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A novel methodology is proposed for continuous monitoring of efficacy data in ongoing antidepressant clinical trials and for decision making to support progression or discontinuation of the trial or one of the treatment arms. The Posterior Probability of Superiority (PPS) resulting from the application of Monte Carlo Markov Chain approach to a longitudinal model describing the time course of placebo and antidepressant drugs was used to estimate criteria to discontinue a treatment arm or the trial for futility, and to predict the treatment effect at study-end while the trial was still ongoing. The decision to stop the study was based on PPS, Predictive Power and on risk analysis based on a non-parametric bootstrap trial simulation. The performance of the Bayesian monitoring was evaluated by the retrospective analysis of 3 clinical trials. The Bootstrap-based methodology was compared to the Conditional Power and the Predictive Probability approaches. The application of the proposed methodology showed the possibility to stop a trial for futility when about 50% of total information was available and to detect signal of a treatment effect when limited information (

Longitudinal dose–response analyses of alitretinoin (an investigational agent in the US) were conducted to supplement results from phase III studies in severe, refractory chronic hand eczema, with objectives to address several outstanding development issues (e.g., optimal dose, possible factors affecting efficacy and/or tolerability). Models were fitted to the physicians' global assessment score and triglycerides over time. Five hundred trials were simulated to evaluate the relevance of findings. Analyses clarified that the optimal dose of alitretinoin was 30 mg once daily, where response rates were ∼10% over placebo at 12 weeks and increased by 5–7% over placebo for every 4 weeks thereafter, for up to 24 weeks. Elderly subjects had higher magnitudes of efficacy and an increased probability of high triglycerides. Results from analyses sufficiently addressed the development issues, thereby adding to the weight of evidence supporting the efficacy and safety of alitretinoin in the treatment of severe, refractory chronic hand eczema.

The current study examined the pharmacokinetics (PK), safety, and tolerability of paroxetine after repeated multiple oral dosing in children and adolescents with major depressive or obsessive-compulsive disorder. In this 6-week, open-label, repeat dose, dose-rising study, 62 patients (27 children and 35 adolescents) were treated with paroxetine 10 mg/day for the first 2 weeks of the study, 20 mg/day for the next 2 weeks, and 30 mg/day for the final 2 weeks. Pharmacokinetic sampling and safety assessments occurred at baseline and subsequently on the final treatment day of each dosing level. Between-patient variability in PK was pronounced at the 10 mg dose level, but markedly reduced at higher doses. A supra-proportional increase in plasma concentrations with increasing dose was evident in both age groups. Data for C(max) and AUC(0-24) indicated that, at each dose level, paroxetine steady-state systemic exposure was higher in children than in adolescents. The differences between age groups, however, diminished with each increasing dose, and were virtually abolished when differences in weight among different age groups were considered. Stepwise regression analysis indicated that both oral clearance and volume of distribution were highly dependent on paroxetine dose, cytochrome P4502D6 genotype, and weight (p

A population pharmacokinetic (PK) analysis was performed on plasma concentrations of GW468816 observed in dogs after 10, 25, and 50 mg/kg/day repeated intravenous administration. A two-compartment model was fitted to the concentration-time data using the NONMEM program. Dose and time dependency of PK parameters was investigated. Selection of the best model was performed using a stepwise approach. A Michaelis-Menten elimination process was used to describe the PK dose dependency, whereas an interoccasion variability on V m (the maximum elimination rate of the Michaelis-Menten elimination process) was initially used to describe the time dependency of the PKs, and the final model included an exponential function to account for time variance on V m . The K m value of the final model was 29.6 μg/mL, whereas V m was estimated to vary with time from 4.97 μg/h/kg at day 1 to a maximum mean value of 9.64 μg/h/kg at day 14. This approach can be applied to either rich or sparse data leading to estimates of individual parameters by using Bayesian feedback. The overall information obtained can be used to interpret toxicological and pharmacological endpoints and integrated with further in vitro – in vivo studies to supply a comprehensive PK behavior before the first time in human studies.

Positron emission tomography (PET) is an imaging technique that is used to investigate ligand-receptor binding in the living brain and to determine the time course of plasma concentration/receptor occupancy (RO). The purpose of this work was to demonstrate the added value of an adaptive-optimal design for PET scan timings and dose selection over traditional study designs involving fixed or educated selections of timings and doses. A k(on)-k(off) model relating plasma concentration to PET data was applied to generate the simulated data. Optimization was performed on scanning timings and doses using the D-optimality criterion. Optimal designs as applied to scanning timings provided unbiased estimates and improved the accuracy of results relative to those of fixed and educated designs. Optimization of both timings and dose provided improvements in accuracy and precision when the initial dose selection was noninformative regarding the time course of RO. These results indicate that adaptive-optimal designs can provide an efficient experimental design for RO studies using PET, by minimizing the number of subjects required and maximizing information related to the plasma concentration-RO relationship.

Aims To investigate whether saliva is a useful alternative to plasma for routine monitoring of nicotine and evaluate the predictive performances of saliva and plasma concentration on craving estimated by a Tiffany Questionnaire on Smoking Urge-Brief Form. Methods Thirteen healthy smokers were enrolled in a randomized, two period, crossover trial. Linear and power models were evaluated to predict the plasma nicotine concentrations from the saliva measurements, whereas a population PK/PD indirect response model was used to predict craving using either saliva or plasma nicotine concentration as the independent variable. Results The results of the analysis revealed that the power model was preferred over the linear one The bias on the predicted plasma concentrations was of 0.47 ng ml−1 with a 95% confidence interval of [-0.57, 1.52] and a precision of 5.68 ng ml−1. The placebo effect model was initially fitted to data, then the indirect response approach (with inhibition in kin) was used to model the craving scores using plasma and saliva nicotine concentrations as independent variables. The two indirect response PK/PD models based on saliva and plasma nicotine concentrations, adequately described the onset, extent, and duration of craving. The maximal inhibition Imax was 0.722 and 1 for saliva and plasma concentrations while the estimated nicotine concentrations giving 50% of the maximal inhibition were 269 ng ml−1 and 24.3 ng ml−1 for saliva and plasma, respectively. Conclusions A good correlation between plasma and saliva nicotine concentrations has been found using a power model. Comparable values of bias and precision on the model-predicted craving indicate that plasma and saliva concentration can equally well be used to predict the onset of tobacco withdrawal induced craving. Analysis of saliva definitely offers a potentially more attractive way to assess nicotine concentration values, as samples can be collected easily and noninvasively. In addition, saliva sampling avoids the pain and discomfort involved in venepuncture. In studies that assess psychological measures, such as subjective mood, blood collection could present a possible confounding factor because of the anxiety and pain that accompanies it. For these reasons saliva can reasonably be considered as the ideal sampling site for all clinical studies conducted for the evaluation of the potential activity of drugs on nicotine deprivation symptoms.

The aim of this study was to characterize the population pharmacokinetic of vinorelbine In elderly patients and to propose a limited-sampling strategy to estimate individual pharmacokinetic parameters.Vinorelbine was administered by a 10 -min continuous Infusion at a dose of 20-30 mg/m 2 . The population parameters were computed, using a three-compartment model, from an Initial group of 27 patients. Twelve additional courses were used for model validation and evaluation of eight different limited-sampling strategies. The inter-individual variability of CL was explained by a linear dependency with age.The population average parameters and the interindlvidual varlabilities (CV%) were: CL=47.1 l/h (31.7%), V=16.61 (64%), k 2 1 =0.776 h 1 (20%), k 3 1 =0.0346 h 1 (15.2%), a=0.431 h 1 (6.84%) and β=0.0167 h 1 (25%). Bayesian estimation with three measured levels (end of infusion, and 6 and 48 h) can be selected, because It allows adequate estimation of CL, elimination half-life and vinorelbine concentrations with a non-significant bias. Moreover, the choice of these three sampling times presents practicality advantages for the patient's comfort. Vinorelbine clearance decreasing with age and AUC being a good predictor of several toxicity end points during vinorelbine treatment, the limited-sampling strategy developed in this paper may be clinically relevant.

Purpose. To develop a new strategy for the in silico evaluation of the optimal in vivo delivery properties of a drug, minimizing a cost function defined by the brain receptor occupancy obtained in positron-emission tomography experiments.

RBP-7000 is a long-acting formulation of risperidone designed for once-monthly subcutaneous injection for the treatment of schizophrenia. The objective was to estimate clinically effective doses of RBP-7000 based on model simulations and on the comparison with other long-acting injectable antipsychotics. A population pharmacokinetic model of RBP-7000 was developed in 90 clinically stable schizophrenic patients having received single/repeated doses of 60, 90, or 120 mg. Model simulations were conducted to compare active moiety plasma exposure after repeated RBP-7000 administrations to the published data of long-acting risperidone injection (Risperdal® Consta®) at 25 and 50 mg, and of paliperidone palmitate (Invega® Sustenna®) at 50 and 100 mg equivalent paliperidone. Predictions of dopamine D2 receptor occupancy were derived from the simulated active moiety concentrations. Simulations showed similar active moiety plasma exposure at steady-state for 90 mg of RBP-7000 and 25 mg of long-acting risperidone. In comparison to risperidone, RBP-7000 reached effective concentrations immediately after the first administration. RBP-7000 at the doses of 60 and 90 mg provided similar active moiety plasma concentrations at steady-state compared to 50 and 100 mg equivalent paliperidone, respectively. These findings provide guidance for dose selection in Phase III clinical trials and suggest potential benefits for RBP-7000 over competitors.

RBP-7000 is a long-acting formulation of risperidone administered once monthly via subcutaneous (SC) injections for the treatment of schizophrenia. The objectives of the present study were to characterize the pharmacokinetics of RBP-7000 after multiple doses in schizophrenic patients on stable oral risperidone therapy and to evaluate the switch between oral risperidone and SC injections of RBP-7000. Data were collected in a phase IIa, open-label, multiple-ascending-dose study where 45 patients clinically stabilized on oral risperidone (2, 3 or 4 mg/day) were switched to receive 60, 90 or 120 mg/month SC injections of RBP-7000, respectively. Patients were thereafter switched back to oral risperidone. An integrated population pharmacokinetic model describing simultaneously risperidone and 9-hydroxyrisperidone after risperidone oral intake and RBP-7000 administration was developed in NONMEM using 5,232 quantifiable plasma concentrations. Predictions of dopamine D2 receptor occupancy were derived using a previously published model. A two-compartment model with first-order absorption was selected for oral risperidone, while a three-compartment model with first-order absorption and a transit compartment absorption model was selected for RBP-7000. Body mass index was identified as a significant covariate affecting the initial absorption of risperidone following RBP-7000 injection. Steady state was reached after the second or third RBP-7000 injection but plasma concentrations close to steady-state values were obtained right after the first injection when switching from oral risperidone therapy. Predicted dopamine D2 receptor occupancy after repeated doses of 90 and 120 mg showed less fluctuation than after oral risperidone with acceptable ranges for clinical efficacy and a potentially safer profile with respect to extrapyramidal side effects. This analysis provided additional insight into the pharmacokinetics of RBP-7000 and for the comparison with oral risperidone treatment. The established model was used to support the design of a planned phase III study.

The objectives of this work were: (1) to characterize the placebo FEV1 response in asthma; (2) to identify the potential factors with strong influence on FEV1; (3) to determine the predictability of the early (week 2) placebo FEV1 response to the longer term (week 12) FEV1 response. Placebo FEV1 data of about 800 subjects from 11 randomized 12-week clinical trials in mild-to-moderate asthmatics were collected. Stepwise logistic regression methods using SAS were used to model the week 12 trough FEV1 change from baseline greater than a clinically relevant value (150 mL) and to select the predictive covariates. The study effect was assessed using hierarchical logistic regression models implemented in WinBUGS. The results indicated that the early (week 2) placebo response was significantly predictive of the FEV1 response at week 12. Age, baseline predicted FEV1, and season showed statistical significance in the model. The final model showed satisfactory predictability with the area under the receiver operating characteristic curve (ROC) of 80%. The late (week 12) FEV1 response with placebo was positively related to the early (week 2) FEV1 change. The use of the predictive modeling approach proposed in this article presents a valuable method to increase the efficiency of clinical trial design in asthma population.

Computer-assisted drug development (CADD) is a knowledge-based process that integrates newly collected information in a drug/disease-specific knowledge frame and provides a rational basis for decision making during drug development. A mathematical model was developed to predict the dosage regimen appropriate to reach a desired human response for a new central nervous system compound from data collected in preclinical studies. The model incorporates uncertainty on the human pharmacokinetic/pharmacodynamic (PK/PD) relationship scaled from animal data, including the affinity adjustment derived from in-vitro receptor binding studies. Brain receptor occupancy, estimated using positron emission tomography imaging, was used as a surrogate marker of clinical efficacy. The CADD approach was used to design the first-time-in-man and the proof-of-concept study. The expected minimal effective dose in man was estimated by simulating a dose-escalating trial, as the dose necessary to reach and maintain during chronic treatment is a target receptor occupancy of less than 70%, assuming that the therapeutic effect is associated with a receptor occupancy of less than 70% at a given probability level (Prob >70%). Finally, the optimal in-vivo release characteristics from a pharmaceutical formulation were evaluated using a convolution-based model linking the in-vivo delivery rate to the PK/PD response, minimizing an appropriate cost function. Clinical trial simulation was used as a supportive tool for decision making by evaluating different scenarios accounting for the uncertainty in the predicted PK/PD relationship, intersubject variability, and drug potency.

Purpose. A population pharmacokinetic-pharmacodynamic model accounting for placebo effect was used to relate nicotine concentration and enforced smoking cessation craving score measured by the Tiffany rating scale short form.

Routine clinical pharmacokinetic (PK) data collected from patients receiving inulin were analyzed to estimate population PK parameters; 560 plasma concentration determinations for inulin were obtained from 90 patients. The data were analyzed using NONMEM. The population PK parameters were estimated using a Constrained Longitudinal Splines (CLS) semiparametric approach and a first-order conditional method (FOCE). The mean posterior individual clearance values were 7.73 L/hr using both parametric and semiparametric methods. This estimation was compared with clearances estimated using standard nonlinear weighted least squares approach (reference value, 7.64 L/hr). The bias was not statistically different from zero and the precision of the estimates was 0.415 L/hr using parametric method and 0.984 L/hr using semiparametric method. To evaluate the predictive performances of the population parameters, 17 new subjects were used. First, the individual inulin clearance values were estimated from drug concentration–time curve using a nonlinear weighted least-squares method then they were estimated using the NONMEM POSTHOC method obtained using parametric and CLS methods as well as an alternative method based on a Monte Carlo simulation approach. The population parameters combined with two individual inulin plasma concentrations (0.25 and 2 hr) led to an estimation of individual clearances without bias and with a good precision. This paper not only evaluates the relative performance of the parametric and the CLS methods for sparse data but also introduces a new method for individual estimation.

The pharmacokinetic profiles of clozapine and its main metabolite, norclozapine, were investigated in 18 chronic schizophrenic inpatients during long-term treatment.Patients received stable daily doses (between 300 and 900mg) for at least 1 month. Plasma drug concentrations were determined by high performance liquid chromatography. The pharmacokinetic parameters were calculated from both noncompartmental and compartmental approaches with zero-order input rate using a kinetic model for simultaneous fit of clozapine and norclozapine (active metabolite) concentrations.Large interpatient variations in pharmacokinetic parameters of the two drugs were observed. Plasma clozapine concentration peaked on average at 2 hours. The mean elimination rate constants from compartments 1 (k(10)) and 2 (k(20 ), elimination rate constant of norclozapine) were 0.087 and 0.156h(-1), respectively. The rate of formation of norclozapine, k(12), averaged 1.25h(-1). The mean fraction of the administered dose converted to norclozapine was estimated to be 66%. The apparent clearance of clozapine (CL/F) averaged 44.7 L/h and the volume of distribution (V(c)/F) was 7.00 L/kg. The pharmacokinetics of clozapine after multiple doses were linear over the range of clozapine plasma concentrations of 145 to 1411 microg/L.This is the first study assessing the pharmacokinetic profile of clozapine plus norclozapine in plasma during long-term treatment. This pharmacokinetic model can be used to determine the population pharmacokinetic parameters of clozapine and norclozapine in order to optimise individual dosage regimens using a Bayesian methodology.

Basic physiologic indirect response models have been proposed to account for the pharmacodynamics of drugs that act by way of inhibition or stimulation of the production or loss of endogenous substances or mediators. In this work, these models were applied to account for the effects of recombinant human erythropoietin (rHuEpo) in man. Indeed, rHuEpo induces a delayed increase of serum soluble transferrin receptors (sTfr) and a delayed decrease in ferritin (fr) concentrations. The purpose of the present study was to compare two pharmacodynamic approaches to relate serum erythropoietin (Epo) concentrations to the effect of rHuEpo on sTfr, and fr, the “indirect effect” and the “effect compartment” models. However, due to the average lag lime of about 50 hr between the first intake of rHuEpo and the onset of the measurable effects, a delay function was incorporated into the “indirect response models” to describe the relationship between the Epo plasma concentrations and the endogenous receptors or mediators affected by the drug and responsible for the effects on sTfr and fr. There are no real differences in the descriptive features of the two models used. For these reasons, the indirect model seems more appropriate because it supplies a possible mechanistic interpretation of the physiological process.

Our objective was to develop: 1) a longitudinal model to describe amyotrophic lateral sclerosis (ALS) disease progression using the revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R); and 2) a probabilistic model to estimate the presence of clusters of trajectories in ALS progression over 12 months of treatment. Three hundred and thirty-eight patients treated with placebo from the PRO-ACT database were included in the analyses. A non-linear Weibull model best described the ALS disease progression, and a stepwise logistic regression approach was used to select the variables predicting a slow or fast disease progression. Results identified two clusters of trajectories: 1) slow disease progressors (46% of patients with a change from baseline of 13%); 2) fast disease progressors (54% of patients with a change from baseline of 49%). ROC curve analysis estimated the optimal cut-off for classifying patients as slow or fast disease progressors given ALSFRS-R measurements at 2-4 weeks. Results showed that the degree of ALS disease progression quantified by the ALSFRS-R symptomatic change on placebo is highly heterogeneous. In conclusion, this finding indicates the potential interest of disease progression models for implementing a population enrichment strategy to control the level of heterogeneity in the patients included in new trials.

Today the CNS drug development poses serious challenges for developers given the low probability of success and the disproportionately high investment costs. This review demonstrates how predictive models can provide quantitative criteria for increasing the efficiency of drug development in CNS. Predictive models can be applied to characterize, understand, and predict a drug's PK and PD behavior; to quantify uncertainty of information about that behavior; to identify factors that could affect the outcomes of a clinical trial through Clinical Trial Simulation (CTS), to identify prognostic factors that could affect the disease progression, to implement optimal and adaptive clinical trial and finally to control the level of placebo response by implementing study designs that minimizes the impact of placebo on study outcomes.

Background: Uncontrolled placebo response has been one of the major culprits in the failure of randomized clinical trials for depression. A major drawback associated with the presence of high placebo response is the increased noiseto- signal ratio that in a majority of cases prevents the detection of treatment effect. The aim of this work was to propose an adaptive randomization study design based on band-pass filtering and evaluate this approach when compared to the traditional study designs. Results: Clinical trial simulations demonstrated that an adaptive randomization approach always outperformed the conventional study designs in improving the signal-to-noise ratio. The improvement directly correlated with the level of placebo response and the variability in response across centers. The proposed strategy does not warrant any unblinding of data. Conclusions: The use of the adaptive randomization design provides a novel methodological approach for signal detection in clinical trials where placebo represents a known confounding factor. The improvement in signal detection was directly proportional to the level of placebo response, the degree of heterogeneity across recruitment centers with a reduced sample size as compared to the traditional study design. These findings support the use of the band-pass filtering approach in an adaptive randomization design as an efficient way to minimize the impact of uncontrolled placebo response and provide rational go/no-go decision criteria in the development of new medicines for psychiatric disorders.

The pharmacokinetics of total and free methotrexate (MTX) were investigated in 50 patients with rheumatoid arthritis. Each patient received 10 mg MTX intramuscularly. The free and total plasma concentrations of MTX were measured over a 36-h period after drug administration by using the Abbott TDx fluorescence polarization immunoassay. Plasma concentrations of MTX were described by a biexponential function. The mean terminal elimination half-lives of total and free MTX were 9.4 and 8.4 h, respectively, and the corresponding mean residence times, 8.5 and 9.2 h. No difference in these parameters was found by comparing total and free MTX. Total plasma clearance of the free fraction averaged 215 ml/min. The statistical comparison of the variations with time of the ratio of free to total MTX during the 36 h after the dose showed that the free fraction was significantly increased for 8 h after drug administration (p < 0.001). To describe these variations, the changes of the free MTX concentrations (unbound) were related to the changes of the total MTX concentrations by using the Hill equation. Mean plasma protein binding ranged from 20 to 57% for these patients.

This study describes the methodology used to calculate the individual clearance (CL) and volume of distribution (Vd) of inulin using 1 or 2 blood samples taken during the disposition and elimination phase after a single intravenous perfusion, and the population parameters. The mean population parameters and their interindividual variability were obtained from an initial group of 90 patients including 38.5% who had diabetes, 49% who were obese, and 12.5% who were diabetic and obese. Among these patients, 44.5% had normal renal function (creatinine clearance ranging from 70 to 150 ml/min/1.73m2) and 20% showed renal insufficiency with a creatinine clearance ranging from 15 to 60 ml/min/1.73m2. A 2-compartment model was fitted to the population data using P-PHARM. The population parameter estimates of CL and Vd were 6.85 ± 1.04 L/h and 4.95 ± 0.84L, respectively. The interindividual variability of CL was explained by a linear dependency between serum creatinine and body area. The interindividual variability of Vd was explained by a linear dependency with body area. A test group of 25 additional patients was used to evaluate the predictive performance of the population parameters. Seven blood samples were collected from each individual in order to calculate individual parameter estimates using standard fitting procedures. These values were compared with those estimated by means of a Bayesian approach using population parameters and 1 or 2 samples selected from the individual observations. The results show that the bias of CL and Vd, estimated using either 1 or 2 samples, was not statistically different from zero, and that the precision of these parameters was excellent.

Many difficulties may arise during the modeling of the time course of Hamilton Rating Scale for Depression (HAMD) scores in clinical trials for the evaluation of antidepressant drugs: (i) flexible designs, used to increase the chance of selecting more efficacious doses, (ii) dropout events, and (iii) adverse effects related to the experimental compound. It is crucial to take into account all these factors when designing an appropriate model of the HAMD time course and to obtain a realistic description of the dropout process. In this work, we propose an integrated approach to the modeling of a double-blind, flexible-dose, placebo-controlled, phase II depression trial that comprises response, tolerability, and dropout. We investigate three different dropout mechanisms in terms of informativeness. Goodness of fit is quantitatively assessed with respect to response (HAMD score) and dropout data. We show that dropout is a complex phenomenon that may be influenced by HAMD evolution, dose changes, and occurrence of drug-related adverse effects. Clinical Pharmacology & Therapeutics (2012); 91 5, 863–871. doi:10.1038/clpt.2011.322

The early stages of the drug development process are often characterized by a limited number of subjects participating the study and a limited number of measurements per individual that can be collected, mainly due to technical, ethical, and cost reasons. The so-called dose escalation studies, performed during phase I, usually involve about 40 subjects or less, and feature observations at no more than three (rarely four or five) dose levels-per-subject. Depending on the complexity of the underlying pharmacokinetics, simple linear models or nonlinear ones (e.g., power, E(max) models) may be appropriate to describe the relationship between the metrics of systemic exposure to the drug (C(max), AUC) and the administered dose. However, in such data-poor scenarios, formulating models based on parametric descriptions is generally hard, and may easily result in model misspecification. Hence, nonparametric or "model-free" solutions, borrowed from the machine learning field, are deemed appealing. We resort to Gaussian process theory to work out Bayesian posterior expectations of a population (a.k.a mixed-effects) regression problem, namely Population Smoothing Splines (PSS). We show that in seven experimental dose escalation studies, Population Smoothing Splines improve on three widely used parametric population methods. Superiority of the model-free technique is confirmed by a simulated benchmark: Population Smoothing Splines compare very favorably even with the true parametric model structure underlying the simulated data.

The orexin system plays a major role in the integration of metabolic and circadian influences that drive wakefulness. This paper describes initial Phase I trials of a novel dual orexin receptor antagonist SB-649868 that has demonstrated preclinical potential for treatment of sleep disorders. The trial designs included a single ascending dose escalation study (dose range: 10–80 mg in the fed and fasted states) and a multiple repeat dose study (dose range: 5–30 mg in the fed state) enrolling a total of 103 male volunteer subjects. SB-649868 was well tolerated at all doses in this study population, with mechanism-related adverse events (e.g. somnolence and fatigue) observed in a majority of subjects after 60 and 80 mg single doses. Although total drug exposure was similar in the fed and fasted states, the rate, but not the extent, of absorption increased in the fed state, resulting in an increased Cmax. The typical estimated half-life of SB-649868 was 3–6 h – comparable with currently used hypnotic agents. Repeated administration of SB-649868 dose-dependently increased exposure to simvastatin (10 mg), suggesting CYP3A4 inhibition ranging from very mild (5 mg) to strong (30 mg). Evening dosing resulted in significant dose-dependent improvement in latency to persistent sleep, total sleep time and wake after sleep onset as measured by polysomnography. Next-morning testing did not detect evidence of residual cognitive effects. Results of these trials support further investigation of SB-649868 and other dual orexin receptor antagonists as potentially effective and well-tolerated treatments for patients with sleep disorders.

Clinical trials with antidepressant drugs often fail to detect drug effect, even with drugs that are known to be efficacious. In a previous publication, we showed that a model-based approach is required to address some of the existing challenges in the design of clinical trial protocols. Here, we illustrate how the implementation of an interim analysis (IA) may help to identify studies that are headed for failure, early in the trial before completion of treatment. In contrast to traditional IA procedures, an adaptive Bayesian approach is proposed to optimize the timing of analysis and decision criteria for futility and efficacy, taking into account enrollment rate and treatment response at intermediate visits in the trial. Validation procedures involving re-enrollment of patients confirmed the performance of the method. Our findings reveal that optimization of the timing and decision criteria at the interim stage is critical for the accuracy of the conclusions about treatment efficacy or futility.

The pharmacokinetics of 1 g of ceftazidime administered intradermally was studied in seven healthy volunteers. The objective of the present study was to find the most appropriate mathematical model to describe the drug intake process. The concentration of ceftazidime in plasma was measured by HPLC. The disposition of the drug was described by a one-compartment pharmacokinetic model, with drug intake occurring by different processes: a zero-order process due to the administration and a first-order intake from the injection site to the systemic circulation. The Weibull model was considered as an approximation of the overall process. The mean Weibull parameters were td (time necessary to transfer 63% of the administered drug into the systemic circulation) of 2.75 +/- 0.75 h, and f (shape) of 1.04 +/- 0.15. The mean elimination half-life was 2.0 +/- 0.4 h. The area under the concentration versus time curve obtained in this study (139 +/- 46 mg.h/L) is very near to literature values reported after single intravenous doses of 1 g of ceftazidime, suggesting that the bioavailability of ceftazidime after intradermal administration may be approximately 100%. Moreover, the mean peak plasma concentration (37 +/- 16 mg/L) is in the same range as that reported in the literature after intramuscular administration of a single dose of 1 g.

The rate-limiting factor in the discovery of novel antidepressants is the inefficient methodology of traditional multicenter randomized clinical trials (RCTs). We applied a model-based approach to a large clinical database (five RCTs in major depressive disorder (MDD), involving 1,837 patients from 124 recruitment centers) with two objectives: (i) to learn about the role of center-specific placebo response in RCT failure and (ii) to apply what is learned to improve the efficiency of RCTs by enhancing the detection of treatment effect (TE). Sensitivity analysis indicated that center-specific placebo response was the most relevant predictor of RCT failure. To reduce the statistical "noise" generated by centers with nonplausible, excessively high/low placebo responses, we developed an enrichment-window strategy. Clinical trial simulation was used to assess the enrichment strategy applied before the standard statistical analysis, resulting in an overall reduction in failure of RCTs from ~50 to ~10%.

In dose escalation studies cohorts of subjects are given increasing doses of a candidate drug to assess safety and tolerability, pharmacokinetics and pharmacological response. The escalation is carried on until a predefined stopping limit is achieved, often identified by a pharmacokinetic endpoint such as peak plasma concentration or area under the plasma concentration-time profile. In the present work, the application of Bayesian methodologies to Phase I dose escalation studies is explored. A Bayesian population model is devised, which provides predictions of dose-response and dose-risk curves, both for individuals already enrolled in the trial and for a new, previously untested subject. Empirical and fully Bayesian estimation algorithms are worked out. Such methods provide equivalent performances on both experimental and simulated datasets. With respect to previous work, it is quantitatively proven not only that a more general and flexible model is identifiable, but also that such flexibility is needed in real scenarios.

A novel mechanistic model based on a disease system analysis paradigm was developed to explore the role of homeostatic mechanisms involved in Alzheimer’s disease (AD) progression. We used longitudinal AD Assessment Scale-cognitive subscale (ADAS-cog) scores from 926 subjects with AD on stable acetylcholinesterase inhibitor therapy randomized to placebo treatment in two 54-week clinical trials. Alternative mechanistic models were evaluated by assuming that the rate of change of ADAS-cog over time was jointly regulated by a process characterizing the deterioration of ADAS-cog and by a process associated with a compensatory regulatory response. The model based on a time-varying deterioration rate of ADAS-cog performed better than the model based on a time-varying homeostatic control. The covariate analysis indicated that baseline Mini-Mental State Examination score, education, age, and apolipoprotein ɛ4 genotype had a significant effect on the level and shape of the trajectories of the mean model predicted ADAS-cog change from baseline.

Positron emission tomography (PET) is an imaging technique that is used to investigate ligand-receptor binding in the living brain and to determine the time course of plasma concentration/receptor occupancy (RO). The purpose of this work was to demonstrate the added value of an adaptive-optimal design for PET scan timings and dose selection over traditional study designs involving fixed or educated selections of timings and doses. A k(on)-k(off) model relating plasma concentration to PET data was applied to generate the simulated data. Optimization was performed on scanning timings and doses using the D-optimality criterion. Optimal designs as applied to scanning timings provided unbiased estimates and improved the accuracy of results relative to those of fixed and educated designs. Optimization of both timings and dose provided improvements in accuracy and precision when the initial dose selection was noninformative regarding the time course of RO. These results indicate that adaptive-optimal designs can provide an efficient experimental design for RO studies using PET, by minimizing the number of subjects required and maximizing information related to the plasma concentration-RO relationship.

A 30-min intravenous (i.v.) infusion of 200 mg of ciprofloxacin was administered twice daily to 12 patients with nosocomial pneumonia scheduled to undergo diagnostic fiberoptic bronchoscopy. The pharmacokinetics of ciprofloxacin were examined at the presumed steady state after 5 days of treatment. Eleven successive plasma samples were collected in the interval from 0 to 12 h after administration, and bronchial mucosa samples were taken 2 h after administration. Concentrations of drug in all samples were assayed by high-performance liquid chromatography with fluorimetric detection. The results showed that the kinetics in plasma did not differ from those determined previously in healthy volunteers. The mean concentrations in plasma peaked at 4.94 +/- 2.90 mg/liter at the end of infusion. The terminal half-life was 4.95 +/- 2.81 h, and the mean residence time 6.13 +/- 3.17 h. A large volume of distribution was calculated: 2.59 +/- 1.43 liters/kg. Mean total body clearance was 23.3 +/- 10.1 liters/h. The concentrations in bronchial mucosa reached 21.6 +/- 5.63 micrograms/g 2 h after drug intake. The tissue-versus-plasma concentration ratios ranged from 10.1 to 26.3 (mean value, 16.9 +/- 5.43). After 6 to 12 days of i.v. treatment, four patients were switched to oral ciprofloxacin. We propose a model for the simultaneous fit of the concentration-time curves obtained after i.v. infusion and oral dosing. The concentrations in tissue observed in this study were in excess of the MICs for bacteria considered to be susceptible to ciprofloxacin.

The 123I-IBZM SPECT measured D2 receptor occupancy (D2RO) in chronically dosed, stabilized schizophrenic patients and its relationship with antipsychotic (AP) pharmacokinetics (PK) over time is still unclear. The aims of this study were: 1) To define the relationship between striatal D2 receptor occupancy (D 2RO) and plasma concentration ( CP) in stabilized schizophrenic patients on clinically relevant doses using 123I-IBZM SPECT; 2) To investigate the time course of AP-induced D2RO and corresponding CP. Forty-six schizophrenic patients on their clinically required doses of risperidone, olanzapine, clozapine or quetiapine were included. D 2RO and CP were measured over time following a sparse-sampling experimental design, and individual PK and D2RO-time profiles were estimated using a population approach. Observed striatal D2RO and CP ranges were 28—75% and 9.4—60.5 ng/mL for risperidone, 22—84% and 8.6—89.5 ng/mL for olanzapine, 5—53% and 41.6—818.2 ng/mL for clozapine and 0—64% and 37.9—719.6 ng/mL for quetiapine. A PK—D2RO relationship was found for the four APs. D2RO pattern over time was stable for risperidone, olanzapine and clozapine but fluctuating for quetiapine. Stabilized schizophrenic patients show a wide range of both D2RO and CP at clinically effective doses of the four AP, suggesting that clinical response to these AP may be maintained with D2RO below 65%. D2RO patterns over time differ between AP. These results should be considered for accurate interpretation of D2RO measurements, proper design of studies and optimization of drug regimens for patients on AP treatment.

The Hamilton depression rating scale (HAM-D(17)) has been the gold standard in depression trials since its introduction in 1960 by Max Hamilton. However, several authors have shown that the HAM-D(17) is multi-dimensional and that subscales of the HAM-D(17) outperform the total scale. In the current study, we assess the sensitivity of the individual HAM-D(17) items in differentiating responders from non-responders over the typical treatment period used in clinical efficacy trials. Based on data from randomised, placebo-controlled trials with paroxetine, a graphical analysis and a statistical analysis were performed to identify the items that are most sensitive to the rate and extent of response irrespective of treatment. From these analyses, two subscales consisting of seven items each were derived and compared to the Bech and Maier and Philip subscales using a linear mixed-effects modelling approach for repeated measures. The evaluation of two clinical trials revealed endpoint sensitivity comparable to the existing subscales. Using a bootstrap technique, we show that the subscales consistently yield higher statistical power compared to the HAM-D(17), although no subscale consistently outperforms the others. In conclusion, this study provides further evidence that not all items of the HAM-D(17) scale are equally sensitive to detect responding patients in a clinical trial. A HAM-D(7) subscale with higher sensitivity to drug effect is proposed consisting of the HAM-D(6) and the suicide item. This response-based subscale increases signal-to-noise ratio and could reduce failure rate in efficacy trials with antidepressant drugs.

Current data on mycophenolate mofetil (MMF) suggest that there is a pharmacokinetic/pharmacodynamic relationship between the mycophenolic acid (MPA) area under the curve (AUC) during treatment and both the risk of acute rejection and the occurrence of side effects. The aim of this study was to characterize the population pharmacokinetics of MPA in kidney transplant patients between the ages of 2 and 21 years and to propose a limited sampling strategy to estimate individual MPA AUCs. Forty-one patients received long-term oral MMF continuous therapy as part of a triple immunosuppressive regimen, which also included cyclosporine or tacrolimus (n=3) and corticosteroids. Therapy was initiated at a dose of 600 mg/m twice daily. The population parameters were calculated from an initial group of 32 patients. The data were analyzed by nonlinear mixed-effect modeling using a 2-compartment structural model with first-order absorption and a lag time. The interindividual variability in the initial volume of distribution was partially explained by the fact that this parameter was weight-dependent. Fifteen concentration-time profiles from 13 patients were used to evaluate the predictive performance of the Bayesian approach and to devise a limited sampling strategy. The protocol, involving two sampling times, 1 and 4 hours after oral administration, allows the precise and accurate determination of MPA AUCs (bias -0.9 microg.h/mL; precision 6.02 microg.h/mL). The results of this study combine the relationships between the pharmacokinetic parameters of MPA and patient covariates, which may be useful for dose adjustment, with a convenient sampling procedure that may aid in optimizing pediatric patient care.

The objective of the present study was to develop a population pharmacokinetic model for nelfinavir mesylate (NFV) and nelfinavir hydroxy-tert-butylamide (M8), the most abundant metabolite of NFV, in infants vertically infected with human immunodeficiency virus type 1 and participating in the Paediatric European Network for Treatment of AIDS 7 study. Plasma NFV concentrations were determined during repeated NFV administrations (two to three times a day). Eighteen infants younger that age 2 years participated in this study. The doses administered ranged from 71 to 203 mg/kg of body weight/day. Pharmacokinetic parameter estimates were obtained by a compartmental approach by using a kinetic model to simultaneously fit NFV and M8 (active metabolite) concentrations. M8 was shown to be formation rate limited and was characterized by first-order rate constants of formation and elimination. Body weight was found to be a more appropriate predictor than age of the changes in (i) the rate of metabolism, (ii) the elimination rate constant of NFV, and (iii) NFV clearance. Population parameters were computed to account for the relationship between the rate of metabolism and body weight. The estimated NFV and M8 elimination half-lives were 4.3 and 2.04 h, respectively. The estimated NFV clearance was 2.13 liters/h/kg. The M8 concentration-to-NFV concentration ratio was 0.64 ± 0.44. In conclusion, the population pharmacokinetic model describing the dispositions of NFV and M8 should facilitate the design of future studies to elucidate the relative contributions of the parent compound and M8 to the pharmacological and toxic effects of NFV therapy.

Background Chronic alcoholic patients are frequently presented for anesthesia and surgery. These patients require higher doses of propofol than control patients for induction of anesthesia, but whether this is because of changes in pharmacokinetics or pharmacodynamics is not known. This study was designed to investigate the influence of chronic ethanol intake on propofol pharmacokinetics. Methods Fifteen chronic alcoholic and 15 control patients, receiving propofol by target-controlled infusion for otolaryngologic surgery, were studied. Blood propofol concentrations were measured at regular intervals during and after the propofol infusion. Nonlinear mixed-effects population models (NONMEM) examining the influence of alcoholism were constructed. The influence of recovery on propofol pharmacokinetic parameters was also addressed. Results The total amount of propofol and the predicted and measured concentrations during all phases of anesthesia did not differ between the two groups. The fact that the measured concentrations at the time of opening eyes were similar further confirmed that the potency of propofol was not modified by the alcoholic status of the patients. Chronic alcoholism was associated with only mild changes in propofol pharmacokinetics (increase in rapid intercompartmental clearance and greater interindividual variability in the central volume of distribution). The rebound in concentration frequently observed during the recovery phase could be related to decreased propofol peripheral volumes of distribution despite an increase in elimination clearance. Conclusions Chronic alcoholism induces only mild changes in the pharmacokinetics of propofol. Conversely, propofol pharmacokinetics are markedly different during anesthesia and surgery or after opening eyes in the recovery period.

The purpose of this study was to develop a pharmacokinetic model simultaneously accounting for topotecan concentrations in plasma and saliva. Thirteen patients with metastatic epithelial ovarian cancer received topotecan. During the first and the second courses of treatment, each patient underwent pharmacokinetic evaluation. Data were analyzed using the nonlinear mixed-effect model program. The saliva concentrations were associated to a peripheral compartment while the central compartment described the plasma concentration time course. Thus, a three-compartment model was used; the basic parameters were: total clearance (CL), initial volume of distribution (V1), transfer rate constants (k12/k21 and k13/k31). The interoccasion variability was taken into account in the model. Data analysis was performed using a three-step approach; in step 2, a close relationship was found between creatinine CL and topotecan CL. The inclusion of this second stage model significantly improved the fit. Large interindividual variability in pharmacokinetic parameters occurred (CL varied from 10.4 to 23 L/h) while interoccasion variability was limited (6%). Seven additional courses were used for model validation. A limited sampling strategy using Bayesian estimation based on two sampling times (saliva at 25 min and plasma plus saliva at 8.5 h after the start of infusion) was developed. This study shows that salivary concentrations can be effectively used for drug monitoring.

To develop a new strategy for the in silico evaluation of the optimal in vivo delivery properties of a drug, minimizing a cost function defined by the brain receptor occupancy obtained in positron-emission tomography experiments.A convolution-based model was formulated to link in vivo delivery rate to plasma concentrations whereas a second-stage model was used to link plasma concentrations to the pharmacodynamic effect. A feedback control approach was applied to identify the optimal in vivo delivery rate given an appropriate optimality criterion. Finally, clinical trial simulation was used as a supportive tool for decision-making by evaluating different scenarios accounting for pharmacokinetic/pharmacodynamic parameter uncertainty, inter-subject variability. and drug potency.The results revealed that the mean in vivo delivery time significantly affects brain receptor occupancy whereas the fraction of the dose available for the systemic circulation shows the highest influence on brain receptor occupancy for a given in vivo delivery rate. Finally, variability on receptor occupancy seems to be more affected by the inter-individual variability on the disposition PK parameters.The integration of convolution-based model. feedback control approach, and clinical trial simulation offers a unique tool for in ilico improvement of the drug development process by identifying critical issues on drug properties, optimal in vivo delivery rate, and potential problems related to the inter-individual variability.

Positron-Emission Tomography (PET) is an imaging technology currently used in drug development as a non-invasive measure of drug distribution and interaction with biochemical target system. The level of receptor occupancy achieved by a compound can be estimated by comparing time-activity measurements in an experiment done using tracer alone with the activity measured when the tracer is given following administration of unlabelled compound. The effective use of this surrogate marker as an enabling tool for drug development requires the definition of a model linking the brain receptor occupancy with the fluctuation of plasma concentrations. However, the predictive performance of such a model is strongly related to the precision on the estimate of receptor occupancy evaluated in PET scans collected at different times following drug treatment. Several methods have been proposed for the analysis and the quantification of the ligand-receptor interactions investigated from PET data. The aim of the present study is to evaluate alternative parameter estimation strategies based on the use of non-linear mixed effect models allowing to account for intra and inter-subject variability on the time-activity and for covariates potentially explaining this variability. A comparison of the different modeling approaches is presented using real data. The results of this comparison indicates that the mixed effect approach with a primary model partitioning the variance in term of Inter-Individual Variability (IIV) and Inter-Occasion Variability (IOV) and a second stage model relating the changes on binding potential to the dose of unlabelled drug is definitely the preferred approach.

Computer-assisted drug development (CADD) is an emerging technology for accelerating drug development based on the integration of mathematical modelling and simulation. This methodology provides a knowledge-based decisional tool on alternative development strategies based on the evaluation of potential risks on drug safety, and the definition of experimental design of new trials with expected power and probability of success. An example of CADD implementation is presented to design the first-time-in-man (FTIM) and the proof-of-concept (PoC) study of a new CNS compound. The final objective of the example presented is not necessarily to supply a success story of a correct prediction of human data from animal studies but to define a credible strategy suitable to design FTIM and PoC studies using preclinical data without the support of any human in vivo information. Rhesus monkey and human PK were initially estimated using allometric scaling on data collected in dogs, cynomolgus monkeys and rats. A PK/PD model was derived from a study conducted in rodent and validated by comparing the model predicted response to the one observed in a PET experiment conducted in rhesus monkey. The final PK/PD model, incorporating potential variability and uncertainty on scaled human prediction together with a receptor affinity adjustment derived from in vitro binding studies, was used to design the first-time-in-man and the proof-of-concept study.

Purpose: The purpose of this work was to estimate the population pharmacokinetic parameters of 5-fluorouracil (5-FU) in patients with advanced colorectal cancer using circadian change kinetics. Methods: Eighty-five patients (32 females, 53 males) were enrolled onto this study. All patients received folinic acid (200 mg/m2) by intravenous infusion over 2 h followed by a 5-FU loading dose (400 mg/m2) and then continuous infusion (600 mg/m2) for 22 h. This whole regimen was repeated on day 2 and was given on a 14-day cycle. Plasma 5-FU determinations were performed by high-performance liquid chromatography with ultraviolet absorbance detection. Pharmacokinetic analyses were performed using the NONMEM computer program through the Visual-NM graphical interface. An open one-compartment pharmacokinetic model with zero-order input rate was used to describe the kinetics of 5-FU; moreover, circadian time-dependent changes in 5-FU concentrations were taken into account in the model. The circadian model was defined as the sum of two cyclic components; the amplitude of the first cyclic component (over 24 h) was about 30% of the average clearance and the amplitude of the second cyclic component (over 12 h) was about 50% of the amplitude of the first component. The acrophase (peak) times of the first and the second periodic component were 04 h 12 m and 00 h 25 m, respectively. The potential sources of variability on the population parameters (65 patients) were investigated using patient's sex, body area, age, body weight, height, liver enzymes and serum creatinine as covariables. Results: Only the estimated clearance circadian changes were different for the two sexes. The population parameter estimates of mean clearance (CL mean ) and initial volume of distribution (V), were as follows: the male subgroup showed a CL mean value twice larger (125 l/h) than the value observed in the female subgroup (65 l/h), and V = 21 l. A validation group of 20 additional patients was used to evaluate the predictive performances of the population parameters. The individual pharmacokinetic parameters were computed by means of a Bayesian fitting procedure. From the resulting individualized parameter values, concentrations of 5-FU in the plasma were calculated. To evaluate the performance of the Bayesian estimation, the experimental concentrations were compared with the predicted ones. Conclusion: In conclusion, a chronomodulated delivery schedule of 5-FU should be performed, using a perfusion rate inversely proportional to the circadian variations of clearance in order to maintain stable 5-FU plasma levels. Such a treatment schedule may result in increased effectiveness of the treatment and decreased occurrence of drug-associated side-effects. The present study develops a complete procedure to efficiently estimate 5-FU clearance in order to optimize dosage regimens in individual patients.

The pharmacokinetic parameters of amikacin were determined in a population of 20 adults and 36 pediatric patients admitted into an intensive care unit. Amikacin was administered by repeated intravenous infusion over 0.5 h (600 to 1,350 mg for adults; 70 to 1,500 mg for children). The number of administrations ranged from 2 to 17, and the number of samples collected from each patient ranged from 2 to 70. The population enrolled in the study had large variabilities in age (0.5 to 85 years), weight (6 to 95 kg), height (72 to 187 cm), creatinine clearance rate (18 to 110 ml/min), blood urea nitrogen concentration (1.5 to 15 mmol/liter), and total protein concentration (30 to 91 g/liter). The mean population parameters and their interindividual variabilities were obtained for an initial group of 44 patients (16 adults and 28 children). A two-compartment model was fitted to the population data by using the computer program P-PHARM. Model selection was guided by evaluation of the minimum objective function and the weighted residuals. The population analysis has been performed with the complete set of the collected data, including the individual serum amikacin concentration together with the individual estimate of the creatinine clearance values. The potential sources of variability in the population parameters were investigated by using patients' age, height, weight, creatinine clearance, blood urea nitrogen concentration, and total protein concentration as covariables. A test group of 12 additional patients (4 adults and 8 children) was used to evaluate the predictive performances of the population parameters. The individual pharmacokinetic parameters were computed by a Bayesian fitting procedure. From the resulting individualized values of the parameters, the concentrations of amikacin in the serum of the patients were calculated. To evaluate the performance of the Bayesian estimation, the experimental concentrations were compared with the predicted ones. The Bayesian approached developed in the study accurately predicts amikacin concentrations in serum and allows for the estimation of amikacin pharmacokinetics parameters, minimizing the risk of bias in the prediction. This was demonstrated in patients with both stable and unstable renal functions.

This paper describes a methodology to calculate methotrexate (MTX) pharmacokinetic parameters after intramuscular administration using two samples and the population parameters. Total and free MTX were measured over a 36-h period in 56 rheumatoid arthritis patients; 14 patients were studied after a two-dose scheme at 15-day intervals. The Hill equation was used to relate the free MTX to the total MTX changes in plasma concentrations, and a two-compartment open model was used to fit the total MTX plasma concentrations. A non-linear mixed effect procedure was used to estimate the population parameters and to explore the interindividual variability in relation to the following covariables: age, weight, height, haemoglobin, erythrocyte sedimentation rate, platelet count, creatinine clearance, rheumatoid factor, C-reactive protein, swelling joint count, and Ritchie's articular index. Population parameters were evaluated for 40 patients using a three-step approach. The population average parameters and the interindividual variabilities expressed as coefficients of variation (CV%) were: CL, 6.94 l center dot h-1 (20.5%); V, 34.8 l (32.2%); k12, 0.0838 h-1 (47.7%); k21, 0.0769 h-1 (61.6%); ka, 4.31 h-1 (58%); Emax, 1.12 mu mol center dot l-1 (19.7%); gamma, 0.932 (12.3%); and EC50, 2.14 mu mol center dot l-1 (27.3%). Thirty additional data sets (16 new patients and 14 patients of the previous population but treated on a separate occasion) were used to evaluate the predictive performance of the population parameters. Twelve blood samples were collected from each individual in order to calculate individual parameters using standard fitting procedures. These values were compared to the ones estimated using a Bayesian approach with population parameters as a priori information together with two samples, selected from the individual observations. The results show that the bias was not statistically different from zero and the precision of these parameters was excellent.

Pharmacokinetic studies with antipyrine were carried out on beagle dogs to determine the consequence of hepatectomy on hepatic drug metabolizing capacity, the rate of hepatic regeneration, and the possible beneficial effect of hepatocellular transplantation. The drug (250 mg) was administered by short IV infusion in three groups of dogs (first group, 65% hepatectomy; second group, 65% hepatectomy with hepatocyte transplantation; third group 80% hepatectomy). Pharmacokinetic parameters of antipyrine were evaluated before surgery and within 10 d after surgery. Blood samples were taken at frequent intervals after drug administration and antipyrine was assayed in plasma by a specific HPLC method with UV detection. Before surgery, the mean elimination half-life was about 1.1 h and total clearance averaged 6 L h-1. In dogs with 65% hepatectomy, no statistical differences in pharmacokinetic parameters of antipyrine appeared before or after surgery. When 65% hepatectomy was associated with hepatocyte transplantation, a significant increase in elimination half-life and a significant decrease in total clearance were observed. The same statistical differences in the pharmacokinetic parameters were observed in the group with 80% hepatectomy. Transplantation of isolated hepatocytes into the spleen did not correct hepatocellular insufficiency. In this study, numerous laboratory tests were performed. A significant correlation was found between serum albumin, cholesterol, factor V, ALAT, total bilirubin, and ratio of amino acids and the pharmacokinetic parameters of antipyrine.

This article proposes an EM-like algorithm for estimating, by maximum likelihood, the population parameters of a nonlinear mixed-effect model given sparse individual data. The first step involves Bayesian estimation of the individual parameters. During the second step, population parameters are estimated using a linearization about those Bayesian estimates. This algorithm (implemented in P-PHARM) is evaluated on simulated data, mimicking pharmacokinetic analyses and compared to the First-Order method and the First-Order Conditional Estimates method (both implemented in NONMEM). The accuracy of the results, within few iterations, shows the estimation capabilities of the proposed approach.

The pharmacokinetics of ceftibuten in plasma and urine were investigated after oral administration. Twelve healthy subjects were treated orally twice daily with 400 mg of the drug for 7 days; on day 8, the subjects received a last dose of 400 mg of ceftibuten. Ceftibuten and its metabolite, the trans isomer of ceftibuten, were assayed in plasma and urine by a specific HPLC method with UV detection. Ceftibuten was rapidly absorbed, as evidenced by the mean time to the maximum observed cis-ceftibuten concentration of 2.4 h. To describe the drug intake process, a Weibull model was used. For the metabolite, the mean time to maximum concentration in plasma was 3.25 h. Mean values for the terminal half-life in plasma were 2.17 h for cis-ceftibuten and 3.19 h for trans-ceftibuten. The overall elimination half-life, tmax, and total and renal clearances of cis-ceftibuten were invariant with respect to duration of dosing. The area under the plasma concentration versus time curve from 0 to infinity and the Cmax of this drug were significantly higher on day 8 than the values predicted from the elimination half-life computed on day 1 of treatment and the dosing interval. The pharmacokinetic parameters of trans-ceftibuten were invariant with respect to duration of dosing. Ceftibuten was well tolerated; there were no clinically significant adverse clinical events. The results from the present study indicate that the levels of cis-ceftibuten in plasma as well as in urine remain above the MICs for susceptible organisms over the dosing interval.

Multiple-dose pharmacokinetics of pefloxacin were evaluated in 25 patients with hepatocellular insufficiency. The severity of liver disease was graded A, B or C according to the Child-Pugh classification. Pharmacokinetic parameters evaluated in patients on day 1 of treatment were compared with those computed in 11 healthy volunteers (the control group) after a single dose. Blood samples were taken at frequent intervals after drug administration and assayed by high performance liquid chromatography. The mean age of patients with liver impairment was slightly greater (59.5 years, range 33 to 81 years) than that of the control group (46.7 years, range 42 to 51 years). In the patients with liver disease, the mean (± SD) half-life of elimination, although highly variable, was significantly longer (46.3 ± 42.5 hours) than in the control group (11.3 ± 3.5 hours, p < 0.001). The total clearance was significantly decreased (1.76 ± 1.31 L/h vs 6.03 ± 2.99 L/h in the control group). In groups B and C of the Child-Pugh classification, total body clearance was about 30% of normal values. Elimination half-life increased by 200% in group B and 373% in group C compared with values in healthy volunteers. Intergroup differences (group B vs group C of the Child-Pugh classification) were not statistically significant. The minimum concentrations inhibiting 90% of Gram-negative strains (MIC90) were exceeded by plasma pefloxacin concentrations throughout treatment. For most patients, trough plasma concentrations were above 2 mg/L and peak plasma concentrations averaged 8.5 mg/L. Large inter- and intraindividual variations in the elimination half-life, total clearance and volume of distribution were observed. A practical index is proposed for estimating the most likely pharmacokinetic parameters for a given patient, taking into account the values of the Child-Pugh score or the prothrombin time.

Phenazone (antipyrine) 1g was given by short intravenous infusion to 62 study participants (10 healthy drug-free volunteers and 52 patients with chronic liver disease). A Bayesian approach was developed to determine the individual pharmacokinetic parameters of phenazone. Statistical characteristics of the population pharmacokinetic parameters were first evaluated for 30 patients. When combined with 1 plasma drug concentration from members of the second group, these led to a Bayesian estimation of individual pharmacokinetic parameters for the remaining 32 individuals. Total clearance computed by Bayesian estimation was compared with maximal likelihood estimation of this parameter, the classical procedure. No statistically significant differences were found. Performance of the developed methodology was evaluated by computing bias and precision. The mean error was 0.0477 L/h. The precision of the prediction of this parameter (0.155 L/h) remained lower than the interindividual standard deviation (0.765 L/h). This procedure enables the estimation of individual pharmacokinetic parameters for phenazone. In this study, numerous laboratory tests were performed. A highly significant correlation (p0.001) was found between phenazone clearance and the prothrombin time, albumin, gamma-globulin, factor V, antithrombin III, fibrinogen and total bilirubin. Discriminant analysis determined that protein, alkaline phosphatase, creatininaemia and gamma-globulin had more significant discriminating power and gave better prognostic results than those seen with the Child-Pugh test.