Skip to main content
Log in

Improved precision of exposure–response relationships by optimal dose-selection. Examples from studies of receptor occupancy using PET and dose finding for neuropathic pain treatment

  • Original Paper
  • Published:
Journal of Pharmacokinetics and Pharmacodynamics Aims and scope Submit manuscript

Abstract

An understanding of the relationship between drug exposure and response is a fundamental basis for any dosing recommendation. We investigate optimal dose-selection for two different types of studies, a receptor occupancy study assessed by positron emission tomography (PET) and a dose-finding study in neuropathic pain treatment. For the PET-study, an inhibitory E-max model describes the relationship between drug exposure and displacement of a radioligand from specific receptors in the brain. The model has a mechanistic basis in the law of mass action and the affinity parameter (Ki PL ) is of primary interest. For optimization of the neuropathic pain study, the model is empirical and the exposure response curve itself is of primary interest. An alternative parameterization of the sigmoid Emax model was therefore used where the plasma concentration corresponding to the minimum relevant efficacy was estimated as a parameter. Optimal design methodology was applied using the D-optimal criterion as well as the Ds-optimal criterion where parameters of interest were defined. For the PET-study it was shown that the precision of Ki PL can be improved by inclusion of brain regions with both high and low receptor density and that the need for high doses is reduced when a brain region with low receptor density is included in the analysis. In the case of the neuropathic pain study it was shown that a Ds-optimal study design using the reparameterized Emax model can improve the precision in the minimum effective dose compared to a D-optimal design.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. International Conference of Harmonisation (ICH) (1994) Dose-response information to support drug registration E4

  2. Food and Drug Administration (FDA) (2003) Guidance for industry: exposure-response relationships—study design, data analysis and regulatory applications

  3. Pinheiro J, Bornkamp B, Glimm E, Bretz F (2013) Model-based dose finding under model uncertainty using general parametric models. Stat Med. doi:10.1002/sim.6052

    PubMed  Google Scholar 

  4. Miller F, Guilbaud O, Dette H (2007) Optimal designs for estimating the interesting part of a dose-effect curve. J Biopharm Stat 17(6):1097–1115. doi:10.1080/10543400701645140

    Article  PubMed  Google Scholar 

  5. Bretz F, Hsu J, Pinheiro J, Liu Y (2008) Dose finding—a challenge in statistics. Biometr J 50(4):480–504. doi:10.1002/bimj.200810438

    Article  Google Scholar 

  6. Dette H, Bretz F, Pepelyshev A, Pinheiro J (2008) Optimal designs for dose-finding studies. J Am Stat Assoc 103(483):1225–1237. doi:10.1198/016214508000000427

    Article  CAS  Google Scholar 

  7. Kagedal M, Cselenyi Z, Nyberg S, Raboisson P, Stahle L, Stenkrona P, Varnas K, Halldin C, Hooker AC, Karlsson MO (2013) A positron emission tomography study in healthy volunteers to estimate mGluR5 receptor occupancy of AZD2066—estimating occupancy in the absence of a reference region. NeuroImage 82:160–169. doi:10.1016/j.neuroimage.2013.05.006

    Article  PubMed  Google Scholar 

  8. Lassen NA, Bartenstein PA, Lammertsma AA, Prevett MC, Turton DR, Luthra SK, Osman S, Bloomfield PM, Jones T, Patsalos PN et al (1995) Benzodiazepine receptor quantification in vivo in humans using [11C]flumazenil and PET: application of the steady-state principle. J Cereb Blood Flow Metab 15(1):152–165. doi:10.1038/jcbfm.1995.17

    Article  CAS  PubMed  Google Scholar 

  9. Farde L, Hall H, Ehrin E, Sedvall G (1986) Quantitative analysis of D2 dopamine receptor binding in the living human brain by PET. Science 231(4735):258–261

    Article  CAS  PubMed  Google Scholar 

  10. Lockwood PA, Cook JA, Ewy WE, Mandema JW (2003) The use of clinical trial simulation to support dose selection: application to development of a new treatment for chronic neuropathic pain. Pharm Res 20(11):1752–1759

    Article  CAS  PubMed  Google Scholar 

  11. Holford NH, Sheiner LB (1981) Understanding the dose-effect relationship: clinical application of pharmacokinetic-pharmacodynamic models. Clin Pharmacokinet 6(6):429–453

    Article  CAS  PubMed  Google Scholar 

  12. Groth AV (2008) Alternative parameterisations of saturable (Emax) models allowing for nesting of non-saturable models. Population Approach Group Europe (PAGE) 17:Abstr 1371

  13. Nyberg J, Ueckert S, Stromberg EA, Hennig S, Karlsson MO, Hooker AC (2012) PopED: an extended, parallelized, nonlinear mixed effects models optimal design tool. Comput Methods Progr Biomed 108(2):789–805. doi:10.1016/j.cmpb.2012.05.005

    Article  Google Scholar 

  14. Foracchia M, Hooker A, Vicini P, Ruggeri A (2004) POPED, a software for optimal experiment design in population kinetics. Comput Methods Progr Biomed 74(1):29–46. doi:10.1016/S0169-2607(03)00073-7

    Article  Google Scholar 

  15. Ueckert S, Hennig S, Nyberg J, Karlsson MO, Hooker AC (2013) Optimizing disease progression study designs for drug effect discrimination. J Pharmacokinet Pharmacodyn 40(5):587–596. doi:10.1007/s10928-013-9331-3

    Article  PubMed  Google Scholar 

  16. Atkinson A, Donev AN (1992) Optimum experimental designs. Oxford University Press, USA

    Google Scholar 

  17. Mintun MA, Raichle ME, Kilbourn MR, Wooten GF, Welch MJ (1984) A quantitative model for the in vivo assessment of drug binding sites with positron emission tomography. Ann Neurol 15(3):217–227. doi:10.1002/ana.410150302

    Article  CAS  PubMed  Google Scholar 

  18. Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, Holden J, Houle S, Huang SC, Ichise M, Iida H, Ito H, Kimura Y, Koeppe RA, Knudsen GM, Knuuti J, Lammertsma AA, Laruelle M, Logan J, Maguire RP, Mintun MA, Morris ED, Parsey R, Price JC, Slifstein M, Sossi V, Suhara T, Votaw JR, Wong DF, Carson RE (2007) Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab 27(9):1533–1539. doi:10.1038/sj.jcbfm.9600493

    Article  CAS  PubMed  Google Scholar 

  19. Cunningham VJ, Rabiner EA, Slifstein M, Laruelle M, Gunn RN (2010) Measuring drug occupancy in the absence of a reference region: the Lassen plot re-visited. J Cereb Blood Flow Metab 30(1):46–50. doi:10.1038/jcbfm.2009.190

    Article  PubMed Central  PubMed  Google Scholar 

  20. Farde L, Nordstrom AL, Wiesel FA, Pauli S, Halldin C, Sedvall G (1992) Positron emission tomographic analysis of central D1 and D2 dopamine receptor occupancy in patients treated with classical neuroleptics and clozapine. Relation to extrapyramidal side effects. Arch Gen Psychiatry 49(7):538–544

    Article  CAS  PubMed  Google Scholar 

  21. Kapur S, Barsoum SC, Seeman P (2000) Dopamine D(2) receptor blockade by haloperidol. (3)H-raclopride reveals much higher occupancy than EEDQ. Neuropsychopharmacology 23(5):595–598. doi:10.1016/S0893-133X(00)00139-1

    Article  CAS  PubMed  Google Scholar 

  22. Freynhagen R, Strojek K, Griesing T, Whalen E, Balkenohl M (2005) Efficacy of pregabalin in neuropathic pain evaluated in a 12-week, randomised, double-blind, multicentre, placebo-controlled trial of flexible- and fixed-dose regimens. Pain 115(3):254–263. doi:10.1016/j.pain.2005.02.032

    Article  CAS  PubMed  Google Scholar 

  23. Dodds MG, Hooker AC, Vicini P (2005) Robust population pharmacokinetic experiment design. J Pharmacokinet Pharmacodyn 32(1):33–64. doi:10.1007/s10928-005-2102-z

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Matts Kågedal.

Electronic supplementary material

Below is the link to the electronic supplementary material.

10928_2015_9410_MOESM1_ESM.tiff

Supplementary material 1 (TIFF 16406 kb). The distribution of the MED for each of the models when they were selected using the likelihood ratio test. The dashed line indicates the true MED. The scale is truncated such that all doses above 4 are set to 4. The cases when no significant effect of a linear versus a no effect model was seen are shown at a dose of 4

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kågedal, M., Karlsson, M.O. & Hooker, A.C. Improved precision of exposure–response relationships by optimal dose-selection. Examples from studies of receptor occupancy using PET and dose finding for neuropathic pain treatment. J Pharmacokinet Pharmacodyn 42, 211–224 (2015). https://doi.org/10.1007/s10928-015-9410-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10928-015-9410-8

Keywords

Navigation