performance of each selected model. Trough concentrations between 3 and 6 months were retrospectively collected to evaluate the predictability of each model using prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. RESULTS: Sixty-seven patients with 360 trough concentrations and eight selected published models were included in this study. None of the models met the predictive precision criteria in prediction-based diagnostics. Meanwhile, four published population pharmacokinetic models showed a normal distribution in NPDE testing. Regarding Bayesian forecasting, all models improved their forecasts with at least one prior information data point. CONCLUSION: Bayesian forecasting is more accurate and precise than other testing methods for predicting drug concentrations. However, none of the evaluated models provides satisfactory predictive performance for generalization to Thai liver transplant patients. This underscores the need for future research to develop population PK models tailored to the Thai population. Such efforts should consider the inclusion of nonlinear pharmacokinetics and region-specific factors, including genetic variability, to improve model accuracy and applicability.

Population pharmacokinetic models of tacrolimus in paediatric solid organ transplant recipients: A systematic review.

AIMS: This study aimed to provide up-to-date information on paediatric population pharmacokinetic models of tacrolimus and to identify factors influencing tacrolimus pharmacokinetic variability. METHODS: Systematic searches in the Web of Science, PubMed, Scopus, Science Direct, Cochrane, EMBASE databases and reference lists of articles were conducted from inception to March 2023. All population pharmacokinetic studies of tacrolimus using nonlinear mixed-effect modelling in paediatric solid organ transplant patients were included. RESULTS: Of the 21 studies reviewed, 62% developed from liver transplant recipients and 33% from kidney transplant recipients. Most studies used a 1-compartment model to describe tacrolimus pharmacokinetics. Body weight was a significant predictor for tacrolimus volume of distribution (Vd/F). The estimated Vd/F for 1-compartment models ranged from 20 to 1890 L, whereas the peripheral volume of distribution (Vp/F) for 2-compartment models was between 290 and 1520 L. Body weight, days post-transplant, CYP3A5 genotype or haematocrit were frequently reported as significant predictors of tacrolimus clearance. The estimated apparent clearance values range between 0.12 and 2.18 L/h/kg, with inter-individual variability from 13.5 to 110.0%. Only 29% of the studies assessed the generalizability of the models with external validation. CONCLUSION: This review highlights the potential factors, modelling approaches and validation methods that impact tacrolimus pharmacokinetics in a paediatric population. The clinician could predict tacrolimus clearance based on body weight, CYP3A5 genotype, days post-transplant or haematocrit. Further research is required to determine the relationship between pharmacogenetics and tacrolimus pharmacodynamics in paediatric patients and confirm the applicability of nonlinear kinetics in this population.

Impact of Pharmacist-Led Implementation of a Community Hospital-Based Outpatient Parenteral Antimicrobial Therapy on Clinical Outcomes in Thailand.

Few studies have analyzed community hospital-based parenteral anti-infective therapy (CohPAT). We aimed to assess the clinical impact of a pharmacist-led implementation of a clinical practice guideline (CPG) for CohPAT, and to determine the pharmacist's role in CohPAT medication management. The prospective-period patients (post-implementation group) were compared with the historical control-period patients (pre-implementation group) for receiving a continuous antimicrobial parenteral injection. A CPG was used for laboratory testing for efficacy and safety, the monitoring of adverse drug events during admission, microbiology results coordination, and dosage adjustment. For any antimicrobial drug-related problems, the pharmacist consulted with the clinicians. Over 14 months, 50 participants were included in each group. In the pre-implementation period, 7 (14%) and 4 (8%) out of 50 patients received an inappropriate dosage and nonlaboratory monitoring for dose adjustment, respectively. The patients received the proper dosage of antimicrobial agents, which increased significantly from 78% pre- to 100% post-implementation (p = 0.000). The pharmacist's interventions during the prospective-period were completely accepted by the clinicians, and significantly greater laboratory monitoring complying with CPG was given to the postimplementation group than the pre-implementation group (100% vs. 60%; p = 0.000). Significantly less patients with unfavorable outcomes (failure or in-hospital mortality) were observed in the post-implementation than in the pre-implementation (6% vs. 26%; p = 0.006) group. For the logistic regression analysis, lower respiratory infection (adjusted OR, aOR 3.68; 95%CI 1.13-12.06) and the post-implementation period (aOR 0.21; 95%CI 0.06-0.83) were significant risk factors that were associated with unfavorable outcomes. Given the better clinical outcomes and the improved quality of septic patient care observed after implementation, pharmacist-led implementation should be adopted in healthcare settings.