INTRODUCTION

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Antibiotics may occasionally induce central nervous system (CNS) side effects, including seizures, in humans. These are observed with fluoroquinolones (5, 39) and -lactams, in particular carbapenems (33). In this family the leading compound, imipenem, presents a relatively high risk of convulsions (1, 3), especially in patients with renal impairment or with bacterial meningitis (2, 41).

Various experimental approaches have been developed to investigate the convulsion liabilities of antibiotics in vivo, including direct intracerebroventricular injection (15, 40). However, this approach does not take into consideration the CNS diffusion characteristics of these drugs, which may have major impacts on their convulsant activity (11). The proconvulsive activity of antibiotics on pentylenetetrazol has also been investigated (8, 30), but many parameters may contribute to the observed proconvulsant effects, making data interpretation complex and potentially misleading (27).

An in vivo experimental approach to the study of the pharmacokinetic-pharmacodynamic (PK-PD) contributions to the convulsant activity of fluoroquinolones alone (11, 12) or in association with other drugs (13, 25) has recently been developed. This approach is based upon previous studies which showed that for convulsant compounds, such as pentylenetetrazol (31) or theophylline (32), the cerebrospinal fluid (CSF) was part of the biophase, meaning that the convulsant activities of these substances are directly related to their concentrations in CSF (7). However, unlike fluoroquinolones, the concentration of imipenem in CSF is not predictive of its convulsant activity (20).

Electroencephalogram (EEG) recording was then considered as a suitable alternative. This approach had occasionally been used to assess the epileptogenic effects of drugs, including antibiotics (14, 16, 17), and could be considerably improved by coupling quantitative EEG recording with PK-PD modeling analysis, as previously done to investigate the desirable CNS effects of drugs (6, 26).

	MATERIALS AND METHODS

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Animals. This work was done in accordance with the Principles of Laboratory Animal Care. Male Sprague-Dawley rats (Depres Breeding Laboratories, St. Doulchard, France) with a body weight between 320 and 350 g were housed in the animal breeding facilities of the laboratory (authorization no. 0028). The animals were placed in wire cages in a 12-h light-dark cycle for 1 week to adjust to the new environment and to overcome stress possibly incurred during transit. They had free access to food (AO4; U. A. R., Villemoisson, France) and water.

Surgery. Five days before the experiment, each rat had five cortical EEG electrodes implanted while under anesthesia (1.25 mg of ketamine [Ketalar], at a concentration of 50 mg ml¹; Parke Davis Laboratories, France, and 0.5 mg of xylazine hydrochloride [Rompum]; Bayer Laboratories, France). The electrodes were screwed into little holes drilled into the skull at the following positions, in relation to bregma: 2 mm anterior, 2 mm lateral (F1 and F2); 4 mm posterior, 2 mm lateral (P1 and P2); and 4 mm anterior, 2 mm lateral (reference electrode). The stainless steel electrodes were connected to a miniature plug fixed to the skull with dental cement. One day before the experiment, two permanent polyethylene catheters were implanted while each rat was under anesthesia (thiopental sodium, 60 mg kg of body weight¹; Sanofi Laboratories, France): one in the left femoral vein for drug administration and the other one in the left femoral artery for blood sample collection. Animals were housed individually in plastic cages. Food was withdrawn 12 h before the experiment, but animals had free access to water until drug administration.

Solutions for administration. Imipenem monohydrate-sodium cilastatin salt (Tienam; Merck, Sharp & Dohme Laboratories, France), was used to prepare a 15.9-mg ml¹ solution of imipenem in 0.9% NaCl.

Drug dosing and blood sampling. The rats in group I (n = 6, weight [mean ± standard deviation] = 335 ± 15 g) received an intravenous (i.v.) infusion of imipenem-cilastatin at a rate of 2.65 mg of imipenem per min for 30 min, corresponding to a dose of 80 mg of imipenem. The rats in groups II and III received the same dose of imipenem, either at an infusion rate of 1.325 mg min¹ for 60 min (group II, n = 6, weight = 335 ± 15 g) or at an infusion rate of 0.883 mg min¹ for 90 min (group III, n = 6, weight = 335 ± 15 g). Drug infusions started between 9:00 a.m. and 12:00 p.m.

EEG measurements. On the day of the experiment each rat was maintained in a plastic bol, and the miniature plug was connected to a moving connector to record the EEG signal. Bipolar EEG leads (F1-P1, F2-P2, F1-F2, and P1-P2) were continuously recorded using a paper polygraph (System 50,000 EEG recorder; Van Gogh, Medelec, France). The signal was band-pass filtered from 0.3 to 75 Hz. The EEG signal from the left hemisphere cortical lead (F2-P2) was simultaneously sampled at 256 Hz and analyzed online by fast Fourier transform (FFT) to determine the EEG total power in the frequency band from 0.5 to 30 Hz (Brain Wave Systems Co., Thornton, Colo.). The FFTs were calculated every 2 s, giving a first EEG power trend which could be visualized before being stored on the hard disk. Subsequently, after artifact removal from this power trend, a data reduction was calculated by averaging this first FFT trend every 1 min, resulting in a secondary trend. Consequently, each data point of the second trend was the mean of 30 consecutive points of the first trend. Corresponding data points of the second trend were used as effect measures for PK-PD modeling. The EEG recordings started 10 min before imipenem infusion and continued until the signals had returned to their baseline values.

Drug analysis. A previously described high-performance liquid chromatography assay (4) was used with minor modifications for imipenem determination. Proteins from serum samples were precipitated by the addition of methanol (1:2, vol/vol), the mixture was centrifuged, and the supernatant was injected. Separation was performed with a Nucleosil C₈ (5 µm, 250 by 0.4 mm [inner diameter]) column. The mobile phase consisted of 0.2 M aqueous borate buffer, pH 7.2, containing 15% (vol/vol) methanol, and the flow rate was 1 ml min¹. The retention time of imipenem was equal to 5.5 min. The chromatographic system consisted of a model L 6000 Merck-Hitachi pump and a Waters 717 plus refrigerated autosampler connected to a Waters 484 UV absorbance detector ( = 313 nm). Chromatographic data were recorded and processed using a Waters 746 integrator. The limit of quantitation of imipenem was 0.5 µg ml¹ in serum. Intraday coefficients of variation calculated at two concentrations were equal to or less than 10%. Corresponding interday coefficients were equal to or less than 13%.

Modeling procedures. A one-compartment open model with zero-order input (R₀) was used to characterize the serum concentration-versus-time profiles of imipenem during and after infusion:

(1)

(2)

where C is the concentration of imipenem in serum at time T, T_inf is the duration of infusion, k_e1 is the elimination rate constant, and V is the apparent volume of distribution.

(3)

(4)

(5)

(6)

(7)

(8)

1

1

	RESULTS

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Following a 30-min infusion of imipenem at a rate of 2.65 mg min¹, corresponding to a dose of 80 mg (group I), the decay of imipenem concentration in serum with time was monoexponential and rapid after infusion was stopped. Limited interindividual variability was observed. PK parameters are presented in Table 1. A dramatic temporal delay between concentration in serum and EEG effect was observed in every individual rat. Only isolated spikes appeared during imipenem infusion, with limited effects on the total power of the EEG signal. Then the frequency and amplitude of the spikes increased dramatically, leading to a relatively sudden increase of the total power, occurring in most animals between one and two half-lives postinfusion. This was accompanied by behavioral troubles, including tremors and partial seizures. The EEG signal reached a maximum at three elimination half-lives postinfusion on average and came back progressively to the baseline. Such a typical behavior is presented in Fig. 1.

View larger version (16K): [in this window] [in a new window]   FIG. 1.   Characteristic EEG changes induced by imipenem infusion (80 mg over 30 min) in a typical rat (group I) before (a) and at the end of (b) infusion, at the maximum effect (c), and after return to the baseline (d).

The indirect-effect model was tentatively fitted to these experimental data. However, it failed to described the lag time before the total power sharply increased, and it was only capable of predicting a progressive increase in the EEG signal, as illustrated in Fig. 2.

View larger version (13K): [in this window] [in a new window]   FIG. 2.   Observed total power of the EEG signal versus time and predicted values (solid line) according to the indirect-effect model with inhibition of the loss of effect, following imipenem infusion (80 mg over 30 min) in the same rat as in Fig. 1.

Much better results were obtained with the effect compartment model. Individual plots of EEG effect versus imipenem concentration in serum showed a spectacular counterclockwise hysteresis, indicating a profound disequilibrium between the concentrations in serum and at the effect site (Fig. 3A). This hysteresis collapsed when the effect was plotted versus concentration in the effect compartment, which could be adequately fitted with a spline function (Fig. 3B). Overall, the effect compartment model provided a good fitting of the relationship between imipenem concentration in serum and EEG effect, as illustrated in Fig. 4, with corresponding parameters accurately estimated (Table 2). The non-statistically significant differences between the parameter values estimated for the three groups (Table 2) and between the observed and predicted values of the derived parameters (Table 3) attest to the robustness of the compartment effect model in various experimental settings. Note that the pharmacokinetic parameters of imipenem were also unaffected by the change in infusion rate (Table 1).

View larger version (16K): [in this window] [in a new window]   FIG. 3.   Measured total power of the EEG signal versus imipenem concentrations in serum (A) and at the effect site (B), for the same rat as in Fig. 1. The solid line represents the best fit of the data according to the spline function model (equation 8).

View larger version (22K): [in this window] [in a new window]   FIG. 4.   Concentrations of imipenem in serum and EEG effect versus time for the same rat as in Fig. 1. The broken line represents the best PK fit to the measured concentrations of imipenem in serum, with the following values for PK parameters: V = 254 ml kg1 and clearance = 14.0 ml min1 kg1. The solid line represents the best fit to the measured total power of the EEG signal effect, according to the effect compartment model, with the following values for PD parameters: P0 = 0.17 mV2, B = 0.0151, n = 8.1, and ke0 = 0.0070 min1.

	DISCUSSION

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Quantitative EEG recording constitutes an interesting experimental approach offering a sensitive, objective, and continuous measure of the neurotoxic effects of imipenem in rats. Furthermore, since variations in the total power of the EEG signal were related to behavioral modifications and occurrence of tremor and partial seizures, changes in EEG can be considered as an appropriate surrogate pharmacodynamic endpoint for the investigation of the epileptogenic activity of imipenem in rats. Compared to EEG recording used in previously published studies (14, 16), the integrated PK-PD modeling approach used here constituted a major improvement. Because imipenem is supposed to interact with GABA_A receptors (8, 16), an indirect-response model with inhibition of the factors controlling drug response (that is, inhibition of GABA_A binding to its receptor sites) was initially selected but was unable to capture the lag time followed by a sudden increase in the EEG effect (Fig. 2).

The ability of the effect compartment model to describe imipenem data suggests that this delay is due to the limited and slow CNS diffusion of imipenem (19, 22, 28), which is also responsible for the important differences observed between the elimination rate constants from the central and effect compartments (Tables 1 and 2). Under similar experimental conditions, no hysteresis was found for midazolam, a drug with extensive and rapid CNS diffusion (26), and only a limited, if any, temporal delay between concentrations and effects with values of k_el and k_e0 close to each other was observed with synthetic opioids (6).

Although the effect compartment provided satisfactory data fitting in one particular situation (80 mg infused over 30 min), it was important to assess its robustness under various experimental conditions. It was initially decided to change the dose as previously done to discriminate between the effect compartment and indirect-effect models (9, 38). However, preliminary experiments showed that no EEG effect was observed when the dose was reduced by 50% and animals died before the end of the experiment when it was increased by 50%. These results are consistent with the sudden and rapid increase of the EEG effect illustrated in Fig. 3A and with the high value of the sigmoidicity factor n in equation 8 (Table 2). However, this precluded dose modification as a way to assess the robustness of the effect compartment model. Keeping the dose constant but changing the duration of infusion by adjusting the infusion rate was therefore considered. Simulations showed that the effect compartment model predicts that the peak of effect should decrease as the duration of infusion increases.

Results obtained following 60- and 90-min infusions, in particular the decrease of P_max as infusion duration increases (Table 3 and Fig. 5A) as well as the lack of statistically significant differences between parameter estimates in the various experimental settings (Table 2), attest to the robustness of the compartment effect model. However, a close look at the data suggests that, although not statistically different, the k_e0 value had a tendency to increase together with the duration of infusion, indicating that the effect compartment model may not capture all of the complexities of the system. Among these, an active metabolite accumulating with time could contribute to the observed EEG effect. Several authors have suggested that the convulsant activity of imipenem was related to the accumulation of an open lactam metabolite (18, 37), but other results suggest that the parent compound itself would be responsible for the neurotoxicity (29, 36). However, this metabolite is not detected in serum and cannot be included in a PK-PD model. Therefore, the effect compartment model may not be perfect, but at least it was satisfactory in predicting the EEG effect of imipenem in a relatively wide range of experimental settings (Table 3). It provides a new and unique way to approach this complex nonlinear concentration-effect relationship. As an example, it was confirmed experimentally (Table 3) that keeping the dose constant but increasing the duration of infusion (and therefore reducing the input rate) allowed a reduction of the epileptogenic effect. As another consequence of this change in the dosing regimen, C_max decreases (Table 1) but the area under the concentration-time curve (AUC) does not, since dose and clearance are kept constant. One could argue that the CNS toxicity of imipenem is essentially related to high concentrations in serum and that apart from the temporal delay, peak concentrations in serum would be predictive of the epileptogenic risk. Simulations conducted with the compartment effect model show that this would not be the case, as infusing imipenem at various combined input rates and durations in order to keep the C_max constant (but not the AUC) would lead to a completely different EEG effect as well. This is illustrated in Fig. 5B, which shows that a slight change in the dosing regimen (for example, infusing imipenem at a rate of 2.50 mg min¹ for 35 min instead of 2.65 mg min¹ for 30 min), which has no effect on C_max, should result in a dramatic increase of the EEG effect. This confirms that the C_max and AUC alone are not good predictors of the epileptogenic risk associated with imipenem. Interestingly, the model also predicts that a reduction in imipenem clearance, as encountered in patients with renal insufficiency, should lead to a much more than proportional increase in the epileptogenic effect. This is consistent with the current knowledge gained from clinical practice, that imipenem CNS toxicity is essentially observed in patients with renal impairment (2) and dosage adjustment based upon renal function may not be adequate to prevent seizures (24).

View larger version (13K): [in this window] [in a new window]   FIG. 5.   Simulated EEG effect for the same rat as in Fig. 1 according to the effect compartment model following imipenem infusions. (A) The same dose (80 mg) administered for various durations, leads to changes in Cmax but not in AUC. Lines correspond to infusions at 0 (bolus), 15, 30, 60, 90, 120, 150, and 180 min; solid lines represent experimental conditions used during this study. (B) Various rates (3.20, 2.85, 2.65, and 2.50 mg min1 for 20, 25, 30, and 35 min, respectively) lead to changes in doses (64, 71, 80, and 88 mg, respectively) and, therefore, AUC, but peak concentrations in serum (Cmax = 437 µg ml1) do not change. The solid line corresponds to an experimental condition used in this study (30-min infusion).

In conclusion, the PK-PD model validated in this study represents a major improvement in the comprehension of the epileptogenic activity of imipenem in rats.