Maximum a posteriori Bayesian estimation of oral cyclosporin pharmacokinetics in patients with stable renal transplants

A Hybrid Model Associating Population Pharmacokinetics with Machine Learning: A Case Study with Iohexol Clearance Estimation

BACKGROUND

Maximum a posteriori Bayesian estimation (MAP-BE) based on a limited sampling strategy and a population pharmacokinetic model is frequently used to estimate pharmacokinetic parameters in individuals, however with some uncertainty (bias). Recent works have shown that the performance in individual estimation or pharmacokinetic parameters can be improved by combining population pharmacokinetic and machine learning algorithms.

OBJECTIVE

 The objective of this work was to investigate the use of a hybrid machine learning/population pharmacokinetic approach to improve individual iohexol clearance estimation.

METHODS

The reference iohexol clearance values were derived from 500 simulated profiles (samples collected between 0.1 and 24.7 h) using a population pharmacokinetic model we recently developed in Monolix and obtained using all the concentration timepoints available. Xgboost and glmnet algorithms able to predict the error of MAP-BE clearance estimates based on a limited sampling strategy (0.1 h, 1 h, and 9 h) versus reference values were developed in a training subset (75%) and were evaluated in a testing subset (25%) and in 36 real patients.

RESULTS

The MAP-BE limited sampling strategy estimated clearance was corrected by the machine learning predicted error leading to a decrease in root mean squared error by 29% and 24%, and in the percentage of profiles with the mean prediction error out of the ± 20% bias by 60% and 40% in the external validation dataset for the glmnet and Xgboost machine learning algorithms, respectively. These results were attributable to a decrease in the eta-shrinkage (shrinkage for a MAP-BE limited sampling strategy = 32.4%, glmnet = 18.2%, and Xgboost = 19.4% in the external dataset).

CONCLUSIONS

 In conclusion, this hybrid algorithm represents a significant improvement in comparison to MAP-BE estimation alone.

Overview of therapeutic drug monitoring of immunosuppressive drugs: Analytical and clinical practices

Immunosuppressant drugs (ISDs) play a key role in short-term patient survival together with very low acute allograft rejection rates in transplant recipients. Due to the narrow therapeutic index and large inter-patient pharmacokinetic variability of ISDs, therapeutic drug monitoring (TDM) is needed to dose adjustment for each patient (personalized medicine approach) to avoid treatment failure or side effects of the therapy. To achieve this, TDM needs to be done effectively. However, it would not be possible without the proper clinical practice and analytical tools. The purpose of this review is to provide a guide to establish reliable TDM, followed by a critical overview of the current analytical methods and clinical practices for the TDM of ISDs, and to discuss some of the main practical aspects of the TDM.

Immunosuppressant quantification in intravenous microdialysate - towards novel quasi-continuous therapeutic drug monitoring in transplanted patients

OBJECTIVES

Therapeutic drug monitoring (TDM) plays a crucial role in personalized medicine. It helps clinicians to tailor drug dosage for optimized therapy through understanding the underlying complex pharmacokinetics and pharmacodynamics. Conventional, non-continuous TDM fails to provide real-time information, which is particularly important for the initial phase of immunosuppressant therapy, e.g., with cyclosporine (CsA) and mycophenolic acid (MPA).

METHODS

We analyzed the time course over 8 h of total and free of immunosuppressive drug (CsA and MPA) concentrations measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in 16 kidney transplant patients. Besides repeated blood sampling, intravenous microdialysis was used for continuous sampling. Free drug concentrations were determined from ultracentrifuged EDTA-plasma (UC) and compared with the drug concentrations in the respective microdialysate (µD). µDs were additionally analyzed for free CsA using a novel immunosensor chip integrated into a fluorescence detection platform. The potential of microdialysis coupled with an optical immunosensor for the TDM of immunosuppressants was assessed.

RESULTS

Using LC-MS/MS, the free concentrations of CsA (fCsA) and MPA (fMPA) were detectable and the time courses of total and free CsA comparable. fCsA and fMPA and area-under-the-curves (AUCs) in µDs correlated well with those determined in UCs (r≥0.79 and r≥0.88, respectively). Moreover, fCsA in µDs measured with the immunosensor correlated clearly with those determined by LC-MS/MS (r=0.82).

CONCLUSIONS

The new microdialysis-supported immunosensor allows real-time analysis of immunosuppressants and tailor-made dosing according to the AUC concept. It readily lends itself to future applications as minimally invasive and continuous near-patient TDM.

Analyses of AUC(0–12) and C0 Compliances within Therapeutic Ranges in Kidney Recipients Receiving Cyclosporine or Tacrolimus

The AUC (area under the concentration time curve) is considered the pharmacokinetic exposure parameter best associated with clinical effects. Unfortunately, no prospective studies of clinical outcomes have been conducted in adult transplant recipients to investigate properly the potential benefits of AUC_(0–12) monitoring compared to the C₀-guided therapy. The aim of the present study was to compare two methods, C₀ (through level) and AUC_(0–12) (area under the concentration time curve), for assessing cyclosporine and tacrolimus concentrations. The study included 340 kidney recipients. The AUC_(0–12) was estimated using a Bayesian estimator and a three-point limited sampling strategy. Therapeutic drug monitoring of tacrolimus performed by using AUC_(0–12) and C₀ showed that tacrolimus in most cases is overdosed when considering C₀, while determination of the AUC_(0–12) showed that tacrolimus is effectively dosed for 27.8–40.0% of patients receiving only tacrolimus and for 25.0–31.9% of patients receiving tacrolimus with MMF (mycophenolate mofetil). In the 1–5 years post-transplantation group, 10% higher CsA (cyclosporine) dose was observed, which was proportionate with a 10% higher AUC_(0–12) exposure value. This indicates good compatibility of the dosage and the AUC(0–12) method. The Bland–Altman plot demonstrated that C₀ and AUC_(0–12) might be interchangeable methods, while the ROC (receiver operating characteristic) curve analysis of the C₀/AUC_(0–12) ratio in the tacrolimus-receiving patient group demonstrated reliable performance to predict IFTA (interstitial fibrosis and tubular atrophy) after kidney transplantation, with an ROC curve of 0.660 (95% confidence interval (CI): 0.576–0.736), p < 0.01. Moreover, AUC_(0–12) and C₀ of tacrolimus depend on concomitant medication and adjustment of the therapeutic range for AUC_(0–12) might influence the results.

Pharmacologic Treatment of Transplant Recipients Infected With SARS-CoV-2: Considerations Regarding Therapeutic Drug Monitoring and Drug-Drug Interactions

COVID-19 is a novel infectious disease caused by the severe acute respiratory distress (SARS)-coronavirus-2 (SARS-CoV-2). Several therapeutic options are currently emerging but none with universal consensus or proven efficacy. Solid organ transplant recipients are perceived to be at increased risk of severe COVID-19 because of their immunosuppressed conditions due to chronic use of immunosuppressive drugs (ISDs). It is therefore likely that solid organ transplant recipients will be treated with these experimental antivirals.

Revisiting myocardial necrosis biomarkers: assessment of the effect of conditioning therapies on infarct size by kinetic modelling

Infarct size is a major predictor of subsequent cardiovascular events following ST-segment elevation myocardial infarction (STEMI) and is frequently used in clinical trials focused on cardioprotection. Approximately assessed through serial blood sampling, it can be accurately measured by imaging techniques, e.g. cardiac magnetic resonance imaging, which is the actual gold standard for infarct size determination but with limited availability in daily practice. We developed a mathematical biomarker kinetic model based on pharmacokinetic compartment models to easily and accurately estimate infarct size using individual data from five clinical trials evaluating the impact of conditioning therapies in STEMI between 2005 and 2013. Serial blood sampling was available in all studies with data regarding creatine kinase (CK), CK specific of cardiomyocytes (CK-MB) and cardiac troponin I. Our model allowed an accurate estimation of biomarker release as a surrogate marker of infarct size and a powerful assessment of conditioning treatments. This biomarker kinetic modelling approach identified CK-MB as the most accurate biomarker in determining infarct size and supports the development of limited sampling strategies that estimate total biomarker amount released with a lower number of samples. It will certainly be a useful add-on to future studies in the field of STEMI and cardioprotection.

Influence of cyclosporine and everolimus on the main mycophenolate mofetil pharmacokinetic parameters: Cross-sectional study

The objective of the present study was to assess the effect of cyclosporine (CsA) on the pharmacokinetic parameters of mycophenolic acid (MPA), an active mycophenolate mofetil (MMF) metabolite, and to compare with the effect of everolimus (EVR).Anonymized medical records of 404 kidney recipients were reviewed. The main MPA pharmacokinetic parameters (AUC(0-12) and Cmax) were evaluated.The patients treated with a higher mean dose of CsA displayed higher MPA AUC(0-12) exposure in the low-dose MMF group (1000 mg/day) (40.50 ± 10.97 vs 28.08 ± 11.03 h mg/L; rs = 0.497, P < 0.05), medium-dose MMF group (2000 mg/day) (43.00 ± 6.27 vs 28.85 ± 11.08 h mg/L; rs = 0.437, P < 0.01), and high-dose MMF group (3000 mg/day) (56.75 ± 16.78 vs 36.20 ± 3.70 h mg/L; rs = 0.608, P < 0.05).A positive correlation was also observed between the mean CsA dose and the MPA Cmax in the low-dose MMF group (Cmax 22.83 ± 10.82 vs 12.08 ± 5.59 mg/L; rs = 0.507, P < 0.05) and in the medium-dose MMF group (22.77 ± 8.86 vs 13.00 ± 6.82 mg/L; rs = 0.414, P < 0.01).The comparative analysis between 2 treatment arms (MMF + CsA and MMF + EVR) showed that MPA AUC(0-12) exposure was by 43% higher in the patients treated with a medium dose of MMF and EVR than in the patients treated with a medium dose of MMF and CsA.The data of the present study suggest a possible CsA versus EVR influence on MMF pharmacokinetics. Study results show that CsA has an impact on the main MPA pharmacokinetic parameters (AUC(0-12) and Cmax) in a CsA dose-related manner, while EVR mildly influence or does not affect MPA pharmacokinetic parameters. Low-dose CsA (lower than 180 mg/day) reduces MPA AUC(0-12) exposure under the therapeutic window and may lead to ineffective therapy, while a high-dose CsA (>240 mg/day) is related to greater than 10 mg/L MPA Cmax and increases the likelihood of adverse events.

Population pharmacokinetics of cyclosporine in transplant recipients

A number of classical pharmacokinetic studies have been conducted in transplant patients. However, they suffer from some limitations, for example, (1) the study design was limited to intense blood sampling in small groups of patients during a certain posttransplant period, (2) patient factors were evaluated one at a time to identify their association with the pharmacokinetic parameters, and (3) mean pharmacokinetic parameters often cannot be precisely estimated due to large intraindividual variability. Population pharmacokinetics provides a potential means of addressing these limitations and is a powerful tool to evaluate the magnitude and consistency of drug exposure. Population pharmacokinetic studies of cyclosporine focused solely on developing limited sampling strategies and Bayesian estimators to estimate drug exposure, have been summarized before, and are, therefore, not a subject of this review. The major focus of this review is to describe factors (demographic factors, hepatic and gastrointestinal functions, drug-drug interactions, genetic polymorphisms of drug metabolizing enzymes and transporters) that have been identified to contribute to the large portion of observed variability in the pharmacokinetics of cyclosporine in transplant patients. This review summarizes and interprets the conclusions as well as the nonlinear mixed-effects modeling methodologies used in such studies. A highly diversified collection of structural models, variability models, and covariate submodels have been evaluated and validated using internal or external validation methods. This review also highlights areas where additional research is warranted to improve the models since a portion of model variability still remains unexplained.

Optimal sampling strategy development methodology using maximum a posteriori Bayesian estimation

Maximum a posteriori Bayesian (MAPB) pharmacokinetic parameter estimation is an accurate and flexible method of estimating individual pharmacokinetic parameters using individual blood concentrations and prior information. In the past decade, many studies have developed optimal sampling strategies to estimate pharmacokinetic parameters as accurately as possible using either multiple regression analysis or MAPB estimation. This has been done for many drugs, especially immunosuppressants and anticancer agents. Methods of development for optimal sampling strategies (OSS) are diverse and heterogeneous. This review provides a comprehensive overview of OSS development methodology using MAPB pharmacokinetic parameter estimation, determines the transferability of published OSSs, and compares sampling strategies determined by MAPB estimation and multiple regression analysis. OSS development has the following components: 1) prior distributions; 2) reference value determination; 3) optimal sampling time identification; and 4) validation of the OSS. Published OSSs often lack all data necessary for the OSS to be clinically transferable. MAPB estimation is similar to multiple regression analysis in terms of predictive performance but superior in flexibility.

Population pharmacokinetics of eltrombopag in healthy subjects and patients with chronic idiopathic thrombocytopenic purpura

The population pharmacokinetics of eltrombopag were characterized in healthy subjects (n = 111) and patients with idiopathic thrombocytopenic purpura (ITP) (n = 88) using nonlinear mixed-effects modeling. The final model was evaluated via graphical diagnostics and through predictive check and nonparametric bootstrap procedures. A 2-compartment model with dual sequential first-order absorption, absorption lag time, and interoccasion variability in absorption adequately described the data. For a typical 70-kg Caucasian male ITP patient not taking corticosteroids, estimated parameters were apparent clearance (CL/F) = 0.668 L/h, apparent volume of the central compartment (Vc/F) = 8.76 L, apparent volume of the peripheral compartment (Vp/F) = 11.3 L, and distributional clearance (Q/F) = 0.399 L/h. Eltrombopag CL/F, Vc/F, Q/F, and Vp/F increased with body weight. For the range of weights included (43-122 kg), the parameters ranged from 26% lower to 41% higher than for a 70-kg individual. The typical eltrombopag CL/F was 33% lower in East Asians compared with other races, 26% lower in patients taking corticosteroids concomitantly, 19% lower in females compared with males, and 17% higher in healthy subjects compared with ITP patients. There was also a dose effect, with CL/F and Vc/F estimated to be respectively 68% and 55% higher for doses 20 mg or less. In conclusion, East Asian race had the largest impact on eltrombopag exposure with a lower initial dose being recommended.

A 50% reduction in cyclosporine exposure in stable renal transplant recipients: renal function benefits

BACKGROUND

Although cyclosporine maintenance therapy reduces the risk of acute rejection and increases short-term graft survival in renal transplant recipients, its associated nephrotoxicity increases the risk of chronic graft dysfunction. The dose that allows an optimal risk-to-benefit ratio has not been established.

METHODS

This multicentre study enrolled stable renal allograft recipients receiving cyclosporine and mycophenolate mofetil without corticosteroids in their second year post-transplant. Patients were randomized to a cyclosporine dose targeted to a standard area under the concentration-time curve (AUC)(0-12 h) (usual exposure, n = 104) or 50% of the study standard AUC(0-12 h) (low exposure, n = 108) using a three-point pharmacokinetic sampling. The primary endpoint was the percentage of patients with treatment failure at 24 months (graft loss/acute rejection/nephrotoxicity/>15% serum creatinine level increase).

RESULTS

Treatment failure was reported in 37 out of 101 (37%) patients in the usual-exposure and 19 out of 106 (18%) patients in the low-exposure groups (P = 0.003). Mean estimated glomerular filtration rate decreased from baseline to 2 years with usual exposure and increased with low exposure (P < 0.001). Mean systolic and diastolic blood pressures were lower with low exposure (P = 0.03 and P = 0.008, respectively).

CONCLUSION

In renal transplant recipients receiving maintenance therapy without corticosteroids, a minimization strategy using three-point pharmacokinetic sampling to reduce and maintain cyclosporine exposure to 50% of the usual levels is safe and reduces the risk of graft dysfunction.

Pharmacokinetic optimization of immunosuppressive therapy in thoracic transplantation: part I

Although immunosuppressive treatments and therapeutic drug monitoring (TDM) have significantly contributed to the increased success of thoracic transplantation, there is currently no consensus on the best immunosuppressive strategies. Maintenance therapy typically consists of a triple-drug regimen including corticosteroids, a calcineurin inhibitor (ciclosporin or tacrolimus) and either a purine synthesis antagonist (mycophenolate mofetil or azathioprine) or a mammalian target of rapamycin inhibitor (sirolimus or everolimus). The incidence of acute and chronic rejection and of mortality after thoracic transplantation is still high compared with other types of solid organ transplantation. The high allogenicity and immunogenicity of the lungs justify the use of higher doses of immunosuppressants, putting lung transplant recipients at a higher risk of drug-induced toxicities. All immunosuppressants are characterized by large intra- and interindividual variability of their pharmacokinetics and by a narrow therapeutic index. It is essential to know their pharmacokinetic properties and to use them for treatment individualization through TDM in order to improve the treatment outcome. Unlike the kidneys and the liver, the heart and the lungs are not directly involved in drug metabolism and elimination, which may be the cause of pharmacokinetic differences between patients from all of these transplant groups. TDM is mandatory for most immunosuppressants and has become an integral part of immunosuppressive drug therapy. It is usually based on trough concentration (C(0)) monitoring, but other TDM tools include the area under the concentration-time curve (AUC) over the (12-hour) dosage interval or the AUC over the first 4 hours post-dose, as well as other single concentration-time points such as the concentration at 2 hours. Given the peculiarities of thoracic transplantation, a review of the pharmacokinetics and TDM of the main immunosuppressants used in thoracic transplantation is presented in this article. Even more so than in other solid organ transplant populations, their pharmacokinetics are characterized by wide intra- and interindividual variability in thoracic transplant recipients. The pharmacokinetics of ciclosporin in heart and lung transplant recipients have been explored in a number of studies, but less is known about the pharmacokinetics of mycophenolate mofetil and tacrolimus in these populations, and there are hardly any studies on the pharmacokinetics of sirolimus and everolimus. Given the increased use of these molecules in thoracic transplant recipients, their pharmacokinetics deserve to be explored in depth. There are very few data, some of which are conflicting, on the practices and outcomes of TDM of immunosuppressants after thoracic transplantation. The development of sophisticated TDM tools dedicated to thoracic transplantation are awaited in order to accurately evaluate the patients' exposure to drugs in general and, in particular, to immunosuppressants. Finally, large cohort TDM studies need to be conducted in thoracic transplant patients in order to identify the most predictive exposure indices and their target values, and to validate the clinical usefulness of improved TDM in these conditions. In part I of the article, we review the pharmacokinetics and TDM of calcineurin inhibitors. In part II, we will review the pharmacokinetics and TDM of mycophenolate and mammalian target of rapamycin inhibitors, and provide an overall discussion along with perspectives.

Opportunities to optimize tacrolimus therapy in solid organ transplantation: report of the European consensus conference

In 2007, a consortium of European experts on tacrolimus (TAC) met to discuss the most recent advances in the drug/dose optimization of TAC taking into account specific clinical situations and the analytical methods currently available and drew some recommendations and guidelines to help clinicians with the practical use of the drug. Pharmacokinetic, pharmacodynamic, and more recently pharmacogenetic approaches aid physicians to individualize long-term therapies as TAC demonstrates a high degree of both between- and within-individual variability, which may result in an increased risk of therapeutic failure if all patients are administered a uniform dose. TAC has undoubtedly benefited from therapeutic drug monitoring, but interpretation of the blood concentration is confounded by the relative differences between the assays. Single time points, limited sampling strategies, and area under concentration-time curve have all been considered to determine the most appropriate sampling procedure that correlates with efficacy. Therapeutic trough TAC concentration ranges have changed since the initial introduction of the drug, while still maintaining adequate immunosuppression and avoiding drug-related adverse effects. Pharmacodynamic markers have also been considered advantageous to the clinician, which may better reflect efficacy and safety, taking into account the between-individual variability rather than whole blood concentrations. The choice of method, differences between methods, and potential pitfalls of the method should all be considered when determining TAC concentrations. The recommendations of this consensus meeting regarding the analytical methods include the following: encourage the development and promote the use of analytical methods displaying a lower limit of quantification (1 ng/mL), perform careful validation when implementing a new analytical assay, participate in external proficiency testing programs, promote the use of certified material as calibrators in high-performance liquid chromatography with mass spectrometric detection methods, and take account of the assay and intermethod bias when comparing clinical trial outcomes. It is also important to consider that TAC concentrations may also be influenced by other factors such as specific pharmacokinetic characteristics associated with the population, drug interactions, pharmacogenetics, adverse events that may alter TAC concentrations, and any change in the oral formulation that may result in pharmacokinetic changes. This meeting emphasized the importance of obtaining multicenter prospective trials to assess the efficacy of alternative strategies to TAC trough concentrations whether it is other single time points or area under the concentration-time curve Bayesian estimation using limited sampling strategies and to select, standardize, and validate routine biomarkers of TAC pharmacodynamics.

Cytochrome P450 3A polymorphisms and immunosuppressive drugs: an update

Among the immunosuppressive drugs currently used in solid-organ transplantation, the calcineurin inhibitors cyclosporine and tacrolimus, and the mammalian target of rapamycin inhibitors sirolimus and everolimus, may be difficult to use because of large interindividual variability in their pharmacokinetic characteristics and a narrow therapeutic index. The promise of pharmacogenetics and pharmacogenomics is to elucidate the inherited basis of differences between individual responses to drugs, in order to identify the right drug and dose for each patient. As cytochrome P450 (CYP)3A4 and CYP3A5 are both involved in the metabolism of these drugs, the consequences of the polymorphism of these genes have been studied. It has been recently shown that the CYP3A5*3 polymorphism is associated with pharmacokinetics of tacrolimus and sirolimus. The association between the CYP3A4 and CYP3A5 polymorphisms and cyclosporine pharmacokinetics is more questionable. It is now of utmost importance to prospectively test these initial results to improve the individualized use of these drugs.

Population pharmacokinetics and bayesian estimator of cyclosporine in pediatric renal transplant patients

Cyclosporine A (CsA) is an immunosuppressive drug widely used in pediatric renal graft recipients. Its large interindividual pharmacokinetic variability and narrow therapeutic index render therapeutic drug monitoring necessary. However, information about CsA pharmacokinetics is scarce and no population pharmacokinetic (popPK) studies in these populations have been reported so far. to the objectives of this study were 1) to develop a PKpop model and identify the individual factors influencing the variability of CsA pharmacokinetics in pediatric kidney recipients; and 2) to build a Bayesian estimator allowing the estimation of the main PK parameters and exposure indices to CsA on the basis of a limited sampling strategy (LSS). The popPK analysis was performed using the NONMEM program. A total of 256 PK profiles of CsA collected in 98 pediatric renal transplant patients (mean age 9.7 +/- 4.5 years old) within the first year posttransplantation were studied. A 2-compartment model with first-order elimination, and Erlang distribution to describe the absorption phase, fitted the data adequately. For Bayesian estimation, the best LSS was determined based on its performance in estimating area under the concentration-time curve (AUC0-12h) and validated in an independent group of 20 patients. The popPK analysis identified body weight and posttransplant delay as individual factors influencing the apparent central volume of distribution and the apparent clearance, respectively. Bayesian estimation allowed accurate prediction of AUC0-12h using predose, C1h, and C3h blood samples with a mean bias between observed and estimated AUC of 0.5% +/- 11% and good precision (root mean square error = 10.9%). This article reports the first popPK study of CsA in pediatric renal transplant patients. It confirms the reliability and feasibility of CsA AUC estimation in this population. The body weight and the posttransplantation delay were identified to influence PK interindividual variability of CsA and were included in the Bayesian estimator developed, which could be helpful in further clinical trials.

Patient characteristics influencing ciclosporin pharmacokinetics and accurate Bayesian estimation of ciclosporin exposure in heart, lung and kidney transplant patients

BACKGROUND AND OBJECTIVES

Population pharmacokinetic studies of ciclosporin microemulsion are needed to identify the individual factors influencing ciclosporin pharmacokinetic variability in transplant patients and to design efficient tools for the accurate estimation of ciclosporin overall exposure (area under the plasma concentration-time curve from 0 to 12 hours [AUC12]). In the present retrospective study, a large database of heart, lung (with or without cystic fibrosis) and kidney (both adult and paediatric) transplant patients receiving ciclosporin microemulsion was analysed with the aims of (i) building a population pharmacokinetic model and finding the main covariates linked with ciclosporin microemulsion pharmacokinetic parameters; and (ii) developing a maximum a posteriori probability Bayesian estimator (MAP-BE) to estimate ciclosporin microemulsion pharmacokinetic parameters using a limited-sampling strategy.

METHODS

3,072 concentration data from 147 patients (i.e. 309 full pharmacokinetic profiles) were analysed using the nonlinear mixed-effects model program NONMEM. The influence of numerous covariates was tested, and the final model was validated by data splitting. For Bayesian estimation, the best limited-sampling strategy was determined based on the D-optimality criterion, and validation performed in an independent group of 60 patients.

RESULTS

The pharmacokinetics of ciclosporin microemulsion were accurately described by a two-compartment model with Erlang distribution for the absorption process. The type of graft and post-transplantation period were identified as significant sources of variability of the absorption parameter. Both apparent volume of the central compartment after oral administration (V1/F) and apparent oral clearance (CL/F) increased with bodyweight. The best limited-sampling strategy for Bayesian estimation was 0 hour, 1 hour and 3 hour post-dose, providing accurate estimation of ciclosporin microemulsion AUC12 in all patients of the test group, with a mean bias of 2.0 +/- 10.5% (range: -19.1% to -21.4% and 95% CI -0.6, +4.7).

CONCLUSION

Population pharmacokinetic analysis of ciclosporin microemulsion in allograft transplants resulted in the design of a new pharmacokinetic model for ciclosporin microemulsion, identification of significant covariates and the design of an accurate MAP-BE based on three blood concentrations and these covariates.

Recent advances in pharmacokinetic modeling

A major part of the science of pharmacokinetics is the modeling of the underlying processes that contribute to drug disposition. The purpose of pharmacokinetic models is to summarize the knowledge gained in preclinical and clinical studies at various stages in drug development and to rationally guide future studies with the use of adequately predictive models. This review highlights a variety of recent advances in mechanistic pharmacokinetic modeling. It is aimed at a broad audience, and hence, an attempt was made to maintain a balance between technical information and practical applications of pharmacokinetic modeling. It is hoped that drug researchers from all disciplines would be able to get a flavor of the function and capacity of pharmacokinetic modelers and their contribution to drug development. While this review is not intended to be a technical reference on modeling approaches, the roles of statistical applications and population methodologies are discussed where appropriate.

Pharmacokinetic study of tacrolimus in cystic fibrosis and non-cystic fibrosis lung transplant patients and design of Bayesian estimators using limited sampling strategies

OBJECTIVES

To: (i) test different pharmacokinetic models to fit full tacrolimus concentration-time profiles; (ii) estimate the tacrolimus pharmacokinetic characteristics in stable lung transplant patients with or without cystic fibrosis (CF); (iii) compare the pharmacokinetic parameters between these two patient groups; and (iv) design maximum a posteriori Bayesian estimators (MAP-BE) for pharmacokinetic forecasting in these patients using a limited sampling strategy.

METHODS

Tacrolimus blood concentration-time profiles obtained on three occasions within a 5-day period in 22 adult lung transplant recipients (11 with CF and 11 without CF) were retrospectively studied. Three different one-compartment models with first-order elimination were tested to fit the data: one with first-order absorption, one convoluted with a gamma distribution to describe the absorption phase, and one convoluted with a double gamma distribution able to describe secondary concentration peaks. Finally, Bayesian estimation using the best model and a limited sampling strategy was tested in the two groups of patients for its ability to provide accurate estimates of the main tacrolimus pharmacokinetic parameters and exposure indices.

RESULTS

The one-compartment model with first-order elimination convoluted with a double gamma distribution gave the best results in both CF and non-CF lung transplant recipients. The patients with CF required higher doses of tacrolimus than those without CF to achieve similar drug exposure, and population modelling had to be performed in CF and non-CF patients separately. Accurate Bayesian estimates of area under the blood concentration-time curve from 0 to 12 hours (AUC12), AUC from 0 to 4 hours, peak blood concentration (Cmax) and time to reach Cmax were obtained using three blood samples collected at 0, 1 and 3 hours in non-CF patients (correlation coefficient between observed and estimated AUC12, R2 = 0.96), and at 0, 1.5 and 4 hours in CF patients (R2 = 0.91).

CONCLUSION

A particular pharmacokinetic model was designed to fit the complex and highly variable tacrolimus blood concentration-time profiles. Moreover, MAP-BE allowing tacrolimus therapeutic drug monitoring based on AUC12 were developed.

Level A in vitro-in vivo Correlation (IVIVC) Model with Bayesian Approach to Formulation Series

In vitro-in vivo correlation (IVIVC) models for formulation series are useful in drug development, but the current models are limited by their inability to include data variability in the predictions. Our goal was to develop a level A IVIVC model that provides predictions with probabilities. The Bayesian approach was used to describe uncertainty related to the model and the data. Three bioavailability studies of levosimendan were used to develop IVIVC model. Dissolution was tested at pH 5.8 with basket. The IVIVC model with Bayesian approach consisted of prior and observed data. All observed data were fitted to the one-compartment model together with prior data. Probability distributions of pharmacokinetic parameters and concentration time profiles were obtained. To test the external predictability of IVIVC model, only dissolution data of formulations E and F were used. The external predictability was good. The possibility to utilize all observed data when constructing IVIVC model, can be considered as a major strength of Bayesian approach. For levosimendan capsule data traditional IVIVC model was not predictable. The usefulness of IVIVC model with Bayesian approach was shown with our data, but the same approach can be used more widely for formulation optimization and for dissolution based biowaivers.

Time-dependent pharmacokinetics of cyclosporine (Neoral) in de novo renal transplant patients

PURPOSE

A model for the large scale temporal trend in the oral bioavailability of microemulsion cyclosporine (Neoral) (CsA) is established, with dependence on post-(renal) transplantation day (PTD).

METHODS

Twenty de novo adult renal transplant recipients were monitored for CsA administered orally q12 h. A model development group (11 patients, 315 blood concentration samples) was screened at 2 h (C(2); n = 92), 3 h (C(3); n = 56) and at predose troughs (C(min); n = 167) over periods of up to 75 days. The final model was tested in nine patients with C(min) (n = 580) monitored across 4-5 years. The doses varied between 100 and 538 mg with an apparent hyperbolic trend in C(2)/dose vs. PTD. A nonlinear mixed effects modelling (NONMEM) approach was used to obtain population and individual patient one-compartment pharmacokinetic (PK) parameters for oral CsA, which carry implicit the bioavailability (F).

RESULTS

In the final PK model (PK-f) the F was modelled via a simple function for the temporal (days) trend of the bioavailability after transplantation as, F(f) = 1-alpha * exp(-lambda * PTD) resulting in a 28% reduction in the unexplained intra-individual variability. The population PK-f parameters were, for apparent clearance [mean, 95% confidence interval (interindividual CV%)] Cl/F(f) = 17.0 (13.8-20.2) L/h (27%), apparent central compartment volume of distribution, V/F(f) = 134 L (108-160) (28%), and lambda = 0.037/day (0.005-0.069) (120%). The absorption rate k(a) and the parameter alpha were approximated iteratively as 4/h and 0.62 respectively. The PK-f was structurally superior to the base model in explaining part of the within subject (occasion) variability and predicting the exposure surrogates C(2) and C(3). Also, the PK-f was better than the base model with Bayesian fitting of individual profiles in that group.

CONCLUSION

The PTD-dependent relative bioavailability model provides a rational means of steering dose titration of CsA in de novo renal transplantation patients by removing the large scale PK adjustment signal, either through nomograms or as a Bayesian prior.

[A case report of unresectable gallbladder cancer that responded remarkably to the combination of thalidomide, celecoxib, and gemcitabine]

Gallbladder cancer is an asymptomatic disease in the early stage and no therapeutic measure is available except surgical intervention. The prognosis for patients with advanced,i.e., unresectable or metastatic disease is dismal, with median survival usually being less than 6 months if not treated with chemotherapy. To date, chemotherapy for gallbladder cancer has been limited by the absence of agents with effective cytotoxic activity. Thalidomide has been shown to have antiangiogenic and immunomodulatory effects, including the inhibition of vascular endothelial growth factor, basic fibroblast growth factor and tumor necrosis factor alpha. Celecoxib is a potent selective COX-2 inhibitor. The reported biological consequences of COX-2 up-regulation include inhibition of apoptosis, increased metastatic potential and promotion of angiogenesis. These events may contribute to cell transformation and tumor progression. Antiangiogenesis represents a significant new strategy for cancer treatment. Therefore,it is important to accept a wide range of different inhibitors such as thalidomide and selective COX-2 inhibitors with conventional cytotoxic agents. Here we show a case of unresectable gallbladder cancer with remarkable improvement in CA19-9 and prolongation of life.

Seeking optimal prescription of cyclosporine ME

Optimal use of cyclosporine microemulsion (CsA ME) in transplant recipients is still a matter of debate. Therapeutic drug monitoring of CsA ME is needed because high variability of inter- and intraindividual exposure to this drug has been reported. Thus, consensus guidelines have been recommended, but the ideal method of follow-up has not yet been found. Pharmacokinetic studies have shown that the 2-hour postdose (C2) sample concentration is more closely correlated with the risk of acute rejection and with toxicity in solid organ recipients compared with the trough (C0) concentration within the first 3 months posttransplantation. For some years, this time point has therefore been used to monitor patients treated with CsA ME. However, there are still some technical (accurate dilution) and practical concerns (education of the patient). Moreover, the target levels of C2, in particular after the first year posttransplantation, are less well defined. Pharmacogenetic studies of the MDR-1 gene as well as the CYP3A4 and CYP3A5 gene polymorphisms could not yet demonstrate any clear influence on the interindividual variations on the pharmacokinetic profile of CsA ME.

Clinical Application of Population Pharmacokinetic Methods Developed for Immunosuppressive Drugs

After a brief overview of the relevant exposure indices for cyclosporine (CsA) and mycophenolate mofetil (MMF), as well as of the different steps necessary to develop maximum a posteriori Bayesian estimators (MAP-BE), this paper presents applications of MAP-BE for CsA or MMF to clinical cases and clinical trials. Ina renal transplant patient under CsA, grade I chronic allograft nephropathy was found at the sixth month posttransplantation, with CsA CO slightly above the target range and C2 markedly below; the AUCO0-12 h Bayesian estimate was quite high, at 5.6 mg h/L, as compared with a mean value of 4.3+0.9 mg.h/L in stable renal transplants at this period; the inconsistent C2 level found could be explained by delayed absorption of CsA in this patient, in which case C2 no longer represents the major part of the AUC. The patient was switched to sirolimus, which resulted in a slow and significant improvement of graft function with no acute rejection. In a 50-year-old female renal transplant recipient administered MMF and CsA and with a very favorable outcome otherwise, progressive anemia appeared 8 months posttransplantation. Clinical investigations were negative,but Bayesian estimation showed a rather high MPA AUCO0-12 h (69.8 mg h/L). After MMF dose reduction, hemoglobin level progressively returned to normal, without erythropoietin injection or blood transfusion. Finally, the feasibility of accurate dose adjustment using these MAP-BE is shown through preliminary results from 2 ongoing multicenter clinical trials, 1 evaluating an AUC-controlled cyclosporine-sparing strategy in stable renal transplants, the second evaluating the benefit of MMF therapeutic drug monitoring based on MPA AUCO0-12 h in de novo renal transplant recipients.

Predicting and preventing adverse drug reactions in the very old

The size of the elderly population has been increasing steadily for several years. Individuals in this age group often have several concomitant diseases that require treatment with multiple medications. These drugs, for various reasons and especially as a consequence of potential accumulation, may be associated with adverse reactions. Of the numerous factors that can favour the occurrence of these adverse drug reactions, the most important are the pathophysiological consequences of aging, particularly as these apply to the very old. Although absorption of drugs is not usually reduced in the elderly, diffusion, distribution and particularly elimination decline with age. Furthermore, while hepatic metabolic function is fairly normal, renal function is usually markedly depressed in very old individuals, and this can translate into clinical consequences if it is not taken into account. This is why, before administration of any drug in the elderly, evaluation of glomerular filtration rate is essential. Validated estimations such as those obtained from the classical Cockcroft-Gault formula or from more recent methodologies are required. In addition to reductions in various organ functions, factors connected with very old age such as frailty, falls, abnormal sensitivity to medications and polypathology, all of which tend to be more common in the last years of life, all directly impact on adverse drug reaction occurrence. Given these characteristics of the elderly population, the best way to reduce the prevalence of adverse drug reactions in this group is to limit drug prescription to essential medications, make sure that use of prescribed agents is clearly explained to the patient, give drugs for as short a period as possible, and periodically re-evaluate all use of drugs in the elderly.

Cyclosporine Monitoring With 2-Hour Postdose Levels in Heart Transplant Recipients

Cyclosporine therapeutic drug monitoring based on 2-hour postdose concentration (C2) compared with conventional trough concentration (C0) can improve clinical outcomes for de novo renal and liver transplant patients. However, in heart transplant patients, published studies are limited. To determine the clinical significance of C2 compared with C0 following orthotopic heart transplantation, the authors measured CsA at C0 and C2 and estimated CsA area under the curve (AUC) using Bayesian estimation and 4 sparse sample algorithms in a cross section of 31 adult patients receiving triple-drug immunosuppression with CsA, mycophenolate mofetil (MMF), and prednisone. CsA was measured using a validated HPLC method. Endomyocardial biopsies were graded based on the ISHLT system. Mean +/- SD values for CsA dose, C0, and C2 were 4.8 +/- 1.4 mg/kg/d, 240 +/- 62 microg/L, and 1319 +/- 469 microg/L, respectively. Correlation with AUC, using different estimation algorithms, was better for C2 (r(2) = 0.79-0.99) than for C0 (r(2)= 0.11-0.52). The mean +/- SD values for C0 (microg/L) and C2 (microg/L) for rejectors (n = 3) were 215 +/- 68 and 949 +/- 204 versus 242 +/- 62 and 1359 +/- 474 for the nonrejectors (P = 0.66 and 0.12, respectively). Fisher exact test P values using the median as threshold value for C0 and C2 (234 microg/L and 1251 microg/L, respectively) were 0.6 and 0.1. Analysis of the data revealed that C0 values in rejectors have wider variability than C2. There were no rejectors among the 16 patients exceeding the C2 median value; for C0, however, there was not an easily identifiable threshold value. There is a trend for a significant relationship between C2 and the incidence of rejection, but the number of rejectors was too small to reach statistical significance. A prospective concentration-control de novo study design is recommended as the most appropriate way to fully evaluate the potential utility of C2 monitoring in heart transplant patients.

Bayesian estimation of cyclosporin exposure for routine therapeutic drug monitoring in kidney transplant patients

AIMS

AUC-based monitoring of cyclosporin A (CsA) is useful to optimize dose adaptation in difficult cases. We developed a population pharmacokinetic model to describe dose-exposure relationships for CsA in renal transplant patients and applied it to the Bayesian estimation of AUCs using three blood concentrations.

METHODS

A total of 84 renal graft recipients treated with CsA microemulsion were included in this study. Population pharmacokinetic analysis was conducted using NONMEM. A two-compartment model with zero-order absorption and a lag time best described the data. Bayesian estimation was based on CsA blood concentrations measured before dosing and 1 h and 2 h post dose. Predictive performance was evaluated using a cross-validation approach. Estimated AUCs were compared with AUCs calculated by the trapezoidal method. The Bayesian approach was also applied to an independent group of eight patients exhibiting unusual pharmacokinetic profiles.

RESULTS

Mean population pharmacokinetic parameters were apparent clearance 30 l h(-1), apparent volume of distribution 79.8 l, duration of absorption 52 min, absorption lag time 7 min. No significant relationships were found between any of the pharmacokinetic parameters and individual characteristics. A good correlation was obtained between Bayesian-estimated and experimental AUCs, with a mean prediction error of 2.8% (95% CI [-0.6, 6.2]) and an accuracy of 13.1% (95% CI [7.5, 17.2]). A good correlation was also obtained in the eight patients with unusual pharmacokinetic profiles (r(2) = 0.96, P < 0.01).

CONCLUSIONS

Our Bayesian approach enabled a good estimation of CsA exposure in a population of patients with variable pharmacokinetic profiles, showing its usefulness for routine AUC-based therapeutic drug monitoring.

Easy-to-use, accurate and flexible individualized Bayesian limited sampling method without fixed time points for ciclosporin monitoring after liver transplantation

BACKGROUND

New methods to estimate the systemic exposure to ciclosporin such as the level 2 h after dosing and limited sampling formulas may lead to improved clinical outcome after orthotopic liver transplantation. However, most strategies are characterized by rigid sampling times.

AIM

To develop and validate a flexible individualized population-pharmacokinetic model for ciclosporin monitoring in orthotopic liver transplantation.

METHODS

A total of 62 curves obtained from 31 patients at least 0.5 year after orthotopic liver transplantation were divided into two equal groups. From 31 curves, relatively simple limited sampling formulas were derived using multiple regression analysis, while using pharmacokinetic software a two-compartment population-pharmacokinetic model was derived from these same data. We then tested the ability to estimate the AUC by the limited sampling formulas and a different approach using several limited sampling strategies on the other 31 curves. The new approach consists of individualizing the mean a priori population-pharmacokinetic parameters of the two-compartment population-pharmacokinetic model by means of maximum a posteriori Bayesian fitting with individual data leading to an individualized population-pharmacokinetic limited sampling model. From the individualized pharmacokinetic parameters, AUC(0-12h) was calculated for each combination of measured blood concentrations. The calculated AUC(0-12h) both from the limited-sampling formulas and the limited-sampling model were compared with the gold standard AUC(0-12h) (trapezoidal rule) by Pearson's correlation coefficient and prediction precision and bias were calculated.

RESULTS

The AUC(0-12h) value calculated by individualizing the population-pharmacokinetic model using several combinations of measured blood concentrations: 0 + 2 h (r(2) = 0.94), 0 + 1 + 2 h (r(2) = 0.94), 0 + 1 + 3 h (r(2) = 0.92), 0 + 2 + 3 h (r(2) = 0.92) and 0 + 1 + 2 + 3 h (r(2) = 0.96) had excellent correlation with AUC(0-12h), better than limited sampling formulas with less than three sampling time points. Even trough level with limited sampling method (r(2) = 0.86) correlated better than the level after 2 h of dosing (r(2) = 0.75) or trough level (r(2) = 0.64) as single values without limited sampling method. Moreover, the individualized population-pharmacokinetic model had a low prediction bias and excellent precision.

CONCLUSION

Multiple rigid sampling time points limit the use of limited sampling formulas. The major advantage of the Bayesian estimation approach presented here, is that blood sampling time points are not fixed, as long as sampling time is known. The predictive performance of this new approach is superior to trough level and that after 2 h of dosing and at least as good as limited sampling formulas. It is of clear advantage in busy out-patient clinics.

Immunosuppressant Drug Monitoring: Is the Laboratory Meeting Clinical Expectations?

OBJECTIVE:

To review the literature relating to immunosuppressant drug measurement as performed in therapeutic drug monitoring laboratories associated with transplantation centers and consider whether the assay methods widely used for patient dosage management achieve acceptable quality criteria in the context of other sources of variability with these drugs.

DATA SOURCES:

Articles used were accessed primarily through MEDLINE, as well as references cited in related publications. Searches were restricted to organ transplantation in humans.

STUDY SELECTION AND DATA EXTRACTION:

Emphasis was placed on the literature relating to the quality of immunosuppressant drug assays, their limitations, and evidence of clinical benefit in dosage individualization.

DATA SYNTHESIS:

There is a dilemma evident between the quality of the analytical services offered by some diagnostic immunoassay manufacturers and the ability of a significant number of clinical laboratories globally to select only appropriate assay methods.

CONCLUSIONS:

In many cases, clinical laboratories fail to meet the reasonable clinical expectations required for interpretation of immunosuppressant drug assay results as an adjunct to optimal dosage individualization and patient care.

Cytochrome P450 3A polymorphisms and immunosuppressive drugs

With the use of powerful immunosuppressive drugs, organ transplantation has become the treatment of choice for many cases of end-stage chronic organ failure. The calcineurin inhibitors, cyclosporine and tacrolimus, which are the backbone of current immunosuppressive regimens, may be difficult to use because of the large interindividual variability of their pharmacokinetic characteristics and a narrow therapeutic index. Since cytochrome P450 (CYP) 3A4 and CYP3A5 are both involved in their metabolism, the consequences of the polymorphism of these enzymes were studied. It has been recently shown that the CYP3A5*3 polymorphism is associated with both the pharmacokinetics and pharmacodynamic consequences of tacrolimus. The association between the CYP3A4 and CYP3A5 polymorphisms and cyclosporine pharmacokinetics is more questionable. It is important to test these initial results prospectively to improve the individualized use of these drugs.

Dose adjustment strategy for oral microemulsion formulation of cyclosporine: population pharmacokinetics-based analysis in kidney transplant patients

The present study aims to determine the population pharmacokinetic parameters of cyclosporine (CsA) after multiple oral administration of the microemulsion formulation, Neoral, in kidney transplant patients and to propose a limited sampling strategy to predict AUC(0-4h) using them and the Bayesian method. The AUC(0-4h) is a parameter that has recently been recommended as an index for the dose adjustment in therapeutic drug monitoring of CsA. Blood samples were obtained at the trough level and at hourly intervals up to 5 hours from 125 patients (78 male and 47 female) who were receiving Neoral twice daily, and whole-blood concentrations of CsA were measured. The population pharmacokinetic parameters were estimated using the NONMEM computer program and a linear two-compartment model with first-order absorption. The observed AUC0-4h and concentrations at different sampling times were compared with those computer-predicted by the Bayesian method, using the population pharmacokinetic parameters and 2 or 3 concentrations from those at 0 h (C(0)), 1 h (C(1)), and 2 h (C(2)) after administration. Typical values for the absorption rate constant (k(a)), elimination rate constant (k(el)), apparent volume of distribution for the central compartment (Vd/F), and oral clearance (CL/F) calculated by population pharmacokinetic analysis were 2.16 hours(-1), 0.547 hours(-1), 43.3 L, and 23.7 L/h, respectively. The CsA concentrations predicted using either the 2-point or 3-point sampling strategy exhibited an excellent correlation with the observed values (R(2) > 0.81), and accordingly, the predicted AUC(0-4h) values were in excellent agreement with those observed. The best predictability of AUC(0-4h) was found for the 3-point sampling strategy using C(0), C(1), and C(2), closely followed by a 2-point sampling strategy using C(1) and C(2). The present findings suggest that a simplified strategy based on population pharmacokinetics can accurately predict AUC(0-4h) from concentrations at 2 or 3 sampling time points, providing an excellent method for the daily dose adjustment of Neoral in routine clinical use for kidney transplant patients.

Population pharmacokinetics and Bayesian estimation of mycophenolic acid concentrations in stable renal transplant patients

BACKGROUND

Therapeutic drug monitoring of mycophenolic acid (MPA) may minimise the risk of acute rejection after transplantation. Area under the curve (AUC) rather than trough concentration-based monitoring is recommended and models for AUC estimation are needed.

OBJECTIVES

To develop a population pharmacokinetic model suitable for Bayesian estimation of individual AUC in stable renal transplant patients.

PATIENTS AND METHODS

The population pharmacokinetics of MPA were studied using nonlinear mixed effects modelling (NONMEM) in 60 patients (index group) receiving MPA on a twice-daily basis. Ten blood samples were collected at fixed timepoints from ten patients and four blood samples were collected at sparse timepoints from 50 patients. Bayesian estimation of individual AUC was made on the basis of three blood concentration measurements and covariates. The predictive performances of the Bayesian procedure were evaluated in an independent group of patients (test group) comprising ten subjects in whom ten blood samples were collected at fixed timepoints.

RESULTS

A two-compartment model with zero-order absorption best fitted the data. Covariate analysis showed that bodyweight was positively correlated with oral clearance. However, the weak magnitude of the reduction in variability (from 34.8 to 28.2%) indicates that administration on a per kilogram basis would be of limited value in decreasing interindividual variability in MPA exposure. Bayesian estimation of pharmacokinetic parameters using samples drawn at 20 minutes and 1 and 3 hours enabled estimation of individual AUC with satisfactory accuracy (bias 7.7%, range of prediction errors 0.43-15.1%) and precision (root mean squared error 12.4%) as compared with the reference value obtained using the trapezoidal method.

CONCLUSION

This paper reports for the first time population pharmacokinetic data for MPA in stable renal transplant patients, and shows that Bayesian estimation can allow accurate prediction of AUC with only three samples. This method provides a tool for therapeutic drug monitoring of MPA or for concentration-effect studies. Its application to MPA monitoring in the early period post-transplantation needs to be evaluated.

Population pharmacokinetic modeling of oral cyclosporin using NONMEM: comparison of absorption pharmacokinetic models and design of a Bayesian estimator

There have been very few population pharmacokinetic (PopPK) studies and Bayesian forecasting methods dealing with cyclosporin (CsA) so far, probably because of the difficulty of modeling the particular absorption profiles of CsA. The present study was conducted in stable renal transplant patients treated with Neoral and employed the NONMEM program. Its goals were (1) to develop a population pharmacokinetic model for CsA based on an Erlang frequency distribution (which describes asymmetric S-shaped absorption profiles) combined with a 2-compartment model; (2) to compare this model with models combining a time-lag parameter and either a zero-order or first-order rate constant and with a model based on a Weibull distribution; and (3) to develop a PK Bayesian estimator for full AUC estimation based on that "Erlang model." The PopPK model was developed in an index set of 70 patients, and then individual PK parameters and AUC were estimated in 10 other patients using Bayesian estimation. The "Erlang" model best described the data, with mean absorption time (MAT), apparent clearance (CL/F), and apparent volume of the central compartment (Vc/F) of 0.78 hours, 26.3 L/h, and 76 L, respectively (interindividual variability CV = 33, 30, and 48%). Bayesian estimation allowed accurate prediction of systemic exposure using only 3 samples collected at 0, 1, and 3 hours. Regression analysis found no significant difference between the predicted and observed concentrations (10 per patient), and AUC(0-12) were estimated with a nonsignificant bias (0.6 to 8.7%) and good precision (RMSE = 5.3%). In conclusion, the Erlang distribution best described CsA absorption profiles, and a Bayesian estimator developed using this model and a mixed-effect PK modeling program provided accurate estimates of CsA systemic exposure using only 3 blood samples.

Switching monitoring of emulsified cyclosporine from trough level to 2-hour level in stable liver transplant patients

After orthotopic liver transplantation (OLT) many patients use emulsified cyclosporine. Recent data showed that blood levels 2 hours after dosing (C-2) better reflect systemic exposure to the drug (area under the blood concentration time curve) than trough levels (C-0) do. We investigated difference in dosage, creatinine clearance (CrCl), blood pressure (BP), freedom from rejection, and relation of C-2, C-0, and AUC while switching 31 stable patients more than 6 months after OLT from C-0 to C-2 monitoring. With C-0 between 90 and 150 ng/mL we collected 24-hour urine, while blood samples were taken at t = 0, 1, 2, 3, 4, 6, and 8 hours after dosing to measure cyclosporine, creatinine, liver tests, and blood pressure and calculated AUC and CrCl. Target AUC was calculated based on C-0. Then the dose was adjusted to two subsequent C-2 values of 600 ng/mL +/- 15%, the above was repeated, and the differences were assessed. Cyclosporine dose was reduced in 21/31 patients (68%) and remained unchanged in 10/31 patients (32%) after conversion. Mean lowering was 69 mg daily (26.9 %, P < 0.0001). After dose reduction the mean increase of CrCl was 7.93 ml/min (11.6%, P = 0.016). Only systolic and mean morning BP decreased slightly but significantly. C-2 correlated better with AUC0-12 (r2 = 0.75) than C-0 (r2 = 0.64). However, 13/21 patients had a second AUC below target AUC and 2 of these 13 patients developed rejection after conversion to C-2 levels. In conclusion, while C-0 monitoring frequently results in overdosing and more renal dysfunction, C-2 monitoring may lead to episodes of underdosing and rejection. Therefore better ways of monitoring cyclosporine dosing need to be devised.

Modelling Ciclosporin Double-Peak Absorption Profiles in the Early Post-Transplantation Period

OBJECTIVE

To apply a recent double-peak absorption model to ciclosporin.

METHODS

Pharmacokinetic evaluation was performed in 20 patients who had undergone de novo renal transplantation and were receiving immunosuppressive therapy with corticosteroids, mycophenolate mofetil and ciclosporin Neoral. Data were analysed by nonlinear mixed-effects modelling using individual and population approaches.

RESULTS

Six patients presented pharmacokinetic profiles with two peaks, whereas 14 curves apparently had a single, sometimes delayed and wide, peak. A one-compartment model with first-order elimination in association with the double-peak absorption model best fitted the data. This model reliably described the pharmacokinetics of ciclosporin, whether or not a double peak was present on the concentration-time profiles.

CONCLUSIONS

The double-peak absorption model could be useful to optimise ciclosporin exposure in the early post-transplantation period.

Relationship between CsA trough blood concentration and severity of acute graft-versus-host disease after paediatric stem cell transplantation from matched-sibling or unrelated donors

In order to determine optimal CsA trough blood concentrations (TBC) in the early post transplantation period, we analysed relationships between TBC and acute graft-versus-host disease (aGVHD) in paediatric SCT. A total of 94 children consecutively underwent allogeneic stem cell transplantation (SCT) from: matched-sibling (MSD) (n=36), mismatched-related (MMRD) (n=3) and unrelated donors (UD) (n=55). GVHD prophylaxis usually included CsA alone or with methotrexate. Antithymocyte globulin was added in UD-SCT. TBC during the first weeks of post transplantation were estimated retrospectively by a Bayesian pharmacokinetic method and statistically associated with aGVHD. In MSD-SCT, the mean TBC during the first 2 weeks post transplantation were 42+/-10 and 90+/-7 ng/ml, respectively, in patients with grade II-IV and 0-I aGVHD (P=0.001). In SCT from UD and MMRD, TBC were 73+/-4 vs 95+/-8 ng/ml (P=0.284). For TBC >85 ng/ml, no patient developed grade II-IV aGVHD, 10 developed mild aGVHD and 30 had no aGVHD. For TBC <65 ng/ml, 7/11 patients receiving an MSD-SCT and 4/18 receiving an UD- or MMRD-SCT developed grade II-IV aGVHD. The mean TBC corresponding to each grade were: no GVHD: 101+/-10 ng/ml, mild: 77+/-11 ng/ml, moderate: 61+/-13 ng/ml, severe: 56+/-15 ng/ml (P <0.001). These results reveal a strong relationship between TBC during the early post transplantation period and the severity of aGVHD in paediatric SCT.

Limited sampling strategies using Bayesian estimation or multilinear regression for cyclosporin AUC(0-12) monitoring in cardiac transplant recipients over the first year post-transplantation

OBJECTIVE

The aim of this study was to develop routinely applicable limited sampling strategies for assessing cyclosporin (CsA) AUC(0-12 h), and possibly other exposure indices such as AUC(0-4 h) and C(max), in heart transplant patients over the first year post-transplantation.

METHODS

First, the individual pharmacokinetics (PKs) of 14 adult heart-transplant patients receiving Neoral were assessed at three post-transplantation periods, at the end of the first week (W1), the third month (M3) and the first year (Y1). To fit blood concentrations, a PK model specially developed for oral CsA was applied. Second, two statistical methods were compared for AUC(0-12 h) estimation using a limited sampling strategy (maximum of three blood samples): multiple regression analysis (MR) and Bayesian estimation (BE).

RESULTS

No significant difference was observed between the individual PK parameters at M3 and Y1, so population modelling was performed taking as a whole the concentration data collected at M3 and Y1. On the contrary, a significant difference ( P<0.05) was found for the C2/dose ratio between W1 and M3 and between W1 and Y1 (mean+/-SD =5.47+/-2.33; 7.78+/-1.05; 6.98+/-2.17 ml(-1 )for W1, M3 and Y1, respectively). Also, C(max)/dose and A were found significantly lower at W1 than at M3 ( P<0.01 and P<0.005, respectively), while lambda(1) was significantly higher at W1 than at both M3 and Y1 ( P<0.01). Using three sampling times (t0 h, t1 h and t3 h), BE allowed an accurate prediction of AUC(0-12 h) (mean bias =3.06+/-12.16%; +1.50+/-1.61%; and -0.20+/-11.42% at W1, M3 and Y1, respectively), AUC(0-4 h )and C(max). MR led to satisfactory estimation of AUC(0-12 h) using only two blood samples collected 2 h and 6 h post-dose (R=0.956-0.993; bias =-5.22 to +4.41; precision =6.38 to 9.90%), but this method is unable to estimate any other exposure index and requires strict respect of sampling times, contrary to BE.

CONCLUSION

Neoral monitoring based on full or abbreviated AUC is possible using BE or MR in heart transplant patients over the first year post-transplantation. BE provides a good description of the individual PK profiles and thus might be useful not only in case of potential discrepancies between C2 and clinical findings, but also for clinical trials aimed at finding optimum PK monitoring in heart recipients.

Bayesian forecasting of oral cyclosporin pharmacokinetics in stable lung transplant recipients with and without cystic fibrosis

The aims of the current study were (1) to study Neoral pharmacokinetics (PK) in stable lung recipients with or without cystic fibrosis (CF), (2) to compare Neoral PK between these two groups, and (3) to design Bayesian estimators for PK forecasting and dose adjustment in these patients using a limited number of blood samples. The individual PK of 19 adult lung transplant recipients, 9 subjects with CF and 10 subjects without CF, were retrospectively studied. Three profiles obtained within 5 days were available for each patient. A PK model combining a gamma distribution to describe the absorption profile and a two-compartment model were applied. Different exposure indices were estimated using nonlinear regression and Bayesian estimation. The PK model developed reliably described the individual PK of Neoral in lung transplant patients with and without CF, and the values of the first and second half-lives were different in these two populations (lambda(1) = 4.14 +/- 3.01 vs. 2.16 +/- 1.75 h(-1); P < 0.01; lambda(2) = 0.36 +/- 0.11 vs. 0.49 +/- 0.12 h(-1); P < 0.01), while the mean absorption time and standard deviation of absorption time tended to be less in patients with cystic fibrosis (P < 0.1). Also, the patients with CF required higher doses than those without CF to achieve similar drug exposure. Consequently, population modeling was performed in CF and non-CF patients separately. Bayesian estimation allowed accurate prediction of AUC(0-12), AUC(0-4), C(max), and T(max) using three blood samples collected at T0h, T1h, and T3h in both groups. This study demonstrated the applicability and good performance of the PK model previously developed for oral cyclosporin and of the MAP Bayesian estimation of cyclosporin systemic exposure in CF and non-CF patients. Moreover, it is the first to propose a monitoring tool specifically designed for cyclosporin monitoring in patients with CF.

Forecasting of Blood Tacrolimus Concentrations Based on the Bayesian Method in Adult Patients Receiving Living-Donor Liver Transplantation

OBJECTIVE

To evaluate Bayesian prediction of blood tacrolimus concentrations in adult patients receiving living-donor liver transplantation (LDLT) using previously obtained population pharmacokinetic parameters.

PATIENTS AND METHODS

Data were retrospectively collected from 47 adult patients receiving LDLT who were not included in the estimation of population pharmacokinetic parameters. Blood tacrolimus concentrations were predicted without or with the empirical Bayesian method using sparse samples obtained in the previous week. Predictive performance of the concentrations was evaluated by the mean prediction error (ME), mean absolute prediction error (MAE) and root mean square error (RMSE) as well as the percentage of successful predictions (percentage of absolute prediction error less than 3 microg/L, %PRED3).

RESULTS

Concentrations predicted by the population mean pharmacokinetic parameter values coincided well with observed concentrations during the period of tacrolimus infusion immediately after the operation. For concentrations during subsequent oral therapy with tacrolimus, predictability by the population mean pharmacokinetic parameter values alone was not satisfactory. Bayesian forecasting using one or two blood concentrations obtained in the previous week significantly decreased (p<0.05) MAE and RMSE compared with predictions based on the population mean pharmacokinetic parameters on postoperative days 21 and 28, but not on day 14. During postoperative days 15-21, %PRED3 was increased to 68.6% or 71.2% with the Bayesian method using one or two blood concentrations, respectively, from 44.9% with the population mean pharmacokinetic parameter values.

CONCLUSION

The present study demonstrated the applicability of the Bayesian method with use of one or two samples for prediction of blood tacrolimus concentrations in adult patients receiving LDLT.

Cyclosporin monitoring in Australasia: 2002 update of consensus guidelines

Therapeutic drug monitoring of cyclosporin (CsA) has been established as part of the routine clinical treatment of patients following organ transplantation for more than 20 years, and based on contemporary knowledge, many consensus guidelines have been published to assist clinics and laboratories attain optimal strategies for patient care. This article addresses the newer directions in CsA monitoring, with particular reference to the Australasian situation that has evolved since the 1993 Australasian guideline. These changes have included the introduction of alternative assay methodologies, changed CsA formulation from Sandimmun to Neoral throughout Australasia, and alternatives to trough concentration (C0) monitoring, especially 2-hour concentration (C2) monitoring and associated validated dilution protocols to accurately quantitate the higher whole blood CsA concentrations. The revision was prepared following a recent survey of all Australasian CsA-monitoring laboratories where discordant practices were evident.

New concepts in cyclosporine monitoring

PURPOSE OF REVIEW

Inadequate cyclosporine exposure is a key risk factor for acute rejection, and may contribute to the development of chronic rejection and graft failure. Pre-dose monitoring does not accurately measure drug exposure because of extensive inter- and intra-patient variability in cyclosporine absorption and metabolism. Limited sampling, using individual timed specimens, offers a new, simple and accurate alternative for clinical monitoring of cyclosporine.

RECENT FINDINGS

The area under the first 4 h of the concentration-time curve (AUC ) and the single-point concentration at 2 h post-dose (C2) are key measures of cyclosporine exposure. De novo studies show that achieving an AUC value of more than 4400 microg.h/l or a C2 level of 1500-2000 microg/l during the first 5 days post-transplant minimizes the risk of rejection and improves graft function. Maintenance studies suggest that reducing the C2 level to approximately 800 microg/l after 3-6 months may improve the serum creatinine level, blood pressure, general well-being and reduce adverse effects.

SUMMARY

Single-point C2 monitoring can be implemented quickly and simply with appropriate site and patient training. The timing of phlebotomy is more critical, but immunoassay bias is lower with 2 h post-dose than with trough level measures. Single-point C2 monitoring may be effective in liver and heart replacement, but initial target levels for liver transplantation are lower because cyclosporine is transported directly to the liver via the portal system. C2 monitoring is now being widely adopted as an accurate and practical measure of drug exposure, and can be combined with pharmacodynamic methods to optimize immunosuppression.