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Purpose: We developed a drug-disease simulation model to predict antitumor response and overall survival in phase III studies from longitudinal tumor size data in phase II trials., Methods: We developed a longitudinal exposure-response tumor-growth inhibition (TGI) model of drug effect (and resistance) using phase II data of capecitabine (n = 34) and historical phase III data of fluorouracil (FU; n = 252) in colorectal cancer (CRC); and we developed a parametric survival model that related change in tumor size and patient characteristics to survival time using historical phase III data (n = 245). The models were validated in simulation of antitumor response and survival in an independent phase III study (n = 1,000 replicates) of capecitabine versus FU in CRC., Results: The TGI model provided a good fit of longitudinal tumor size data. A lognormal distribution best described the survival time, and baseline tumor size and change in tumor size from baseline at week 7 were predictors (P < .00001). Predicted change of tumor size and survival time distributions in the phase III study for both capecitabine and FU were consistent with observed values, for example, 431 days (90% prediction interval, 362 to 514 days) versus 401 days observed for survival in the capecitabine arm. A modest survival improvement of 39 days (90% prediction interval, -21 to 110 days) versus 35 days observed was predicted for capecitabine., Conclusion: The modeling framework successfully predicted survival in a phase III trial on the basis of capecitabine phase II data in CRC. It is a useful tool to support end-of-phase II decisions and design of phase III studies.

For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic-pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose-toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.

Objective: The objective of the present investigation was to develop a population pharmacodynamic model for midazolam- and lorazepam-induced sedation upon long-term continuous infusion in critically ill patients., Methods: The study was conducted in 59 patients receiving lorazepam and 54 patients receiving midazolam by continuous infusion for at least 24 h. Repeated blood samples were obtained for determination of the concentrations of lorazepam and midazolam. The level of sedation was assessed using a 5-point sedation scale., Results: The pharmacokinetics of lorazepam and midazolam was described with previously proposed pharmacokinetic models. For the pharmacodynamics, the probability that the sedation was equal to or more than a specific score was described using a sigmoid E(max) model. The EC(50) values of lorazepam for the sedation scores equal or larger than 2-5 were 6.1, 57, 184 and 529 ng/ml, respectively. The corresponding values for midazolam were 216, 483, 1,100 and 2,200 ng/ml. Inter-individual variability in the EC(50) values was relatively high with a CV of 68% for lorazepam and 86% for midazolam (p=0.035). No covariates explaining part of the observed inter-individual variability were identified., Conclusion: The population pharmacodynamic model shows a similarly wide intra- and inter-individual variability in the pharmacodynamics of both lorazepam and midazolam. Thus, the previously observed differences in "ease of titration" between lorazepam and midazolam are unrelated to pharmacodynamic factors.

Aims: Allometric equations have proven useful for the extrapolation of animal data to determine pharmacokinetic parameters in man. It has been proposed that these equations are also applicable over the human size range including the paediatric population. The aim of this work was to study the relationship between various pharmacokinetic parameters for propofol and body weight using data from rats, children and adults. Furthermore, the utility of allometric scaling is evaluated by the prediction of propofol concentrations in humans based on data obtained in the rat., Methods: The relationship between the pharmacokinetic parameters of propofol obtained in rats, children and adults was analyzed by plotting the logarithmically transformed parameters against the corresponding logarithmically transformed body weights. In addition, based on allometric equations, pharmacokinetic parameters obtained in rats were scaled to humans. These parameters were used to simulate propofol concentrations in long-term sedated critically ill patients using NONMEM. Simulated concentrations were then compared with actually observed concentrations in humans., Results: The relationship between pharmacokinetic parameters of propofol from rats, children and adults was in good agreement with those from the literature on allometric modelling. For clearance, intercompartmental clearance, central volume of distribution and peripheral volume of distribution, the power parameters were 0.78, 0.73, 0.98 and 1.1, respectively, and r2 values for the linear correlations were 0.990, 0.983, 0.977 and 0.994, respectively. On the basis of data obtained after a single bolus injection in the rat, adequate predictions of propofol concentrations in critically ill patients can be made using allometric equations, despite the long-term nature of the use of the drug, the large number of infusion changes per day and/or differences in state of health and age., Conclusions: For propofol, allometric scaling has proved to be valuable for cross species extrapolation. Furthermore, the use of the allometric equation between adults and children seems to be an adequate tool for the development of rational dosing schemes for children of varying body weights, and requires further study.

The objective of this investigation was to compare the in vivo potency and intrinsic activity of buspirone and its metabolite 1-(2-pyrimidinyl)-piperazine (1-PP) in rats by pharmacokinetic-pharmacodynamic modeling. Following intravenous administration of buspirone (5 or 15 mg/kg in 15 min) or 1-PP (10 mg/kg in 15 min), the time course of the concentrations in blood were determined in conjunction with the effect on body temperature. The pharmacokinetics of buspirone and 1-PP were analyzed based on a two-compartment model with metabolite formation. Differences in the pharmacokinetics of buspirone and 1-PP were observed with values for clearance of 13.1 and 8.2 ml/min and for terminal elimination half-life of 25 and 79 min, respectively. At least 26% of the administered dose of buspirone was converted into 1-PP. Complex hypothermic effects versus time profiles were observed, which were successfully analyzed on the basis of a physiological indirect response model with set-point control. Both buspirone and 1-PP behaved as partial agonists relative to R-(+)-8-hydroxy-2-(di-n-propylamino)tetralin (R-8-OH-DPAT) with values of the intrinsic activity of 0.465 and 0.312, respectively. Differences in the potency were observed with values of 17.6 and 304 ng/ml for buspirone and 1-PP, respectively. The results of this analysis show that buspirone and 1-PP behave as partial 5-hydroxytryptamine(1A) agonists in vivo and that following intravenous administration the amount of 1-PP formed is too small to contribute to the hypothermic effect.