Population pharmacokinetics of cyclosporine A in pediatric patients with thalassemia undergoing allogeneic hematopoietic stem cell transplantation.

PURPOSE: To establish the population pharmacokinetics (PPK) model of cyclosporine A(CsA) in pediatric patients with thalassemia undergoing allogeneic hematopoietic stem cell transplantation (HSCT), aiming at providing a reference for clinical dose individualization of CsA. METHODS: Children with thalassemia who underwent allogeneic HSCT were enrolled retrospectively. The PPK structural model and the random variable model of CsA were established on NONMEN. And goodness of fit plots (GOFs), visual predictive check (VPC), and bootstrap and normalized prediction distribution errors (NPDE) were used to evaluate the final model. RESULTS: A one-compartment model with first-order absorption was employed to fit the base model. A total of 74 pediatric patients and 600 observations of whole blood concentration were included. The final model included weight (WT) in clearance (CL), alongside post-operative day (POD), fluconazole (FLUC), voriconazole (VORI), posaconazole (POSA), and red blood cell count (RBC) significantly. All the model evaluations were passed. CONCLUSION: In the PPK model based on the pediatric cohort on CsA with thalassemia undergoing allogeneic HSCT, WT, POD, FLUC, VORI, POSA, and RBC were found to be the significant factors influencing CL of CsA. The reliability and robustness of the final model were excellent. It is expected that the PPK model can assist in individualizing dosing strategy clinically.

Pharmacokinetics of Imatinib Mesylate and Development of Limited Sampling Strategies for Estimating the Area under the Concentration-Time Curve of Imatinib Mesylate in Palestinian Patients with Chronic Myeloid Leukemia.

BACKGROUND AND OBJECTIVE: Imatinib is a tyrosine kinase inhibitor used in the treatment of chronic myeloid leukemia (CML). The area under the concentration-time curve (AUC) is a pharmacokinetic parameter that symbolizes overall exposure to a drug, which is correlated with complete cytogenetic and treatment responses to imatinib, as well as its side effects in patients with CML. The limited sampling strategy (LSS) is considered a sufficiently precise and practical method that can be used to estimate pharmacokinetic parameters such as AUC, without the need for frequent, costly, and inconvenient blood sampling. This study aims to investigate the pharmacokinetic parameters of imatinib, develop and validate a reliable and practical LSS for estimating imatinib AUC0-24, and determine the optimum sampling points for predicting the imatinib AUC after the administration of once-daily imatinib in Palestinian patients with CML. METHOD: Pharmacokinetic profiles, involving six blood samples collected during a 24-h dosing interval, were obtained from 25 Palestinian patients diagnosed with CML who had been receiving imatinib for at least 7 days and had reached a steady-state level. Imatinib AUC0-24 was calculated using the trapezoidal rule, and linear regression analysis was performed to assess the relationship between measured AUC0-24 and concentrations at each sampling time. All developed models were analyzed to determine their effectiveness in predicting AUC0-24 and to identify the optimal sampling time. To evaluate predictive performance, two error indices were employed: the percentage of root mean squared error (% RMSE) and the mean predictive error (% MPE). Bland and Altman plots, along with mountain plots, were utilized to assess the agreement between measured and predicted AUC. RESULTS: Among the one-timepoint estimations, predicted AUC0-24 based on concentration of imatinib at the eighth hour after administration (C8-predicted AUC0-24) demonstrated the highest correlation with the measured AUC (r2 = 0.97, % RMSE = 6.3). In two-timepoint estimations, the model consisting of C0 and C8 yielded the highest correlation between predicted and measured imatinib AUC (r2 = 0.993 and % RMSE = 3.0). In three-timepoint estimations, the combination of C0, C1, and C8 provided the most robust multilinear regression for predicting imatinib AUC0-24 (r2 = 0.996, % RMSE = 2.2). This combination also outperformed all other models in predicting AUC. The use of a two-timepoint limited sampling strategy (LSS) for predicting AUC was found to be reliable and practical. While C0/C8 exhibited the highest correlation, the use of C0/C4 could be a more practical and equally accurate choice. Therapeutic drug monitoring of imatinib based on C0 can also be employed in routine clinical practice owing to its reliability and practicality. CONCLUSION: The LSS using one timepoint, especially C0, can effectively predict imatinib AUC. This approach offers practical benefits in optimizing dose regimens and improving adherence. However, for more precise estimation of imatinib AUC, utilizing two- or three-timepoint concentrations is recommended over relying on a single point.

Effectiveness and safety of once-daily tacrolimus formulations in de novo liver transplant recipients: The PRETHI study.

Data comparing long-term effectiveness and safety of once-daily tacrolimus formulations in de novo liver transplantation are scarce. We compared the effectiveness, pharmacokinetic profile, and safety of LCPT (Envarsus) and PR-Tac (Advagraf) for up to 12 months post-transplant. Adult de novo liver transplant recipients who started IR-Tac (Prograf) and were converted to LCPT or PR-Tac 3-5 days post-transplant were included. Data from 163 patients were analyzed, 87 treated with LCPT and 76 with PR-Tac. The incidence of treatment failure was 30.5% in the LCPT group versus 23.0% in the PR-Tac group (p = .291). Biopsy-proven acute rejection (BPAR) was reported in 26.8% of patients in the LCPT group and 17.6% in the PR-Tac group (p = .166). Graft loss was experienced in one patient (1.2%) in the LCPT group and three patients (4.1%) in the PR-Tac group (p = .346). Death was registered in three patients (3.7%) in the LCPT group and three patients (4.1%) in the PR-Tac group (p > .999). Patients in the LCPT group showed 45.7% higher relative bioavailability (Cmin /total daily dose [TDD]; p < .01) with similar Cmin and 33.3% lower TDD versus PR-Tac (p < .01). The evolution of renal function, safety profile, and the incidence of post-transplant renal failure, dyslipidemia, obesity, hypertension, and diabetes mellitus were similar in patients treated with LCPT and PR-Tac. In de novo liver transplant patients, LCPT and PR-Tac showed comparable effectiveness with higher relative bioavailability, similar Cmin and lower TDD in the LCPT group. Renal function, safety, and post-transplant complications were comparable in LCPT and PR-Tac groups.

Developing a mechanistic understanding of the nonlinear pharmacokinetics of letermovir and prospective drug interaction with everolimus using physiological-based pharmacokinetic modeling.

Letermovir is approved for use in cytomegalovirus-seropositive hematopoietic stem cell transplant recipients and is investigated in other transplant settings. Nonlinear pharmacokinetics (PKs) were observed in clinical studies after intravenous and oral dosing across a wide dose range, including the efficacious doses of 240 and 480 mg. A physiologically-based PK (PBPK) model for letermovir was built to develop a plausible explanation for the nonlinear PKs observed in clinical studies. In vitro studies suggested that letermovir elimination and distribution are mediated by saturable uridine glucuronosyltransferases (UGT)-metabolism and by saturable hepatic uptake via organic anion-transporting polypeptides (OATP) 1B. A sensitivity analysis of parameters describing the metabolism and distribution mechanisms indicated that the greater than dose-proportional increase in letermovir exposure is best described by a saturable OATP1B-mediated transport. This PBPK model was further used to evaluate the drug interaction potential between letermovir and everolimus, an immunosuppressant that may be co-administered with letermovir depending on regions. Because letermovir inhibits cytochrome P450 (CYP) 3A and everolimus is a known CYP3A substrate, an interaction when concomitantly administered is anticipated. The drug-drug interaction simulation confirmed that letermovir will likely increase everolimus are under the curve by 2.5-fold, consistent with the moderate increase in exposure observed with midazolam in the clinic. The output highlights the importance of drug monitoring, which is common clinical practice for everolimus to maintain safe and efficacious drug concentrations in the targeted patient population when concomitantly administered with letermovir.

Thalidomide interaction with inflammation in idiopathic pulmonary fibrosis.

The "Thalidomide tragedy" is a landmark in the history of the pharmaceutical industry. Despite limited clinical trials, there is a continuous effort to investigate thalidomide as a drug for cancer and inflammatory diseases such as rheumatoid arthritis, lepromatous leprosy, and COVID-19. This review focuses on the possibilities of targeting inflammation by repurposing thalidomide for the treatment of idiopathic pulmonary fibrosis (IPF). Articles were searched from the Scopus database, sorted, and selected articles were reviewed. The content includes the proven mechanisms of action of thalidomide relevant to IPF. Inflammation, oxidative stress, and epigenetic mechanisms are major pathogenic factors in IPF. Transforming growth factor-ß (TGF-ß) is the major biomarker of IPF. Thalidomide is an effective anti-inflammatory drug in inhibiting TGF-ß, interleukins (IL-6 and IL-1ß), and tumour necrosis factor-α (TNF-α). Thalidomide binds cereblon, a process that is involved in the proposed mechanism in specific cancers such as breast cancer, colon cancer, multiple myeloma, and lung cancer. Cereblon is involved in activating AMP-activated protein kinase (AMPK)-TGF-ß/Smad signalling, thereby attenuating fibrosis. The past few years have witnessed an improvement in the identification of biomarkers and diagnostic technologies in respiratory diseases, partly because of the COVID-19 pandemic. Hence, investment in clinical trials with a systematic plan can help repurpose thalidomide for pulmonary fibrosis.

Impact of genetic polymorphisms on tacrolimus trough blood concentration in Chinese liver transplant recipients.

Purpose: The aim of this study was to analyze the effects of various genetic polymorphisms and clinical factors on tacrolimus (TAC) concentration in the convalescence period (CP) and stabilization period (SP) post-liver transplantation. Patients & methods: A total of 13 SNPs were genotyped in 97 Chinese liver transplant recipients. Associations between SNPs and TAC trough blood concentration/dose ratio (C0/D) were analyzed using different genetic models in both CP and SP. Results: Only five SNPs were significantly associated with TAC log (C0/D) in the CP, and none showed a significant association in the SP. We identified rs15524 (CYP3A5), rs9200 (C6), albumin and creatinine as independent predictors of TAC C0/D in the CP. Furthermore, a final model in the CP explained a total of 30.5% TAC variation. Conclusion: Our study results suggest that in the early stages post-transplantation surgery, recipients' genetic and clinical factors exert a short-term impact on TAC metabolism that gradually decreases with time.

Influence of SLCO1B1 Polymorphisms on the Pharmacokinetics of Mycophenolic Acid in Renal Transplant Recipients.

OBJECTIVE: This study was designed to analyze the correlation between single nucleotide polymorphisms (SNP) related to drug metabolism and pharmacokinetics of mycophenolic acid (MPA) during long-term follow-up. MATERIALS AND METHOD: A retrospective cohort study involving 71 renal transplant recipients was designed. Blood samples were collected to extract total DNAs, followed by target sequencing based on next-generation sequencing technology. The MPA area under the curve (AUC) was calculated according to the formula established in our center. The general linear model and linear regression model were used to analyze the association between SNPs and MPA AUC. RESULTS: A total of 689 SNPs were detected in our study, and 90 tagger SNPs were selected after quality control and linkage disequilibrium analysis. The general linear model analysis showed that 9 SNPs significantly influenced MPA AUC. A forward linear regression was conducted, and the model with the highest identical degree (r2=0.55) included 4 SNPs (SLCO1B1: rs4149036 [P < 0.0001], ABCC2: rs3824610 [P = 0.005], POR: rs4732514 [P = 0.006], ABCC2: rs4148395 [P = 0.007]) and 6 clinical factors (age [P < 0.0001], gender [P < 0.0001], the incident of acute rejection (AR) [P = 0.001], albumin [P < 0.0001], duration after renal transplantation [P = 0.01], lymphocyte numbers [P = 0.026]). The most relevant SNP to MPA AUC in this model was rs4149036. The subgroup analysis showed that rs4149036 had a significant influence on MPA AUC in the older group (P = 0.02), high-albumin group (P = 0.01), male group (P = 0.046), and both within-36-month group (P = 0.029) and after-36-month group (P = 0.041). The systematic review included 4 studies, and 2 of them showed that the mutation in SLCO1B1 resulted in lower MPA AUC, which was contrary to our study. CONCLUSION: A total of 4 SNPs (rs4149036, rs3824610, rs4148395, and rs4732514) were identified to be significantly correlated with MPA AUC. Rs4149036, located in SLCO1B1, was suggested to be the most relevant SNP to MPA AUC, which had a stronger influence on recipients who were elder, male, or with high serum albumin. Furthermore, 6 clinical factors, including age, gender, occurrence of acute rejection, serum albumin, time from kidney transplantation, and blood lymphocyte numbers, were found to affect the concentration of MPA.

Loss of Function ABCG2 c.421C>A (rs2231142) Polymorphism Increases Steady-State Exposure to Mycophenolic Acid in Stable Renal Transplant Recipients: An Exploratory Matched Cohort Study.

INTRODUCTION: Polymorphism ABCG2 c.421C>A (rs2231142) results in reduced activity of the important drug efflux transporter breast cancer-resistance protein (BCRP/ABCG2). One study has suggested that it may affect enterohepatic recirculation of mycophenolic acid (MPA). We evaluated the effect of rs2231142 on steady-state exposure to MPA in renal transplant recipients. METHODS: Consecutive, stable adult (age ≥ 16 years) renal transplant recipients on standard MPA-based immunosuppressant protocols (N = 68; 43 co-treated with cyclosporine, 25 with tacrolimus) underwent routine therapeutic drug monitoring after a week of initial treatment, and were genotyped for ABCG2 c.421C>A and 11 polymorphisms in genes encoding enzymes and transporters implicated in MPA pharmacokinetics. ABCG2 c.421C>A variant versus wild-type (wt) patients were matched with respect to demographic, biopharmaceutic, and genetic variables (full optimal combined with exact matching) and compared for dose-adjusted steady-state MPA pharmacokinetics [frequentist and Bayes (skeptical neutral prior) estimates of geometric means ratios, GMR]. RESULTS: Raw data (12 variant versus 56 wt patients) indicated around 40% higher total exposure (frequentist GMR = 1.45, 95% CI 1.10-1.91; Bayes = 1.38, 95% CrI 1.07-1.81) and around 30% lower total body clearance (frequentist GMR = 0.66, 0.58-0.90; Bayes = 0.71, 0.53-0.95) in variant carriers than in wt controls. The estimates were similar in matched data (11 variant versus 43 wt patients): exposure GMR = 1.41 (1.11-1.79) frequentist, 1.39 (1.15-1.81) Bayes, with 90.7% and 85.5% probability of GMR > 1.20, respectively; clearance GMR = 0.73 (0.58-0.93) frequentist, 0.71 (0.54-0.95) Bayes. Sensitivity analysis indicated low susceptibility of the estimates to unmeasured confounding. CONCLUSIONS: Loss-off-function polymorphism ABCG2 c.421C>A increases steady-state exposure to MPA in stable renal transplant patients.

Population Pharmacokinetics of Tacrolimus in Pediatric Patients With Umbilical Cord Blood Transplant.

Tacrolimus was frequently used in pediatric patients with umbilical cord blood transplant for the prevention of graft-versus-host disease. The aim of the present study was to evaluate the population pharmacokinetics of tacrolimus among pediatric patients with umbilical cord blood transplant and find potential influenced factors. A total of 275 concentrations from 13 pediatric patients were used to build a polulation pharmacokinetic model using a nonlinear mixed-effects modeling approach. The impact of demographic features, biological characteristics, and concomitant medications, including sex, age, body weight, postoperative day, white blood cell count, red blood cell count, hemoglobin, platelets, hematocrit, blood urea nitrogen, creatinine, aspartate transaminase, alanine transaminase, total bilirubin, albumin, and total protein were investigated. The pharmacokinetics of tacrolimus were best described by a 1-compartment model with first- and zero-order mixed absorption and first-order elimination. The clearance and volume of distribution of tacrolimus were 1.93 L/h and 75.1 L, respectively. A covariate analysis identified that postoperative day and co-administration with trimethoprim-sulfamethoxazole were significant covariates influencing clearance of tacrolimus. Frequent blood monitoring and dose adjustment might be needed with the prolongation of postoperative day and coadministration with trimethoprim-sulfamethoxazole.

Drug-drug interactions of immunosuppressants and other drugs in kidney post-transplant recipients

Introduction: Immunosuppressants (ISS) are the most crucial tools used in the therapeutic regimens of transplant recipients. Nevertheless, these drugs are not the only ones adopted by patients; therefore, knowing the possible drug-drug interactions (DDIs) between immunosuppressants and other drugs commonly used in kidney transplant recipients is essential to ensure the effectiveness and safety of treatments. In this way, the objective is analyzing the DDIs between the immunosuppressants and other commonly used medications on kidney transplant adult recipients with active medical records undergoing post-transplant follow-up for 4.4 years (mean). Methods: First, we performed a cross-sectional study based on patients' records, in which the patient's profile and drugs used were examined, and after we analyzed DDIs by the Micromedex Drug Interactions® database. Results: We analyzed 176 patients with a mean age of 47.6(± 12.5); most were male (67.7%), and the majority received a kidney from a deceased donor (81.4%). Patients were exposed to 15.0 (± 5.4) different medicines after the transplantation, and 7.4 (± 4.0) of these medicines were simultaneous. After analyzing the DDIs according to the severity of interaction, documentation quality interaction effect, clinical management and probable interaction mechanism, the most frequent interaction was with tacrolimus, classified as moderate, and the 3 major causes of interaction occurred with azathioprine according to the Micromedex database. The primary medicines involved with immunosuppressant interactions were proton pump inhibitors, ranitidine, domperidone, amlodipine, enalapril, allopurinol, cyclobenzaprine, amitriptyline, fluoxetine, and ciprofloxacin. These DDIs' effects were related to, mainly, increase their immunosuppressant activity. Conclusion: Although the immunosuppressants analyzed lacked many clinical DDIs significance with other medicines, the healthcare team needs to monitor their DDIs' effects to prevent and minimize side effects in transplanted recipients.

The combination of exposure to Tacrolimus, mycophenolic acid, Inosine 5'-Monophosphate Dehydrogenase activity and inhibition in the first week define early histological outcomes in renal transplant recipients.

Therapeutic drug monitoring is routine for Tacrolimus, while levels are not routinely monitored for mycophenolic acid (MPA). This study investigated the effect of early post-transplant pharmacokinetics (PK) of MPA and Tacrolimus along with the pharmacodynamics (PD) of MPA on biopsy-proven acute rejection (BPAR) after renal transplantation. A prospective PK/PD study with limited sampling (three blood samples) was conducted in renal transplant recipients on week 1, around Day 6 (n = 42) and at the 3rd-month biopsy on Day 90 (n = 23). The partial exposures (area under curve [AUC]0-3.5 h ) of both MPA and Tacrolimus obtained during the first week were more predictive of rejection (combined clinical and subclinical rejection) by Day 90 than their trough concentrations or Day 90 exposures. Patients with rejection had significantly worse renal function (eGFR) and a comparatively lower exposure to MPA during the first post-transplant week. The lower MPA exposure was also associated with sub-optimal inosine monophosphate dehydrogenase (IMPDH) inhibition in patients with rejection, and the probability of rejection was higher in the presence of an increased pre-transplant IMPDH activity. A composite of parameters, including MPA exposure and IMPDH activity was found to predict acute rejection and may be beneficial along with tacrolimus monitoring early after renal transplantation.

Cytochrome P450 oxidoreductase variant A503V contributes to the increased CYP3A5 activity with tacrolimus in vitro.

BACKGROUND: Tacrolimus is a immunosuppressant drug in transplantation with a narrow therapeutic range and high pharmacokinetic variability. Clinical studies have revealed that POR*28 contributes enhanced tacrolimus clearance in CYP3A5 expressers. However, it remains unknown that how exactly the POR polymorphism could influence the metabolism of tacrolimus via CYP3A5 in vitro. RESEARCH DESIGN & METHODS: A503V is an amino acid sequence variant encoded by POR*28. Wild-type (WT) and A503V POR, with WT CYP3A5 were expressed in recombinant HepG2 cells and reconstituted proteins. Michaelis constant (Km) and maximum velocity (Vmax) of CYP3A5 with tacrolimus as substrates were determined, and catalytic efficiency is expressed as Vmax/Km. RESULTS: Both WT and A503V POR down-regulated the CYP3A5 mRNA expression, and WT POR rather than A503V down-regulated the protein expression of CYP3A5 in recombinant HepG2 cells. Compared with WT POR, A503V increased metabolism of tacrolimus by CYP3A5 in both cellular and protein levels. CONCLUSION: A503V can affect CYP3A5-catalyzed tacrolimus metabolism in vitro, which suggests that A503V has the potential to serve as a biomarker for tacrolimus treatment in transplantation recipients.

Effect of drug combination on tacrolimus target dose in renal transplant patients with different CYP3A5 genotypes.

Various factors, including genetic polymorphisms, drug-drug interactions, and patient characteristics influence the blood concentrations of tacrolimus in renal transplant patients. In the present study, we established a population pharmacokinetic model to explore the effect of combined use of Wuzhi capsules/echinocandins and the patients' biochemical parameters such as haematocrit on blood concentrations and target doses of tacrolimus in renal transplant patients with different CYP3A5 genotypes. The aim of the study was to propose an individualised tacrolimus administration regimen for early renal transplant recipients.In this retrospective cohort study, we included 240 renal transplant recipients within 21 days of surgery (174 males and 66 females, mean age 39.4 years), who received tacrolimus alone (n = 54), in combination with Wuzhi capsules (99) or caspofungin (57) or micafungin (30). We collected demographic characteristics, clinical indicators, CYP3A5 genotypes, and 1950 steady-state concentrations of tacrolimus and included them in population pharmacokinetic model. An additional 110 renal transplant recipients and 625 steady-state concentrations of tacrolimus were included for external validation of the model. The population pharmacokinetic model was established and Monte Carlo was used to simulate probabilities for achieving the target concentration for individual tacrolimus administration.A two-compartment model of first-order absorption and elimination was developed to describe the population pharmacokinetics of tacrolimus. CYP3A5 genotypes and co-administration of Wuzhi capsules, as well as time after renal transplantation and haematocrit, were important factors affecting the clearance of tacrolimus. We found no obvious change in trend in the scatter plot of tacrolimus clearance rate vs. haematocrit. The Monte Carlo simulation indicated the following recommended doses of tacrolimus alone: 0.14 mg⋅kg-1⋅d-1 for genotype CYP3A5*1*1, 0.12 mg⋅kg-1⋅d-1 for CYP3A5*1*3, and 0.10 mg⋅kg-1⋅d-1 for CYP3A5*3*3. For patients receiving the combination with Wuzhi capsules, the recommended doses of tacrolimus were 0.10 mg⋅kg-1⋅d-1 for CYP3A5*1*1, 0.08 mg⋅kg-1⋅d-1 for CYP3A5*1*3, and 0.06 mg⋅kg-1⋅d-1 for CYP3A5*3*3 genotypes. Caspofungin or micafungin had no effect on the clearance of tacrolimus in renal transplant recipients.The population pharmacokinetics of tacrolimus in renal transplant patients was evaluated and the individual administration regimen of tacrolimus was simulated. For early kidney transplant recipients receiving tacrolimus treatment, not only body weight, but also CYP3A5 genotypes and drugs used in combination should be considered when determining the target dose of tacrolimus.

Population pharmacokinetic and dose optimization of mycophenolic acid in children with anti-neutrophilic cytoplasmic antibody-associated nephritis.

PURPOSE: Anti-neutrophilic cytoplasmic antibody (ANCA)-associated vasculitis is a rare autoimmune disease. Mycophenolic acid (MPA) is widely used for ANCA-associated nephritis (AAN) but with large pharmacokinetic variability. This study aims to investigate clinical factors impacting MPA disposition in pediatric AAN. METHODS: We retrospectively collected 391 MPA concentrations from 25 children diagnosed with AAN. A population pharmacokinetic model was developed to explore the potential effects of demographics and biochemical covariates on MPA. Monte Carlo simulations were performed to optimize dosage regimen. RESULTS: MPA pharmacokinetics best fitted a two-compartment model with first-order absorption and linear elimination. The pharmacokinetic parameters for Ka, CL/F, Vc/F, Vp/F, and Q/F were 0.45 h-1, 9.86 L/h, 19.69 L, 408.32 L, and 23.01 L/h. Dosage form significantly affected drug absorption. CL/F significantly decreased with increasing cystatin C, while decreasing with myeloperoxidase. Cystatin C was superior to serum creatinine in predicting apparent clearance of MPA. A dose regimen of 650 mg/m2 twice daily was required to achieve target exposure in children with normal renal function and no inflammation. The combined effects of myeloperoxidase concentration and renal function resulted in a sixfold range of MPA dose. CONCLUSION: This was the first study of MPA population pharmacokinetic model in children with AAN. Myeloperoxidase was not only a biomarker of AAN, but also an inflammatory factor to impact drug CL. The influence of renal function and underlying diseases on drug metabolism should be fully considered in personalized medication for AAN.

Differences in kinetics of tacrolimus concentration after letermovir discontinuation by type of concomitant azole antifungal.

Letermovir is commonly used for CMV prophylaxis after allogeneic hematopoietic cell transplantation (HCT). Pharmacokinetic studies have shown an increase in tacrolimus exposure among healthy volunteers who took letermovir. However, studies in HCT recipients are needed because these patients are typically using concomitant antifungals with different degrees of CYP3A4 inhibition that may further interact with tacrolimus pharmacokinetics. In this study, we retrospectively evaluated the kinetics of tacrolimus concentration after letermovir discontinuation by type of concomitant azole antifungal in 57 HCT recipients. The median fold change in tacrolimus concentration-to-dose (C/D) ratio after discontinuing letermovir was 0.64 (range 0.43-0.99) with fluconazole and 1.10 (range 0.59-1.73) with voriconazole (p < 0.001). The tacrolimus C/D ratio decreased ≥ 30% after discontinuing letermovir (p < 0.001) in 66% of patients on fluconazole and 9% on voriconazole. Among patients whose tacrolimus C/D ratio decreased ≥ 30%, three (9%) patients in the fluconazole group and one (4%) in the voriconazole group experienced worsening of GVHD. Careful monitoring of tacrolimus concentration is important after letermovir discontinuation to avoid worsening of GVHD due to decreased tacrolimus concentration.

Fixed-dose administration and pharmacokinetically guided adjustment of busulfan dose for patients undergoing hematopoietic stem cell transplantation: a meta-analysis and cost-effectiveness analysis.

This study aims to evaluate the efficacy, safety, and long-term cost-effectiveness of fixed-dose busulfan (Bu) administration and pharmacokinetically (PK) guided adjustment of Bu dose for patients who underwent hematopoietic stem cell transplantation. The efficacy and safety of both dosing strategies were compared using a systematic review and meta-analysis. A Markov model was used in estimating relevant cost and health outcomes from the perspective of the health system. The primary outcomes of interest were lifetime cost, quality adjusted life-years (QALYs) gained, and incremental cost-effectiveness ratio (ICER) in dollar per QALY gained. Results showed that progression-free survival and overall survival in the PK-guided group were higher than that in the fixed-dose group, and the PK-guided group was associated with low non-relapse mortality and relapse rate. In contrast to safety, the incidence of acute graft-versus-host disease (GVHD) was the same in the two groups (P > 0.05). Cost-effectiveness analysis showed that the QALY of the PK-guided group (12.8135 QALYs and $582,475.07) increased by 2.0609 relative to that in the fixed-dose group (10.7526 QALYs and $562,833.20), and the ICER was $9530.72/QALY. One-way and probability sensitivity analyses confirmed the reliability of the results. In conclusion, the PK-guided approach has higher efficacy and is safer.

Can Published Population Pharmacokinetic Models of Busulfan Be Used for Individualized Dosing in Chinese Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation? An External Evaluation.

Busulfan is a bifunctional alkylating agent that is widely used before hematopoietic stem cell transplantation (HSCT), in combination with other chemotherapeutic drugs. As of 2020, there is no population pharmacokinetic (popPK) model for busulfan in Chinese pediatric patients. A systemic external evaluation of 11 published popPK models was conducted in Chinese pediatric patients undergoing HSCT. Forty pediatric patients were enrolled in this study, with a total of 183 blood concentrations. The relative prediction error (PE%), median PE%, median absolute PE%, and percentage of PE% within ±20% and ±30% were calculated in prediction-based diagnostics. Simulation-based diagnostics were conducted through a prediction- and variability-corrected visual predictive check and the normalized prediction distribution error. The relative individual prediction error was calculated using Bayesian forecasting with 1 to 3 concentration points. The 1-compartment open linear popPK model, which was built by Su-jin Rhee et al (model H), incorporating the patient's body surface area, age, dosing day, and aspartate aminotransferase as significant covariates had preferable predictability than other popPK models. In prediction-based diagnostics, the median PE%, percentage of PE% within ±20%, and percentage of PE% within ±30% of model H were 8.48%, 45.35%, and 59.56%, respectively. The normalized prediction distribution error of model H showed that it followed the normal distribution. Based on Bayesian forecasting, model H showed good predictive performance. Thus, model H was the most appropriate model that can be used clinically for individualized dosage adjustments in Chinese pediatric HSCT patients.

Time-Dissociated Pharmacokinetic Pharmacodynamic Model of Cyclosporine Among Malaysian Renal Transplant Recipients.

BACKGROUND: Cyclosporine is an essential component of many immunosuppressive regimens. However, its pharmacokinetic and pharmacodynamic (PKPD) modeling has not been widely investigated. This study aims to develop a time-dissociated PKPD model of cyclosporine in renal transplant patients. 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.

Intrapatient Variability in Tacrolimus Trough Levels Over 2 Years Affects Long-Term Allograft Outcomes of Kidney Transplantation.

This study aimed to determine the impact of tacrolimus (TAC) trough level (C0) intrapatient variability (IPV) over a period of 2 years after kidney transplantation (KT) on allograft outcomes. In total, 1,143 patients with low immunologic risk were enrolled. The time-weighted coefficient variability (TWCV) of TAC-C0 was calculated, and patients were divided into tertile groups (T1: < 24.6%, T2: 24.6%-33.7%, T3: ≥ 33.7%) according to TAC-C0-TWCV up to post-transplant 1st year. They were classified into the low/low, low/high, high/low, and high/high groups based on a TAC-C0-TWCV value of 33.7% during post-transplant 0-1st and 1st-2nd years. The allograft outcomes among the three tertile and four TAC-C0-TWCV groups were compared. The T3 group had the highest rate of death-censored allograft loss (DCGL), and T3 was considered an independent risk factor for DCGL. The low/low group had the lowest and the high/high group had the highest risk for DCGL. Moreover, patients with a mean TAC-C0 of ≥5 ng/ml in the high/high group were at the highest risk for DCGL. Thus, TAC-IPV can significantly affect allograft outcomes even with a high mean TAC-C0. Furthermore, to improve allograft outcomes, a low TAC-IPV should be maintained even after the first year of KT.

Effect of UGT polymorphisms on pharmacokinetics and adverse reactions of mycophenolic acid in kidney transplant patients.

Mycophenolic acid (MPA) is a common immunosuppressive drug for kidney transplantation patients, and is characterized by a narrow therapeutic index and significant individual variability. UGTs are the main enzymes responsible for the metabolism of MPA. Although, many studies have focused on the relationship between UGT polymorphisms and pharmacokinetics and adverse reactions of MPA, the conclusion are controversial. We reviewed the relevant literature and summarized the significant influences of UGT polymorphisms, such as UGT1A8 (rs1042597, rs17863762), UGT1A9 (rs72551330, rs6714486, rs17868320, rs2741045, rs2741045) and UGT2B7 (rs7438135, rs7439366, rs7662029), on the pharmacokinetics of MPA and its metabolites and adverse reactions. The review provides a reference for guiding the individualized administration of MPA and reducing adverse reactions to MPA.