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Semi-mechanistic Modelling of the Analgesic Effect of Gabapentin in the Formalin-Induced Rat Model of Experimental Pain

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Abstract

Purpose

The formalin-induced rat model of nociception involves moderate continuous pain. Formalin-induced pain results in a typical repetitive flinching behaviour, which displays a biphasic pattern characterised by peaks of pain. Here we described the time course of pain response and the analgesic effect of gabapentin using a semi-mechanistic modelling approach.

Methods

Male Sprague-Dawley rats received gabapentin (10–100 mg/kg) or placebo 1 h prior to the formalin injection, as per standard protocol. A reduction in the frequency of the second peak of flinching was used as a behavioural measure of gabapentin-mediated anti-nociception. The flinching response was modelled using a mono-exponential function to characterise the first peak and an indirect response model with a time variant synthesis rate for the second. PKPD modelling was performed using a population approach in NONMEM v.7.1.2.

Results

The time course of the biphasic response was adequately described by the proposed model, which included separate expressions for each phase. Gabapentin was found to reversibly decrease, but not suppress the flinching frequency of the second response peak only. The mean IC50 estimate was 7,510 ng/ml, with relative standard error (RSE%) of 40%.

Conclusions

A compartmental, semi-mechanistic model provides the basis for further understanding of the formalin-induced flinching response and consequently to better characterisation of the properties of gabapentin, such as the potency in individual animals. Moreover, despite high exposure levels, model predictions show that gabapentin does not completely suppress behavioural response in the formalin-induced pain model.

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Abbreviations

CI:

confidence interval

COX-2:

cyclo-oxygenase 2

CV:

coefficient of variation

GABA:

γ-amino butyric acid

IIV:

inter-individual variability

MED:

median effective dose

MOFV:

minimum objective function value

NK1:

neuroenkephalin 1

NMDA:

N-methyl d-aspartate

PKPD:

pharmacokinetics and pharmacodynamics

RSE:

relative standard error

VPC:

visual predictive check

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ACKNOWLEDGMENTS AND DISCLOSURES

The authors acknowledge the contribution of Scott Marshall (Modelling & Simulation, Pfizer, Sandwich, UK), Ian Machin (Pain Research Unit, Sandwich, UK), and Dinesh DeAlwis (Global PK/PD/TS Europe, Eli Lilly, Erl Wood, UK), who have shared their experience with TIPharma and provided valuable insight into the issues faced by R&D during early drug development. Top Institute Pharma, a tripartite consortium involving industry, academia and the Netherlands government, has sponsored the PhD research programme of A. Taneja.

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Authors and Affiliations

  1. Division of Pharmacology, Leiden Academic Centre for Drug Research, POBox 9502, 2300 RA, Leiden, The Netherlands

    A. Taneja, M. Danhof & O. Della Pasqua

  2. Department of Pharmacy and Pharmaceutical Technology Faculty of Pharmacy, University of Navarra, Pamplona, Spain

    I. F. Troconiz

  3. Clinical Pharmacology Modelling & Simulation, GlaxoSmithKline, Uxbridge, Middlesex, UK

    O. Della Pasqua

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  1. A. Taneja
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on behalf of the neuropathic pain project of the PKPD modelling platform

Corresponding author

Correspondence to O. Della Pasqua.

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Taneja, A., Troconiz, I.F., Danhof, M. et al. Semi-mechanistic Modelling of the Analgesic Effect of Gabapentin in the Formalin-Induced Rat Model of Experimental Pain. Pharm Res 31, 593–606 (2014). https://doi.org/10.1007/s11095-013-1183-4

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