Skip to main content
SpringerLink
Log in

Prediction of in Vivo Tissue Distribution from in Vitro Data. 2. Correlation Between in Vitro and in Vivo Tissue Distribution of a Homologous Series of Nine 5-n-Alkyl-5-Ethyl Barbituric Acids

  • Published:
Pharmaceutical Research Aims and scope Submit manuscript

Abstract

Purpose. To evaluate the ability to determine accurate in vivo tissue-to-unbound plasma distribution coefficients (Kpue) from in vitro data.

Methods. Fresh pieces of fifteen rat tissues/organs were incubated at 37°C with a homologous series of nine barbiturates covering a wide range of lipophilicity (Log P 0.02 to 4.13). Steady-state in vivo Kpu e values were estimated from the tissue and plasma concentrations following simultaneous dosing by constant rate i.v. infusion of all nine barbiturates. Drug concentrations in the tissues and media were determined by HPLC with UV or mass spectrometric detection.

Results. The pharmacokinetics of the barbiturate series following constant rate i.v. infusion indicated a range of clearance (0.49 to 30 ml.min\-1.kg\-1) and volume of distribution at steady state (0.51 to 1.9 l.kg\-1) values. Good agreement was observed between the in vitro and in vivo Kpu values, although for the most lipophilic barbiturates the in vitro data underpredicted the in vivo tissue distribution for all tissues.

Conclusions. The in vitro system for predicting the extent of in vivo tissue distribution works well for compounds of widely differing lipophilicity, although for the most lipophilic drugs it may result in an underprediction of in vivo values.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. H.-S. G. Chen and J. F. Gross. Estimation of tissue-to-plasma partition coefficients used in physiological pharmacokinetic models. J. Pharmacokinet. Biopharm. 7:117–125 (1979).

    PubMed  Google Scholar 

  2. K. B. Bischoff, R. L. Dedrick, and D. S. Zaharko. Preliminary model for methotrexate pharmacokinetics. J. Pharm. Sci. 59:149–154 (1970).

    PubMed  Google Scholar 

  3. A. Benareggi and M. Rowland. Physiologic modeling of cyclosporin kinetics in rat and man. J. Pharmacokinet. Biopharm. 19:21–50 (1991).

    PubMed  Google Scholar 

  4. J. L. Gabrielsson, L. K. Paalzow, and L. Nordstrom. A physiologically based pharmacokinetic model for theophylline disposition in the pregnant and nonpregnant rat. J. Pharmacokinet. Biopharm. 12:149–165 (1984).

    PubMed  Google Scholar 

  5. L. Granero, J. Chesa-Jimenez, V. Monserrat, M. Almela, M.-J. Gimeno, F. Torres-Molina, and J.-E. Peris-Ribera. Physiological pharmacokinetic model for ceftazidime disposition in the rat and its application to prediction of plasma concentration in humans. Eur. J. Pharm. Sci. 1:3–11 (1993).

    Google Scholar 

  6. Y. Igari, Y. Sugiyama, S. Awazu, and M. Hanano. Comparative physiologically based pharmacokinetics of hexobarbital, phenobarbital and thiopental in the rat. J. Pharmacokinet. Biopharm. 10:53–75 (1982).

    PubMed  Google Scholar 

  7. G. E. Blakey, I. A. Nesterov, P. A. Arundel, L. J. Aarons, and M. Rowland. Quantitative structure pharmacokinetics relationships: 1. Development of a whole-body physiologically based model to characterize changes in pharmacokinetics across a homologous series of barbiturates in the rat. J. Pharmacokinet. Biopharm. 25:277–312 (1997).

    PubMed  Google Scholar 

  8. R. Gubser, C. DiFransesco, and M. H. Bickel. Uptake of lipophilic model compounds into the isolated perfused rat epididymal adipose tissue. J. Pharmacol. Exp. Therap. 237:967–971 (1986).

    Google Scholar 

  9. C.-H. Chou, A. M. Evans, G. Fornasini, and M. Rowland. Relationship between lipophilicity and hepatic dispersion and distribution for a homologous series of barbiturates in the isolated perfused in situ rat liver. Drug Metab. Dispos. 21:933–938 (1993).

    PubMed  Google Scholar 

  10. A. Heatherington and M. Rowland. Estimation of reference spaces in the perfused rat hindlimb. Eur. J. Pharm. Sci. 2:261–270 (1994).

    Google Scholar 

  11. M. H. Bickel, R. M. Raaflaub, M. Hellmuller, and E. J. Stauffer. Characterization of drug distribution and binding competition by two-chamber and multi-chamber distribution dialysis. J. Pharm. Sci. 76:68–74 (1987).

    PubMed  Google Scholar 

  12. T. M. Ludden, L. S. Schanker, and R. C. Lanman. Binding of organic compounds to rat liver and lung. Drug Metab. Dispos. 4:8–16 (1976).

    PubMed  Google Scholar 

  13. M. H. Bickel and J. W. Steele. Binding of basic and acidic drugs to rat tissue subcellular fractions. Chemico-Biol. Int. 8:151–162 (1974).

    Google Scholar 

  14. W. O. Berndt. Use of the tissue slice technique for evaluation of renal transport processes. Env. Health Persp. 15:73–88 (1976).

    Google Scholar 

  15. R. Drew and Z. H. Siddik. Effect of a specific 5HT uptake inhibitor (citalopram) on drug accumulation by rat lung slices. Pharmacol. 20:27–31 (1980).

    Google Scholar 

  16. C. Post, R. G. G. Andersson, A. Ryrfeldt, and E. Nilsson. Transport and binding of lidocaine by lung slices and perfused lung of rats. Acta Pharmacol. Tox. 43:156–163 (1978).

    Google Scholar 

  17. P. Ballard, P. A. Arundel, D. E. Leahy, and M. Rowland. Prediction of in vivo tissue distribution from in vitro data 2. Influence of albumin diffusion from tissue slices during an in vitro incubation on estimated tissue-to-unbound plasma partition coefficients (Kpu). Pharm. Res. 20:857–863.

  18. P. Ballard, D. E. Leahy, and M. Rowland. Prediction of in vivo tissue distribution from in vitro data. 1. Experiments with markers of aqueous spaces. Pharm. Res. 17:660–663 (2000).

    PubMed  Google Scholar 

  19. S. Toon and M. Rowland. Structure-pharmacokinetic relationships among the barbiturates in the rat. J. Pharmacol. Exp. Ther. 225:752–763 (1983).

    PubMed  Google Scholar 

  20. G. Blakey. Whole body tissue distribution of the 5-alkyl-5-ethyl barbituric acids in the rat (preliminary results). PhD thesis, University of Manchester, 1993.

  21. S. H. Steiner, M. J. Moor, and M. H. Bickel. Kinetics of distribution and adipose tissue storage as a function of lipophilicity and chemical structure. I. Barbiturates. Drug Metab. Dispos. 19:8–14 (1991).

    PubMed  Google Scholar 

  22. C. B. Frederick, D. W. Potter, M. I. Chang-Mateu, and M. E. Andersen. A physiologically-based pharmacokinetic and pharmacodynamic model to describe the oral dosing of rats with ethyl acrylate and its implications for risk assessment. Tox. Appl. Pharmacol. 114:246–260 (1992).

    Google Scholar 

  23. V. Fiserova-Bergerova, M. Tichy, and F. J. Di Carlo. Effects of biosolubility on pulmonary uptake and disposition of gases and vapors of lipophilic chemicals. Drug Metab. Rev. 15:1033–1070 (1984).

    PubMed  Google Scholar 

  24. J. H. Lin, Y. Sugiyama, S. Awazu, and M. Hanano. In vitro and in vivo evaluation of the tissue blood partition coefficient for physiological pharmacokinetic models. J. Pharmacokinet. Biopharm. 10:637–647 (1982).

    PubMed  Google Scholar 

  25. H. Harashima, Y. Sugiyama, Y. Sawada, T. Iga, and M. Hanano. Comparison between in vivo and in vitro tissue-to-plasma unbound concentration ratios (Kp,f) of quinidine in rats. J. Pharm. Pharmacol. 36:340–342 (1984).

    PubMed  Google Scholar 

  26. G. Schuhmann, B. Fichtl, and H. Kurz. Prediction of drug distribution in vivo on the basis of in vitro binding data. Biopharm. Drug Dispos. 8:73–86 (1987).

    PubMed  Google Scholar 

  27. P. Poulin and F.-P. Theil. Prediction of pharmacokinetics prior to in vivo studies. I. Mechanism-based prediction of volume of distribution. J. Pharm. Sci. 91:129–156 (2002).

    Article  PubMed  Google Scholar 

  28. P. Poulin and F.-P. Theil. Prediction of pharmacokinetics prior to in vivo studies. II. Generic physiologically based pharmacokinetic models of drug disposition. J. Pharm. Sci. 91:1358–1370 (2002).

    PubMed  Google Scholar 

  29. I. Nestorov, L. J. Aarons, and M. Rowland. Quantitative structure-pharmacokinetics relationships: II. A mechanistically based model to evaluate the relationship between tissue distribution parameters and compound lipophilicity. J. Pharmacokinet. Biopharm. 26:521–545 (1998).

    PubMed  Google Scholar 

  30. T. D. Yih and J. M. van Rossum. Ks values of some homologous series of barbiturates and the relationship with the lipophilicity and metabolic clearance. Biochem. Pharmacol. 26:2117–2120 (1977).

    PubMed  Google Scholar 

  31. C. Hansch, A. R. Steward, S. M. Anderson, and D. Bentley. The parabolic dependence of drug action upon lipophilic character as revealed by a study of hypnotics. J. Med. Chem. 11:1–11 (1967).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Discovery-DMPK, Mereside, AstraZeneca, Alderley Park, Cheshire, SK10 4TG, United Kingdom

    Peter Ballard

  2. Cyprotex, 15 Beech Lane, Macclesfield, Cheshire, SK10 2DR, United Kingdom

    David E. Leahy

  3. dSchool of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, M13 9PL, United Kingdom

    Malcolm Rowland

Authors
  1. Peter Ballard
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David E. Leahy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Malcolm Rowland
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter Ballard.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ballard, P., Leahy, D.E. & Rowland, M. Prediction of in Vivo Tissue Distribution from in Vitro Data. 2. Correlation Between in Vitro and in Vivo Tissue Distribution of a Homologous Series of Nine 5-n-Alkyl-5-Ethyl Barbituric Acids. Pharm Res 20, 864–872 (2003). https://doi.org/10.1023/A:1023912318133

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1023912318133

Search

Navigation