Skip to main content

Molecular Field-Derived Descriptors for the Multivariate Modeling of Pharmacokinetic Data

  • Chapter

Abstract

The optimization of pharmacokinetic properties is still one of the greatest challenges in lead optimization, and for the most part it is based on trial and error. As pharmacokinetics is closely linked with physicochemical properties, experimental design and quantitative structure-property modeling are key factors to systematically explore physicochemical property space and to establish stable, predictive models for lead optimization. However, experimental measurements of relevant parameters are often time-consuming, difficult and expensive. Furthermore, in vitro/in vivo approaches require the synthesis of compounds and cannot be used for the priorization of synthesis targets.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. GRID v. 16, Molecular Discovery Ltd., West Way House, Elms Parade, Oxford, 1997.

    Google Scholar 

  2. G. Cruciani, M. Pastor, VolSurf, version 0.0.2, MIA (Multivariate Infometric Analysis), 1998. 3 I. T. Jolliffe, Principal Component Analysis, Springer Verlag, Ney York, 1986.

    Google Scholar 

  3. S. Wold, E. Johansson, M. Cocchi, PLS- Partial Least-Squares Projections to Latent Structures. In: 3D QSAR in Drug Design, ESCOM, Leiden, 1993, pp. 523–550.

    Google Scholar 

  4. S. Hellberg, M. Sjöström, B. Skagerberg, S. Wold, J. Med. Chem. 1987, 30, 1126–1135.

    Article  CAS  Google Scholar 

  5. SIMCA-S, version 6.01, UMETRI AB, Omet, 1997.

    Google Scholar 

  6. K. Palm, P. Stenberg, K. Luthman, P. Artursson, Pharm. Res. 1997, 14, 568–571.

    Article  CAS  Google Scholar 

  7. S. Wold, Technometrics 1979, 20, 379–405.

    Google Scholar 

  8. E. Marengo, R. Todeschini, Chem. Intel. Lab. Syst. 1992, 16, 37–44.

    Article  CAS  Google Scholar 

  9. R.C. Young, R.C. Mitchell, T.H. Brown, C.R. Ganellin, R. Griffiths, M. Jones, K.K. Rana, D. Saunders, I.R. Smith, N.E. Sore, T.J. Wilks, J. Med. Chem. 1988, 31, 656–671.

    Article  CAS  Google Scholar 

  10. F. Lombardo, I.F. Blake, W.J. Curatolo, J. Med. Chem. 1996, 39, 4750–4755.

    Article  CAS  Google Scholar 

  11. M.H. Abraham, H.S. Chadha, R.C. Mitchell, J. Pharm. Sei. 1994, 83, 1257–1268.

    Article  CAS  Google Scholar 

  12. C. Fleck, H. Bräunlich, Arzneim.-Forsch./Drug Res. 1990, 40,(11) 942–946.

    CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer Science+Business Media New York

About this chapter

Cite this chapter

Guba, W., Cruciani, G. (2000). Molecular Field-Derived Descriptors for the Multivariate Modeling of Pharmacokinetic Data. In: Gundertofte, K., Jørgensen, F.S. (eds) Molecular Modeling and Prediction of Bioactivity. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4141-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-1-4615-4141-7_9

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6857-1

  • Online ISBN: 978-1-4615-4141-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics