Body weight-based initial dosing of tacrolimus in renal transplantation: Is this an ideal approach?

Pharmacokinetic interactions between tacrolimus and Wuzhi capsule in liver transplant recipients: Genetic polymorphisms affect the drug interaction

Wuzhi capsule (WZC), a commonly used Chinese patent medicine to treat various types of liver dysfunction in China, increases the exposure of tacrolimus (TAC) in liver transplant recipients. However, this interaction has inter-individual variability, and the underlying mechanism remains unclear. Current research indicates that CYP3A4/5 and drug transporters influence the disposal of both drugs. This study aims to evaluate the association between TAC dose-adjusted trough concentration (C/D) and specific genetic polymorphisms of CYP3A4/5, drug transporters and pregnane x receptor (PXR), and plasma levels of major WZC components, deoxyschisandrin and γ-schisandrin, in liver transplant patients receiving both TAC and WZC. Liquid chromatography-tandem-mass spectrometry was used to detect the plasma levels of deoxyschisandrin and γ-schisandrin, and nine polymorphisms related to metabolic enzymes, transporters and PXR were genotyped by sequencing. A linear mixed model was utilized to assess the impact of the interaction between genetic variations and WZC components on TAC lnC/D. Our results indicate a significant association of TAC lnC/D with the plasma levels of deoxyschisandrin and γ-schisandrin. Univariate analysis demonstrated three polymorphisms in the genes ABCB1 (rs2032582), ABCC2 (rs2273697), ABCC2 (rs3740066), and PXR (rs3842689) interact with both deoxyschisandrin and γ-schisandrin, influencing the TAC lnC/D. In multiple regression model analysis, the interactions between deoxyschisandrin and both ABCB1 (rs2032582) and ABCC2 (rs3740066), post-operative day (β < 0.001, p < 0.001), proton pump inhibitor use (β = -0.152, p = 0.008), body mass index (β = 0.057, p < 0.001), and ABCC2 (rs717620, β = -0.563, p = 0.041), were identified as significant factors of TAC lnC/D, accounting for 47.89% of the inter-individual variation. In summary, this study elucidates the influence of the interaction between ABCB1 and ABCC2 polymorphisms with WZC on TAC lnC/D. These findings offer a scientific basis for their clinical interaction, potentially aiding in the individualized management of TAC therapy in liver transplant patients.

Incomplete Data and Potential Risks of Drugs in People with Obesity

PURPOSE OF REVIEW

To provide examples of knowledge gaps in current pharmaceutical treatments for people with obesity and call for changes to regulatory and pharmaceutical clinical research requirements during the drug discovery and development process.

RECENT FINDINGS

Treatment of obesity and its comorbidities often require the use of prescription drugs, many of which have not been fully evaluated in people with obesity. Despite a growing body of research on this topic, the impact of obesity on the pharmacokinetics and pharmacodynamics of drugs is often under-studied by drug sponsors and regulators, and subsequently underappreciated by clinicians and caretakers. There are currently multiple opportunities for pharmaceuticals to include dosing information specifically for patients with obesity in order to ensure safety and efficacy of drugs in this population. Additionally, there are serious gaps between what is known about the effects of obesity on drug disposition and the current use of drugs according to drug prescribing information and clinical practice. There is currently no requirement to test drugs in people with obesity during the drug approval process, even when preliminary data suggests there may be altered kinetics in this population. The lack of information on the safe and effective use of drugs in people with obesity may be contributing to poorer health outcomes in this population.

Retrospective evaluation of LCP-tacrolimus (Envarsus XR) dosing in de novo kidney transplant

INTRODUCTION

Tacrolimus is known to exhibit significant inter- and intra-patient pharmacokinetic (PK) and pharmacodynamic (PD) variability regarding therapeutic response. LCP-tacrolimus (LCPT-Envarsus XR) was approved in 2018 for use as a de novo immunosuppressive agent in kidney transplants, but there is limited evidence to guide de novo dosing of LCPT in patients with obesity. The primary objective of this study was to evaluate the impact of different calculated weight-based de novo LCPT dosing on early transplant outcomes.

METHODS

This was a retrospective study of patients with obesity (BMI ≥ 30 kg/m2 ) who received a kidney transplant at the University of Illinois Hospital and Health System (UIH), between March 2019 and March 2021. Subjects were included if were age 18 years or older and received de novo LCPT throughout index hospitalization. The primary endpoint of this study was to compare correlations between the first tacrolimus trough level and dosing weight strategy (e.g., TBW, AdjBW, IBW).

RESULTS

There was a statistically significant, though modest, correlation between all three dosing strategies and the first tacrolimus trough level (TBW correlation coefficient = .431, p < .001; AdjBW correlation coefficient = .455, p < .001; IBW correlation coefficient = .465; p < .001). In regression modeling for supratherapeutic levels each additional .01 mg/kg increase in dose by TBW, AdjBW, and IBW increased the odds of a supratherapeutic level by 1.46, 1.34, and 1.24, respectively (p < .001).

CONCLUSIONS

The use of LCPT in kidney transplant recipients with obesity dosed using TBW demonstrated the strongest correlation with initial supratherapeutic tacrolimus levels. Larger prospective studies are needed to investigate the further impact of body weight on dosing regimens in the obese population.

Compare the performance of multiple machine learning models in predicting tacrolimus concentration for infant patients with living donor liver transplantation

BACKGROUND

This study aims to establish multiple ML models and compare their performance in predicting tacrolimus concentration for infant patients who received LDLT within 3 months after transplantation.

METHODS

Retrospectively collected basic information and relevant biochemical indicators of included infant patients. CMIA was used to determine tacrolimus C₀ . PCR was used to determine the donors' and recipients' CYP3A5 genotypes. Multivariate stepwise regression analysis and stepwise elimination covariates were used for covariates selection. Thirteen machine learning algorithms were applied for the development of prediction models. APE, the ratio of the APE ≤3 ng ml^-1 and ideal rate (the proportion of the predicted value with a relative error of 30% or less) were used to evaluate the predictive performance of the model.

RESULTS

A total of 163 infant patients were included in this study. In the case of the optimal combination of covariates, the Ridge model had the lowest APE, 2.01 (0.85, 3.35 ng ml^-1 ). The highest ratio of the APE ≤3 ng ml^-1 was the LAR model (71.77%). And the Ridge model showed the highest ideal rate (55.05%). For the Ridge model, GRWR was the most important predictor.

CONCLUSIONS

Compared with other ML models, the Ridge model had good predictive performance and potential clinical application.

Influential Factors and Efficacy Analysis of Tacrolimus Concentration After Allogeneic Hematopoietic Stem Cell Transplantation in Children with β-Thalassemia Major

Purpose

To analyze factors influencing tacrolimus (TAC) trough concentration (C₀) in β-thalassemia major (β-TM) pediatric patients after allogeneic hematopoietic stem cell transplantation (Allo-HSCT) and to investigate the effects of genotype polymorphism and drug-drug interactions on TAC trough concentration in children with β-TM. Furthermore, to analyze the correlation between TAC C₀ and efficacy and adverse reactions.

Patients and Methods

Prospectively collection of demographic information and details of combined treatment of patients with β-TM receiving HSCT, and genotypes of CYP3A4, CYP3A5, and ABCB1 (rs1045642, rs1128503, rs2032582) were obtained for each patient. Univariate analysis and multiple linear regression analysis were used to investigate influencing factors on TAC C₀. The impact of different genotypes and the co-administration of azole antifungal drugs on β-TM patients receiving TAC were evaluated, together with the correlation between acute graft-versus-host disease (aGVHD), infection, and liver injury of TAC C₀.

Results

A total of 46 patients with 587 concentration data were included. The multiple linear regression results showed that the patient's sex, weight, postoperative time, hemoglobin, platelet count, serum cystatin C, and combined voriconazole were independent influencing factors of the infusion trough concentration/daily dose, C₀/D_iv. Age, body surface area, postoperative time, co-administration of voriconazole, and CYP3A4*18B are independent influencing factors of C₀/D_po. Group comparisons showed that voriconazole can affect TAC C₀ administered intravenously (IV) and orally in β-TM pediatric patients, while patient genotype can affect TAC C₀ during oral administration. TAC C₀ does not correlate with aGVHD or liver injury, but infection may be associated with TAC C₀.

Conclusion

The concentration of TAC should be closely monitored when co-administered with voriconazole. It is worth considering that the influence of genotype on the trough concentration of oral TAC and individualized drug administration warrant investigation. Finally, this study indicated that C₀ is not suitable as an indicator of the efficacy of TAC.