Application of a Combined “Effect Compartment/Indirect Response Model” to the Central Nervous System Effects of Tiagabine in the Rat

  • Adriaan Cleton
  • Henrik J. M. M. de Greef
  • Peter M. Edelbroek
  • Robert A. Voskuyl
  • Meindert DanhofEmail author


Pharmacological inhibition of GABA uptake transporters provides a mechanism for increasing GABAergic transmission, which may be useful in the treatment of various neurological disorders. The purpose of our investigations was to develop an integrated pharmacokinetic–pharmacodynamic (PK/PD) model for the characterization of the pharmacological effect of tiagabine, R-N-(4,4-di-(3-methylthien-2-yl)but-3-enyl)nipecotic acid, in individual rats in vivo. The tiagabine-induced increase in the amplitude of the EEG 11.5–30 Hz frequency band (β), was used as pharmacodynamic endpoint. Chronically instrumented male Wistar rats were randomly allocated to four groups which received an infusion of 3, 10, or 30 mg kg−1\((\bar x \pm SE,{\text{ }}n = 23)\)\(96 \pm 9\)ml min-1 kg−1, 1.5ŷ0.1 L kg−1and 20ŷ0.2 min.A time delay was observed between the occurrence of maximum plasma drug concentrations and maximal response. A physiological PK/PD model has been used to account for this time delay, in which a biophase was postulated to account for tiagabine available to the GABA uptake carriers in the synaptic cleft and the increase in EEG effect was considered an indirect response due to inhibition of GABA uptake carriers. The population values for the pharmacodynamic parameters characterizing the delay in pharmacological response relative to plasma concentrations were keo=0.030 min−1and kout=81 min−1, respectively. Because of the large difference in these values the PK/PD model was simplified to the effect compartment model. Population estimates\((\bar x \pm SE)\)were E0=155 ŷ 6 μV, Emax=100 ŷ 5 μV, EC50=287 ŷ 7 ng ml−1, Hill factor=1.8 ŷ 0.2 and keo=0.030 ŷ 0.002 min−1. The results of this analysis show that for tiagabine the combined “effect compartment-indirect response” model can be simplified to the classical “effect compartment” model.

pharmacokinetics pharmacodynamics effect compartment model indirect response sigmoid Emax tiagabine GABA uptake inhibitor 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    P. Krogsgaard-Larsen. Inhibitors of the GABA uptake systems. Mol. Cel. Biochem. 31:105-121(1980).CrossRefGoogle Scholar
  2. 2.
    P. Krogsgaard-Larsen, O. M. Larsson, and A. Schousboe. GABA uptake inhibitors: relevance to antiepileptic drug research. Epileps. Res. 1:77-93 (1987).CrossRefGoogle Scholar
  3. 3.
    F. E. Ali, W. E. Bondinell, P. A. Dandridge, J. S. Frazee, E. Garvey, G. R. Girard, C. Kaiser, T. W. Ku, J. J. Lafferty, G. I. Moonsammy, H.-J. Oh, J. A. Rush, P. E. Setler, O. D. Stringer, J. W. Venslavsky, B. W. Volpe, L. M. Younger, and C. L. Zirke. Orally active and potent inhibitors of gamma-aminobutyric acid uptake. J. Med. Chem. 28:653-660 (1985).PubMedCrossRefGoogle Scholar
  4. 4.
    C. Braestrup, E. B. Nielsen, U. Sonnewald, L. J. S. Knutsen, K. E. Andersen, J. A. Jansen, K. Frederiksen, P. H. Andersen, A. Mortensen, and P. Suzdak, (R)-N-[4,4-Bis(3-Methyl-2-thienyl)but-3-en-1-yl]Nipecotic acid binds with high affinity to the brain γ-aminobutyric acid uptake carrier. J. Neurochem. 54:639-647 (1990).PubMedCrossRefGoogle Scholar
  5. 5.
    P. Suzdak and J. A. Jansen. A review of the preclinical pharmacology of tiagabine: a potent and selective anticonvulsant GABA uptake inhibitor. Epilepsia 36:612-626 (1995).PubMedCrossRefGoogle Scholar
  6. 6.
    W. J. Jusko and H. C. Ko. Physiologic indirect response models characterize diverse types of pharmacodynamic effects. Clin. Pharmacol. Ther. 56:406-419 (1994).PubMedCrossRefGoogle Scholar
  7. 7.
    N. L. Dayneka, V. Garg, and W. J. Jusko. Comparison of four basic models of indirect pharmacodynamic responses. J. Pharmacokin. Biopharm. 21:457-478 (1993).CrossRefGoogle Scholar
  8. 8.
    L. B. Sheiner, D. R. Stanski, S. Vozeh, R. D. Miller, and J. Ham. Simultaneous modelling of pharmacokinetics and pharmacodynamics: Application to d-tubocurarine. Clin. Pharmacol. Ther. 25:358-371 (1979).PubMedGoogle Scholar
  9. 9.
    R. Nagashima, R. A. O'Reilly, and G. Levy. Kinetics of pharmacologic effects in man: the anticoagulant action of warfarin. Clin. Pharmacol. Ther. 10:22-35 (1969).PubMedGoogle Scholar
  10. 10.
    Z.-X. Xu, Y.-N. Sun, D. C. DuBois R. R. Almon, and W. J. Jusko. Third-generation model for corticosteroid pharmacodynamics: roles of glucocorticoid receptor mRNA and tyrosine aminotransferase mRNA in rat liver. J. Pharmacokin. Biopharm. 23: 163-181 (1995).CrossRefGoogle Scholar
  11. 11.
    G. L. Levy. Mechanism-based pharmacodynamic modelling. Clin. Pharmacol. Ther. 56:356-357 (1994).PubMedCrossRefGoogle Scholar
  12. 12.
    D. Verotta and L. B. Sheiner. A general conceptual model for non-steady state pharmacokinetic/pharmacodynamic data. J. Pharmacokin. Biopharm. 23:1-4 (1995).CrossRefGoogle Scholar
  13. 13.
    W. J. Jusko, H. C. Ko, and W. F. Ebling. Convergence of direct and indirect pharmacodynamic response models. J. Pharmacokin. Biopharm. 23:5-8 (1995).CrossRefGoogle Scholar
  14. 14.
    D. Verotta and L. B. Sheiner. Rejoinder. J. Pharmacokin. Biopharm. 23:9-10 (1995).CrossRefGoogle Scholar
  15. 15.
    J. W. Mandema and M. Danhof. Pharmacokinetic-pharmacodynamic modelling of the central nervous system effects of heptabarbital using aperiodic EEG analysis. J. Pharmacokin. Biopharm. 18:459-481 (1990).CrossRefGoogle Scholar
  16. 16.
    L. E. Gustavson and S.-Y. Chu. High performance liquid chromatographic procedure for the determination of tiagabine concentrations in human plasma using electrochemical detection. J. Chrom. 574: 313-318 (1992).CrossRefGoogle Scholar
  17. 17.
    R. C. Schoemaker and A. F. Cohen. Estimating impossible curves using NONMEM. Br. J. Clin. Pharmacol. 42:283-290 (1996).PubMedCentralPubMedCrossRefGoogle Scholar
  18. 18.
    S. L. Beal and L. B. Sheiner (eds.). NONMEM users guide, NONMEM project group, University of California, San Francisco, CA (1992).Google Scholar
  19. 19.
    H. Akaike. A new look at the statistical model identification. IEEE Transactions on Automat. Control 19:716-723 (1974).CrossRefGoogle Scholar
  20. 20.
    M. Gibaldi and D. Perrier. Non-compartmental analysis based on statistical moment theory. In Pharmacokinetics (2nd ed.), Marcel Dekker, New Yorkm 1982, pp. 409-424.Google Scholar
  21. 21.
    A. Fink-Jensen, P. D. Suzdak, M. D. B. Swedberg, M. E. Judge, L. Hansen, and P. G. Nielsen. The γ-aminobutyric acid (GABA) uptake inhibitor, tiagabine, increases extracellular brain levels of GABA in awake rats. Eur. J. Pharmacol. 220:197-201 (1992).PubMedCrossRefGoogle Scholar
  22. 22.
    M. Lancel, J. Faulhaber, and R. A. Deisz. Effect of the GABA uptake inhibitor tiagabine on sleep and EEG power spectra in the rat. Br. J. Pharmacol. 123:1471-1477 (1998).PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    A. M. L. Coenen, E. H. M. Blezer, and V. Luijtelaar. Effects of the GABA uptake inhibitor tiagabine on electroencephalogram, spike-wave discharges and behaviour of rats. Epilepsy Res. 21:89-94 (1995).PubMedCrossRefGoogle Scholar
  24. 24.
    L. B. Sheiner and D. Verotta. Further notes on physiological indirect response models. Clin. Pharmacol. Ther. 58:238-240 (1995).PubMedCrossRefGoogle Scholar
  25. 25.
    E. A. Van Schaick, H. J. M. M. De Graaf, A. P. IJzerman, and M. Danhof. Physiological indirect effect modelling of the anti-lipolytic effects of adenosine A1 receptor agonists. J. Pharmacokin. Biopharm. 25:713-730 (1997).CrossRefGoogle Scholar
  26. 26.
    E. Snoeck, V. Pitrovskij, P. Jacqmin, A. Van Peer, M. Danhof, K. Ver Donck, R. Woestenborghs, H. Van Belle, L. Van Bortel, R. Van Gool, A. Dupont, and J. Heykants. Population analysis of the nonlinear red blood cell partitioning and the concentration-effect relationship of draflazine following various infusion rates. Br. J. Clin. Pharmacol. 43:603-612 (1997).PubMedCentralPubMedCrossRefGoogle Scholar
  27. 27.
    E. Snoeck, K. Ver Donck, P. Jacqmin, H. Van Belle, A. G. Dupont, A. Van Peer, and M. Danhof. Physiological red blood cell kinetic model to explain the apparent discrepancy between adenosine breakdown inhibition and nucleoside transport occupancy of draflazine. J. Pharmacol. Exp. Ther. 286:142-149 (1998).PubMedGoogle Scholar
  28. 28.
    J. C. Rekling, H. Jahnsen, and A. M. Laursen. The effect of two lipophilic γ-aminobutyric acid uptake blockers in CA1 of the rat hippocampal slice. Br. J. Pharmacol. 99:103-106 (1990).PubMedCentralPubMedCrossRefGoogle Scholar
  29. 29.
    C. H. Davies, S. N. Davies, and G. L. Collingridge. Paired-pulse depression of monosynaptic GABA-mediated inhibitory post-synaptic responses in rat hippocampus. J. Physiol. 424:513-531 (1990).PubMedCentralPubMedCrossRefGoogle Scholar
  30. 30.
    S. M. Thompson and B. H. Gähwiler. Effects of the GABA uptake inhibitor tiagabine on inhibitory synaptic potentials in rat hippocampal slice cultures. J. Neurophysiol. 67:1698-1701 (1992).PubMedGoogle Scholar
  31. 31.
    A. Cleton, R. A. Voskuyl, and M. Danhof. Adaptive changes in the pharmacodynamics of midazolam in different models of epilepsy: kindling, cortical stimulation, genetic absence epilepsy. Br. J. Pharmacol. 125:615-620 (1998).PubMedCentralPubMedCrossRefGoogle Scholar
  32. 32.
    J. W. Mandema, E. Tukker, and M. Danhof. Pharmacokinetic-pharmacodynamic modelling of the EEG effects of midazolam in individual rats: influence of rate and route of administration. Br. J. Pharmacol. 102:663-668 (1991).PubMedCentralPubMedCrossRefGoogle Scholar
  33. 33.
    A. Wessén, K. Parivar, M. Widman, A. Nilsson, and P. Hartvig. Concentration-effect relationships of eltanolone given as a bolus dose or constant rate intravenous infusion to healthy male volunteers. Anesthesiology 84:1317-1326 (1996).PubMedCrossRefGoogle Scholar
  34. 34.
    A. Patat, F. le Coz, C. Dubruc, J.-M. Gandon, G. Durrieu, I. Cimarotsi, S. Jezequil, O. Curet, I. Zieleniuk, H. Allain, and P. Rosenzwieg. Pharmacodynamics and pharmacokinetics of two dosage regimens of befloxatone, a new reversible and selective monoamine oxidase inhibitor, at steady state in healthy volunteers. J. Clin. Pharmacol. 36:216-229 (1996).PubMedCrossRefGoogle Scholar
  35. 35.
    E. H. Cox, T. Kerbusch, P. H. van der Graaf, and M. Danhof. Pharmacokinetic-pharmacodynamic modelling of the EEG effect of synthetic opioids in the rat: correlation with the interaction at the μ-opioid receptor. J. Pharmacol. Exp. Ther. 284:1095-1103 (1998).PubMedGoogle Scholar
  36. 36.
    T. Rydberg, A. Jönsson, M. O. Karlsson, and A. Melander. Concentration-effect relations of glibenclamide and its active metabolites in human: modelling of pharmacokinetics and pharmacodynamics. Br. J. Clin. Pharmacol. 43:373-381 (1997).PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Plenum Publishing Corporation 1999

Authors and Affiliations

  • Adriaan Cleton
    • 1
  • Henrik J. M. M. de Greef
    • 1
  • Peter M. Edelbroek
    • 2
    • 3
  • Robert A. Voskuyl
    • 2
  • Meindert Danhof
    • 1
    Email author
  1. 1.Division of Pharmacology, Leiden/Amsterdam Center for Drug ResearchLeiden UniversityLeidenThe Netherlands
  2. 2.Stichting Epilepsie Instellingen NederlandHeemstede
  3. 3.Department of PhysiologyLeiden University Medical CenterLeidenThe Netherlands

Personalised recommendations