Robust optimal design for the estimation of hyperparameters in population pharmacokinetics

Journal of Pharmacokinetics and Biopharmaceutics

Volumn 26, Issue 6, 1998, Pages 689-716

  Tod, Michel ^a   Mentré, France ^b   Merlé, Yann ^b   Mallet, Alain ^b  

^a AVICENNE HOSPITAL   (France)

^b PITIÉ SALPÊTRIÈRE HOSPITAL   (France)

Author keywords

D optimality; Experimental design; Population pharmacokinetics

Indexed keywords

DRUG;

ARTICLE; DRUG ABSORPTION; DRUG MONITORING; METHODOLOGY; POPULATION DYNAMICS; PRIORITY JOURNAL; SAMPLING;

HUMANS; MODELS, BIOLOGICAL; PHARMACOKINETICS; POPULATION SURVEILLANCE;

EID: 0032465920     PISSN: 0090466X     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1020703007613     Document Type: Article

References (28)

1. L. B. Sheiner, B. Rosenberg, and K. L. Melmon. Modeling of individual pharmacokinetics for computer-aided dosage. Comput. Biomed. Res. 5:441-459 (1972).
2. L. B. Sheiner and T. M. Ludden. Population pharmacokinetics/pharmacodynamics. Ann. Rev. Pharmacol. Toxicol. 32:185-209 (1992).
3. S. Vozeh, J. L. Steimer, M. Rowland, P. Morselli, F. Mentré, L. P. Balant, and L. Aarons. The use of population pharmacokinetics in drug development. Clin. Pharmacokin. 30:81-93 (1996).
4. P. Burtin, F. Mentré J. Van Bree, and J. L. Steimer. Sparse sampling for assessment of drug exposure in toxicological studies. Eur. J. Drug Metab. Pharmacokin. 22:105-111 (1996).
5. A. H. Thomson and B. H. Whiting. Bayesian parameter estimation and population pharmacokinetics. Clin. Pharmacokin. 22:447-467 (1992).
6. M. K. Al-Banna, A. W. Kelman, and B. Whiting. Experimental design and efficient parameter estimation in population pharmacokinetics. J. Pharmacokin. Biopharm. 18:347-360 (1990).
7. Y. Hashimoto and L. B. Sheiner. Designs for population pharmacodynamics: Value of pharmacokinetic data and population analysis. J. Pharmacokin. Biopharm. 19:333-353 (1991).
8. J. Wang and L. Endrenyi. A computationally efficient approach for the design of population pharmacokinetic studies. J. Pharmacokin. Biopharm. 20:279-294 (1992).
9. E. I. Ette, C. A. Howie, A. W. Kelman and B. Whiting. Experimental design and efficient parameter estimation in preclinical pharmacokinetic studies. Pharm. Res. 12:729-737 (1995).
10. E. N. Jonsson, J. R. Wade, and M. O. Karlsson. Comparison of some practical sampling strategies for population pharmacokinetic studies. J. Pharmacokin. Biopharm. 24:245-263 (1996).
11. V. Breant, B. Charpiat, J. M. Sab, P. Maire, and R. W. Jeliffe. How many patients and blood levels are necessary for population pharmacokinetic analysis? Eur. J. Clin. Pharmacol. 51:283-288 (1996).
12. F. Mentré, P. Burtin, Y. Merlé, J. Van Bree, A. Mallet, and J. L. Steimer. Sparse-sampling optimal designs in pharmacokinetics and toxicokinetics. Drug Inform. J. 29:997-1019 (1995).
13. F. Mentré, A. Mallet, and D. Baccar. Optimal design in nonlinear random effect models. Biometrika 84:429-442 (1997).
14. E. Walter and L. Pronzato. Qualitative and quantitative experiment design for phenomenological models - A survey. Automatica 26:195-213 (1990).
15. D. Z. D'Argenio. Optimal sampling times for pharmacokinetic experiments. J. Pharmacokin. Biopharm. 9:739-756 (1981).
16. E. Walter and L. Pronzato. Optimal experiment design for nonlinear models subject to large prior uncertainties. Am. J. Physiol. 253:R530-R534 (1987).
17. L. Pronzato and E. Walter. Robust experiment design via stochastic approximation. Math. Biosci. 75:103-120 (1985).
18. D. Z. D'Argenio. Incorporating prior parameter uncertainty in the design of sampling schedules for pharmacokinetic parameter estimation experiments. Math. Biosci. 99:105-118 (1990).
19. N. L. Johnson and S. Kotz. Distributions in Statistics: Continuous Multivariate Distributions, Wiley, New York, 1972, pp. 158-180.
20. G. N. Saridis. Stochastic approximation methods for identification and control - A survey. IEEE Trans. Automat. Contr. 19:798-809 (1974).
21. M. Tod and J. M. Rocchisani. Implementation of OSPOP, an algorithm for the estimation of optimal sampling times in pharmacokinetics by the ED, EID, and API criteria. Comput. Meth. Prog. Biomed. 50:13-22 (1996).
22. H. Kesten. Accelerated stochastic approximation methods. Ann. Math. Statist. 29:41-59 (1958).
23. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery. Numerical Recipes in C, 2nd Ed., Cambridge University Press, 1992, pp. 1-993.
24. P. L. Odell and A. H. Feiveson. A numerical procedure to generate a sample covariance matrix. J. Am. Statist. Soc. 313:199-203 (1966).
25. M. Tod and J. M. Rocchisani. Comparison of ED, EID, and API criteria for the robust optimization of sampling times in pharmacokinetics. J. Pharmacokin. Biopharm. 25:515-537 (1997).
26. L. Pronzato and E. Walter. Robust experiment design via maximin optimization. Math. Biosci. 89:161-176 (1988).
27. J. Kiefer and J. Wolfowitz. The equivalence of two extremum problems. Can. J. Math. 12:362-366 (1960).
28. L. Pronzato, C. Y. Huang, E. Walter, Y. Le Roux, and A. Frydman. Planification d'Expériences pour l'Estimation de Paramètres PK. Informatique et Santé 2, Springer-Verlag, 1989, pp. 3-13.