Modelling changes in the pharmacokinetics of tacrolimus during pregnancy after kidney transplantation: A retrospective cohort study.

AIMS: Pregnancy after kidney transplantation is realistic but immunosuppressants should be continued to prevent rejection. Tacrolimus is safe during pregnancy and is routinely dosed based on whole-blood predose concentrations. However, maintaining these concentrations is complicated as physiological changes during pregnancy affect tacrolimus pharmacokinetics. The aim of this study was to describe tacrolimus pharmacokinetics throughout pregnancy and explain the changes by investigating covariates in a population pharmacokinetic model. METHODS: Data of pregnant women using a twice-daily tacrolimus formulation following kidney transplantation were retrospectively collected from 6 months before conception, throughout gestation and up to 6 months postpartum. Pharmacokinetic analysis was performed using nonlinear mixed effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. The final model was evaluated using goodness-of-fit plots, visual predictive checks and a bootstrap analysis. RESULTS: A total of 260 whole-blood tacrolimus predose concentrations from 14 pregnant kidney transplant recipients were included. Clearance increased during pregnancy from 34.5 to 41.7 L/h, by 15, 19 and 21% in the first, second and third trimester, respectively, compared to prior to pregnancy. This indicates a required increase in the tacrolimus dose by the same percentage to maintain the prepregnancy concentration. Haematocrit and gestational age were negatively correlated with tacrolimus clearance (P ≤ 0.01), explaining 18% of interindividual and 85% of interoccasion variability in oral clearance. CONCLUSIONS: Tacrolimus clearance increases during pregnancy, resulting in decreased exposure to tacrolimus, which is explained by gestational age and haematocrit. To maintain prepregnancy target whole-blood tacrolimus predose concentrations during pregnancy, increasing the dose is required.

A Population Pharmacokinetic Model to Predict the Individual Starting Dose of Tacrolimus for Tunisian Adults after Renal Transplantation.

BACKGROUND: Tacrolimus is the most frequently used immunosuppressive drug for preventing renal rejection. However, its use is hampered by its narrow therapeutic index and large intra and interpatient variability in pharmacokinetics. The objective of this study was to externally validate a tacrolimus population pharmacokinetic model developed for the Dutch population and adjust the model for the Tunisian population for use in predicting the starting dose requirement after kidney transplantation. METHODS: Data on tacrolimus exposure were obtained from kidney transplant recipients (KTRs) during the first 3 months post-transplantation. External validation of the Dutch model and its adjustment for the Tunisian population was performed using nonlinear mixed-effects modeling. RESULTS: In total, 1901 whole-blood predose tacrolimus concentrations from 196 adult KTRs were analyzed. According to a visual predictive check, the Dutch model underestimated the starting dose for the Tunisian adult population. The effects of age, together with the CYP3A5*3 and CYP3A4*22 genotypes on tacrolimus clearance were significantly different in the Tunisian population than in the Dutch population. Based on a bodyweight-based dosing, only 21.9% of tacrolimus concentrations were within the target range, whereas this was estimated to be 54.0% with the newly developed model-based dosing. After adjustment, the model was successfully validated internally in a Tunisian population. CONCLUSIONS: A starting-dose population pharmacokinetic model of tacrolimus for Tunisian KTRs was developed based on a previously published Dutch model. Using this starting dose could potentially increase the percentage of patients achieving target tacrolimus concentrations after the initial starting dose.

Individualized dosing algorithms for tacrolimus in kidney transplant recipients: current status and unmet needs.

INTRODUCTION: Tacrolimus is a potent immunosuppressive drug with many side effects including nephrotoxicity and post-transplant diabetes mellitus. To limit its toxicity, therapeutic drug monitoring (TDM) is performed. However, tacrolimus' pharmacokinetics are highly variable within and between individuals, which complicates their clinical management. Despite TDM, many kidney transplant recipients will experience under- or overexposure to tacrolimus. Therefore, dosing algorithms have been developed to limit the time a patient is exposed to off-target concentrations. AREAS COVERED: Tacrolimus starting dose algorithms and models for follow-up doses developed and/or tested since 2015, encompassing both adult and pediatric populations. Literature was searched in different databases, i.e. Embase, PubMed, Web of Science, Cochrane Register, and Google Scholar, from inception to February 2023. EXPERT OPINION: Many algorithms have been developed, but few have been prospectively evaluated. These performed better than bodyweight-based starting doses, regarding the time a patient is exposed to off-target tacrolimus concentrations. No benefit in reduced tacrolimus toxicity has yet been observed. Most algorithms were developed from small datasets, contained only a few tacrolimus concentrations per person, and were not externally validated. Moreover, other matrices should be considered which might better correlate with tacrolimus toxicity than the whole-blood concentration, e.g. unbound plasma or intra-lymphocytic tacrolimus concentrations.

P-glycoprotein, FK-binding Protein-12, and the Intracellular Tacrolimus Concentration in T-lymphocytes and Monocytes of Kidney Transplant Recipients.

BACKGROUND: . Transplant recipients may develop rejection despite having adequate tacrolimus whole blood predose concentrations (C 0 ). The intra-immune cellular concentration is potentially a better target than C 0 . However, little is known regarding intracellular tacrolimus concentration in T-lymphocytes and monocytes. We investigated the tacrolimus concentrations in both cell types and their relation with the expression and activity of FK-binding protein (FKBP)-12 and P-glycoprotein (P-gp). METHODS: . T-lymphocytes and monocytes were isolated from kidney transplant recipients followed by intracellular tacrolimus concentration measurement. FKBP-12 and P-gp were quantified with Western blot, flow cytometry, and the Rhodamine-123 assay. Interleukin-2 and interferon-γ in T-lymphocytes were measured to quantify the effect of tacrolimus. RESULTS: . Tacrolimus concentration in T-lymphocytes was lower than in monocytes (15.3 [8.5-33.4] versus 131.0 [73.5-225.1] pg/million cells; P < 0.001). The activity of P-gp (measured by Rhodamine-123 assay) was higher in T-lymphocytes than in monocytes. Flow cytometry demonstrated a higher expression of P-gp (normalized mean fluorescence intensity 1.5 [1.2-1.7] versus 1.2 [1.1-1.4]; P = 0.012) and a lower expression of FKBP-12 (normalized mean fluorescence intensity 1.3 [1.2-1.7] versus 1.5 [1.4-2.0]; P = 0.011) in T-lymphocytes than monocytes. Western blot confirmed these observations. The addition of verapamil, a P-gp inhibitor, resulted in a 2-fold higher intra-T-cell tacrolimus concentration. This was accompanied by a significantly fewer cytokine-producing cells. CONCLUSIONS: . T-lymphocytes have a higher activity of P-gp and lower concentration of the FKBP-12 compared with monocytes. This explains the relatively lower tacrolimus concentration in T-lymphocytes. The addition of verapamil prevents loss of intracellular tacrolimus during the cell isolation process and is required to ensure adequate intracellular concentration measurement.

Best Practices to Implement Dried Blood Spot Sampling for Therapeutic Drug Monitoring in Clinical Practice.

BACKGROUND: Sampling of blood at home to determine the concentration of drugs or other compounds can be effective in limiting hospital-based sampling. This could lower hospital visits and patient burden, improve the quality of life, and reduce health care costs. Dried blood spot (DBS) microsampling is often used for this purpose, wherein capillary blood, obtained by pricking the heel or finger, is used to measure different analytes. Although DBS has several advantages over venous blood sampling, it is not routinely implemented in clinical practice. To facilitate the bench to bedside transition, it is important to be aware of certain challenges that need to be considered and addressed. RESULTS: Here, important considerations regarding the implementation of DBS in clinical practice, the choice of patients, blood sampling, transport, and laboratory analysis are discussed. In addition, we share our experience and provide suggestions on how to deal with these problems in a clinical setting.

A Population Pharmacokinetic Model of Whole-Blood and Intracellular Tacrolimus in Kidney Transplant Recipients.

BACKGROUND AND OBJECTIVE: The tacrolimus concentration within peripheral blood mononuclear cells may correlate better with clinical outcomes after transplantation compared to concentrations measured in whole blood. However, intracellular tacrolimus measurements are not easily implemented in clinical practice. The prediction of intracellular concentrations based on whole-blood concentrations would be a solution for this. Therefore, the aim of this study was to describe the relationship between intracellular and whole-blood tacrolimus concentrations in a population pharmacokinetic (popPK) model. METHODS: Pharmacokinetic analysis was performed using non-linear mixed effects modelling software (NONMEM). The final model was evaluated using goodness-of-fit plots, visual predictive checks, and a bootstrap analysis. RESULTS: A total of 590 tacrolimus concentrations from 184 kidney transplant recipients were included in the study. All tacrolimus concentrations were measured in the first three months after transplantation. The intracellular tacrolimus concentrations (n = 184) were best described with an effect compartment. The distribution into the effect compartment was described by the steady-state whole-blood to intracellular ratio (RWB:IC) and the intracellular distribution rate constant between the whole-blood and intracellular compartments. Lean body weight was negatively correlated [delta objective function value (ΔOFV) -8.395] and haematocrit was positively correlated (ΔOFV = - 6.752) with RWB:IC, and both lean body weight and haematocrit were included in the final model. CONCLUSION: We were able to accurately describe intracellular tacrolimus concentrations using whole-blood concentrations, lean body weight, and haematocrit values in a popPK model. This model may be used in the future to more accurately predict clinical outcomes after transplantation and to identify patients at risk for under- and overexposure. Dutch National Trial Registry number NTR2226.

The use of freeze-dried blood samples affects the results of a dried blood spot analysis.

Dried blood spot (DBS) microsampling has several advantages over venous blood sampling. In a clinical validation study of tacrolimus microsampling it was noted that tacrolimus DBS concentrations ([Tac]DBS) were systematically higher than tacrolimus whole-blood concentrations ([Tac]WB). This observation was explored by investigating the effect of using freeze-dried standards (STFD) for [Tac]DBS measurement. For all experiments, both non-frozen whole-blood samples and whole-blood samples that were frozen and thawed (to simulate freeze-drying) of 10 patients were analyzed. Multiple tacrolimus concentrations were measured: 1) [Tac]WB, 2) [Tac]DBS, where 15 µL was volumetrically applied to a pre-punched DBS disk, and 3) [Tac]DBS, where 50 µL was applied before a 6 mm DBS disk was punched from the card. All tacrolimus concentrations were determined independently using STFD and standards made of non-frozen blood spiked with tacrolimus (STSP). In both non-frozen and frozen and thawed whole-blood samples, [Tac]WB measured with STFD appeared similar to [Tac]WB measured with STSP (Ratios 1.061 and 1.077, respectively). In non-frozen samples, the median ratio between the [Tac]DBS measured with STFD, and [Tac]WB measured with STFD (the reference method), was 1.396. When blood was volumetrically applied to the DBS card (to eliminate the effect of the spreading over the filter paper), this ratio was 1.009. In conclusion, when using DBS microsampling to quantify concentrations of analytes, one should be aware that using the commercially available freeze-dried blood samples for the preparation of standards may affect the spreading of blood on the filter-paper, leading to a systematic error in the results.

Model-Based Tacrolimus Follow-up Dosing in Adult Renal Transplant Recipients: A Simulation Trial.

BACKGROUND: Initial algorithm-based dosing appears to be effective in predicting tacrolimus dose requirement. However, achieving and maintaining the target concentrations is challenging. Model-based follow-up dosing, which considers patient characteristics and pharmacological data, may further personalize treatment. This study investigated whether model-based follow-up dosing could lead to more accurate tacrolimus exposure than standard therapeutic drug monitoring (TDM) in kidney transplant recipients after an initial algorithm-based dose. METHODS: This simulation trial included patients from a prospective trial that received an algorithm-based tacrolimus starting dose followed by TDM. For every measured tacrolimus predose concentration (C 0,obs ), model-based dosing advice was simulated using the InsightRX software. Based on previous tacrolimus doses and C 0 , age, body surface area, CYP3A4 and CYP3A5 genotypes, hematocrit, albumin, and creatinine, the optimal next dose, and corresponding tacrolimus concentration (C 0,pred ) were predicted. RESULTS: Of 190 tacrolimus C 0 values measured in 59 patients, 121 (63.7%; 95% CI 56.8-70.5) C 0,obs were within the therapeutic range (7.5-12.5 ng/mL) versus 126 (66.3%, 95% CI 59.6-73.0) for C 0,pred ( P = 0.89). The median absolute difference between the tacrolimus C 0 and the target tacrolimus concentration (10.0 ng/mL) was 1.9 ng/mL for C 0,obs versus 1.6 ng/mL for C 0,pred . In a historical cohort of 114 kidney transplant recipients who received a body weight-based starting dose followed by TDM, 172 of 335 tacrolimus C 0 (51.3%) were within the therapeutic range (10.0-15.0 ng/mL). CONCLUSIONS: The combination of an algorithm-based tacrolimus starting dose with model-based follow-up dosing has the potential to minimize under- and overexposure to tacrolimus in the early posttransplant phase, although the additional effect of model-based follow-up dosing on initial algorithm-based dosing seems small.

Association Between the Intracellular Tacrolimus Concentration in CD3 + T Lymphocytes and CD14 + Monocytes and Acute Kidney Transplant Rejection.

BACKGROUND: Intracellular tacrolimus concentration in peripheral blood mononuclear cells (PBMCs) (TAC [PBMC] ) has been proposed to better represent its active concentration than its whole blood concentration. As tacrolimus acts on T lymphocytes and other white blood cells, including monocytes, we investigated the association of tacrolimus concentration in CD3 + T lymphocytes (TAC [CD3] ) and CD14 + monocytes (TAC [CD14] ) with acute rejection after kidney transplantation. METHODS: From a total of 61 samples in this case-control study, 28 samples were obtained during biopsy-proven acute rejection (rejection group), and 33 samples were obtained in the absence of rejection (control group). PBMCs were collected from both cryopreserved (retrospectively) and freshly obtained (prospectively) samples. CD3 + T lymphocytes and CD14 + monocytes were isolated from PBMCs, and their intracellular tacrolimus concentrations were measured. RESULTS: The correlation between tacrolimus whole-blood and intracellular concentrations was poor. TAC [CD3] was significantly lower than TAC [CD14] (median 12.8 versus 81.6 pg/million cells; P < 0.001). No difference in TAC [PBMC] (48.5 versus 44.4 pg/million cells; P = 0.82), TAC [CD3] (13.4 versus 12.5 pg/million cells; P = 0.28), and TAC [CD14] (90.0 versus 72.8 pg/million cells; P = 0.27) was found between the rejection and control groups. However, freshly isolated PBMCs showed significantly higher TAC [PBMC] than PBMCs from cryopreserved samples. Subgroup analysis of intracellular tacrolimus concentrations from freshly isolated cells did not show a difference between rejectors and nonrejectors. CONCLUSIONS: Differences in TAC [CD3] and TAC [CD14] between patients with and without rejection could not be demonstrated. However, further optimization of the cell isolation process is required because a difference in TAC [PBMC] between fresh and cryopreserved cells was observed. These results need to be confirmed in a study with a larger number of patients.

Monitoring intracellular tacrolimus concentrations and its relationship with rejection in the early phase after renal transplantation.

INTRODUCTION: After kidney transplantation, rejection and drug-related toxicity occur despite tacrolimus whole-blood pre-dose concentrations ([Tac]blood) being within the target range. The tacrolimus concentration within peripheral blood mononuclear cells ([Tac]cells) might correlate better with clinical outcomes. The aim of this study was to investigate the correlation between [Tac]blood and [Tac]cells, the evolution of [Tac]cells and the [Tac]cells/[Tac]blood ratio, and to assess the relationship between tacrolimus concentrations and the occurrence of rejection. METHODS: In this prospective study, samples for the measurement of [Tac]blood and [Tac]cells were collected on days 3 and 10 after kidney transplantation, and on the morning of a for-cause kidney transplant biopsy. Biopsies were reviewed according to the Banff 2019 update. RESULTS: Eighty-three [Tac]cells samples were measured of 44 kidney transplant recipients. The correlation between [Tac]cells and [Tac]blood was poor (Pearson's r = 0.56 (day 3); r = 0.20 (day 10)). Both the dose-corrected [Tac]cells and the [Tac]cells/[Tac]blood ratio were not significantly different between days 3 and 10, and the median inter-occasion variability of the dose-corrected [Tac]cells and the [Tac]cells/[Tac]blood ratio were 19.4% and 23.4%, respectively (n = 24). Neither [Tac]cells, [Tac]blood, nor the [Tac]cells/[Tac]blood ratio were significantly different between patients with biopsy-proven acute rejection (n = 4) and patients with acute tubular necrosis (n = 4) or a cancelled biopsy (n = 9; p > 0.05). CONCLUSION: Tacrolimus exposure and distribution appeared stable in the early phase after transplantation. [Tac]cells was not significantly associated with the occurrence of rejection. A possible explanation for these results might be related to the low number of patients included in this study and also due to the fact that PBMCs are not a specific enough matrix to monitor tacrolimus concentrations.

Therapeutic drug monitoring of immunosuppressive drugs in hepatology and gastroenterology.

Immunosuppressive drugs have been key to the success of liver transplantation and are essential components of the treatment of inflammatory bowel disease (IBD) and autoimmune hepatitis (AIH). For many but not all immunosuppressants, therapeutic drug monitoring (TDM) is recommended to guide therapy. In this article, the rationale and evidence for TDM of tacrolimus, mycophenolic acid, the mammalian target of rapamycin inhibitors, and azathioprine in liver transplantation, IBD, and AIH is reviewed. New developments, including algorithm-based/computer-assisted immunosuppressant dosing, measurement of immunosuppressants in alternative matrices for whole blood, and pharmacodynamic monitoring of these agents is discussed. It is expected that these novel techniques will be incorporate into the standard TDM in the next few years.

Cholesterol Embolization Syndrome After Kidney Transplantation: A Case Series and Systematic Review.

BACKGROUND: Cholesterol embolization syndrome (CES) is an uncommon but well-known cause of renal failure in native kidneys, but little is known about CES in kidney transplant recipients. The aim of this study was to determine the incidence, clinical characteristics, histopathology, and prognosis of CES after kidney transplantation. METHODS: CES cases in both transplanted and native kidneys (control group) were identified by searching the databases of the divisions of Nephrology and Pathology of our institution. Clinical data were retrospectively collected. Biopsies were classified according to the latest Banff 2019 Update. Second, a systematic literature search was performed (December 01, 2020) of Ovid MEDLINE, EMBASE, the Cochrane Central Register of controlled trials, Google Scholar, and Web of Science. RESULTS: CES was observed in for-cause biopsies of 11 out of 2350 (0.47%) kidney transplant recipients transplanted between January 1, 2006, and December 31, 2018 (0.0009 cases per person-year). All patients had ≥1 cardiovascular risk factor, and 9 donors were expanded criteria donors. Graft loss occurred in 27.3% of the patients diagnosed with CES. Eight transplant biopsies with CES were also classified as biopsy-proven acute rejection. Transplant biopsies showed signs of inflammation (arteritis, n = 7; interstitial inflammation, n = 5; tubulitis, n = 7). One patient with CES in a native kidney was identified. The biopsy of the native kidney only showed arteritis and classified as an isolated "v" lesion. The literature search resulted in 188 unique articles of which 20 were included. A total of 47 cases of CES after kidney transplantation was reported. Cholesterol emboli were found in <1% of all kidney transplant biopsies. In 57.8% of the kidney transplant biopsies with CES described in literature, concomitant inflammation was present. CONCLUSIONS: CES is an uncommon cause of kidney transplant failure, although the incidence of CES may be underestimated. CES may mimic rejection as it can be accompanied by arteritis.

A systematic review and meta-analysis of enzyme-linked immunosorbent spot (ELISPOT) assay for BK polyomavirus immune response monitoring after kidney transplantation.

BK virus (BKV) infection after kidney transplantation can cause BKV nephropathy (BKVAN) resulting in graft dysfunction and allograft loss. The treatment for BKVAN is reduction of the immunosuppressive load which increases the risk of kidney transplant rejection. There is no biomarker to monitor BKV activity besides BK viral load. The value of the Enzyme-Linked Immunosorbent Spot (ELISPOT) assay as a tool to monitor the recipient's anti-BKV immune response after transplantation was investigated systematically. Electronic databases, including MEDLINE, Scopus, and the Cochrane Central Register of Controlled Trials were searched for studies of ELISPOT evaluating the immune response against BKV. BKV status was categorized as "active BKV infection" and as "resolving BKV infection". Random-effects model meta-analysis was performed to determine the diagnostic performance of the ELISPOT assay, after stratifying patients into groups based on positive and negative ELISPOT results. One-hundred twenty-seven articles were identified of which nine were included. Patients with negative ELISPOT had an increased risk of having active BKV replication (odds ratio of 71.9 (95%-CI 31.0-167.1). Pooled sensitivity was 0.95 (95%-CI 0.89-0.98) and specificity was 0.88 (95%-CI 0.78-0.94). The standardized mean difference of the number of IFN-γ producing cells between patients with active BKV infection compared with patients who had resolving BKV infection was -2.09 (95%-CI -2.50, -1.68). The ELISPOT assay is a useful tool for BKV risk assessment and in combination with BKV load may support clinicians in guiding immunosuppressive therapy in patients with BKV replication.

Avoiding Tacrolimus Underexposure and Overexposure with a Dosing Algorithm for Renal Transplant Recipients: A Single Arm Prospective Intervention Trial.

Bodyweight-based tacrolimus dosing followed by therapeutic drug monitoring is standard clinical care after renal transplantation. However, after transplantation, a meager 38% of patients are on target at first steady-state and it can take up to 3 weeks to reach the target tacrolimus predose concentration (C0 ). Tacrolimus underexposure and overexposure is associated with an increased risk of rejection and drug-related toxicity, respectively. To minimize subtherapeutic and supratherapeutic tacrolimus exposure in the immediate post-transplant phase, a previously developed dosing algorithm to predict an individual's tacrolimus starting dose was tested prospectively. In this single-arm, prospective, therapeutic intervention trial, 60 de novo kidney transplant recipients received a tacrolimus starting dose based on a dosing algorithm instead of a standard, bodyweight-based dose. The algorithm included cytochrome P450 (CYP)3A4 and CYP3A5 genotype, body surface area, and age as covariates. The target tacrolimus C0 , measured for the first time at day 3, was 7.5-12.5 ng/mL. Between February 23, 2019, and July 7, 2020, 60 patients were included. One patient was excluded because of a protocol violation. On day 3 post-transplantation, 34 of 59 patients (58%, 90% CI 47-68%) had a tacrolimus C0 within the therapeutic range. Markedly subtherapeutic (< 5.0 ng/mL) and supratherapeutic (> 20 ng/mL) tacrolimus concentrations were observed in 7% and 3% of the patients, respectively. Biopsy-proven acute rejection occurred in three patients (5%). In conclusion, algorithm-based tacrolimus dosing leads to the achievement of the tacrolimus target C0 in as many as 58% of the patients on day 3 after kidney transplantation.

Monitoring the tacrolimus concentration in peripheral blood mononuclear cells of kidney transplant recipients.

AIMS: Tacrolimus is a critical dose drug and to avoid under- and overexposure, therapeutic drug monitoring is standard practice. However, rejection and drug-related toxicity occur despite whole-blood tacrolimus pre-dose concentrations ([Tac]blood ) being on target. Monitoring tacrolimus concentrations at the target site (within peripheral blood mononuclear cells; [Tac]cells ) may better correlate with drug-efficacy. The aim of this study was to (1) investigate the relationship between [Tac]blood and [Tac]cells , (2) identify factors affecting the tacrolimus distribution in cells and whole-blood, and (3) study the relationship between [Tac]cells and clinical outcomes after kidney transplantation. METHODS: A total of 175 renal transplant recipients were prospectively followed. [Tac]blood and [Tac]cells were determined at Months 3, 6 and 12 post-transplantation. Patients were genotyped for ABCB1 1199G>A and 3435C>T, CYP3A4 15389C>T, and CYP3A5 6986G>A. Data on rejection and tacrolimus-related nephrotoxicity and post-transplant diabetes mellitus were collected. RESULTS: Correlations between [Tac]blood and [Tac]cells were moderate to poor (Spearman's r = 0.31; r = 0.41; r = 0.61 at Months 3, 6 and 12, respectively). The [Tac]cells /[Tac]blood ratio was stable over time in most patients (median intra-patient variability 39.0%; range 3.5%-173.2%). Age, albumin and haematocrit correlated with the [Tac]cells /[Tac]blood ratio. CYP3A5 and CYP3A4 genotype combined affected both dose-corrected [Tac]blood and [Tac]cells . ABCB1 was not significantly related to tacrolimus distribution. Neither [Tac]blood nor [Tac]cells correlated with clinical outcomes. CONCLUSIONS: The correlation between [Tac]blood and [Tac]cells is poor. Age, albumin and haematocrit correlate with the [Tac]cells /[Tac]blood ratio, whereas genetic variation in ABCB1, CYP3A4 and CYP3A5 do not. Neither [Tac]blood nor [Tac]cells correlated with clinical outcomes.

Iron deficiency after kidney transplantation.

Iron deficiency (ID) is highly prevalent in kidney transplant recipients (KTRs) and has been independently associated with an excess mortality risk in this population. Several causes lead to ID in KTRs, including inflammation, medication and an increased iron need after transplantation. Although many studies in other populations indicate a pivotal role for iron as a regulator of the immune system, little is known about the impact of ID on the immune system in KTRs. Moreover, clinical trials in patients with chronic kidney disease or heart failure have shown that correction of ID, with or without anaemia, improves exercise capacity and quality of life, and may improve survival. ID could therefore be a modifiable risk factor to improve graft and patient outcomes in KTRs; prospective studies are warranted to substantiate this hypothesis.

Usage of Tacrolimus and Mycophenolic Acid During Conception, Pregnancy, and Lactation, and Its Implications for Therapeutic Drug Monitoring: A Systematic Critical Review.

BACKGROUND: Conception, pregnancy, and lactation following solid organ transplantation require appropriate management. The most frequently used immunosuppressive drug combination after solid organ transplantation consists of tacrolimus (Tac) plus mycophenolic acid (MPA). Here, the effects of Tac and MPA on fertility, pregnancy, and lactation are systematically reviewed, and their implications for therapeutic drug monitoring (TDM) are discussed. METHODS: A systematic literature search was performed (August 19, 2019) using Ovid MEDLINE, EMBASE, the Cochrane Central Register of controlled trials, Google Scholar, and Web of Science, and 102 studies were included. Another 60 were included from the reference list of the published articles. RESULTS: As MPA is teratogenic, women who are trying to conceive are strongly recommended to switch from MPA to azathioprine. MPA treatment in men during conception seems to have no adverse effect on pregnancy outcomes. Nevertheless, in 2015, the drug label was updated with additional risk minimization measures in a pregnancy prevention program. Data on MPA pharmacokinetics during pregnancy and lactation are limited. Tac treatment during conception, pregnancy, and lactation seems to be safe in terms of the health of the mother, (unborn) child, and allograft. However, Tac may increase the risk of hypertension, preeclampsia, preterm birth, and low birth weight. Infants will ingest very small amounts of Tac via breast milk from mothers treated with Tac. However, no adverse outcomes have been reported in children exposed to Tac during lactation. During pregnancy, changes in Tac pharmacokinetics result in increased unbound to whole-blood Tac concentration ratio. To maintain Tac concentrations within the target range, increased Tac dose and intensified TDM may be required. However, it is unclear if dose adjustments during pregnancy are necessary, considering the higher concentration of (active) unbound Tac. CONCLUSIONS: Tac treatment during conception, pregnancy and lactation seems to be relatively safe. Due to pharmacokinetic changes during pregnancy, a higher Tac dose might be indicated to maintain target concentrations. However, more evidence is needed to make recommendations on both Tac dose adjustments and alternative matrices than whole-blood for TDM of Tac during pregnancy. MPA treatment in men during conception seems to have no adverse effect on pregnancy outcomes, whereas MPA use in women during conception and pregnancy is strongly discouraged.