Advertisement

Sparse data analysis

  • L. Aarons
Article

Summary

In recent years there has been a growing interest in techniques capable of analyzing sparse data, particularly gathered during Phase III clinical trials, and there is now pressure on manufacturers to obtain more kinetic and dynamic information from Phase III studies. Techniques for the analysis of sparse data are reviewed drawing on a number of examples taken from pharmacokinetic and pharmacodynamic experiments.

Keywords

Sparse data analysis population pharmacokinetics pharmacodynamics NONMEM drug development 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Whiting B., Kelman A.W., Grevel J. (1986): Population pharmacokinetics. Theory and application. Clin. Pharmacokinet., 11, 387–401.PubMedCrossRefGoogle Scholar
  2. 2.
    Aarons L. (1991): Population pharmacokinetics: theory and practice. Br. J. Clin. Pharmacol., 32, 669–670.PubMedGoogle Scholar
  3. 3.
    New Strategies in Drug Development and Clinical Evaluation: the Population Approach. (1992): Rowland M., Aarons L. (eds). Luxembourg, Commission of the European Communities.Google Scholar
  4. 4.
    Jochemsen R. (1992): Current experience of population pharmacokinetics within the pharmaceutical industry: an introduction. In: Rowland M., Aarons L. (eds). New Strategies in Drug Development and Clinical Evaluation: the Population Approach. Luxembourg, Commission of the European Communities, pp. 127–130.Google Scholar
  5. 5.
    Gibaldi M., Perrier D. (1982): Pharmacokinetics. 2nd edn. New York, Marcel Dekker.Google Scholar
  6. 6.
    Lindstrom F.T., Birkes D.S. (1984): Estimation of population pharmacokinetic parameters using destructively obtained experimental data: a simulation study of the one-compartment open model. Drug Met. Rev., 15, 195–264.CrossRefGoogle Scholar
  7. 7.
    Ludden T., Allerheiligen S.R.B., Burk R.F. (1991): Application of population analysis to physiological pharmacokinetics. J. Pharmacokinet. Biopharm. (Suppl), 19, 101S-113S.CrossRefGoogle Scholar
  8. 8.
    Driscoll M.S., Ludden T.M., Casto D.T., Littlefield L.C. (1989): Evaluation of theophylline pharmacokinetics in a pediatric population using mixed effects models. J. Pharmacokinet. Biopharm., 17, 141–168.PubMedCrossRefGoogle Scholar
  9. 9.
    Kelman A.W., Thomson A.H., Whiting B., Bryson S.M., Steedman D.A. (1984): Estimation of gentamicin clearance and volume of distribution in neonates and young children. Br. J. Clin. Pharmacol., 18, 685–692.PubMedGoogle Scholar
  10. 10.
    Moore E.S., Faix R.G., Banagale R.C., Grasela T.H. (1989): The population pharmacokinetics of theophylline in neonates and young infants. J. Pharmacokinet. Biopharm., 17, 47–66.PubMedCrossRefGoogle Scholar
  11. 11.
    Aarons L. (1991): The kinetics of flurbiprofen in synovial fluid. J. Pharmacokinet. Biopharm., 19, 265–269.PubMedCrossRefGoogle Scholar
  12. 12.
    Winstanley P.A., Watkins W.M. (1992): Pharmacology and parasitology: integrating experimental methods and approaches to falciparum malaria. Br. J. Clin. Pharmacol., 33, 575–581.PubMedGoogle Scholar
  13. 13.
    Beal S.L., Sheiner L.B. (1982): Estimating population kinetics. CRC Crit. Rev. Biomed. Eng., 8, 195–222.Google Scholar
  14. 14.
    Amisaki T., Tatsuhara T. (1988): An alternative two stage method via the EM-algorithm for the estimation of population pharmacokinetic parameters. J. PharmacobioDyn., 11, 335–348.PubMedGoogle Scholar
  15. 15.
    Lindstrom M.J., Bates D.M. (1990): Nonlinear mixed effects models for repeated measures data. Biometrics, 46, 673–687.PubMedCrossRefGoogle Scholar
  16. 16.
    Vonesh E.F., Carter R.L. (1992): Mixed-effects nonlinear regression for unbalanced repeated measures. Biometrics, 48, 1–17.PubMedCrossRefGoogle Scholar
  17. 17.
    Mallet A. (1986): A maximum likelihood estimation method for random coefficient regression models. Biometrika, 73, 645–656.CrossRefGoogle Scholar
  18. 18.
    Mallet A., Mentre F., Steimer J.-L., Lokiec F. (1988): Nonparametric maximum likelihood estimation for population pharmacokinetics, with application to cyclosporine. J. Pharmacokinet. Biopharm., 16, 311–327.PubMedCrossRefGoogle Scholar
  19. 19.
    Mallet A., Mentre F., Gilles J., et al. (1988): Handling covariates in population pharmacokinetics, with an application to gentamicin. Biomed. Meas. Inf. Cont., 2, 138–146.Google Scholar
  20. 20.
    Mentre F., Mallet A. (1992): Experiences with NPML — application to dosage individualisation of cyclosporine, gentamicin and zidovudine. In: Rowland M., Aarons L. (eds). New Strategies in Drug Development and Clinical Evaluation: the Population Approach. Luxembourg, Commission of the European Communities, pp. 75–88.Google Scholar
  21. 21.
    Schumitsky A. (1991): Nonparametric EM algorithms for estimating prior distributions. Appl. Math. Comput., 45, 143–157.CrossRefGoogle Scholar
  22. 22.
    Davidian M., Gallant A.R. (1992): Smooth nonparametric maximum likelihood estimation for population pharmacokinetics with application to quinidine. J. Pharmacokinet. Biopharm., 20, 529–556.PubMedCrossRefGoogle Scholar
  23. 23.
    Racine-Poon A., Smith A.F.M. (1990): Population models. In: Berry D.A. (ed.) Statistical Methodology in the Pharmaceutical Sciences. New York, Marcel Dekker, pp. 139–162.Google Scholar
  24. 24.
    Racine-Poon A. (1992): A Bayesian approach to the prediction of the plasma concentration range of carbamazepine in epileptic patients. In: Rowland M., Aarons L. (eds.) New Strategies in Drug Development and Clinical Evaluation: the Population Approach. Luxembourg, Commission of the European Communities, pp. 91–98.Google Scholar
  25. 25.
    Sheiner L.B., Beal S.L. (1982): Bayesian individualisation of pharmacokinetics: simple implementation and comparison with non-Bayesian methods. J. Pharm. Sci., 71, 1344–1348.PubMedCrossRefGoogle Scholar
  26. 26.
    Vozeh S., Steiner C. (1987): Estimates of the population pharmacokinetic parameters and performance of Bayesian feedback: a sensitivity analysis. J. Pharmacokinet. Biopharm., 15, 511–528.PubMedCrossRefGoogle Scholar
  27. 27.
    Sanathanan L., Peck C., Temple R., Lieberman R., Pledger G. (1991): Randomization, pharmacokinetically-controlled dosing and titration: an integrated approach for designing clinical trials. Drug Inf. J., 25, 425–431.Google Scholar
  28. 28.
    Aarons L., Vozeh S., Wenk M., Weiss Ph., Follath F. (1989): Population pharmacokinetics of tobramycin. Br. J. Clin. Pharmacol., 28, 305–314.PubMedGoogle Scholar
  29. 29.
    Aarons L., Mandeman J.W., Danhof M. (1991): A population analysis of the pharmacokinetics of midazolam in the rat. J. Pharmacokinet. Biopharm., 19, 485–496.PubMedCrossRefGoogle Scholar
  30. 30.
    Sheiner L.B., Benet L.Z. (1985): Premarketing observational studies of population pharmacokinetics of new drugs. Clin. Pharmacol. Ther., 38, 481–487.PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 1993

Authors and Affiliations

  • L. Aarons
    • 1
  1. 1.Pharmacy DepartmentUniversity of ManchesterManchesterUK

Personalised recommendations