Optimizing Individualized Dosage Regimens of Potentially Toxic Drugs

  • Roger W. Jelliffe
  • Alan Schumitzky
  • Robert Leary
  • Andreas Botnen
  • Ashutosh Gandhi
  • Pascal Maire
  • Xavier Barbaut
  • Nathalie Bleyzac
  • Irina Bondareva


The end product of drug development is the use of the drug in clinical therapy. When a drug has a narrow margin of therapeutic safety, we must steer its dosage between one that is too low, and likely to be ineffective on the one hand, or too high, and likely to be toxic, on the other. We must carefully plan and individualize the dosage for each patient, to achieve some desired target goal such as a serum concentration, or its profile over time. We must then observe the patient, and if needed, monitor serum concentrations at appropriate intervals. These intervals should be frequent enough so we can evaluate the patient when there are relatively small changes in the total amount of drug in the body between observations, so that if toxicity develops, we detect it in an early stage of its development so we can make the appropriate adjustment in dosage early, rather than later, after toxicity has become more severe and dangerous.


Serum Concentration Minimum Inhibitory Concentration Target Goal POSTANTIBIOTIC Effect Measured Serum Concentration 
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  1. 1.
    Cohen J: Make Your Medicine Safe. ISBN: 0–380–79075–0. Avon Books Inc., New York, 1998.Google Scholar
  2. 2.
    Evans W: General Principles of Applied Pharmacokinetics, Chapter 1, in Applied Pharmacokinetics: Principles of Therapeutic Drug Monitoring, ed. By Evans W, Schentag J, and Jusko W. Applied Therapeutics Inc., Vancouver B.C., 1992.Google Scholar
  3. 3.
    van Lent-Evers N, Mathot R, Geus W, van Hout B, and Vinks A: Impact of Goal-Oriented and Model-Based Clinical Pharmacokinetic Dosing of Aminoglycosides on Clinical Outcome: A Cost-Effectiveness Analysis. Therap. Drug Monit. 221: 63–73, 1999.CrossRefGoogle Scholar
  4. 4.
    Reuning R, Sams R, and Notari R: Role of Pharmacokinetics in Drug Dosage Adjustment. 1. Pharmacologic Effects, Kinetics, and Apparent Volume of Distribution of Digoxin. J. Clin. Pharmacol. 13: 127–141, 1973.Google Scholar
  5. 5.
    Jelliffe R, Schumitzky A, Van Guilder M, Liu M, Hu L, Maire P, Gomis P, Barbaut X, and Tahani B: Individualizing Drug Dosage Regimens: Roles of Population Pharmacokinetic and Dynamic Models, Bayesian Fitting, and Adaptive Control. Therap. Drug Monit., 15: 380–393,1993.CrossRefGoogle Scholar
  6. 6.
    Sheiner LB, Beal S, Rosenberg B, and Marathe V: et al.: Forecasting Individual Pharmacokinetics. Clin. Pharmacol. Ther., 31: 294–305, 1979.Google Scholar
  7. 7.
    Jelliffe R, Iglesias T, Hurst A, Foo K, and Rodriguez J: Individualizing Gentamicin Dosage Regimens: A Comparative Review of Selected Models, Data Fitting Methods, and Monitoring Strategies. Clin. Pharmacokinet. 21: 461–478, 1991.CrossRefGoogle Scholar
  8. 8.
    Nelder JA and Mead R: A Simplex Method for Function Minimization. Computer Journal 7: 308–313,1965.CrossRefGoogle Scholar
  9. 9.
    Caceci MS and Cacheris WP: Fitting Curves to Data: The Simplex Algorithm is the Answer. BYTE Magazine, May 1984, pp. 340–362.Google Scholar
  10. 10.
    De Groot MH: Probability and Statistics, Second Edition, Addison - Wesley Publishing Co., Reading, MA, 1989, pp. 422–423.Google Scholar
  11. 11.
    Sawchuk R and Zaske D: Pharmacokinetics of Dosing Regimens which Utilize Multiple Intravenous Infusions: Gentamicin in Burn Patients. J. Pharmacokin. Biopharm 4: 183–195, 1976.CrossRefGoogle Scholar
  12. 12.
    Jelliffe R, Schumitzky A, Bayard D, Milman M, Van Guilder M, Wang X, Jiang F, Barbaut X, and MaireP:Model-Based, Goal-Oriented, Individualised Drug Therapy: Linkage of Population Modelling, New “Multiple Model” Dosage Design, Bayesian Feedback, and Individualized Target Goals. Clin. Pharmacokinet. 34: 57–77, 1998.CrossRefGoogle Scholar
  13. 13.
    Mallet A: A Maximum Likelihood Estimation Method for Random Coefficient Regression Models. Biometrika. 73: 645–656, 1986.CrossRefGoogle Scholar
  14. 14.
    Schumitzky A: Nonparametric EM Algorithms for Estimating Prior Distributions. App. Math. and Computation. 45: 143–157, 1991.CrossRefGoogle Scholar
  15. 15.
    Jelliffe R: Estimation of Creatinine Clearance in Patients with Unstable Renal Function, without a Urine Specimen. Am. J. Nephrol. 22: 320–324, 2002.PubMedCrossRefGoogle Scholar
  16. 16.
    Maire P, Jelliffe R, Dumarest C, Roux D, Breant V, Charpiat B, Vermeulen E, Brazier J, and Courpron P: Controle Adaptatif Optimal des Posologies: Experience des Aminosides en Geriatrie. in Information et Medicaments. Comptes Rendus du Colloque AIM-IF et IRT, Paris, December 1989, ed. by Venot A and Degoulet P, Volume 2 of Informatique et Sante, directed by Degoulet P, Springer Verlag, Paris, 154–169, 1989.Google Scholar
  17. 17.
    Hurst A, Yoshinaga M, Mitani G, Foo K, Jelliffe R, and Harrison E.: Application of a Bayesian Method to Monitor and Adjust Vancomycin Dosage Regimens. Antimicrob. Agents Chemother., 34; 1165–1171, 1990.CrossRefGoogle Scholar
  18. 18.
    Jelliffe R, Schumitzky A, Van Guilder M, and Jiang F: User Manual for Version 10.7 of the USC*PACK Collection of PC Programs. December 1, 1995. Laboratory of Applied Pharmacokinetics, University of Southern California School of Medicine, Los Angeles, CA.Google Scholar
  19. 19.
    Jelliffe R: Clinical Applications of Pharmacokinetics and Control Theory: Planning, Monitoring, and Adjusting Dosage Regimens of Aminoglycosides, Lidocaine, Digitoxin, and Digoxin. In Maronde R, ed: Topics in Clinical Pharmacology and Therapeutics, Spmger-Verlag, New York, 1986, pp. 26–82.CrossRefGoogle Scholar
  20. 20.
    Rodman J, Jelliffe R, Kolb E, Tuey D, de Guzman M, Wagers P, and Haywood L: Clinical Studies with Computer-Assisted Initial Lidocaine Therapy. Arch. Int. Med. 144: 703–709, 1984.CrossRefGoogle Scholar
  21. 21.
    Bleyzac N, Souillet G, Magron P, Janoly A, Martin P, Bertrand Y, Galambrun C, Dai Q, Maire P, Jelliffe R, and Aulagner G: Improved Clinical Outcome of Paediatric Bone Marrow Recipients using a Test Dose and Bayesian Pharmacokinetic Individualization of Busulfan Dosage Regimens. Bone Marrow Transplantation 28: 743–751, 2001.PubMedCrossRefGoogle Scholar
  22. 22.
    Marcus Haug, Pharm.D., and Peter Slugg, M.D., Personal communication.Google Scholar
  23. 23.
    Maire P, Barbaut X, Vergnaud JM, El Brouzi M, Confesson M, Pivot C, Chuzeville M, Ivanoff N, Brazier J, and Jelliffe R: Computation of Drug Concentrations in Endocardial Vegetations in Patients during Antibiotic Therapy. Int. J. Bio-Med. Comput., 36: 77–85, 1994.CrossRefGoogle Scholar
  24. 24.
    Bayer A, Crowell D, Yih J, Bradley D, and Norman D: Comparative Pharmacokinetics and Pharmacodynamics of Amikacin and Ceftazidime in Tricuspid and Aortic Vegetations in ExperimentalPseudomonasEndocarditis. J. Infect. Dis., 158: 355–359, 1988.PubMedCrossRefGoogle Scholar
  25. 25.
    Bayer A, Crowell D, Nast C, Norman D, and Borelli R: Intravegetation Antimicrobial Distribution in Aortic Endocarditis Analyzed by Computer-Generated Model: Implications for Treatment. Chest, 97: 611–617, 1990.PubMedCrossRefGoogle Scholar
  26. 26.
    Zhi J, Nightingale CH, and Quintiliani R: Microbial Pharmacodynamics of Pipericillin in Neutropenic Mice of Systemic Infection due to Pseudomonas Aeruginosa. J Phamracokin. Biopharm. 4: 355–375, 1988.Google Scholar
  27. 27.
    Schumitzky A: personal communication.Google Scholar
  28. 28.
    Bouvier D’Ivoire M, and Maire P: Dosage Regimens of Antibacterials: Implications of a Pharmacokinetic/Pharmacodynamic Model. Drug Invest. 11: 229–239, 1996.CrossRefGoogle Scholar
  29. 29.
    Craig W, and Ebert S: Killing and Regrowth of Bacteria in Vitro: a Review. Scand J Infect Dis Suppl 74: 63–70, 1991.Google Scholar
  30. 30.
    Mouton J, Vinks AATMM, and Punt N: Pharmacokinetic-Pharrnacodynamic Modeling of Ceftazidime during Continuous and Intermittent Infusion. Chapter 6, pp 95–110, in the Ph.D. Thesis of Vinks AATMM: Strategies for Pharmacokinetic Optimization of Continuous Infusion Therapy of Ceftazidime and Aztreonam in Patients with Cystic Fibrosis, November, 1996.Google Scholar
  31. 31.
    Bertsekas D: Dynamic Programming: deterministic and stolchastic modes. Englewood Cliffs (NJ): Prentice-Hall, pp. 144–146, 1987.Google Scholar
  32. 32.
    Jelliffe R, Bayard D, Milman M, Van Guilder M, and Schumitzky A: Achieving Target Goals most Precisely using Nonparametric Compartmental Models and “Multiple Model” Design of Dosage Regimens. Therap. Drug Monit. 22: 346–353, 2000.CrossRefGoogle Scholar
  33. 33.
    Jelliffe R, Bayard D, Schumitzky A, Milman M, Jiang F, Leonov S, Gandhi A, and Botnen A: A New Clinical Software Package for Multiple Model (MM) Design of Drug Dosage Regimens for Planning, Monitoring, and Adjusting Optimally Individualized Drug Therapy for Patients. Presented at the 4thInternational Meeting on Mathematical Modeling, Technical University of Vienna, Vienna, Austria, February 6, 2003.Google Scholar
  34. 34.
    Jelliffe R: A Mathematical Analysis of Digitalis Kinetics in Patients with Normal and Reduced Renal Function. Math. Biosci. 1: 305–325, 1967.CrossRefGoogle Scholar
  35. 35.
    Leary R, Jelliffe R, Schumitzky A, and Van Guilder M: A Unified Parametric/Nonparametric Approach to Population PK/PD Modeling. Presented at the Annual Meeting of the Population Approach Group in Europe, Paris, France, June 6–7, 2002.Google Scholar
  36. 36.
    Bayard D and Jelliffe R: Bayesian Estimation of Posterior Densities for Pharmacokinetic Models having Changing Parameter Values. Presented at the Annual Meetings of the Society for Computer Simulation, San Diego CA, January 23–27, 2000. Published in the Proceedings, Health Sciences Simulation, pp. 75–83.Google Scholar
  37. 37.
    D’Argenio D: Optimal Sampling Times for Pharmacokinetic Experiments. J. Pharmacokin. Biopharm., 9: 739–756, 1981.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Roger W. Jelliffe
    • 1
  • Alan Schumitzky
    • 1
  • Robert Leary
    • 2
  • Andreas Botnen
    • 3
  • Ashutosh Gandhi
    • 1
  • Pascal Maire
    • 4
  • Xavier Barbaut
    • 5
  • Nathalie Bleyzac
    • 4
  • Irina Bondareva
    • 6
  1. 1.Laboratory of Applied PharmacokineticsUniversity of Southern California School of MedicineLos AngelesUSA
  2. 2.San Diego Supercomputer CenterUniversity of CaliforniaSan DiegoUSA
  3. 3.Center for BioinformaticsUniversity of OsloNorway
  4. 4.Hospices Civils de LyonFrance
  5. 5.Hospice de BeauneFrance
  6. 6.lnstitute of Physical and Chemical MedicineMoscowRussia

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