Clinical Pharmacokinetics and Impact of Hematocrit on Monitoring and Dosing of Tacrolimus Early After Heart and Lung Transplantation

Long short-term memory algorithm for personalized tacrolimus dosing: A simple and effective time series forecasting approach post-lung transplantation

BACKGROUND

Management of tacrolimus trough levels (TTLs) influences morbidity and mortality after lung transplantation. Several studies have explored pharmacokinetic and artificial intelligence models to monitor tacrolimus levels. However, many models depend on a wide range of variables, some of which, like genetic polymorphisms, are not commonly tested for in regular clinical practice. This study aimed to verify the efficacy of a novel approach simply utilizing time series data of tacrolimus dosing, with the objective of accurately predicting trough levels in a variety of clinical settings.

METHODS

Data encompassing 36 clinical variables for each patient were gathered, and a multivariate long short-term memory algorithm was applied to forecast subsequent TTLs based on the selected clinical variables. The tool was developed using a dataset of 87,112 data points from 117 patients, and its efficacy was confirmed using 6 additional cases.

RESULTS

Shapley additive explanations revealed a significant correlation between trough levels and prior dose-concentration data. By using simple trend learning of dose, administration route, and previous trough levels of tacrolimus, we could predict values within 30% of the actual values for 88.5% of time points, which facilitated the creation of a tool for simulating TTLs in response to dosage adjustments. The tool exhibited the potential for rectifying clinical misjudgments in a simulation cohort.

CONCLUSIONS

Utilizing our time series forecasting tool, precise prediction of trough levels is attainable independently of other clinical variables through the analysis of historical tacrolimus dose-concentration trends alone.

Examining Whole Blood, Total and Free Plasma Tacrolimus in Elderly Kidney Transplant Recipients

BACKGROUND

Therapeutic monitoring is routinely performed to ensure tacrolimus whole-blood concentrations fall within a predefined target. Despite this, patients still experience inefficacy and toxicity that could be related to variability in free (unbound) tacrolimus exposure. Therefore, the aim of this study was to compare tacrolimus-free plasma (C u ), total plasma (C p ), and whole-blood (C wb ) concentrations in adult kidney transplant recipients and to characterize tacrolimus disposition across different matrices.

METHODS

Twelve-hour concentration-time profiling was performed in 15 recipients, allowing simultaneous measurement of C u , C p , and C wb . Pharmacokinetic parameters were estimated using noncompartmental analysis. The relationship between C wb and C p were examined using a capacity-limited binding model, incorporating the hematocrit fraction ( fHCT ) to estimate maximum binding concentration ( Bmax ) and dissociation constant ( Kd ). The relationship between C p and C u was evaluated using a linear binding model to estimate the nonspecific binding parameter ( Nplasma ). Nonlinear regression analysis was used to obtain estimates of Bmax , Kd , and Nplasma .

RESULTS

A total of 195 paired C wb , C p , and C u values were collected. The median ratios of C wb :C p , C p :C u , and C wb :C u were 9:1, 20:1, and 138:1, respectively. Variability in free plasma exposure was large; free trough values ranged from 8 to 51 ng/L and free area-under-the-concentration-time-curve values ranged from 424 to 7160 ng·h/L. Median (range) estimates of Bmax , Kd , and Nplasma were 90.4 µg/L (22.4-752.5 µg/L), 2.36 µg/L (0-69.2 µg/L), and 0.05 (0.035-0.085), respectively. The interindividual variability (CV%) in binding parameters was considerable ( Bmax 117.2%; Nplasma 32.5%).

CONCLUSIONS

Large variability was observed in tacrolimus-free plasma exposure and binding parameters. Future research to characterize the relationship between tacrolimus C u and patient outcomes may be of benefit.

A validated UPLC-MS/MS method for the quantification of immunosuppressive drugs in peripheral blood mononuclear cells using liquid-liquid extraction with low temperature purification without complex pretreatment steps

Immunosuppressive drugs (ISDs) are given to avoid the allograft rejection after transplantation. The concentrations of ISDs should be closely monitored owing to their wide inter-individual variability in its pharmacokinetics and narrow therapeutic window. Currently, the whole blood concentration measurement is the major approach of therapeutic drug monitoring of clinical ISDs in organ transplantation. Its correlation with the efficacy of ISDs remains elusive. While the acute rejection after transplantation may occur even when whole-blood ISDs concentrations are within the target range. Since the site of action of ISDs are within the lymphocyte, direct measurement of drug exposure in target cells may more accurately reflect the clinical efficacy of ISDs. Although several methods have been developed for the peripheral blood mononuclear cells (PBMCs) extraction and drug concentration measurement, the complex pre-processing has limited the study of the relationship between intracellular ISDs concentrations and the occurrence of rejection. In this study, the extraction of ISDs in PBMCs was carried out by the liquid-liquid extraction with low temperature purification, without centrifugation. The lower limit of quantitation were 0.2 ng/mL for cyclosporine A, tacrolimus and sirolimus, 1.0 ng/mL for mycophenolic acid, and the within-run and between-run coefficient of variations were both less than 12.4 %. The calibration curves of mycophenolic acid had a linear range (ng/mL): 1.0-128.0 (r2 = 0.9992). The calibration curves of other three ISDs had a linear range (ng/mL): 0.2-20.48 (r2 > 0.9956). A total of 157 clinical samples were analyzed by the UPLC-MS/MS for ISDs concentration in blood or plasma ([ISD]blood or plasma) and the concentration within PBMCs ([ISD]PBMC). Although there was strong association between [ISD]PBMC and [ISD]blood or plasma, the large discrepancies between concentration within [ISD]blood or plasma and [ISD]PBMC were observed in a small proportion of clinical samples. The developed method with short analysis time and little amounts of blood sample can be successfully applied to therapeutic drug monitoring of ISDs in PBMCs for analysis of large numbers of clinical samples and is helpful to explore the clinical value of ISDs concentration in PBMCs.

Tacrolimus Variability and Clinical Outcomes in the Early Post-lung Transplantation Period: Oral Versus Continuous Intravenous Administration

BACKGROUND AND OBJECTIVE

High variability in tacrolimus pharmacokinetics directly after lung transplantation (LuTx) may increase the risk for acute kidney injury (AKI) and transplant rejection. The primary objective was to compare pharmacokinetic variability in patients receiving tacrolimus orally versus intravenously early after LuTx.

METHODS

Pharmacokinetic and clinical data from 522 LuTx patients transplanted between 2010 and 2020 in two university hospitals were collected to compare orally administered tacrolimus to intravenous tacrolimus early post-transplantation. Tacrolimus blood concentration variability, measured as intrapatient variability (IPV%) and  percentage of time within the therapeutic range (TTR%), was analyzed within the first 14 days after LuTx. Secondary outcomes were AKI, acute rejection, length of stay in the intensive care unit (ICU), and mortality in the ICU and during hospital admission.

RESULTS

We included 224 patients in the oral and 298 in the intravenous group. The mean adjusted IPV% was 10.8% (95% confidence interval [CI] 6.9-14.6; p < 0.001) higher in the oral group (27.2%) than the intravenous group (16.4%). The mean TTR% was 7.3% (95% CI - 11.3 to - 3.4; p < 0.001) lower in the oral group (39.6%) than in the intravenous group (46.9%). The incidence of AKI was 46.0% for oral and 42.6% for intravenous administration (adjusted odds ratio [OR] 1.2; 95% CI 0.8-1.8; p = 0.451). The frequencies of clinically diagnosed acute rejection in the oral and intravenous groups were nonsignificant (24.6% vs 17.8%; OR 1.5 [95% CI 1.0-2.3; p = 0.059]). ICU and hospital mortality rate and ICU length of stay were similar.

CONCLUSIONS

Administering tacrolimus orally directly after LuTx leads to a higher variability in blood concentrations compared to intravenous administration. There was no difference in the occurrence of AKI or transplant rejection.

Effects of CYP3A5 Genotype on Tacrolimus Pharmacokinetics and Graft-versus-Host Disease Incidence in Allogeneic Hematopoietic Stem Cell Transplantation

Tacrolimus (Tac) is pivotal in preventing acute graft-versus-host disease (GVHD) after allogeneic hematopoietic stem cell transplantation (alloHSCT). It has been reported that genetic factors, including CYP3A5*3 and CYP3A4*22 polymorphisms, have an impact on Tac metabolism, dose requirement, and response to Tac. There is limited information regarding this topic in alloHSCT. The CYP3A5 genotype and a low Tac trough concentration/dose ratio (Tac C0/D ratio) can be used to identify fast metabolizers and predict the required Tac dose to achieve target concentrations earlier. We examined 62 Caucasian alloHSCT recipients with a fast metabolizer phenotype (C0/dose ratio ≤ 1.5 ng/mL/mg), assessing CYP3A5 genotypes and acute GVHD incidence. Forty-nine patients (79%) were poor metabolizers (2 copies of the variant *3 allele) and 13 (21%) were CYP3A5 expressers (CYP3A5*1/*1 or CYP3A5*1/*3 genotypes). CYP3A5 expressers had lower C0 at 48 h (3.7 vs. 6.2 ng/mL, p = 0.03) and at 7 days (8.6 vs. 11.4 ng/mL, p = 0.04) after Tac initiation, tended to take longer to reach Tac therapeutic range (11.8 vs. 8.9 days, p = 0.16), and had higher incidence of both global (92.3% vs. 38.8%, p < 0.001) and grade II-IV acute GVHD (61.5% vs. 24.5%, p = 0.008). These results support the adoption of preemptive pharmacogenetic testing to better predict individual Tac initial dose, helping to achieve the therapeutic range and reducing the risk of acute GVHD earlier.

Emerging therapeutic drug monitoring technologies: considerations and opportunities in precision medicine

In recent years, the development of sensor and wearable technologies have led to their increased adoption in clinical and health monitoring settings. One area that is in early, but promising, stages of development is the use of biosensors for therapeutic drug monitoring (TDM). Traditionally, TDM could only be performed in certified laboratories and was used in specific scenarios to optimize drug dosage based on measurement of plasma/blood drug concentrations. Although TDM has been typically pursued in settings involving medications that are challenging to manage, the basic approach is useful for characterizing drug activity. TDM is based on the idea that there is likely a clear relationship between plasma/blood drug concentration (or concentration in other matrices) and clinical efficacy. However, these relationships may vary across individuals and may be affected by genetic factors, comorbidities, lifestyle, and diet. TDM technologies will be valuable for enabling precision medicine strategies to determine the clinical efficacy of drugs in individuals, as well as optimizing personalized dosing, especially since therapeutic windows may vary inter-individually. In this mini-review, we discuss emerging TDM technologies and their applications, and factors that influence TDM including drug interactions, polypharmacy, and supplement use. We also discuss how using TDM within single subject (N-of-1) and aggregated N-of-1 clinical trial designs provides opportunities to better capture drug response and activity at the individual level. Individualized TDM solutions have the potential to help optimize treatment selection and dosing regimens so that the right drug and right dose may be matched to the right person and in the right context.

Intracellular tacrolimus concentration correlates with impaired renal function through regulation of the IS-AHR-ABC transporter in peripheral blood mononuclear cells

BACKGROUNDS

Tacrolimus (TAC) concentration in peripheral blood mononuclear cells (PBMCs) is regarded as a better predictor of its immunosuppressive effect than the TAC concentration in whole blood. However, whether the exposure of TAC in PBMCs or WB was altered in post-transplant recipients with renal impairment remains unclear.

METHODS

We investigated the relationship of trough TAC concentration in WB and PBMCs with renal functions in post-transplant recipients. The pharmacokinetic profiles of TAC in PBMCs and WB in the two chronic kidney disease (CKD) rat models were examined using UPLC-MS/MS. Western blotting and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) were used to analyze the expression of proteins and mRNAs related to TAC metabolism and transport, respectively. In addition, the effects of uremic toxins on human PBMCs were investigated using whole-transcriptome sequencing (RNA sequencing [RNA-seq]).

RESULTS

We observed a decrease in the trough TAC concentration in PBMCs in the recipients with estimated glomerular filtration rate (eGFR) < 90 mL/min, compared with those of recipients with eGFR > 90 mL/min, but there was no difference in blood based on TAC concentrations (C0Blood). In a 150-patient post-transplant cohort, no significant relationship was observed between PBMCs and WB concentrations of TAC, and the eGFR value was correlated with TAC C0PBMCs but not with TAC C0Blood. In two CKD rat models, the TAC pharmacokinetic profile in the PBMCs was significantly lower than that in the control group; however, the blood TAC pharmacokinetic profiles in the two groups were similar. Transcriptome results showed that co-incubation of human PBMCs with uremic toxins upregulated the expression of AHR, ABCB1, and ABCC2. Compared to control rats, plasma IS increased by 1.93- and 2.26-fold and the expression of AHR, P-gp, and MRP2 in PBMCs was higher in AD and 5/6 nephrectomy (NX) rats, without modifying the expression of other proteins related to TAC exposure.

CONCLUSION

The pharmacokinetics of TAC in PBMCs changed with a decline in renal function. Uremic toxins accumulate during renal insufficiency, which activates AHR, upregulates the expression of P-gp and MRP2, and affects their intracellular concentrations. Our findings suggest that monitoring TAC concentrations in PBMCs is more important than monitoring WB concentrations in post-transplant recipients with renal impairment.

A Physiologically Based Pharmacokinetic Approach to Recommend an Individual Dose of Tacrolimus in Adult Heart Transplant Recipients

Tacrolimus is the principal immunosuppressive drug which is administered after heart transplantation. Managing tacrolimus therapy is challenging due to a narrow therapeutic index and wide pharmacokinetic (PK) variability. We aimed to establish a physiologically based pharmacokinetic (PBPK) model of tacrolimus in adult heart transplant recipients to optimize dose regimens in clinical practice. A 15-compartment full-PBPK model (Simbiology® Simulator, version 5.8.2) was developed using clinical observations from 115 heart transplant recipients. This study detected 20 genotypes associated with tacrolimus metabolism. CYP3A5*3 (rs776746), CYP3A4*18B (rs2242480), and IL-10 G-1082A (rs1800896) were identified as significant genetic covariates in tacrolimus pharmacokinetics. The PBPK model was evaluated using goodness-of-fit (GOF) and external evaluation. The predicted peak blood concentration (Cmax) and area under the drug concentration-time curve (AUC) were all within a two-fold value of the observations (fold error of 0.68-1.22 for Cmax and 0.72-1.16 for AUC). The patients with the CYP3A5*3/*3 genotype had a 1.60-fold increase in predicted AUC compared to the patients with the CYP3A5*1 allele, and the ratio of the AUC with voriconazole to alone was 5.80 when using the PBPK model. Based on the simulation results, the tacrolimus dosing regimen after heart transplantation was optimized. This is the first PBPK model used to predict the PK of tacrolimus in adult heart transplant recipients, and it can serve as a starting point for research on immunosuppressive drug therapy in heart transplant patients.

Population Pharmacokinetic Analysis for Model-Based Therapeutic Drug Monitoring of Tacrolimus in Chinese Han Heart Transplant Patients

BACKGROUND AND OBJECTIVE

Tacrolimus has become the first-line immunosuppressant for preventing rejection after heart transplantation. The present study aimed to investigate genetic variants and clinical factors affecting the variability of tacrolimus in Chinese Han heart transplant patients using a population pharmacokinetic approach.

METHODS

The retrospective study included 53 hospitalized patients with 547 tacrolimus concentrations for analysis. Nonlinear mixed-effects modeling was used to develop the population pharmacokinetics model for tacrolimus in patients with heart transplants, followed by Monte Carlo simulations to design initial dosing regimens.

RESULTS

In our study, the mutation rate of CYP3A4*18B (C>T) was 27.36%. An oral one-compartment model with first-order absorption and elimination was used to describe the pharmacokinetics of tacrolimus in heart transplant patients. In the final model, the estimated apparent clearance (CL/F) and volume of distribution (V/F) were 532.5 L/h [12.20% interindividual variability, IIV] and 16.87 L (23.16% IIV), respectively. Albumin, postoperative time, and rs2242480 (CYP3A4*18B) gene polymorphisms were the significant covariates affecting CL/F, and creatinine clearance had significant effects on the V/F.

CONCLUSION

The population pharmacokinetic model of tacrolimus in heart transplant patients can better estimate the population and individual pharmacokinetic parameters of patients and can provide a reference for the design of individualized dosing regimens.

Prediction of tacrolimus and Wuzhi tablet pharmacokinetic interaction magnitude in renal transplant recipients

AIM

Wuzhi tablets are a dose-sparing agent for tacrolimus (TAC) in China and increase the bioavailability of TAC. The current study aimed to evaluate the pharmacokinetic interaction magnitude of Wuzhi and TAC and explore the potential determinants of this interaction.

METHODS

This study performed a retrospective, self-controlled study of 138 renal transplant recipients who were co-administered TAC and Wuzhi. The trough concentration (C0) of TAC at baseline and 3, 7, 14 and 21 days after Wuzhi co-therapy initiation was measured, and the CYP3A5 polymorphism was genotyped. The corresponding clinical factors were recorded. The ratio of dose-adjusted C0 (C0/D) post- and pre-combination therapy (ΔC0/D) indicates the interaction magnitude. Univariate and multivariate analyses were used to identify determinants and establish the prediction model.

RESULTS

ΔC0/D reached a steady state within 14 days. The geometrical mean ΔC0/D was 2.91 (range 1.02-9.49, IQR 2.13-3.80). ΔC0/D was blunted in CYP3A5 expressers (estimated effect: -39.8%, P = .001) and affected by hematocrit (Hct) (+24.0% per 10% increase, P = .005) and baseline C0/D (-31.9% per 1 ng·ml^-1 ·mg^-1 increase, P < .001). The prediction model was ΔC0/D = .319baseline C0/D × 1.398CYP3A5 (expressers = 0/non-expressers = 1) × 1.024Hct × 1.744, and it explained 28.1% of the variability.

CONCLUSION

Our study is the first attempt to date to give an assessment of the magnitude of pharmacokinetic interaction between TAC and Wuzhi in a cohort of renal transplant recipients, and CYP3A5 genotypes, baseline C0/D and Hct were identified as determinants of this interaction.

The impact of cytochrome P450 3A5 genotype on early tacrolimus metabolism and clinical outcomes in lung transplant recipients

Background Tacrolimus (Tac) is the cornerstone of immunosuppressant therapy after lung transplantation (LTx). It shows great inter-individual variability in pharmacokinetics, which could partly be explained by pharmacogenetic factors. Aim We aim to investigate the influence of cytochrome P450 3A5 (CYP3A5) genotypes on early post-LTx Tac metabolism and whether it is affected by concomitant use of azole antifungals. Also, we explored the association between CYP3A5 genotype and clinical outcomes. Method 90 recipients who underwent LTx from 2017 to 2019 were enrolled in the study. The effect of CYP3A5 genotype on Tac metabolism and interaction with azole antifungals were assessed during week 1-4 after transplantation. Associations between CYP3A5 genotype and the incidence of acute kidney injury (AKI), length of hospital stay and mortality were analyzed. ResultsCYP3A5*1 carriers had lower dose adjusted concentration (C/D) than CYP3A5*3/*3 group at all time points (p < 0.05). The dose ratio of CYP3A5*1 carriers to CYP3A5*3/*3 was between 1.3 and 2.4 when comparable concentrations were reached. Use of azole antifungals did not blunt the effect of CYP3A5 genotypes on Tac metabolism. Logistic regression showed Tac concentration ≥ 7.5 ng/mL at week 1 was associated with higher incidence of AKI. No statistically significant difference was found between CYP3A5 genotypes and the length of hospital stay. Kaplan-Meier analysis showed no statistically significant difference between 30-day or 1-year mortality and CYP3A5 genotype. Conclusion CYP3A5 genotype could affect Tac metabolism early after LTx. However, it had no influence on the incidence of AKI, length of hospital stay and mortality.

Variability of Tacrolimus Trough Concentration in Liver Transplant Patients: Which Role of Inflammation?

Tacrolimus presents high intra and inter-individual variability in its blood trough concentration (Cmin). Knowledge of the factors that are involved in tacrolimus Cmin variability is thus clinically important to prevent or limit it. Inflammation can affect the pharmacokinetic properties of drugs. We evaluated the contribution of acute inflammation in the pharmacokinetic variability of tacrolimus blood Cmin in a large cohort of liver transplant patients. Demographic, biological, and clinical data from 248 liver transplant patients treated with tacrolimus from January 2010 to December 2016 were retrospectively collected from medical records. In total, 1573 Cmin/dose and concomitant C-reactive protein (CRP) measurements were analysed. In multivariate analysis, the log Cmin/dose of tacrolimus was significantly and positively associated with the hematocrit, ALAT, and CRP concentrations. CRP concentrations were higher (p = 0.003) for patients with tacrolimus overexposure (i.e., tacrolimus Cmin > 15 µg/L) (median CRP (10th–90th percentiles): 27 mg/L (3–149 mg/L), n = 91) than they were for patients with a tacrolimus Cmin ≤ 15 µg/L (13 mg/mL (3–95 mg/L), n = 1482)). CRP in the fourth quartile (49 to 334 mg/L) was associated with a 2.6-fold increased risk of tacrolimus Cmin overexposure. Our study provides evidence that inflammation contributes to tacrolimus Cmin variability and suggests that inflammation should be considered for the correct interpretation of tacrolimus blood concentration.

Factors Affecting Time-Varying Clearance of Cyclosporine in Adult Renal Transplant Recipients: A Population Pharmacokinetic Perspective

AIM

The pharmacokinetic (PK) properties of cyclosporine (CsA) in renal transplant recipients are patient- and time-dependent. Knowledge of this time-related variability is necessary to maintain or achieve CsA target exposure. Here, we aimed to identify factors explaining variabilities in CsA PK properties and characterize time-varying clearance (CL/F) by performing a comprehensive analysis of CsA PK factors using population PK (popPK) modeling of long-term follow-up data from our institution.

METHODS

In total, 3674 whole-blood CsA concentrations from 183 patients who underwent initial renal transplantation were analyzed using nonlinear mixed-effects modeling. The effects of potential covariates were selected according to a previous study and well-accepted theoretical mechanisms. Model-informed individualized therapeutic regimens were also evaluated.

RESULTS

A two-compartment model adequately described the data and the estimated mean CsA CL/F was 32.6 L h^-1 (relative standard error: 5%). Allometrically scaled body size, hematocrit (HCT) level, CGC haplotype carrier status, and postoperative time may contribute to CsA PK variability. The CsA bioavailability in patients receiving a prednisolone dose (PD) of 80 mg was 20.6% lower than that in patients receiving 20 mg. A significant decrease (52.6%) in CL/F was observed as the HCT increased from 10.5% to 60.5%. The CL/F of the non-CGC haplotype carrier was 14.4% lower than that of the CGC haplotype carrier at 3 months post operation.

CONCLUSIONS

By monitoring body size, HCT, PD, and CGC haplotype, changes in CsA CL/F over time could be predicted. Such information could be used to optimize CsA therapy. CsA dose adjustments should be considered in different postoperative periods.

Case Report: Low Hematocrit Leading to Tacrolimus Toxicity

Tacrolimus is a calcineurin inhibitor characterized by a narrow therapeutic index and high intra- and inter-individual pharmacokinetic variability. Therapeutic drug monitoring in whole-blood is the standard monitoring procedure. However, tacrolimus extensively binds to erythrocytes, and tacrolimus whole-blood distribution and whole-blood trough concentrations are strongly affected by hematocrit. High whole-blood tacrolimus concentrations at low hematocrit may result in high unbound plasma concentrations and increased toxicity. We present the case of a 16-year-old girl with kidney and liver transplant in whom low concentrations of tacrolimus in the context of low hematocrit led to significant increase in the dosage of tacrolimus and participate, along with a genetic polymorphism of ABCB1, in nephrotoxicity.

Functional CYP3A variants affecting tacrolimus trough blood concentrations in Chinese renal transplant recipients

The aim of this study was to identify novel genetic variants affecting tacrolimus trough blood concentrations. We analyzed the association between 58 single nucleotide polymorphisms (SNPs) across the CYP3A gene cluster and the log-transformed tacrolimus concentration/dose ratio (log (C₀/D)) in 819 renal transplant recipients (Discovery cohort). Multivariate linear regression was used to test for associations between tacrolimus log (C₀/D) and clinical factors. Luciferase reporter gene assays were used to evaluate the functions of select SNPs. Associations of putative functional SNPs with log (C₀/D) were further tested in 631 renal transplant recipients (Replication cohort). Nine SNPs were significantly associated with tacrolimus log (C₀/D) after adjustment for CYP3A5*3 and clinical factors. Dual luciferase reporter assays indicated that the rs4646450 G allele and rs3823812 T allele were significantly associated with increased normalized luciferase activity ratios (p < 0.01). Moreover, CYP3A7*2 was associated with higher TAC log(C₀/D) in the group of CYP3A5 expressers. Age, serum creatinine and hematocrit were significantly associated with tacrolimus log (C₀/D). CYP3A7*2, rs4646450, and rs3823812 are proposed as functional SNPs affecting tacrolimus trough blood concentrations in Chinese renal transplant recipients. Clinical factors also significantly affect tacrolimus metabolism.

Model-Informed Precision Dosing of Everolimus: External Validation in Adult Renal Transplant Recipients

BACKGROUND AND OBJECTIVE

The immunosuppressant everolimus is increasingly applied in renal transplantation. Its extensive pharmacokinetic variability necessitates therapeutic drug monitoring, typically based on whole-blood trough concentrations (C₀). Unfortunately, therapeutic drug monitoring target attainment rates are often unsatisfactory and patients with on-target exposure may still develop organ rejection. As everolimus displays erythrocyte partitioning, haematocrit-normalised whole-blood exposure has been suggested as a more informative therapeutic drug monitoring marker. Furthermore, model-informed precision dosing has introduced options for more sophisticated dose adaptation. We have previously developed a mechanistic population pharmacokinetic model, which described everolimus plasma pharmacokinetics and enabled estimation of haematocrit-normalised whole-blood exposure. Here, we externally evaluated this model for its utility for model-informed precision dosing.

METHODS

The retrospective dataset included 4123 pharmacokinetic observations from routine clinical therapeutic drug monitoring in 173 renal transplant recipients. Model appropriateness was confirmed with a visual predictive check. A fit-for-purpose analysis was conducted to evaluate whether the model accurately and precisely predicted a future C₀ or area under the concentration-time curve (AUC) from prior pharmacokinetic observations. Bias and imprecision were expressed as the mean percentage prediction error (MPPE) and mean absolute percentage prediction error (MAPE), stratified on 6 months post-transplant. Additionally, we compared dose adaptation recommendations of conventional C₀-based therapeutic drug monitoring and C₀- or AUC-based model-informed precision dosing, and assessed the percentage of differences between observed and haematocrit-normalised C₀ (∆C₀) and AUC (∆AUC) exceeding ± 20%.

RESULTS

The model showed adequate accuracy and precision for C₀ and AUC prediction at ≤ 6 months (MPPE_C0: 8.1 ± 2.5%, MAPE_C0: 26.8 ± 2.1%; MPPE_AUC: - 9.7 ± 5.1%, MAPE_AUC: 13.3 ± 3.9%) and > 6 months post-transplant (MPPE_C0: 4.7 ± 2.0%, MAPE_C0: 25.4 ± 1.4%; MPPE_AUC: - 0.13 ± 4.8%, MAPE_AUC: 13.3 ± 2.8%). On average, dose adaptation recommendations derived from C₀-based and AUC-based model-informed precision dosing were 2.91 ± 0.01% and 13.7 ± 0.18% lower than for conventional C₀-based therapeutic drug monitoring at ≤ 6 months, and 0.93 ± 0.01% and 3.14 ± 0.04% lower at > 6 months post-transplant. The ∆C₀ and ∆AUC exceeded ± 20% on 13.6% and 14.3% of occasions, respectively.

CONCLUSIONS

We demonstrated that our population pharmacokinetic model was able to accurately and precisely predict future everolimus exposure from prior pharmacokinetic measurements. In addition, we illustrated the potential added value of performing everolimus therapeutic drug monitoring with haematocrit-normalised whole-blood concentrations. Our results provide reassurance to implement this methodology in clinical practice for further evaluation.

Tacrolimus and Mycophenolic Acid Blood Concentration and Cellular Rejection After Heart Transplantation in First Endomyocardial Biopsy

BACKGROUND

Tacrolimus and mycophenolic acid (MPA) are the most important immunosuppressive drugs in modern heart transplantation. The pharmacokinetics of tacrolimus are best described by a 2-compartment model. MPA has very variable pharmacokinetics. The aim of this research was to compare kinetics of the immunosuppressants' blood levels in a group of patients with and without graft rejection.

MATERIALS AND METHODS

The study was a retrospective analysis of 39 consecutive adult orthotopic heart transplantations (OHT): 10 (9 men and 1 woman) in group R had graft rejection (ISHLT >2) in the first biopsy and 29 (22 men and 7 women) in group C were without rejection. Ischemic cardiomyopathy occurred in 2 of 7 and nonischemic cardiomyopathy in 8 of 22 (group R and group C, respectively).

RESULTS

Patients did not differ between groups except diabetes, which occurred more often in group R. Immunosuppressive drug levels were: group R and group C, respectively, 2.13 ± 0.49 and 2.11 ± 0.72 μg/mL; P = .93 for mycophenolate mofetil (MMF) and 9.42 ± 1.76 and 9.63 ± 2.30 ng/mL; P = .75 for tacrolimus. ICU stay was 14 ± 11 vs 15 ± 15 days; P = .76. There were 2 of 6 primary graft failures, 1 of 1 neurologic complications, and 0 of 6 reoperations (P < .05) in group R and group C, respectively. One patient died from group C in 30 days. During the hospital stay the incidence of graft rejection was diagnosed in 20 patients (16men and 4 women) (ISHLT >2 in endomyocardial biopsy) in the study population.

CONCLUSIONS

Monitoring of tacrolimus concentration in the early post--heart transplant period does not identify patients with rejection in the authors' study. Monitoring concentration of MMF does not identify patients with rejection. Further investigation is needed to evaluate factors responsible for post--heart transplant rejection in the early phase.