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• W2059389975 abstract "The in vivo evaluation of the antitumour effect using xenografted mice is a fundamental step in the preclinical development process of oncology drugs. In this type of experiments tumour cells from immortalized human cell lines are inoculated in athymic mice; the animals are then randomized in groups treated either with a vehicle or an active treatment and the corresponding tumour growth curves are compared for obtaining information on the efficacy of tested compounds. In this respect, one of the most usual metrics is the tumour growth inhibition. Tumour growth inhibition is calculated as difference between tumour weight in treated and control animals expressed as percentage of tumour weight in control animals. However, this metric is dose- and schedule-dependent and may be strongly influenced by the time-point at which the measurements are performed. We recently developed a simple and effective pharmacokinetic-pharmacodynamic model linking the plasma concentrations of anticancer compounds to the effect on the tumour growth (Simeoni et al. 2004). The model successfully described the growth of total tumour mass obtained in mice given anticancer drugs, providing physiologically relevant parameters. In this communication two examples of its application to a discovery candidate and to a known anticancer drug are shown. The dependencies of tumour growth inhibition on the experimental conditions are also discussed using simulations. The experiments performed using A2780 human ovarian carcinoma cell lines were implanted sub cuteinto the left flank of nude mice (n=6–10/group). At palpable tumour, mice received placebo or the active drug (Drug A or vinblastine). Tumour dimensions were measured by caliper and tumour weights were calculated, assuming unit density, as D · d2/2, where D and d are the larger and the smaller dimensions, respectively. The pharmacokinetics were investigated in separate groups (n=3–5) of tumour-bearing mice. The drug concentrations in plasma were measured using liquid chromatography with tandem mass spectrometry. Compartmental pharmacokinetic models were fitted to the plasma concentration-time data using non-linear regression (Winnonlin program, v. 3.1, Pharsight). The pharmacodynamic model is summarized in the scheme reported in fig. 1. It is considered that, in control animals (unperturbed growth), the tumour mass grows exponentially up to a threshold weight, above which the growth becomes linear with time. The model parameters λ0 and λ1 provide estimates of the rates of growth in these two phases. In the treated animals the growth is perturbed by the anticancer treatment that makes some cells non-proliferating, eventually bringing them to death. In this case, the tumour growth rate is decreased proportionally to both plasma drug concentrations and weight of proliferating tumour cells, via a parameter k2, which is representative of the potency of the anticancer agent. Cells affected by drug action stop proliferating and pass through different stages, characterized by progressive degrees of damage and, eventually, they die. This can be described using a transit compartmental system, characterized by a first order rate constant k1. In the model, the total tumour weight is obtained as the sum of the weights of proliferating and damaged cells. The model was simultaneously fitted to the average tumour mass data obtained in control and treated animals, using non-linear regression (Winnonlin, v. 3.1, Pharsight). Scheme of the pharmacokinetic-pharmacodynamic (PK-PD) model. Unperturbed growth: w(t): total tumour mass, w0: initial tumor mass, λ0: rate constant of exponential growth, λ1: slope of the linear growth, ψ: shape factor. Perturbed growth: Z1(t): proliferating tumour mass, Z2(t), Z3(t), Z4(t): mass of tumour cells in the different stage of damage, K2 proportionality constant representing the potency of the agent, K1 first-order transfer rate constant. Candidate Drug A. In this example, the model was used prospectively to simulate the outcome of subsequent studies. In a preliminary experiment, mice were given Drug A intraperitoneally, bid×13 days at a dose level of 45 mg/kg (fig. 2). Based on the known pharmacokinetics of Drug A, the model was fitted to the data and the following pharmacodynamic parameters were calculated: w0=0.008 g, λ0=0.019 h−1, λ1=0.029 g · hr−1, K1=0.13 hr−1, K2=7.3 · 10–6 ml · hr−1 · ng−1. It was subsequently decided to test the candidate using intravenous dosing. For this purpose it was considered interesting to use the model for predicting the outcome of three possible regimens (t.i.d.×1 day, q.d.×11 days, b.i.d.×4 days). Preliminary pharmacokinetic data after intravenous dosing were used to simulate the expected plasma profiles at the different dosing regimens and the corresponding tumour growth curves were generated using the pharmacodynamic parameters previously estimated from the intraperitoneal experiment. Predictions and observations are shown in fig. 3. Despite some quantitative differences, essentially due to the different growth of controls, the qualitative agreement between predictions and observations at the three different schedules was excellent. It has also to be considered that many factors can influence the response in case of different administration routes (e.g., first-pass formation of active metabolites), so that this approach may help in interpreting the occurrence of such complexities. Observed and model-fitted tumour growth curves obtained in nude mice given intraperitoneally Drug A (45 mg/kg b.i.d.×13 days from Day 8). Left panel. Tumour growth curves predicted in nude mice given intravenously Drug A at 60 mg/kg dose level either t.i.d.×1 day, q.d.×11 days or b.i.d.×4 days from Day 9. Predictions were based on PD parameters obtained after the intraperitoneal administration. Right panel. Tumour growth curves observed in nude mice given Drug A intravenously at 60 mg/kg dose level either t.i.d.×1 day, q.d.×11 days or b.i.d.×4 days from Day 9. Vinblastine. Mice were given either the vehicle or vinblastine intravenous in single dose or q.4d×2 at the dose level of 3 mg/kg. The pharmacokinetic analysis was performed using an ancillary group of animals. The good agreement between the observed and model-fitted tumour growth data in the different experimental arms is shown in fig. 4. Observed and model-fitted tumour growth curves obtained in nude mice given either the vehicle or vinblastine intravenously (3 mg/kg given either as a single dose or q.4d×2 from Day 8). In the inset the fitting of the pharmacokinetic data is shown. Considerations on the experimental design. For evaluating the dependence of tumour growth inhibition metric from the experimental design, the outcome of different intravenous treatments of vinblastine was simulated: single doses of 1 or 6 mg/kg or 1 mg/kg given q.4d×2. For each treatment the average tumour growth curves were generated using the data of the previous experiment and the corresponding tumour growth inhibition were calculated and plotted (fig. 5). Maximal values of tumour growth inhibition were reached at different time points and biased estimations would have been obtained in case tumour growth inhibition was measured at a fixed time (e.g., as typically done for cytotoxics, 7 days after the end of treatment). Lower panel. Tumour growth curves predicted in nude mice given either the vehicle or vinblastine intravenously (1 mg/kg either as a single dose or q.4d×2 and 6 mg/kg single dose from Day 8). Upper panel. Tumour growth inhibition versus time curves derived using the predicted data of the lower panel. Further examples of the successful application of a pharmacokinetic-pharmacodynamic approach for modeling and predicting the tumour growth in xenografted mice have been presented. Compared to experimental tumour growth inhibition, the model is able to provide parameters that are not dependent on the experimental conditions. Thus they can be used prospectively for predicting the outcome of the subsequent experiments based on preliminary results. The model can be used in support to oncology research for ranking compounds and optimizing the experimental designs, allowing consistent savings in terms of resources and time. The authors would like to thank the scientists of the bioanalytical department involved in the generation of the pharmacokinetic data." @default.
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• W2059389975 title "A Pharmacokinetic-Pharmacodynamic Model for Predicting Tumour Growth Inhibition in Mice: A Useful Tool in Oncology Drug Development" @default.
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• W2059389975 doi "https://doi.org/10.1111/j.1742-7843.2005.pto960325.x" @default.
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