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      Genotype-guided model significantly improves accuracy of tacrolimus initial dosing after liver transplantation

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          Summary

          Background

          The initial dose of tacrolimus after liver transplantation (LT) is critical for rapidly achieving the steady state of the drug concentration, minimizing the potential adverse reactions and warranting long-term patient prognosis. We aimed to develop and validate a genotype-guided model for determining personalized initial dose of tacrolimus.

          Methods

          By combining pharmacokinetic modeling, pharmacogenomic analysis and multiple statistical methods, we developed a genotype-guided model to predict individualized tacrolimus initial dose after LT in the discovery (n = 150) and validation cohorts (n = 97) respectively. This model was further validated in a prospective, randomized and single-blind clinical trial from August, 2021 to February, 2022 (n = 40, ChiCTR2100050288).

          Findings

          Our model included donor's and recipient's genotypes, recipient's weight and total bilirubin, which achieved an area under the curve of receiver operating characteristic curve (AUC of ROC) of 0.88 and 0.79 in the discovery and validation cohorts, respectively. We found that patients who were given tacrolimus within the recommended concentration range (RCR) (4–10 ng/mL), the new-onset metabolic syndromes are lower, especially for new-onset diabetes (p = 0.043). In the clinical trial, compared to those in experience-based (EB) group, patients in the model-based (MB) group were more likely to achieving the RCR (75% vs 40%, p = 0.025) with a more variable individualized dose (0.023–0.096 mg/kg/day vs 0.045–0.057 mg/kg/day). Moreover, significantly fewer medication adjustments were required for the MB group than the EB group (2.75 ± 2.01 vs 6.05 ± 3.35, p = 0.001).

          Interpretation

          Our genotype-based model significantly improved the initial dosing accuracy of tacrolimus and reduced the number of medication adjustments, which are critical for improving the prognosis of LT patients.

          Funding

          National Natural Science Foundation of China, Shanghai three-year action plan, National Science and Technology Major Project of China.

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          Most cited references29

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          Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines for CYP3A5 Genotype and Tacrolimus Dosing.

          Tacrolimus is the mainstay immunosuppressant drug used after solid organ and hematopoietic stem cell transplantation. Individuals who express CYP3A5 (extensive and intermediate metabolizers) generally have decreased dose-adjusted trough concentrations of tacrolimus as compared with those who are CYP3A5 nonexpressers (poor metabolizers), possibly delaying achievement of target blood concentrations. We summarize evidence from the published literature supporting this association and provide dosing recommendations for tacrolimus based on CYP3A5 genotype when known (updates at www.pharmgkb.org).
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            Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation.

            The aim of this review is to analyse critically the recent literature on the clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplant recipients. Dosage and target concentration recommendations for tacrolimus vary from centre to centre, and large pharmacokinetic variability makes it difficult to predict what concentration will be achieved with a particular dose or dosage change. Therapeutic ranges have not been based on statistical approaches. The majority of pharmacokinetic studies have involved intense blood sampling in small homogeneous groups in the immediate post-transplant period. Most have used nonspecific immunoassays and provide little information on pharmacokinetic variability. Demographic investigations seeking correlations between pharmacokinetic parameters and patient factors have generally looked at one covariate at a time and have involved small patient numbers. Factors reported to influence the pharmacokinetics of tacrolimus include the patient group studied, hepatic dysfunction, hepatitis C status, time after transplantation, patient age, donor liver characteristics, recipient race, haematocrit and albumin concentrations, diurnal rhythm, food administration, corticosteroid dosage, diarrhoea and cytochrome P450 (CYP) isoenzyme and P-glycoprotein expression. Population analyses are adding to our understanding of the pharmacokinetics of tacrolimus, but such investigations are still in their infancy. A significant proportion of model variability remains unexplained. Population modelling and Bayesian forecasting may be improved if CYP isoenzymes and/or P-glycoprotein expression could be considered as covariates. Reports have been conflicting as to whether low tacrolimus trough concentrations are related to rejection. Several studies have demonstrated a correlation between high trough concentrations and toxicity, particularly nephrotoxicity. The best predictor of pharmacological effect may be drug concentrations in the transplanted organ itself. Researchers have started to question current reliance on trough measurement during therapeutic drug monitoring, with instances of toxicity and rejection occurring when trough concentrations are within 'acceptable' ranges. The correlation between blood concentration and drug exposure can be improved by use of non-trough timepoints. However, controversy exists as to whether this will provide any great benefit, given the added complexity in monitoring. Investigators are now attempting to quantify the pharmacological effects of tacrolimus on immune cells through assays that measure in vivo calcineurin inhibition and markers of immunosuppression such as cytokine concentration. To date, no studies have correlated pharmacodynamic marker assay results with immunosuppressive efficacy, as determined by allograft outcome, or investigated the relationship between calcineurin inhibition and drug adverse effects. Little is known about the magnitude of the pharmacodynamic variability of tacrolimus.
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              A Randomized Controlled Trial Comparing the Efficacy of Cyp3a5 Genotype-Based With Body-Weight-Based Tacrolimus Dosing After Living Donor Kidney Transplantation.

              Patients expressing the cytochrome P450 (CYP) 3A5 gene require a higher tacrolimus dose to achieve therapeutic exposure compared with nonexpressers. This randomized-controlled study investigated whether adaptation of the tacrolimus starting dose according to CYP3A5 genotype increases the proportion of kidney transplant recipients being within the target tacrolimus predose concentration range (10-15 ng/mL) at first steady-state. Two hundred forty living-donor, renal transplant recipients were assigned to either receive a standard, body-weight-based or a CYP3A5 genotype-based tacrolimus starting dose. At day 3, no difference in the proportion of patients having a tacrolimus exposure within the target range was observed between the standard-dose and genotype-based groups: 37.4% versus 35.6%, respectively; p = 0.79. The proportion of patients with a subtherapeutic (i.e. 15 ng/mL) Tac predose concentration in the two groups was also not significantly different. The incidence of acute rejection was comparable between both groups (p = 0.82). Pharmacogenetic adaptation of the tacrolimus starting dose does not increase the number of patients having therapeutic tacrolimus exposure early after transplantation and does not lead to improved clinical outcome in a low immunological risk population.
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                Author and article information

                Contributors
                Journal
                eClinicalMedicine
                EClinicalMedicine
                eClinicalMedicine
                Elsevier
                2589-5370
                24 November 2022
                January 2023
                24 November 2022
                : 55
                : 101752
                Affiliations
                [a ]Organ Transplantation Clinical Medical Center of Xiamen University, Department of Organ Transplantation, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361005, Fujian, China
                [b ]Organ Transplantation Institute of Xiamen University, Fujian Provincial Key Laboratory of Organ and Tissue Regeneration, School of Medicine, Xiamen University, Xiamen, 361005, Fujian, China
                [c ]Department of General Surgery, Shanghai General Hospital, Shanghai Jiao Tong University, 200080, Shanghai, China
                [d ]Bio-Med Big Data Center, Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 200031, Shanghai, China
                [e ]Department of General Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, Henan, China
                [f ]Hongqiao International Institute of Medicine, Shanghai Tong Ren Hospital and Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, 200050, Shanghai, China
                Author notes
                []Corresponding author. pengzhihai1958@ 123456163.com
                [∗∗ ]Corresponding author. weituozhang@ 123456126.com
                [∗∗∗ ]Corresponding author. lihao6656@ 123456163.com
                [∗∗∗∗ ]Corresponding author. drjunweifan@ 123456163.com
                [g]

                Co-first author, these authors contributed equally to this work.

                Article
                S2589-5370(22)00481-3 101752
                10.1016/j.eclinm.2022.101752
                9700266
                36444212
                a297cc8f-63b3-46be-a7a3-027bd78b6ba9
                © 2022 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 20 June 2022
                : 31 October 2022
                : 1 November 2022
                Categories
                Articles

                tacrolimus,liver transplantation,pharmacogenomics,precision medicine

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