A new model for the population pharmacokinetics of didanosine in healthy subjects

Didanosine (ddI) is a component of highly active antiretroviral therapy drug combinations, used especially in resource-limited settings and in zidovudine-resistant patients. The population pharmacokinetics of ddI was evaluated in 48 healthy volunteers enrolled in two bioequivalence studies. These data, along with a set of co-variates, were the subject of a nonlinear mixed-effect modeling analysis using the NONMEM program. A two-compartment model with first order absorption (ADVAN3 TRANS3) was fitted to the serum ddI concentration data. Final pharmacokinetic parameters, expressed as functions of the co-variates gender and creatinine clearance (CL CR), were: oral clearance (CL = 55.1 + 240 x CL CR + 16.6 L/h for males and CL = 55.1 + 240 x CL CR for females), central volume (V2 = 9.8 L), intercompartmental clearance (Q = 40.9 L/h), peripheral volume (V3 = 62.7 + 22.9 L for males and V3 = 62.7 L for females), absorption rate constant (Ka = 1.51/h), and dissolution time of the tablet (D = 0.43 h). The intraindividual (residual) variability expressed as coefficient of variation was 13.0%, whereas the interindividual variability of CL, Q, V3, Ka, and D was 20.1, 75.8, 20.6, 18.9, and 38.2%, respectively. The relatively high (>30%) interindividual variability for some of these parameters, observed under the controlled experimental settings of bioequivalence trials in healthy volunteers, may result from genetic variability of the processes involved in ddI absorption and disposition.

Pantoprazole intraveineux aux soins intensifs pédiatriques: un modèle de pharmacocinétique de population

Objectifs : Définir les paramètres pharmacocinétiques du pantoprazole intraveineux en soins intensifs pédiatriques et déterminer l’influence qu’exercent sur ceux-ci les facteurs démographiques, le syndrome de réponse inflammatoire systémique (SRIS), la dysfonction hépatique et l’administration d’un inhibiteur du cytochrome (CYP) 2C19. Méthode : Cent cinquante-six concentrations plasmatiques de pantoprazole provenant d’une population de 20 patients (âgés de 10 jours à 16.4 ans) à risque ou atteints d’une hémorragie gastroduodénale de stress, ayant reçu des doses quotidiennes de pantoprazole de 19.9 à 140.6 mg/1.73m2, ont été analysées selon les méthodes non compartimentale et de modélisation non linéaire à effets mixtes. Résultats : Une clairance médiane (CL) de 0.14 L/h/kg, un volume apparent de distribution de 0.20 L/kg et une demi-vie d’élimination de 1.7 h ont été déterminés via l’approche non compartimentale. Le modèle populationnel à deux compartiments avec une infusion d’ordre zéro et une élimination d’ordre un représentait fidèlement la cinétique du pantoprazole. Le poids, le SRIS, la dysfonction hépatique et l’administration d’un inhibiteur du CYP2C19 constituaient les covariables significatives rendant compte de 75 % de la variabilité interindividuelle observée pour la CL. Seul le poids influençait significativement le volume central de distribution (Vc). Selon les estimations du modèle final, un enfant de cinq ans pesant 20 kg avait une CL de 5.28 L/h et un Vc de 2.22 L. La CL du pantoprazole augmentait selon l’âge et le poids tandis qu’elle diminuait respectivement de 62.3%, 65.8% et 50.5% en présence d’un SRIS, d’un inhibiteur du CYP2C19 ou d’une dysfonction hépatique. Conclusion : Ces résultats permettront de guider les cliniciens dans le choix d’une dose de charge et dans l’ajustement des posologies du pantoprazole en soins intensifs pédiatriques dépendamment de facteurs fréquemment rencontrés dans cette population.

Optimisation du processus de développement du médicament grâce à la modélisation PK et les simulations d’études cliniques

Le développement d’un médicament est non seulement complexe mais les retours sur investissment ne sont pas toujours ceux voulus ou anticipés. Plusieurs médicaments échouent encore en Phase III même avec les progrès technologiques réalisés au niveau de plusieurs aspects du développement du médicament. Ceci se traduit en un nombre décroissant de médicaments qui sont commercialisés. Il faut donc améliorer le processus traditionnel de développement des médicaments afin de faciliter la disponibilité de nouveaux produits aux patients qui en ont besoin. Le but de cette recherche était d’explorer et de proposer des changements au processus de développement du médicament en utilisant les principes de la modélisation avancée et des simulations d’essais cliniques. Dans le premier volet de cette recherche, de nouveaux algorithmes disponibles dans le logiciel ADAPT 5® ont été comparés avec d’autres algorithmes déjà disponibles afin de déterminer leurs avantages et leurs faiblesses. Les deux nouveaux algorithmes vérifiés sont l’itératif à deux étapes (ITS) et le maximum de vraisemblance avec maximisation de l’espérance (MLEM). Les résultats de nos recherche ont démontré que MLEM était supérieur à ITS. La méthode MLEM était comparable à l’algorithme d’estimation conditionnelle de premier ordre (FOCE) disponible dans le logiciel NONMEM® avec moins de problèmes de rétrécissement pour les estimés de variances. Donc, ces nouveaux algorithmes ont été utilisés pour la recherche présentée dans cette thèse. Durant le processus de développement d’un médicament, afin que les paramètres pharmacocinétiques calculés de façon noncompartimentale soient adéquats, il faut que la demi-vie terminale soit bien établie. Des études pharmacocinétiques bien conçues et bien analysées sont essentielles durant le développement des médicaments surtout pour les soumissions de produits génériques et supergénériques (une formulation dont l'ingrédient actif est le même que celui du médicament de marque, mais dont le profil de libération du médicament est différent de celui-ci) car elles sont souvent les seules études essentielles nécessaires afin de décider si un produit peut être commercialisé ou non. Donc, le deuxième volet de la recherche visait à évaluer si les paramètres calculer d’une demi-vie obtenue à partir d'une durée d'échantillonnage réputée trop courte pour un individu pouvaient avoir une incidence sur les conclusions d’une étude de bioéquivalence et s’ils devaient être soustraits d’analyses statistiques. Les résultats ont démontré que les paramètres calculer d’une demi-vie obtenue à partir d'une durée d'échantillonnage réputée trop courte influençaient de façon négative les résultats si ceux-ci étaient maintenus dans l’analyse de variance. Donc, le paramètre de surface sous la courbe à l’infini pour ces sujets devrait être enlevé de l’analyse statistique et des directives à cet effet sont nécessaires a priori. Les études finales de pharmacocinétique nécessaires dans le cadre du développement d’un médicament devraient donc suivre cette recommandation afin que les bonnes décisions soient prises sur un produit. Ces informations ont été utilisées dans le cadre des simulations d’essais cliniques qui ont été réalisées durant la recherche présentée dans cette thèse afin de s’assurer d’obtenir les conclusions les plus probables. Dans le dernier volet de cette thèse, des simulations d’essais cliniques ont amélioré le processus du développement clinique d’un médicament. Les résultats d’une étude clinique pilote pour un supergénérique en voie de développement semblaient très encourageants. Cependant, certaines questions ont été soulevées par rapport aux résultats et il fallait déterminer si le produit test et référence seraient équivalents lors des études finales entreprises à jeun et en mangeant, et ce, après une dose unique et des doses répétées. Des simulations d’essais cliniques ont été entreprises pour résoudre certaines questions soulevées par l’étude pilote et ces simulations suggéraient que la nouvelle formulation ne rencontrerait pas les critères d’équivalence lors des études finales. Ces simulations ont aussi aidé à déterminer quelles modifications à la nouvelle formulation étaient nécessaires afin d’améliorer les chances de rencontrer les critères d’équivalence. Cette recherche a apporté des solutions afin d’améliorer différents aspects du processus du développement d’un médicament. Particulièrement, les simulations d’essais cliniques ont réduit le nombre d’études nécessaires pour le développement du supergénérique, le nombre de sujets exposés inutilement au médicament, et les coûts de développement. Enfin, elles nous ont permis d’établir de nouveaux critères d’exclusion pour des analyses statistiques de bioéquivalence. La recherche présentée dans cette thèse est de suggérer des améliorations au processus du développement d’un médicament en évaluant de nouveaux algorithmes pour des analyses compartimentales, en établissant des critères d’exclusion de paramètres pharmacocinétiques (PK) pour certaines analyses et en démontrant comment les simulations d’essais cliniques sont utiles.

Optimisation de l’administration des médicaments chez les enfants transplantés grâce à la pharmacocinétique de population

Ce travail de thèse porte sur l’application de la pharmacocinétique de population dans le but d’optimiser l’utilisation de certains médicaments chez les enfants immunosupprimés et subissant une greffe. Parmi les différents médicaments utilisés chez les enfants immunosupprimés, l’utilisation du busulfan, du tacrolimus et du voriconazole reste problématique, notamment à cause d’une très grande variabilité interindividuelle de leur pharmacocinétique rendant nécessaire l’individualisation des doses par le suivi thérapeutique pharmacologique. De plus, ces médicaments n’ont pas fait l’objet d’études chez les enfants et les doses sont adaptées à partir des adultes. Cette dernière pratique ne prend pas en compte les particularités pharmacologiques qui caractérisent l’enfant tout au long de son développement et rend illusoire l’extrapolation aux enfants des données acquises chez les adultes. Les travaux effectués dans le cadre de cette thèse ont étudié successivement la pharmacocinétique du busulfan, du voriconazole et du tacrolimus par une approche de population en une étape (modèles non-linéaires à effets mixtes). Ces modèles ont permis d’identifier les principales sources de variabilités interindividuelles sur les paramètres pharmacocinétiques. Les covariables identifiées sont la surface corporelle et le poids. Ces résultats confirment l’importance de tenir en compte l’effet de la croissance en pédiatrie. Ces paramètres ont été inclus de façon allométrique dans les modèles. Cette approche permet de séparer l’effet de la mesure anthropométrique d’autres covariables et permet la comparaison des paramètres pharmacocinétiques en pédiatrie avec ceux des adultes. La prise en compte de ces covariables explicatives devrait permettre d’améliorer la prise en charge a priori des patients. Ces modèles développés ont été évalués pour confirmer leur stabilité, leur performance de simulation et leur capacité à répondre aux objectifs initiaux de la modélisation. Dans le cas du busulfan, le modèle validé a été utilisé pour proposer par simulation une posologie qui améliorerait l’atteinte de l’exposition cible, diminuerait l’échec thérapeutique et les risques de toxicité. Le modèle développé pour le voriconazole, a permis de confirmer la grande variabilité interindividuelle dans sa pharmacocinétique chez les enfants immunosupprimés. Le nombre limité de patients n’a pas permis d’identifier des covariables expliquant cette variabilité. Sur la base du modèle de pharmacocinétique de population du tacrolimus, un estimateur Bayesien a été mis au point, qui est le premier dans cette population de transplantés hépatiques pédiatriques. Cet estimateur permet de prédire les paramètres pharmacocinétiques et l’exposition individuelle au tacrolimus sur la base d’un nombre limité de prélèvements. En conclusion, les travaux de cette thèse ont permis d’appliquer la pharmacocinétique de population en pédiatrie pour explorer les caractéristiques propres à cette population, de décrire la variabilité pharmacocinétique des médicaments utilisés chez les enfants immunosupprimés, en vue de l’individualisation du traitement. Les outils pharmacocinétiques développés s’inscrivent dans une démarche visant à diminuer le taux d'échec thérapeutique et l’incidence des effets indésirables ou toxiques chez les enfants immunosupprimés suite à une transplantation.

A pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion

Objective Levodopa in presence of decarboxylase inhibitors is following two-compartment kinetics and its effect is typically modelled using sigmoid Emax models. Pharmacokinetic modelling of the absorption phase of oral distributions is problematic because of irregular gastric emptying. The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Methods The modelling involved pooling data from two studies and fixing some parameters to values found in literature (Chan et al. J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):307-31). The first study involved 12 patients on 3 occasions and is described in Nyholm et al. Clinical Neuropharmacology 2003:26:156-63. The second study, PEDAL, involved 3 patients on 2 occasions. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function from video recordings on a treatment response scale between -3 and 3, where -3 represents severe parkinsonism and 3 represents severe dyskinesia.) were repeatedly collected until the clinical effect was back at baseline. At this point, the usual infusion rate was started and sampling continued for another two hours. Different structural absorption models and effect models were evaluated using the value of the objective function in the NONMEM package. Population mean parameter values, standard error of estimates (SE) and if possible, interindividual/interoccasion variability (IIV/IOV) were estimated. Results Our results indicate that Duodopa absorption can be modelled with an absorption compartment with an added bioavailability fraction and a lag time. The most successful effect model was of sigmoid Emax type with a steep Hill coefficient and an effect compartment delay. Estimated parameter values are presented in the table. Conclusions The absorption and effect models were reasonably successful in fitting observed data and can be used in simulation experiments.

Interaction Between Nitrous Oxide, Sevoflurane, and Opioids: A Response Surface Approach

BACKGROUND:: The interaction of sevoflurane and opioids can be described by response surface modeling using the hierarchical model. We expanded this for combined administration of sevoflurane, opioids, and 66 vol.% nitrous oxide (N2O), using historical data on the motor and hemodynamic responsiveness to incision, the minimal alveolar concentration, and minimal alveolar concentration to block autonomic reflexes to nociceptive stimuli, respectively. METHODS:: Four potential actions of 66 vol.% N2O were postulated: (1) N2O is equivalent to A ng/ml of fentanyl (additive); (2) N2O reduces C50 of fentanyl by factor B; (3) N2O is equivalent to X vol.% of sevoflurane (additive); (4) N2O reduces C50 of sevoflurane by factor Y. These four actions, and all combinations, were fitted on the data using NONMEM (version VI, Icon Development Solutions, Ellicott City, MD), assuming identical interaction parameters (A, B, X, Y) for movement and sympathetic responses. RESULTS:: Sixty-six volume percentage nitrous oxide evokes an additive effect corresponding to 0.27 ng/ml fentanyl (A) with an additive effect corresponding to 0.54 vol.% sevoflurane (X). Parameters B and Y did not improve the fit. CONCLUSION:: The effect of nitrous oxide can be incorporated into the hierarchical interaction model with a simple extension. The model can be used to predict the probability of movement and sympathetic responses during sevoflurane anesthesia taking into account interactions with opioids and 66 vol.% N2O.

Labeling the human skeleton with 41Ca to assess changes in bone calcium metabolism

Bone research is limited by the methods available for detecting changes in bone metabolism. While dual X-ray absorptiometry is rather insensitive, biochemical markers are subject to significant intra-individual variation. In the study presented here, we evaluated the isotopic labeling of bone using 41Ca, a long-lived radiotracer, as an alternative approach. After successful labeling of the skeleton, changes in the systematics of urinary 41Ca excretion are expected to directly reflect changes in bone Ca metabolism. A minute amount of 41Ca (100 nCi) was administered orally to 22 postmenopausal women. Kinetics of tracer excretion were assessed by monitoring changes in urinary 41Ca/40Ca isotope ratios up to 700 days post-dosing using accelerator mass spectrometry and resonance ionization mass spectrometry. Isotopic labeling of the skeleton was evaluated by two different approaches: (i) urinary 41Ca data were fitted to an established function consisting of an exponential term and a power law term for each individual; (ii) 41Ca data were analyzed by population pharmacokinetic (NONMEM) analysis to identify a compartmental model that describes urinary 41Ca tracer kinetics. A linear three-compartment model with a central compartment and two sequential peripheral compartments was found to best fit the 41Ca data. Fits based on the use of the combined exponential/power law function describing urinary tracer excretion showed substantially higher deviations between predicted and measured values than fits based on the compartmental modeling approach. By establishing the urinary 41Ca excretion pattern using data points up to day 500 and extrapolating these curves up to day 700, it was found that the calculated 41Ca/40Ca isotope ratios in urine were significantly lower than the observed 41Ca/40Ca isotope ratios for both techniques. Compartmental analysis can overcome this limitation. By identifying relative changes in transfer rates between compartments in response to an intervention, inaccuracies in the underlying model cancel out. Changes in tracer distribution between compartments were modeled based on identified kinetic parameters. While changes in bone formation and resorption can, in principle, be assessed by monitoring urinary 41Ca excretion over the first few weeks post-dosing, assessment of an intervention effect is more reliable approximately 150 days post-dosing when excreted tracer originates mainly from bone.

Modeling of transfer kinetics at the serum-cerebrospinal fluid barrier in rabbits with experimental meningitis: application to grepafloxacin

The goals of the present study were to model the population kinetics of in vivo influx and efflux processes of grepafloxacin at the serum-cerebrospinal fluid (CSF) barrier and to propose a simulation-based approach to optimize the design of dose-finding trials in the meningitis rabbit model. Twenty-nine rabbits with pneumococcal meningitis receiving grepafloxacin at 15 mg/kg of body weight (intravenous administration at 0 h), 30 mg/kg (at 0 h), or 50 mg/kg twice (at 0 and 4 h) were studied. A three-compartment population pharmacokinetic model was fit to the data with the program NONMEM (Nonlinear Mixed Effects Modeling). Passive diffusion clearance (CL(diff)) and active efflux clearance (CL(active)) are transfer kinetic modeling parameters. Influx clearance is assumed to be equal to CL(diff), and efflux clearance is the sum of CL(diff), CL(active), and bulk flow clearance (CL(bulk)). The average influx clearance for the population was 0.0055 ml/min (interindividual variability, 17%). Passive diffusion clearance was greater in rabbits receiving grepafloxacin at 15 mg/kg than in those treated with higher doses (0.0088 versus 0.0034 ml/min). Assuming a CL(bulk) of 0.01 ml/min, CL(active) was estimated to be 0.017 ml/min (11%), and clearance by total efflux was estimated to be 0.032 ml/min. The population kinetic model allows not only to quantify in vivo efflux and influx mechanisms at the serum-CSF barrier but also to analyze the effects of different dose regimens on transfer kinetic parameters in the rabbit meningitis model. The modeling-based approach also provides a tool for the simulation and prediction of various outcomes in which researchers might be interested, which is of great potential in designing dose-finding trials.

Evaluation of 41calcium as a new approach to assess changes in bone metabolism: effect of a bisphosphonate intervention in postmenopausal women with low bone mass

A new technique was evaluated to identify changes in bone metabolism directly at high sensitivity through isotopic labeling of bone Ca. Six women with low BMD were labeled with 41Ca up to 700 days and treated for 6 mo with risedronate. Effect of treatment on bone could be identified using 41Ca after 4-8 wk in each individual. INTRODUCTION: Isotopic labeling of bone using 41Ca, a long-living radiotracer, has been proposed as an alternative approach for measuring changes in bone metabolism to overcome current limitations of available techniques. After isotopic labeling of bone, changes in urinary 41Ca excretion reflect changes in bone Ca balance. The aim of this study was to validate this new technique against established measures. Changes in bone Ca balance were induced by giving a bisphosphonate. MATERIALS AND METHODS: Six postmenopausal women with diagnosed osteopenia/osteoporosis received a single oral dose of 100 nCi 41Ca for skeleton labeling. Urinary 41Ca/40Ca isotope ratios were monitored by accelerator mass spectrometry up to 700 days after the labeling process. Subjects received 35 mg risedronate per week for 6 mo. Effect of treatment was monitored using the 41Ca signal in urine and parallel measurements of BMD by DXA and biochemical markers of bone metabolism in urine and blood. RESULTS: Positive response to treatment was confirmed by BMD measurements, which increased for spine by +3.0% (p = 0.01) but not for hip. Bone formation markers decreased by -36% for bone alkaline phosphatase (BALP; p = 0.002) and -59% for procollagen type I propeptides (PINP; p = 0.001). Urinary deoxypyridinoline (DPD) and pyridinoline (PYD) were reduced by -21% (p = 0.019) and -23% (p = 0.009), respectively, whereas serum and urinary carboxy-terminal teleopeptides (CTXs) were reduced by -60% (p = 0.001) and -57.0% (p = 0.001), respectively. Changes in urinary 41Ca excretion paralleled findings for conventional techniques. The urinary 41Ca/40Ca isotope ratio was shifted by -47 +/- 10% by the intervention. Population pharmacokinetic analysis (NONMEM) of the 41Ca data using a linear three-compartment model showed that bisphosphonate treatment reduced Ca transfer rates between the slowly exchanging compartment (bone) and the intermediate fast exchanging compartment by 56% (95% CI: 45-58%). CONCLUSIONS: Isotopic labeling of bone using 41Ca can facilitate human trials in bone research by shortening of intervention periods, lowering subject numbers, and having easier conduct of cross-over studies compared with conventional techniques.

Response surface modeling of the interaction between propofol and sevoflurane

BACKGROUND: Propofol and sevoflurane display additivity for gamma-aminobutyric acid receptor activation, loss of consciousness, and tolerance of skin incision. Information about their interaction regarding electroencephalographic suppression is unavailable. This study examined this interaction as well as the interaction on the probability of tolerance of shake and shout and three noxious stimulations by using a response surface methodology. METHODS: Sixty patients preoperatively received different combined concentrations of propofol (0-12 microg/ml) and sevoflurane (0-3.5 vol.%) according to a crisscross design (274 concentration pairs, 3 to 6 per patient). After having reached pseudo-steady state, the authors recorded bispectral index, state and response entropy and the response to shake and shout, tetanic stimulation, laryngeal mask airway insertion, and laryngoscopy. For the analysis of the probability of tolerance by logistic regression, a Greco interaction model was used. For the separate analysis of bispectral index, state and response entropy suppression, a fractional Emax Greco model was used. All calculations were performed with NONMEM V (GloboMax LLC, Hanover, MD). RESULTS: Additivity was found for all endpoints, the Ce(50, PROP)/Ce(50, SEVO) for bispectral index suppression was 3.68 microg. ml(-1)/ 1.53 vol.%, for tolerance of shake and shout 2.34 microg . ml(-1)/ 1.03 vol.%, tetanic stimulation 5.34 microg . ml(-1)/ 2.11 vol.%, laryngeal mask airway insertion 5.92 microg. ml(-1) / 2.55 vol.%, and laryngoscopy 6.55 microg. ml(-1)/2.83 vol.%. CONCLUSION: For both electroencephalographic suppression and tolerance to stimulation, the interaction of propofol and sevoflurane was identified as additive. The response surface data can be used for more rational dose finding in case of sequential and coadministration of propofol and sevoflurane.

Population pharmacokinetics of hydroxychloroquine in patients with rheumatoid arthritis

Hydroxychloroquine (HCQ) is an antimalarial drug that is also used as a second-line treatment of rheumatoid arthritis (RA). Clinically, the use of HCQ is characterized by a long delay in the onset of action, and withdrawal of treatment is often a result of inefficacy rather than from toxicity. The slow onset of action can be attributed to the pharmacokinetics (PK) of HCQ, and wide interpatient variability is evident. Tentative relationships between concentration and effect have been made, but to date, no population PK model has been developed for HCQ. This study aimed to develop a population PK model including an estimation of the oral bioavailability of HCQ. In addition, the effects of the coadministration of methotrexate on the PK of HCQ were examined. Hydroxychloroquine blood concentration data were combined from previous pharmacokinetic studies in patients with rheumatoid arthritis. A total of 123 patients were studied, giving the data cohort from four previously published studies. Two groups of patients were included: 74 received hydroxychloroquine (HCQ) alone, and 49 received HCQ and methotrexate (MTX). All data analyses were carried out using the NONMEM program. A one-compartment PK model was supported, rather than a three-compartment model as previously published, probably because of the clustering of concentrations taken at the end of a dosing interval. The population estimate of bioavailability of 0.75 (0.07), n = 9, was consistent with literature values. The parameter values from the final model were: (Cl) over bar = 9.9 +/- 0.4 L/h, (V) over bar 605 +/- 91 L, (k(d)) over bar = 0.77 +/- 0.22 hours(-1), (t(tag)) over bar = 0.44 +/- 0.02 hours. Clearance was not affected by the presence of MTX, and, hence, steady-state drug concentrations and maintenance dosage requirements were similar. A population PK model was successfully developed for HCQ.

Population pharmacokinetic analysis of mycophenolic acid in renal transplant recipients following oral administration of mycophenolate mofetil

Aim To develop a population pharmacokinetic model for mycophenolic acid in adult kidney transplant recipients, quantifying average population pharmacokinetic parameter values, and between- and within-subject variability and to evaluate the influence of covariates on the pharmacokinetic variability. Methods Pharmacokinetic data for mycophenolic acid and covariate information were previously available from 22 patients who underwent kidney transplantation at the Princess Alexandra Hospital. All patients received mycophenolate mofetil 1 g orally twice daily. A total of 557 concentration-time points were available. Data were analysed using the first-order method in NONMEM (version 5 level 1.1) using the G77 FORTRAN compiler. Results The best base model was a two-compartment model with a lag time (apparent oral clearance was 271 h(-1), and apparent volume of the central compartment 981). There was visual evidence of complex absorption and time-dependent clearance processes, but they could not be successfully modelled in this study. Weight was investigated as a covariate, but no significant relationship was determined. Conclusions The complexity in determining the pharmacokinetics of mycophenolic acid is currently underestimated. More complex pharmacokinetic models, though not supported by the limited data collected for this study, may prove useful in the future. The large between-subject and between-occasion variability and the possibility of nonlinear processes associated with the pharmacokinetics of mycophenolic acid raise questions about the value of the use of therapeutic monitoring and limited sampling strategies.

Toward better outcomes with tacrolimus therapy: Population pharmacokinetics and individualized dosage prediction in adult liver transplantation

Patient outcomes in transplantation would improve if dosing of immunosuppressive agents was individualized. The aim of this study is to develop a population pharmacokinetic model of tacrolimus in adult liver transplant recipients and test this model in individualizing therapy. Population analysis was performed on data from 68 patients. Estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F) using the nonlinear mixed effects model program (NONMEM). Factors screened for influence on these parameters were weight, age, sex, transplant type, biliary reconstructive procedure, postoperative day, days of therapy, liver function test results, creatinine clearance, hematocrit, corticosteroid dose, and interacting drugs. The predictive performance of the developed model was evaluated through Bayesian forecasting in an independent cohort of 36 patients. No linear correlation existed between tacrolimus dosage and trough concentration (r(2) = 0.005). Mean individual Bayesian estimates for CL/F and V/F were 26.5 8.2 (SD) L/hr and 399 +/- 185 L, respectively. CL/F was greater in patients with normal liver function. V/F increased with patient weight. CL/F decreased with increasing hematocrit. Based on the derived model, a 70-kg patient with an aspartate aminotransferase (AST) level less than 70 U/L would require a tacrolimus dose of 4.7 mg twice daily to achieve a steady-state trough concentration of 10 ng/mL. A 50-kg patient with an AST level greater than 70 U/L would require a dose of 2.6 mg. Marked interindividual variability (43% to 93%) and residual random error (3.3 ng/mL) were observed. Predictions made using the final model were reasonably nonbiased (0.56 ng/mL), but imprecise (4.8 ng/mL). Pharmacokinetic information obtained will assist in tacrolimus dosing; however, further investigation into reasons for the pharmacokinetic variability of tacrolimus is required.

Prospective evaluation of a D-optimal designed population pharmacokinetic study

Recently, methods for computing D-optimal designs for population pharmacokinetic studies have become available. However there are few publications that have prospectively evaluated the benefits of D-optimality in population or single-subject settings. This study compared a population optimal design with an empirical design for estimating the base pharmacokinetic model for enoxaparin in a stratified randomized setting. The population pharmacokinetic D-optimal design for enoxaparin was estimated using the PFIM function (MATLAB version 6.0.0.88). The optimal design was based on a one-compartment model with lognormal between subject variability and proportional residual variability and consisted of a single design with three sampling windows (0-30 min, 1.5-5 hr and 11 - 12 hr post-dose) for all patients. The empirical design consisted of three sample time windows per patient from a total of nine windows that collectively represented the entire dose interval. Each patient was assigned to have one blood sample taken from three different windows. Windows for blood sampling times were also provided for the optimal design. Ninety six patients were recruited into the study who were currently receiving enoxaparin therapy. Patients were randomly assigned to either the optimal or empirical sampling design, stratified for body mass index. The exact times of blood samples and doses were recorded. Analysis was undertaken using NONMEM (version 5). The empirical design supported a one compartment linear model with additive residual error, while the optimal design supported a two compartment linear model with additive residual error as did the model derived from the full data set. A posterior predictive check was performed where the models arising from the empirical and optimal designs were used to predict into the full data set. This revealed the optimal'' design derived model was superior to the empirical design model in terms of precision and was similar to the model developed from the full dataset. This study suggests optimal design techniques may be useful, even when the optimized design was based on a model that was misspecified in terms of the structural and statistical models and when the implementation of the optimal designed study deviated from the nominal design.

Population pharmacokinetics and association between A77 1726 plasma concentrations and disease activity measures following administration of leflunomide to people with rheumatoid arthritis

Aims To investigate the concentration-effect relationship and pharmacokinetics of leflunomide in patients with rheumatoid arthritis (RA). Methods Data were collected from 23 RA patients on leflunomide therapy (as sole disease modifying antirheumatic drug (DMARD)) for at least 3 months. Main measures were A77 1726 (active metabolite of leflunomide) plasma concentrations and disease activity measures including pain, duration/intensity of morning stiffness, and SF-36 survey. A population estimate was sought for apparent clearance (CL/F ) and volume of distribution was fixed (0.155 l kg(-1)). Factors screened for influence on CL/F were weight, age, gender and estimated creatinine clearance. Results Significantly higher A77 1726 concentrations were seen in patients with less swollen joints and with higher SF-36 mental summary scores than in those with measures indicating more active disease (P < 0.05); concentration-effect trends were seen with five other disease activity measures. Statistical analysis of all disease activity measures showed that mean A77 1726 concentrations in groups with greater control of disease activity were significantly higher than those in whom the measures indicated less desirable control (P < 0.05). There was large between subject variability in the dose-concentration relationship. A steady-state infusion model best described the pharmacokinetic data. Inclusion of age as a covariate decreased interindividual variability (P < 0.01), but this would not be clinically important in terms of dosage changes. Final parameter estimate (% CV interindividual variability) for CL/F was 0.0184 l h(-1) (50%) (95% CI 0.0146, 0.0222). Residual (unexplained) variability (% CV) was 8.5%. Conclusions This study of leflunomide in patients using the drug clinically indicated a concentration-effect relationship. From our data, a plasma A77 1726 concentration of 50 mg l(-1) is more likely to indicate someone with less active disease than is a concentration around 30 mg l(-1). The marked variability in pharmacokinetics suggests a place for individualized dosing of leflunomide in RA therapy.