The Absorption Profile of Pregabalin in Chronic Pancreatitis

Authors


Author for correspondence: Anne E. Olesen, Mech-Sense, Department of Gastroenterology, Aalborg Hospital, Aarhus University Hospital, Mølleparkvej 4, 9000 Aalborg, Denmark (fax + 45 99326507, e-mail aeo@mech-sense.com).

Abstract

It was recently shown that pregabalin decreased pain associated with chronic pancreatitis. It is well known that pancreatitis patients suffer from fat malabsorption with accompanying diarrhoea because of loss of exocrine pancreatic enzyme production. This may lead to changes in the mucosal surface in the small intestine and possibly affect the absorption of pregabalin. The pharmacokinetics of pregabalin has never been investigated in patients suffering from chronic pancreatitis. The aim of this study was to develop a population pharmacokinetic model of pregabalin administered to patients with chronic pancreatitis. The pregabalin population pharmacokinetic analysis was conducted on data from fifteen patients with chronic pancreatitis. Each patient received 75 mg of pregabalin (oral capsule). Pregabalin concentrations were measured using a validated liquid chromatographic method. Data analysis was performed using non-linear mixed effects modelling methodology as implemented by NONMEM. A one-compartment model with first-order absorption and elimination adequately described pregabalin pharmacokinetics. Time to maximum observed plasma concentration (Tmax) was 1.53 (95% CI 1.09–2.05). The maximum plasma concentration (Cmax) was 1.98 μg/ml (95% CI 1.69–2.34), and area under the plasma concentration–time profile (area under the curve) was 18.2 μg*hr/ml (95% CI 14.7–26.3). Pregabalin is well absorbed in patients with chronic pancreatitis, and the pharmacokinetic profile of pregabalin is not extensively affected by chronic pancreatitis.

Patients diagnosed with chronic pancreatitis often suffer from pain. In parallel, they can have a history of alcoholic abuse making opioids, with their associated abuse potential together with other side effects as, for example, bowel dysfunction, less suitable for these patients [1]. Support for an underlying neuropathic pain component in chronic pancreatitis has been documented in various basic and clinical studies, for review see Drewes et al. [2]. Accordingly, evidence of central reorganization, impaired descending pain modulation and central sensitization was previously documented in studies from our group [3-7]. Treatments with opioids are often insufficient in the treatment of neuropathic pain. Therefore, new treatment approaches are warranted.

Pregabalin exerts a range of effects on pain transmission, and although the precise mechanism of action is not completely understood, it likely involves the binding of the drug to calcium channels in the central nervous system [8]. In animal experiments, it has been shown that pregabalin primarily exerts its effect in the dorsal horn, by reducing the ascending pain signals. Pregabalin is a ligand of the α2δ subunit of the voltage-gated calcium channel, and binding of pregabalin to this site results in reduced calcium influx at the nerve terminals and therefore a reduced release of several excitatory neurotransmitters, including glutamate, substance P (SP), calcitonin-gene-related peptide (CGRP) and noradrenaline [9, 10]. This may be the basis for the analgesic effect. Moreover, studies in human beings have suggested that this drug can inhibit central sensitization [11, 12]. The evidence for the clinical effect of pregabalin in neuropathic pain is substantial and is documented in a number of randomized clinical trials [13-15]. Recently, we documented pregabalin's role in the pain treatment of patients with chronic pancreatitis [16].

Pregabalin is absorbed in the small intestine [17]. The clinical pharmacokinetics of pregabalin has been investigated in healthy volunteers, patients with various degrees of renal function and patients with various chronic pain disorders (diabetic neuropathy, post-herpetic neuralgia, chronic low back pain, osteoarthritis and fibromyalgia) or partial seizures [18-20]. It is well known that pancreatitis patients suffer from malabsorption [21-23]. This could lead to changes in the mucosal surface in the small intestine and possibly change the absorption of pregabalin in these patients. In addition, many patients suffering from chronic pancreatitis are also treated with opioids, which may induce side effects such as opioid-induced bowel dysfunction (OIBD) and hereby possibly affecting drug absorption [24].

Drug absorption has never been investigated in patients suffering from pancreatitis. We suggested that the simple and linear kinetics of pregabalin [25] would make it possible to study how drug absorption may vary in these patients. The aim of this study was to characterize single-dose pharmacokinetics of pregabalin in patients with chronic pancreatitis by a population pharmacokinetic model.

Method

Study design

Patients were recruited for a double-blind, placebo-controlled, parallel group study of pregabalin conducted in the Netherlands and Denmark [16]. The present study presents the pharmacokinetic data obtained in the pregabalin arm at the Danish site only (Department of Gastroenterology, Aalborg Hospital, Denmark) as the site in the Netherlands did not collect blood for pharmacokinetic analysis, as this was not intended in the original study protocol. Patients fasted for at least 4 hr prior to dosing. After dosing, each patient received a standard sandwich and a soft drink. Approvals from the local Ethics Committee (N-20080028MCH) and the Danish Medicines Agency (2612-3758) were obtained prior to study start. All patients were informed of the potential risks of the study, were provided written informed consent before entering the study and were free to withdraw at any time at their own discretion. The study followed the ICH-GCP guidelines and was monitored by the GCP unit, Aarhus University Hospital, Denmark.

Patients

The study included male and female patients between the ages of 18 and 70 years with a diagnosis of chronic pancreatitis based on the Mayo Clinic diagnostic criteria, abdominal pain typical for chronic pancreatitis (i.e. dull epigastric pain, perhaps radiating to the back) and chronic pain (i.e. pain ≥ 3 days/week for at least 3 months). Eligible patients visiting the outpatient hospital clinic in Aalborg (between October 2008 and April 2010) were recruited. Women were required to use a reliable method of contraception unless they were post-menopausal. Patients were excluded if they suffered from other acute or generalized chronic pain syndromes (e.g. irritable bowel syndrome), had a history of major depression, were previously diagnosed with moderate to severe renal impairment (eGFR was estimated by the modification of diet in renal disease (MDRD) study equation using blood test results of serum creatinine [26]), were treated with pregabalin during the previous 4 months, had hypersensitivity or known allergy to pregabalin, had any clinically significant cardiac rhythm abnormality or any evidence of untreated myocardial ischaemia or injury. Patients taking concomitant analgesic medication were included if pain treatment was stable before start of the study. Both patients on stable opioid medication and patients on non-opioid analgesics were included.

Drug administration and blood sampling

Pfizer Clinical Research Operations provided capsules of 75 mg pregabalin. After 4 hr of fasting, each patient received a single 75-mg dose of pregabalin orally (capsule) with 240 ml of water.

Venous blood samples were collected in glass tubes (5 ml) containing heparin. Samples were centrifuged, and the plasma transferred to plastic tubes and stored frozen at −80°C until pregabalin concentration analyses. Blood samples were collected before dosing and 0, 15, 30 min., 1, 1.5, 2, 3, 4 and 6 hr after pregabalin administration.

Pregabalin assay

Plasma samples were assayed for pregabalin concentration using a validated modification of the high-performance liquid chromatographic method with UV absorbance detection [27]. The lower limit of quantitation was 2 μM. The analyses were performed at the Epilepsy Hospital Filadelfia, Dianalund, Denmark.

Pharmacokinetic modelling

Data analysis was performed by modelling plasma concentrations versus time using non-linear mixed effects modelling methodology as implemented by the software programme NONMEM 7.2 (ICON Development Solutions, Hanover, MD, USA). Pregabalin population pharmacokinetic parameters (mean and interpatient variability) as well as relationships between the mean and various covariates were estimated. Maximum plasma concentration (Cmax), the time it occurred (Tmax), half-life (t½) and area under the plasma concentration–time curve (AUC) values were estimated.

Model building and validation

A one-compartment model with first-order absorption and elimination was used to characterize the observed plasma concentrations of pregabalin. Shoji et al. [28] found this model to be adequate. The model was parameterized using absorption half-life math formula elimination half-life math formula apparent volume of distribution V/F, lag time tlag and additive residual error with standard deviation σ. An additive residual error model was used considering the range of measurements. These parameters were assumed to be log-normally distributed across the population with variance–covariance matrix Ω of the random effects η. Excluding the time lag increases the objective function by about 130 points.

The model building process was performed iteratively. The Bateman function (which is the analytical solution for the pharmacokinetic model) was programmed in NONMEM's $PRED block.

Bateman function:

display math

Area under the curve was estimated using the integral of the concentration–time relationship:

display math

where math formulaand math formula.

Maximum plasma concentration was calculated as Tmax =log(kabs/kel)/(kabs − kel) + tlag, and the time it occurred Cmax is the Bateman function with Tmax substituted for time. Thus, Cmax = C (t = Tmax).

Internal validation was performed in two ways. Firstly, using the non-parametric bootstrap, the distributions of the model parameters were obtained and compared with those of the final model. The bootstrap also provided distributions of derived parameters, such as AUC and V/F. Secondly, a visual predictive check was performed by calculating median and 95% concentration intervals from 9999 simulated data sets from the final model. The bootstrap and visual predictive checks (VPC) were performed using R (R Foundation for Statistical Computing, Vienna, Austria) and software designed by one of the authors (E.O.).

Statistics

Model parameters, estimated by NONMEM's first-order conditional estimation method, are presented as mean ± standard error. Derived parameters such as Tmax, Cmax and AUC, estimated by the bootstrap, are given as median and 95% confidence interval for the population.

Results

Fifteen patients [8 women and 7 men aged 25–73 years (mean 54 ± 11.08)] participated in the study. Height was 1.74 ± 0.12 m and weight 68.02 ± 19.13 kg. No side effects appeared immediately after a single dose of 75 mg pregabalin. eGFR was 117.75 ± 29.40 ml/min./1.73 m2, and all patients had a GFR > 67 ml/min./1.73 m2. Demographic data are given in table 1.

Table 1. Patient demographics
Patient nr.Age (years)GenderHeight (m)Weight (kg)eGFR (ml/min./1.73 m2)
143Female1.635095.08
255Male1.85105111.61
353Female1.6762108.87
457Female1.6852112.05
550Male1.789797.13
658Male1.9780106.78
758Male1.8069.2118.42
873Female1.675899.88
964Female1.5746.8167.30
1057Female1.6288.596.85
1157Male1.8360165.62
1225Female1.6354129.58
1348Male1.7973118.76
1463Male1.9282.868.00
1543Female1.6342170.39

Pharmacokinetics

Pregabalin was rapidly absorbed after oral administration of a single 75-mg dose in all volunteers. Tmax, Cmax and AUC were computed from 1000 bootstrap data fits. Time to maximum observed plasma concentration (Tmax) was 1.53 hr (95% CI 1.09–2.05). The maximum plasma concentration (Cmax) was 1.98 μg/ml (95% CI 1.69–2.34), and area under the plasma concentration–time profile (AUC) was 18.2 μg*hr/ml (95% CI 14.7–26.3).

Figure 1 shows the individual plasma pregabalin concentration–time profiles, and fig. 2 shows three examples of data fits.

Figure 1.

Individual plasma pregabalin concentration–time profiles after single oral administration of 75 mg pregabalin. Solid lines: Visual predictive checks as model fit and 95% prediction intervals. Patients with ID 2, ID 4, ID 9 and ID 12 had small and large math formula(absorption half-life) and small V/F (apparent volume of distribution) and large tlag(lag time), respectively. Cpregabalin = pregabalin plasma concentration; hr = hours.

Figure 2.

Three examples of data fits. Data fits are based on their coefficient of determination (R2) (left panel: worst; middle panel: median; right panel: best). Cpregabalin = pregabalin plasma concentration; hr = hours.

The patient with ID2 was an outlier regarding absorption. For this volunteer, absorption half-life was nearly zero, and residuals had larger standard deviation and were correlated (visual inspection). However, the remaining parameters were within their distributions, and therefore, absorption compartment for the volunteer with ID2 was eliminated and given its own sigma (0.330 ± 0.00588). This caused the variability in math formulaand σ to disappear. Patients with ID 4 and ID 12 had larger math formula and tlag, respectively, and patient with ID 9 (height: 1.57 m and weight: 46.8 kg) had low V/F. From the plots of their corresponding (normally distributed) ηs versus ID, they were not judged as outliers.

Pregabalin pharmacokinetic parameters are summarized in table 2. ETA shrinkages were 7.7%, −1.6% and 6.8% for math formula, V/F and tlag, respectively.

Table 2. Estimates of pharmacokinetic parameters for pregabalin
 EstimateS.E.ω2S.E. (ω2)
  1. Pharmacokinetic parameter estimates with their standard errors (S.E.) for pregabalin after a single oral administration of 75 mg pregabalin with significant interpatient variances.

  2. ω2 = interpatient variances; S.E. = standard errors; math formula = absorption half-life; math formula = elimination half-life; V/F = apparent volume of distribution; tlag = lag time; αMF = the gender effect on V/F; σ = standard deviation.

math formula (hr)0.2820.05740.5870.254
math formula (hr)4.570.208  
V/F (L)30.62.350.08040.0348
tlag (hr)0.3770.06370.3310.161
σ (μg/ml)0.1250.0153  

Goodness-of-fit plots are presented in figs 3 and 4. These indicate that a one-compartment model with first-order absorption and elimination described the data. Finally, the bootstrap analysis did not show any discrepancies between final model parameter estimates and bootstrap parameter distributions.

Figure 3.

Goodness-of-fit plots. Goodness-of-fit plots with measured plasma concentrations (Cp, measured) versus population predicted (Cp, pop) (panel A) and versus individual predicted (Cp, ind) (panel B).

Figure 4.

Goodness-of-fit plots. Panel (A, population) conditional weighted residuals versus time; Panel (B) individual weighted residuals versus time (hr = hours).

Discussion

A one-compartment model with first-order absorption and elimination adequately described pregabalin pharmacokinetics in patients with chronic pancreatitis. Pregabalin was well absorbed in this patient group. We refrained from exploring more complex pharmacokinetic models, because (1) Shoji et al. [28] found that a one-compartment model with first-order absorption and elimination adequately described their data (with comparable sampling), (2) our results and theirs are more easily compared if the pharmacokinetic models are the same, (3) the data would support a more refined model of absorption kinetics only if a more refined model of disposition kinetics were available and (4) the goodness-of-fit plots did not indicate model misspecification.

For practical reasons, it was impossible to collect more blood samples in a larger sample size or over a longer period. However, pharmacokinetic parameters were found using non-linear mixed effects modelling methodology as implemented by NONMEM, where the precision of the parameters showed that sampling was adequate.

For patients with chronic pancreatitis, steatorrhoea and concomitant use of drugs such as opioids can change motility and secretion and lead to malabsorption [29]. This can be related to low secretion of the enzymes responsible for digestion as well as concomitant bacterial overgrowth found in up to 40% of patients [30]. The overgrowth is probably due to a defect in the interdigestive ‘house keeper’ function of gastrointestinal motility and biliopancreatic secretion. The low pancreatic secretion of enzymes may also favour the development of bacterial colonies. Bacterial overgrowth may interfere with the normal intestinal milieu and lead to atrophic mucosa with structural abnormalities that can decrease drug absorption [31]. It has previously been demonstrated that administration of pregabalin capsules with food reduces the rate, but not the extent, of systemic pregabalin availability [18]. Furthermore, it was suggested that AUC and not Cmax is a better predictor of pregabalin efficacy because of a slight delay between onset of efficacy and significant plasma concentrations. Additionally, reductions in rate, accompanied by a similar extent of drug absorption, are expected to have a minimal impact on clinical effects. Hence, pregabalin capsules can be administered without regard to meals [18]. Supported by the fact that AUC was comparable (18.2 μg*hr/ml in patients compared with 15.6 μg*hr/ml in healthy volunteers), it is not assumed that the present results were affected by consumption of a standard sandwich and a soft drink half an hour after dosing.

Shoji et al. [28] investigated the population pharmacokinetics of pregabalin in healthy volunteers and found the following estimates where the effect of food intake on math formulaand tlagwas taken into account: math formula = log(2)/(3.96/38) = 6.65 hr; math formula = log(2)/(7.99/(1 − 0.927)) = 1.19 hr; V/F = 35.6 l; tlag = 0.243*(1 + 0.813) = 0.441 hr.

These values correspond with our findings in patients (table 2). However, no specific comparative study was performed to investigate differences between healthy volunteers and patients, and therefore, more specific comparisons were impossible.

The GFR is widely accepted as the best overall index of kidney function. Chronic kidney disease can be defined as a GFR <60 ml/min./1.73 m2 [32]. It has been demonstrated that renal function affects the pharmacokinetics of pregabalin [19]. In patients with chronic pancreatitis, a normal eGFR was verified (mean 117.75 ± 29.40 ml/min./1.73 m2), and therefore, low eGFR could not affect the absorption profile of pregabalin in the present study. However, in the treatment for pain in patients with chronic pancreatitis, kidney function should be taken into consideration before initiation of pregabalin treatment.

It has been demonstrated in healthy volunteers that pregabalin is rapidly absorbed after oral administration, with peak plasma concentrations occurring between 0.7 and 1.3 hr for 75 mg oral administration (capsule). Bockbrader and coworkers concluded that, in healthy volunteers and patients with partial seizures or chronic pain, the only factor having a clinically significant influence on steady-state plasma pregabalin concentration is renal function [20]. This was supported by Shoji et al., [28] who demonstrated that renal function (measured as creatinine clearance) was a clinically influential covariate on CL/F in healthy individuals, patients with impaired renal function, patients with post-herpetic neuralgia or diabetic neuropathy. Recently, a case report was published on pregabalin assay in a patient with widespread neuropathic pain and late-onset gluten intolerance [33]. In coeliac disease, there are a number of changes in the gut that could affect drug exposure, for example, rate of gastric emptying, intraluminal pH changes and stunted small intestinal villi. However, it was demonstrated that the blood levels measured in this patient did not differ from healthy male volunteers enrolled in previous studies [33]. The present study is the first study performed in patients with chronic pancreatitis to investigate whether chronic pancreatitis could lead to a different absorption of pregabalin.

Conclusion

Pregabalin is well absorbed in patients with chronic pancreatitis. The disease does not affect the pharmacokinetic profile of pregabalin extensively, and dosage reduction should not be necessary in these patients, if renal function is normal.

Acknowledgement

The study was supported by a free grant from Pfizer Research and Development, and Pfizer Clinical Research Operations provided capsules of 75 mg pregabalin.

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