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しょうじさだい
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1 Statistical Analyses in Clinical PPK/PD Studies Bridging Studies using NONMEM Yoshiro TOMONO Clinical Pharmacology Biometrics, Biometrics, Pfizer Pharmaceuticals Inc., Tokyo Summary: The present paper reports a new approach to building a population pharmacokinetic and phar macodynamic model (PPK/PD) and interpreting clinical data. In design of PK studies for the bridging strategy, a simple formula which gives the 90 per cent confidence interval to prove no ethnic PK difference is proposed, which derives the approximate estimation method for calculation of power and sample size for the parallel group design. In clinical studies, it is important to apply a technique to analyze the linking model with the drug concentra tion (pharmacokinetics, PK) and the efficacy (pharmacodynamics, PD) which are related closely. Effect compartment model and Jusko-type indirect PD model examples are shown using PPK/PD model analyzed with NONMEM. Recently the validation method of NONMEM is concerned. The bootstrap approach has been to use to ass ess the stability and predictive performance of a pharmacokinetic model developed using NONMEM. Guidance for Industry: Population Pharmacokinetics suggested the use of the bootstrap procedure as a satisfactory method for the validation and checking of population models in the drug approval process. Although validation methods are still being evaluated and may require further testing. The PPK/PD approaches are hopeful about the future in the field of drug development and drug evalua tion. Key words: Population pharmacokinetics, Pharmacodynamics, NONMEM, Effect compartment, In direct model, Bridging study, Interoccasion variability, Model varidation, Bootstrapping

2) FDA: Guidance for Industry, Population Pharmacokinet ics. February 1999. 3) Gough, K., Hutchison, M., Keene, O., Byron, B., Ellis, S., Lancey, L. and McKellar, J.

7 2) FDA: Guidance for Industry, Population Pharmacokinet ics. February ) Gough, K., Hutchison, M., Keene, O., Byron, B., Ellis, S., Lancey, L. and McKellar, J.: Assessment of dose propor tionality: report from the statisticians in the pharmaceuti cal industry/pharmacokenetics US joint working party. Drug Inf. J., 29: (1995). 4) Beal, S. and Sheiner, L.: The NONMEM System. The American Statistician, 34: (1980). 5) Boeckman, A. J., Sheiner, L. B. and Beal, S. L.: NON MEM users guide, Parts I-VIII; Division of Clinical Phar macology, University of California, San Francisco (1998). 6) Colburn, W.: Estimating the Accumulation of Drugs. J. Pharm. Sci., 72: (1983). 8) Diletti, E., Hauschke, D. and Steinijans, V. W.: Sample size determination for bioequivalence assessment by means of confidence intervals. Int. J. Clin. Pharmacol. Ther. Toxicol., 29: 1-8 (1991). 9) Elashoff, J. D.: nquery Advisor Version 3.0 User's Guide. Los Angeles, CA (1999). 10) Stagni, G., Shepherd, A. M. M., Liu, Y. and Gillespie, W.: New mathematical implementation of generalized phar macodynamic models : Method and clinical evaluation. J.

8 Pharmacokinet. Biopharm., 21: ). 11) Sheiner, L. B., Stanski, D. R. and Vozeh, S.: Simultaneous modelling of pharmacokinetics and pharmacodynamics: Application to d-tubocurarine. Clin. Pharmacol. Ther., 25: (1979). 12) Holford, N. H. G. and Sheiner, L. B.: Understanding the dose-effect relationship: clinical application of pharmacoki netic-pharmacodynamic models. Clin. Pharmacokinet., 6: (1981). 13) Fuseau, E. and Sheiner, L. B.: Simultaneous modeling of pharmacokinetics and pharnracodynamics with a non-para metric pharmacodynamic model. Clin. Pharmacol. Ther., 35: (1984). 14) Kato, R., Sotohata, I., Tuzuki, J., Inagaki, H., Tanahashi, T., Hayashi, H., Yokota, M., Ito, A., Noro, T., Shimomura, M., Ise, S. and Tomono, Y.: Population phar macokinetics and pharmacodynamics analysis after a sin gle intravenous administration of Flecainide acetate. Jpn. J. Clin. Pharmacol. Ther., 28: 1-14 (1997). 15) Jusko, W. J. and Ko, H. C.: Physiologic indirect response models characterize diverse types of pharmacodynamic effects. Clin. Pharmacol. Ther., 56: (1994). 16) Tomono, Y. and Yamato, C.: Influence of drug concentra tion on clearance of endogenous substance study of drug concentration-dependent kinetics using NONMEM. Jpn. J. TDM, 12: (1995). 17) Holford, N. H. and Peace, K. E.: Metodologic aspects of a population pharmacodyanmic model for cognitive effects in Alzheimer patients treated with tacrine. Proc Natl Acad Sci USA, 89: (1992). 18) Sheiner, L. B.: A new approach to the analysis of analgesic drug trials illustrated with bromfenac data. Clin. Phar macol. Ther., 56: (1994). 20) Karlson, M. O. and Sheiner, L. B.: The importance of modeling interoccasion variability in population phar macokinetic analyses. J. Pharmacokinet. Biopharm., 21: (1993). 21) Vozeh, S., Maitre, P. O. and Stanski, D. R.: Evaluation of population (NONMEM) pharmacokinetic parameter esti mations. J. Pharmacokinet. Biopharm., 18: (1990). 22) Ette, E. I.: Stability and performance of a population phar macokinetic model. J. Clin. Pharmacol., 37: (1997). 23) Koike, Y., Tomono, Y., Tanaka, H. and Mineshita, S.: A new approach to the drug evaluation: Population phar macokinetic and pharmacodynamic (PK/PD) analysis. Jpn. J. Clin. Pharmacol. Ther., 27: (1996).

Vol. 36, Special Issue, S 3 S 18 (2015) PK Phase I Introduction to Pharmacokinetic Analysis Focus on Phase I Study 1 2 Kazuro Ikawa 1 and Jun Tanaka 2

Vol. 36, Special Issue, S 3 S 18 (2015) PK Phase I Introduction to Pharmacokinetic Analysis Focus on Phase I Study 1 2 Kazuro Ikawa 1 and Jun Tanaka 2 1 2 1 Department of Clinical Pharmacotherapy, Hiroshima