Pharmacokinetics of centhaquin citrate in a dog model

Abstract

Objectives

Centhaquin citrate is a novel agent that is being developed for use in the resuscitation of patients with haemorrhagic shock. While pharmacokinetics have been described in small animal models, the pharmacokinetic parameters of centhaquin citrate in large mammals have yet to be described.

Methods

Four healthy Beagle dogs (two males and two females) were given an intravenous bolus of 1.0 mg/kg centhaquin citrate. Plasma concentrations were measured at baseline and at ten time points within 24 h after administration. Multiple compartmental models were built and compared. The nonparametric adaptive grid function within the Pmetrics package for R was used for parameter estimation. Predicted concentrations were calculated using population mean and individual Bayesian posterior parameters.

Key Findings

Centhaquin citrate pharmacokinetic parameters were best described using a two-compartment model. Median (IQR) values for K_e, V_c, V_p, K_cp and K_pc were 4.9 (4.4–5.2) h⁻¹, 328.4 (304.0–331.9) l, 1000.6 (912.3–1042.4) l, 10.6 (10.3–11.1) h⁻¹ and 3.2 (2.9–3.7) h⁻¹, respectively.

Conclusions

Pharmacokinetic parameters of centhaquin citrate in a large mammal have been described. A large volume of distribution and rapid elimination were observed, consistent with previous work in rats.

centhaquin citrate, dog, pharmacokinetics

Introduction

Post-traumatic haemorrhagic shock is associated with significant morbidity and mortality; most deaths occur within the first six hours.^[1] Early, judicious resuscitation with crystalloids, colloids or blood products is frequently employed but can be associated with deleterious effects such as dilution of plasma coagulation factors, hypothermia, acidosis and worsening of shock.^[2–12] There is no single optimal method of resuscitation,^[13] and hence, novel resuscitative agents are needed.

Centhaquin (2-[2-(4-(3-methyphenyl)-1-piperazinyl)]ethyl-quinoline) is a centrally acting cardiovascular active agent with positive inotropic effects. Previously, centhaquin has been shown to significantly improve survival in several animal models of hypovolemic shock.^[14–16] Low doses of centhaquin can significantly decrease blood lactate, increase mean arterial pressure (MAP) and improve cardiac output (CO) parameters that are central to the management of patients with haemorrhagic shock.^[14–17] Centhaquin is thought to act at the α_2B-adrenergic receptors to produce venous constriction with a subsequent increase in venous return to the heart.^[18] Resuscitative effect of centhaquin was attenuated by selective α₂-adrenergic receptor antagonists, yohimbine or atipamezole.^[14] We propose that centhaquin in low doses acts on α_2B-adrenergic receptors to produce venous constriction and a consequent increase in venous return to the heart, and stimulation of sodium sense through brain α_2B-adrenergic receptors to increase the intravascular blood volume. These effects lead to an increase in CO and tissue blood perfusion which appears to be responsible for its resuscitative action. Additionally, centhaquin centrally stimulates renal sodium reabsorption to increase intravascular blood volume.^[18] These actions are believed to be responsible for centhaquin's observed resuscitative action through increases in CO and tissue perfusion.

Centhaquin is prepared as the citrate salt to improve water solubility for intravenous administration.^[19] The cardiovascular activity of centhaquin citrate is greater than centhaquin administered in a nonsalt form. Centhaquin citrate is a promising novel agent for resuscitation in haemorrhagic shock.

The purpose of this study was to characterize the pharmacokinetics of centhaquin citrate in dogs, with the ultimate goal of developing this medication for the treatment of patients with haemorrhagic shock. This is the first pharmacokinetic study of centhaquin in large mammals and will help to clarify its pharmacokinetic properties.

Methods

Animals

Four healthy Beagle dogs (two males and two females; Isoquimen India Pvt. Ltd., Hyderabad, India) weighing 11.5–16.5 kg were housed individually in adjacent kennels. Animal rooms were environmentally controlled at a temperature of 23 ± 1 °C and a relative humidity of 50 ± 10%. Food and water were made available continuously. The illumination was controlled to give approximately a sequence of 12-h light and dark cycles. All procedures and animal care protocols were approved by the Institutional Animal Ethics Committee (IAEC), Sipra Lab, Hyderabad, India.

Drugs and chemicals

Centhaquin citrate was synthesized by Pharmazz India Private Limited as previously described.^[19,20] HPLC-grade acetonitrile, methanol, chloroform, trifluoroacetic acid and water were obtained from Merck (Merck Specialties Pvt. Ltd., Mumbai, India). All the other reagents and materials used were of analytical grade.

Sampling and quantification

Centhaquin citrate was administered to Beagle dogs through the cephalic vein at a dose of 1.0 mg/kg with a diluent volume of 1.5 ml/kg. Blood samples (1.0 ml) were withdrawn with a hypodermic syringe from contralateral cephalic vein before dosing and postdose at 5, 10, 15 and 30 min, 1, 2, 4, 8, 12 and 24 h. Samples were immediately transferred into chilled K3 EDTA vacutainers. The samples were centrifuged at 1600g for 15 min at 0 °C to separate plasma. Plasma was frozen at −70 °C for batch assay.

A reverse phase HPLC method was used for quantitative analysis of centhaquin citrate in dog plasma. Before analysis, plasma proteins were separated by methanol precipitation, and centhaquin citrate was extracted using chloroform. Assays were performed using the prominence ultrafast liquid chromatography system (Shimadzu Corporation, Kyoto, Japan) with solvent delivery units (LC-20AD; Shimadzu) and variable wavelength photodiode array detector (SPD-M20A; Shimadzu). Before analysis, the mobile phase was filtered through 0.2 μm filter and degassed by sonication. Ciprofloxacin 12.5 μg/ml was utilized as an internal standard to verify consistent extraction. Chromatographic separation was achieved using C₁₈ column (250 mm × 4.6 mm, 5 μm, 120 Å pore diameter, Enable C₁₈ G, Spinco Biotech, Hyderabad, India). The mobile phase consisted of 0.1% trifluoroacetic acid in water (A) and acetonitrile: methanol [50 : 50 v/v] (B) in ratio of 42 : 58 (A : B). Elution was isocratic at a flow rate of 0.6 ml/min. The injection volume was 20 μl, and the analysis was performed at 22 °C. Detection of centhaquin citrate was performed at 239 nm. Assessment of peaks was performed using LC solutions software (Shimadzu Corporation). The method was validated using three different concentration levels of centhaquin citrate (low, medium and high) as quality controls (QCs; n = 6/concentration) and the LLOQ (n = 6) prepared in dog plasma. Precision was calculated as relative standard deviation (RSD) where the standard deviation was divided by the mean. Accuracy was quantified as the mean calculated concentration divided by the nominal concentration. Precision and accuracy were calculated both inter and intraday. Accuracy and precision were required to be ±15%, except at the LLOQ where 20% was considered acceptable.^[21] The mean extraction recovery was calculated by comparing the mean peak areas of centhaquin citrate QCs in plasma and diluent. The matrix effect was calculated by comparison with centhaquin citrate peak areas from plasma samples with the peak areas of corresponding working standard prepared in diluent.

Compartmental model building

One- and two-compartment models were fit using the nonparametric adaptive grid (NPAG) algorithm within the Pmetrics package (Los Angeles, CA) for R.^[22,23] Nonparametric mixed-effects models were created using NPAG, with each model parameter being described as a set of discrete support points and the associated probability of each value.^[22] Individual animal weight was considered as a covariate to model parameters. Individual linear regressions and R² values were utilized to identify potential relationships. Input (IV bolus) and output components were modelled as mass transit, and compartmental transfer was estimated using differential equations. The inverse of the estimated assay variance was used as the first estimate for weighting in the PK modelling. Final weighting was accomplished by making the assumption that total observation variance was proportional, with a scalar (gamma) to assay variance (error = SD × gamma where SD = C₀ + C₁Y with inputs of C₀ = 0.6 and C₁ = 0.15 ng/ml).^[24] Two-compartment model parameters included elimination coefficient (K_e), volume of central compartment (V_c) and intercompartmental transfer rates (i.e. K_cp, K_pc). The volume of the peripheral compartment (V_p) was calculated for each of the support points from the following equations, where combined intercompartmental transfer (i.e. Q) is mathematically described as

$$Q=K_{cp}\ast V_c$$

1

and

$$V_p=Q/K_{pc}$$

2

Therefore, substitution for Q resulted in

$$V_p=\left(K_{cp}\ast V_c\right)/K_{pc}$$

3

Goodness-of-model fit was assessed by regression of the observed–predicted plots, coefficients of determination and log-likelihood values, as previously described.^[25,26] Predictive performance was evaluated using mean prediction error (bias) and the mean bias-adjusted squared prediction error (imprecision) of the population and individual (median) prediction models. The best-fit model was determined by the rule of parsimony and use of the Akaike's information criteria (AIC) as calculated in Pmetrics.^[22,27]

Predicted centhaquin citrate concentrations were calculated at one-minute intervals based on median population parameters as well as individual median Bayesian posterior parameter estimates for each subject.

To estimate pharmacokinetic parameters, a noncompartmental analysis was completed. Median individual Bayesian posterior predicted time–observation profiles were used for calculations. Pharmacokinetic values were estimated using the ‘makeNCA’ command within the Pmetrics package for R (Los Angeles, CA, USA).^[22]

Results

Assay

Chromatographic separation was achieved within a run-time of 21.0 ± 1.0 min. A representative chromatogram can be found in Figure 1. The method exceeded standards for accuracy and precision, with linearity from 8.16 to 81.6 ng/ml (R² = 0.997, Figure 2).^[21] The intra- and interday precision (RSD) ranged from 2.32% to 3.51% at LLOQ concentration and 0.94% to 2.09% at other QC levels. The intra- and interday assay accuracy ranged from 85.66% to 91.83% for LLOQ and 88.70% to 99.27% for other QCs. The mean extraction recovery of centhaquin citrate from plasma was 98.26% at LLOQ and ranged from 95.27% to 99.32% at other QCs. The matrix effect for plasma centhaquin citrate was −1.74% at LLOQ concentration and ranged from −0.67% to −4.64% for other QCs. The matrix effect on centhaquin citrate assay in dog plasma was negligible, and the matrix did not influence the extent of ionization. The method was simple, sensitive, accurate and reproducible and has been successfully applied in this study.

Figure 1

Chromatogram of blank plasma spiked with centhaquin citrate acquired using Prominence ultrafast liquid chromatography system.

Figure 2

Standard curve of centhaquin citrate in plasma (Concentrations range used: 8.16–81.6 ng/ml).

Actual concentrations and model fits

Measured concentrations for each dog (n = 4) are shown in Figure 3a. Model convergence was attained with one- and two-compartment models, and a two-compartment model was found to be the most explanatory and parsimonious model [AIC −542.8 vs −438.2, P = 0.004; observed vs predicted plot of the population (R² = 0.981 vs 0.886); Bayesian individual predictions (R² = 0.997 vs 0.886) for two- vs one-compartment models]. Weight of the dogs was not found to significantly modify volume (R² = 0.16, P > 0.99) or any other model parameter (P > 0.05 for all) and therefore was not utilized as a covariate. The final scalar for observation variance weighting (gamma) was found to be 0.213 for the two-compartment model.

Figure 3

(a) Actual concentrations over the first 4 h. (b) Bayesian predicted concentrations over the first hour.

In the two-compartment model, four discrete support points were identified. Parameter estimates and measures of central tendency are shown in Table 1. Reasonable %CVs (<20%) for physiologic parameters (i.e. K_e, V_p, and V_c) were shown, and therefore, these parameters were considered acceptable as population estimates.

Table 1

Measures of central tendency and precision for parameter estimates

	Mean	Median	Standard deviation	Coefficient of variation
Ke (h−1)	4.80	4.88	0.78	16.19
Vc (l)	307.38	328.41	41.28	13.43
Vp (l)	977.33	1000.61	85.44	8.74
Kcp (h−1)	10.79	10.64	0.90	8.34
Kpc (h−1)	3.45	3.21	0.83	23.91

V_c, volume of central compartment; V_p, volume of peripheral compartment; K_e, elimination constant; K_cp, transfer constant from central to peripheral compartment; K_pc, transfer constant from peripheral to central compartment.

Observed vs predicted plots for the population are shown in Figure 4 for the 2-compartment model. Individual Bayesian predictions (data not shown) were slightly better as described below. Bias and imprecision for the population two-compartment model were −1.01 ng/ml and 3.79 ng²/ml², respectively. The Bayesian posterior predicted two-compartment model had bias and imprecision values of −0.02 ng/ml and 1.0 ng²/ml², respectively. Fitted Bayesian predicted concentrations are shown in Figure 3b.

Figure 4

Observed vs Predicted Plots for the population.

As described in Methods, median Bayesian posteriors were used to conduct a noncompartmental analysis (Table 2). The volume of distribution (V_dss) was estimated to be relatively large [median (IQR): 1414 (1331–1484 l)], and a rapid half-life were observed [median (IQR): 0.81 (0.79–0.82) h⁻¹].

Table 2

Noncompartmental analysis derived pharmacokinetic properties

	Median (IQR)
AUC (ng/ml × h)	8.7 (8.6–9.1)
AUC (0-inf) (ng/ml × h)	8.7 (8.6–9.1)
Cmax (ng/ml)	34.3 (31.6–38.0)
Tmax (h)	0.017 (0.017–0.017)
Cl (l/h)	1542 (1392–1662)
Vdss (l)	1414 (1331–1484)
Thalf (h)	0.81 (0.79–0.82)

AUC, area under the concentration time curve; AUC (0-inf), area under the concentration time curve from time 0 to infinity; C_max, maximum plasma concentration; T_max, time to C_max; Cl, clearance, calculated as dose/AUC(0-inf); Vd_ss, volume of distribution at steady state; Thalf, half-life; IQR, interquartile range.

Discussion

Centhaquin citrate is a novel agent being developed for the treatment of haemorrhagic shock. Previously, we have shown significantly improved survival in haemorrhaged rats treated with centhaquin plus resuscitation with hypertonic saline or lactated ringers compared to either agent alone.^[15,16,28] To our knowledge, this study is the first to describe the pharmacokinetics of centhaquin citrate in a large mammal (i.e. a dog). The pharmacokinetics of centhaquin in a healthy rat model have been reported previously.^[29] In this model, centhaquin also exhibited a rapid half-life and large volume of distribution.

We utilized nonparametric, compartmental, pharmacokinetic-modelling and were able to estimate population parameters for both the population mean and individual Bayesian parameters. Estimated parameters included intercompartmental transfer rates (K_cp and K_pc) which describe the transfer of drug from the central compartment (i.e. compartment c) to and from the periphery (i.e. compartment p). These parameters are estimated and do not have physiologic value. Additionally, we estimated the apparent volume of distribution in the central and peripheral compartments (V_c and V_p, respectively). These parameters are theoretical volumes that would be necessary to contain the mass of the drug at the concentration found in that compartment. Finally, the model estimated the elimination rate constant (K_e), which describes the rate at which drug is removed from the central compartment. The K_e suggests a rapid elimination. Our model shows an excellent fit (R² = 0.981) in the population model, representing a well-controlled laboratory experiment. These fits were improved when utilizing the Bayesian model (R² = 0.997).

Noncompartmental analyses for centhaquin showed a relatively short half-life (48 min) and a very large volume of distribution (1414 l; IQR 1331–1484 l). This suggests wide distribution of centhaquin into the tissues from the central compartment as well as rapid clearance of the drug. It is important to note that 48 min represents a terminal half-life, not the half-life at steady state. Changes in drug concentration for centhaquin in healthy rats were also well explained from a two-compartment model.^[29] In both studies, the first phase of drug concentration decline was prompt and was explained by our model as K_e + K_cp. At steady state, the decline of drug concentration is explained by the sum of the elimination and distributive properties (i.e. transfer from plasma to and from tissue). That is, drug concentration change is the sum of the elimination constant (K_e) plus the peripheral distribution constant (K_cp) minus the distribution to central compartment constant (K_pc). When calculated in this manner, the mean steady-state half-life of centhaquin in dogs is rapid (i.e. 3.43 min). The discordance between the apparent steady-state half-life calculated from compartmental analyses and the half-life calculated from a noncompartmental analyses suggests a prolonged tissue release phase. These results may warrant continuous infusion strategies for centhaquin for treatment of shock if pharmacodynamic activity is directly related to drug concentrations from the central compartment.

This study is limited by the use of a single species of dogs. Pharmacokinetic studies in rats have been published previously, and pharmacokinetic studies in humans are underway.^[29] Pharmacodynamic studies to determine optimal dosing are ongoing. While only four dogs were studied, extensive pharmacokinetic sampling was performed. This design was utilized to minimize repeated studies in animals.^[30] The coefficients of variation demonstrated that parameter estimates were reasonably precise (i.e. %CV <25% for all parameters). However, the target population for centhaquin (i.e. trauma patients with substantial blood loss) will likely be more heterogeneous given their clinical status. Further work is needed to clarify dosing schemes necessary to achieve maintenance of MAP and CO goals in haemorrhagic shock. Individual patient titration may be necessary to achieve optimal outcomes

Conclusions

In summary, the pharmacokinetic parameters of centhaquin citrate in dogs have been described with a two-compartment model. The results of our compartmental analysis are consistent with the results from a previous pharmacokinetic study in healthy rats.^[29] Further studies to characterize the pharmacokinetics of centhaquin citrate in humans and to determine optimal dosing schemes are ongoing.

Declarations

Conflict of interest

Anil Gulati has issued and pending patents, and Manish Lavhale and E. Jeevan Kumar are employed by Pharmazz, Inc. having rights to those patents. Drs. J. N. O'Donnell, P. O'Donnell and Scheetz have no conflict of interests to report.

Funding

Anil Gulati has issued and pending patents, and Manish Lavhale and E. Jeevan Kumar are employed by Pharmazz, Inc. having rights to those patents. Drs. J. N. O'Donnell, E. P. O'Donnell and Scheetz have no relevant funding related to this work.