Clinical Pharmacokinetics

, Volume 37, Issue 1, pp 1–16 | Cite as

Achieving an Optimal Outcome in the Treatment of Infections

The Role of Clinical Pharmacokinetics and Pharmacodynamics of Antimicrobials
  • Ronald C. Li
  • Min Zhu
  • Jerome J. Schentag
Review Articles Drug Disposition


Over the past few decades, the importance of applying pharmacokinetic principles to the design of drug regimens has been increasingly recognised by clinicians. From the perspective of antimicrobial chemotherapy, an improvement in clinical outcome and/or a reduction in toxicity are of primary interest. Before application of these pharmacokinetic theories can be effective, the interrelationships between antimicrobial, pathogen and host factors must be clearly defined. Information regarding the pharmacokinetics of the antimicrobial and the quantification of pathogen susceptibility is required.

Even though susceptibility end-points such as minimum inhibitory concentration (MIC) and minimum bactericidal concentration are widely employed, they do not provide any information on dynamic changes of bacterial densities. In this regard, time-kill studies can provide more basic knowledge of the complex bacterial responses to the antimicrobial. Better prediction of these responses can be afforded by the use of mathematical models.

More recently, various surrogate end-points employing a combination of suitable pharmacokinetic parameters and susceptibility data, for example the ratio of peak concentration to MIC, the area under the concentration-time curve above the MIC (AUC>mic ), the time above the MIC, or the area under the inhibitory curve (AUIC), have been suggested for better prediction of the activity of different classes of antimicrobials. To allow more extensive investigations of the contribution of pharmacokinetics to the pharmacodynamics of antimicrobials, various in vitro kinetic models have been developed. However, certain limitations exist, and it is necessary to avoid over-interpretation of the data generated by these models. Two important microbial dynamic responses, postantibiotic effect and resistance selection, must be further explored before the full impact of pharmacokinetics on antimicrobial chemotherapy can be depicted.

The present paper aims at discussing all the relevant factors and provides some pertinent information on the use of pharmacokinetic-pharmacodynamic principles in antimicrobial therapy.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Schentag JJ, Ballow CH, Paladino JA, et al. Dual individualization with antibiotics: integrated antibiotic management strategies for use in hospitals. In: Evans WE, Schentag JJ, Jusko WJ, editors. Applied pharmacokinetics: principles of therapeutic drug monitoring. 3rd ed. Vancouver: Applied Therapeutics Inc., 1992: 17/1–20.Google Scholar
  2. 2.
    Federspil P, Schatzle W, Tiesler E. Pharmacokinetics and ototoxicity of gentamicin, tobramycin, and amikacin. J Infect Dis 1976; 134 Suppl.: S200–5.PubMedCrossRefGoogle Scholar
  3. 3.
    Tablan OC, Reyes MP, Rintelmann WF, et al. Renal and auditory toxicity of high dose, prolonged therapy with gentamicin and tobramycin in Pseudomonas endocarditis. J Infect Dis 1984; 149(2): 257–63.PubMedCrossRefGoogle Scholar
  4. 4.
    Dahlgren JG, Anderson ET, Hewitt WL. Gentamicin blood levels: a guide to nephrotoxicity. Antimicrob Agents Chemother 1975; 8(1): 58–62.PubMedCrossRefGoogle Scholar
  5. 5.
    Smith CR, Lipsky JJ, Lietman PS. Relationship between aminoglycoside-induced nephrotoxicity and auditory toxicity. Antimicrob Agents Chemother 1979; 15(6): 780–2.PubMedCrossRefGoogle Scholar
  6. 6.
    Craig WA. Once daily versus multiple-daily dosing of aminoglycosides. J Chemother 1995; 7 Suppl. 2: 47–52.PubMedGoogle Scholar
  7. 7.
    National Committee for Clinical Laboratory Standards. Methods for dilution antimicrobial susceptibility tests for bacteria that grow aerobically. 3rd ed. Approved standard. NCCLS document M7-A3. Villanova, PA: National Committee for Clinical Laboratory Standards, 1993.Google Scholar
  8. 8.
    Garrett ER. Kinetics of antimicrobial action. Scand J Infect Dis 1978; 14 Suppl.: 54–85.Google Scholar
  9. 9.
    Garrett ER, Heman-Ackah SM. Microbial kinetics and dependencies of individual and combined antibiotic inhibitors of protein synthesis. Antimicrob Agents Chemother 1973; 4: 574–84.PubMedCrossRefGoogle Scholar
  10. 10.
    Garrett ER, Wright OK. Quantitative adherence of sulfonamide action on microbial growth to a receptor-site model. J Pharm Sci 1967; 56: 1576–85.PubMedCrossRefGoogle Scholar
  11. 11.
    Li RC, Nix DE, Schentag JJ. Pharmacodynamic modeling of bacterial kinetics: β-lactam antibiotics against Escherichia coli. J Pharm Sci 1994; 83: 970–5.PubMedCrossRefGoogle Scholar
  12. 12.
    Li RC. Simultaneous pharmacodynamic analysis of the lag and bactericidal phases exhibited by β-lactams against Escherichia coli. Antimicrob Agents Chemother 1996; 40: 2306–10.PubMedGoogle Scholar
  13. 13.
    Ma HUM, Chiu FCK, Li RC. Mechanistic investigation of the reduction in antimicrobial activity of ciprofloxacin by metal cations. Pharm Res 1997; 14: 366–70.PubMedCrossRefGoogle Scholar
  14. 14.
    Hall MJ, Middleton RF, Westmacott D. The fractional inhibitory concentration (FIC) index as a measure of synergy. J Antimicrob Chemother 1983; 11: 427–33.PubMedCrossRefGoogle Scholar
  15. 15.
    Li RC, Schentag JJ, Nix DE. The FME method: a new way to characterize the effect of antibiotic combinations and other nonlinear pharmacologie responses. Antimicrob Agents Chemother 1993; 37: 523–31.PubMedCrossRefGoogle Scholar
  16. 16.
    Li RC, Nix DE, Schentag JJ. Performance of the fractional maximal effect method: comparative interaction studies of ciprofloxacin and protein synthesis inhibitors. J Chemother 1996; 8: 25–32.PubMedGoogle Scholar
  17. 17.
    Hyatt JM, Nix DE, Stratton CW, et al. In vitro pharmacodynamics of piperacillin, piperacillin-tazobactam, and ciprofloxacin alone and in combination against Staphylococcus aureus, Klebsiella pneumoniae, Enterobacter cloacae, and Pseudomonas aeruginosa. Antimicrob Agents Chemother 1995; 39: 1711–6.PubMedCrossRefGoogle Scholar
  18. 18.
    Nix DE, Goodwin SD, Peloquin CA, et al. Antibiotic tissue penetration and its relevance: impact of tissue penetration on infection response. Antimicrob Agents Chemother 1991; 35(10): 1953–9.PubMedCrossRefGoogle Scholar
  19. 19.
    Kunin CM, Craig WA. Significance of serum protein and tissue binding of antimicrobial agents. Annu Rev Med 1976; 27: 287–300.PubMedCrossRefGoogle Scholar
  20. 20.
    Peterson LR, Moody JA, Fasching CE, et al. Influence of protein binding on therapeutic efficacy of cefoperazone. Antimicrob Agents Chemother 1989; 33: 566–8.PubMedCrossRefGoogle Scholar
  21. 21.
    Li RC, Cheng NC, Yung L. Impact of protein binding on antimicrobial activity: application of the gradient plate technique on ceftriaxone. 1997 Annual Meeting of the American Association of Pharmaceutical Scientists: 1997 Nov 2–6: Boston. Pharm Res 1997; 14(11): S71.Google Scholar
  22. 22.
    Nicolau DP, Quintiliani R, Nightingale CH. Antibiotic kinetics and dynamics for the clinican. Med Clin North Am 1995; 79(3): 477–95.PubMedGoogle Scholar
  23. 23.
    Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis 1998; 26: 1–12.PubMedCrossRefGoogle Scholar
  24. 24.
    Hyatt JM, McKinnon PS, Zimmer GS, et al. The importance of pharmacokinetic-pharmacodynamic surrogate markers to outcome: focus on antibacterial agents. Clin Pharmacokinet 1995; 28(2): 143–60.PubMedCrossRefGoogle Scholar
  25. 25.
    Moore RD, Lietman PS, Smith CR. Clinical response to aminoglycoside therapy: importance of the ratio of peak concentration to minimal inhibitory concentration. J Infect Dis 1987; 155(1): 93–9.PubMedCrossRefGoogle Scholar
  26. 26.
    Lacy MK, Nicolau DP, Nightingale CH, et al. The pharmacodynamics of aminoglycosides. Clin Infect Dis 1998; 27: 23–7.PubMedCrossRefGoogle Scholar
  27. 27.
    Forrest A, Ballow CH, Nix DE, et al. Development of a population pharmacokinetic model and optimal sampling strategies for intravenous ciprofloxacin. Antimicrob Agents Chemother 1993; 37(5): 1065–72.PubMedCrossRefGoogle Scholar
  28. 28.
    Forrest A, Nix DE, Ballow CH, et al. Pharmacodynamics of intravenous ciprofloxacin in seriously ill patients. Antimicrob Agents Chemother 1993; 1073–81.Google Scholar
  29. 29.
    Schentag JJ, Nix DE, Adelman MH. Mathematical examination of dual individualization principles (I): relationships between AUC above MIC and area under the inhibitory curve for cefmenoxime, ciprofloxacin, and tobramycin. Drug Intell Clin Pharm 1991; 25(10): 1050–7.Google Scholar
  30. 30.
    Goss TF, Forrest A, Nix DE, et al. Mathematical examination of dual individualization principles (II): the rate of bacterial eradication at the same area under the inhibitory curve is more rapid for ciprofloxacin than for cefmenoxime. Ann Pharmacother 1994; 28(7–8): 863–8.PubMedGoogle Scholar
  31. 31.
    Luzier A, Goss TF, Cumbo TJ, et al. Mathematical examination of dual individualization principles (III): development of a scoring system for pneumonia staging and quantitation of response to antibiotics: results in cefmenoxime-treated patients. Ann Pharmacother 1992; 26(11): 1358–65.PubMedGoogle Scholar
  32. 32.
    Nix DE, Sands MF, Peloguin CA, et al. Dual individualization of intravenous ciprofloxacin in patients with nosocomial lower respiratory tract infection. Am J Med 1987; 84(4A): 352–6.Google Scholar
  33. 33.
    Hamano S, Tsuji A, Asano T, et al. Kinetic analysis and characterization of the bacterial regrowth after treatment of Escherichia coli with β-lactam antibiotics. J Pharm Sci 1984; 73(10): 1422–7.PubMedCrossRefGoogle Scholar
  34. 34.
    Tsuji A, Hamano S. Asano T, et al. Microbial kinetics of β-lactam antibiotics against Escherichia coli. J Pharm Sci 1984; 73(10): 1418–22.PubMedCrossRefGoogle Scholar
  35. 35.
    Davies J. Inactivation of antibiotics and the dissemination of resistance genes. Science 1994; 264(5157): 375–82.PubMedCrossRefGoogle Scholar
  36. 36.
    Nikaido H. Prevention of drug access to bacterial targets: permeability barriers and active efflux. Science 1994; 264(5157): 382–8.PubMedCrossRefGoogle Scholar
  37. 37.
    Yang YJ, Livermore DM, Williams RJ. Chromosomal β-lactamase expression and antibiotic resistance in Enterobacter cloacae. J Med Microbiol 1988; 25(3): 227–33.PubMedCrossRefGoogle Scholar
  38. 38.
    Arthur M, Brisson-Noel A, Courvalin P. Origin and evolution of genes specifying resistance to macrolide, lincosamide and streptogramin antibiotics: data and hypotheses. J Antimicrob Chemother 1987; 20(6): 783–802.PubMedCrossRefGoogle Scholar
  39. 39.
    Mattie H. A mathematical description of short-term effects of β-lactam antibiotics on bacterial growth in vitro. Curr Microbiol 1978; 1: 106–9.CrossRefGoogle Scholar
  40. 40.
    Guerillot F, Carret G, Flandrois JR. Mathematical model for comparison of time-killing curves. Antimicrob Agents Chemother 1993; 37: 1685–9.PubMedCrossRefGoogle Scholar
  41. 41.
    Grasso S, Meinardi G, Carneri I, et al. New in vitro model to study the effect of antibiotic concentration and rate of elimination on antibacterial activity. Antimicrob Agents Chemother 1978; 13: 570–6.PubMedCrossRefGoogle Scholar
  42. 42.
    Nishida M, Murakawa T, Kamimura T, et al. Bactericidal activity of cephalosporins in an in vitro model simulating serum levels. Antimicrob Agents Chemother 1978; 6: 6–12.CrossRefGoogle Scholar
  43. 43.
    Bergan T, Carlsen IB, Fuglesang JE. An in vitro model for monitoring bacterial responses to antibiotic agents under simulated in vivo conditions. Infection 1980; 8: S96-S102.CrossRefGoogle Scholar
  44. 44.
    Grasso S. Historical review of in-vitro models. J Antimicrob Chemother 1985; 15 Suppl.: 99–102.PubMedGoogle Scholar
  45. 45.
    Reeves DS. Advantages and disadvantages of an in vitro model with two compartments connected by a dialyser: results of experiments with ciprofloxacin. J Antimicrob Chemother 1985; 15 Suppl.: 159–67.PubMedCrossRefGoogle Scholar
  46. 46.
    Blaser J, Stone BB, Zinner SH. Two compartment kinetic model with multiple artificial capillary units. J Antimicrob Chemother 1985; 15 Suppl.: 131–7.PubMedCrossRefGoogle Scholar
  47. 47.
    Sous H, Hirsch I. Bactericidal efficacy of cefmenoxime in an in vitro model system simulating tissue kinetics. 13th International Congress of Chemotherapy, Vienna, Austria. Contribution SE 8.3/1–2.Google Scholar
  48. 48.
    Blaser J. In-vitro model for simultaneous simulation of the serum kinetics of two drugs with different half-lives. J Antimicrob Chemother 1985; 15 Suppl.: 125–30.PubMedGoogle Scholar
  49. 49.
    Shah PM. Simultaneous simulation of two different concentration time curves in vitro. J Antimicrob Chemother 1985; 15 Suppl.: 261–4.PubMedGoogle Scholar
  50. 50.
    Zabinski RA, Vance-Bryan K, Krinke AJ, et al. Evaluation of activity of temafloxacin against Bacteroides fragilis by an in vitro pharmacodynamic system. Antimicrob Agents Chemother 1993; 37: 2454–8.PubMedCrossRefGoogle Scholar
  51. 51.
    Garrison MW, Vance-Bryan K, Larson TA, et al. Assessment of effects of protein binding on daptomycin and vancomycin killing of Staphylococcus aureus by using an in vitro pharmacodynamic model. Antimicrob Agents Chemother 1990; 34: 1925–31.PubMedCrossRefGoogle Scholar
  52. 52.
    Dalhoff A. Differences between bacteria grown in vitro and in vivo. J Antimicrob Chemother 1985; 15 Suppl.: 175–95.PubMedGoogle Scholar
  53. 53.
    Seeberg AH, Wiedeman B. Application of in vitro models: development of resistance. J Antimicrob Chemother 1985; 15 Suppl.: 241–9.PubMedGoogle Scholar
  54. 54.
    Gilbert P. The theory and relevance of continuous culture. J Antimicrob Chemother 1985; 15 Suppl.: 1–6.PubMedCrossRefGoogle Scholar
  55. 55.
    Lorian V, Satta G. Differences between in vitro and in vivo studies [letter to the editor]. Antimicrob Agents Chemother 1988; 32: 1600–1.PubMedCrossRefGoogle Scholar
  56. 56.
    Haag R, Lexa P, Werkhauser I. Artifacts in dilution pharmacokinetic models caused by adherent bacteria. Antimicrob Agents Chemother 1986; 29: 765–8.PubMedCrossRefGoogle Scholar
  57. 57.
    Nolting A, Dalla Costa T, Rand KH, et al. Pharmacokinetic-pharmacodynamic modeling of the antibiotic effect of pipericillin in vitro. Pharm Res 1996; 13(1): 91–6.PubMedCrossRefGoogle Scholar
  58. 58.
    Madaras-Kelly KJ, Ostergaard BE, Havde LB, et al. Twenty-four-hour area under the concentration-time curve/MIC ratio as a generic predictor of fluoroquinolone antimicrobial effect by using three strains of Pseudomonas aeruginosa and an in vitro pharmacodynamic model. Antimicrob Agents Chemother 1996; 40(3): 627–32.PubMedGoogle Scholar
  59. 59.
    Chavanet P, Dalle F, Delisle P, et al. Experimental efficacy of combined ceftriaxone and amoxycillin on penicillin-resistant and broad-spectrum cephalosporin-resistant Streptococcus pneumoniae infection. J Antimicrob Chemother 1998; 41: 237–46.PubMedCrossRefGoogle Scholar
  60. 60.
    Zhi JG, Nightingale CH, Quintiliani R. Microbial pharmacodynamics of piperacillin in neutropenic mice of systematic infection due to Pseudomonas aeruginosa. J Pharmacokinet Biopharm 1988; 16: 355–75.PubMedGoogle Scholar
  61. 61.
    Craig WA, Redington J, Ebert SC. Pharmacodynamics of amikacin in vitro and in mouse thigh and lung infections. J Antimicrob Chemother 1991; 27 Suppl. C: 29–40.PubMedCrossRefGoogle Scholar
  62. 62.
    Craig WA. Antimicrobial resistance issues of the future. Diagn Microbiol Infect Dis 1996; 25: 213–7.PubMedCrossRefGoogle Scholar
  63. 63.
    Zhi JG, Nightingale CH, Quintiliani R. Impact of dosage regimens on the efficacy of piperacillin against Pseudomonas aeruginosa in neutropenic mice. J Pharm Sci 1988; 77: 991–2.PubMedCrossRefGoogle Scholar
  64. 64.
    Vogelman B, Gudmundsson S, Leggett J, et al. Correlation of antimicrobial pharmacokinetic parameters with therapeutic efficacy in an animal model. J Infect Dis 1988; 158(4): 831–47.PubMedCrossRefGoogle Scholar
  65. 65.
    Craig WA, Gudmundsson S. The postantibiotic effect. In: Lorian V, editor. Antibiotics in laboratory medicine. 3rd ed. Baltimore: William & Wilkins Co., 1991; 403–31.Google Scholar
  66. 66.
    Zhanel GC, Hoban DJ, Harding GKM. The postantibiotic effect: a review of in vitro and in vivo data. DICP Ann Pharmacother 1991; 25: 153–63.Google Scholar
  67. 67.
    Li RC, Lee SW, Kong CH. Correlation between bactericidal activity and postantibiotic effect for five antibiotics with different mechanisms of action. J Antimicrob Chemother 1997; 40: 39–45.PubMedCrossRefGoogle Scholar
  68. 68.
    Li RC, Zhu ZY, Lee SW, et al. Antibiotic exposure and its relationship to postantibiotic effect and bactericidal activity: constant versus exponentially decreasing tobramycin levels against Pseudomonas aeruginosa. Antimicrob Agents Chemother 1997; 41: 1808–11.PubMedGoogle Scholar
  69. 69.
    Zhu ZY, Li RC. Impact of pharmacokinetics on the postantibiotic effect exhibited by Pseudomonas aeruginosa following tobramycin exposure: application of an in vitro model. J Antimicrob Chemother 1998; 42: 61–5.PubMedCrossRefGoogle Scholar
  70. 70.
    Craig WA. Post-antibiotic effects in experimental infection models: relationship to in-vitro phenomena and to treatment of infections in man. J Antimicrob Chemother 1993; 31 Suppl. D: 149–58.PubMedGoogle Scholar
  71. 71.
    Vogelman B, Gudmundsson S, Turnidge J, et al. In vivo postantibiotic effect in a thigh infection in neutropenic mice. J Infect Dis 1988; 157: 287–98.PubMedCrossRefGoogle Scholar
  72. 72.
    Prins JM, Buller HR, Kuijper EJ, et al. Once versus thrice daily gentamicin in patient with serious infections. Lancet 1993; 341: 335–9.PubMedCrossRefGoogle Scholar
  73. 73.
    Firsov AA, Vostrov SN, Shevchenko AA, et al. A new approach to in vitro comparisons of antibiotics in dynamic models: equivalent area under the curve/MIC breakpoints and equi-efficient doses of trovafloxacin and ciprofloxacin against bacteria of similar susceptibilities. Antimicrob Agents Chemother 1998; 42: 2841–7.PubMedGoogle Scholar
  74. 74.
    Schentag JJ, Nix DE, Forrest A, et al. AUIC: the universal parameter within the constraint of a reasonable dosing interval. Ann Pharmacother 1996; 30(9): 1029–31.PubMedGoogle Scholar
  75. 75.
    McGowan Jr JE. Antimicrobial resistance in hospital organisms and its relation to antibiotic use. Rev Infect Dis 1983; 5: 1033–48.PubMedCrossRefGoogle Scholar
  76. 76.
    Gaynes RP, Culver DH, Horan TC, et al. Trends in methicillin-resistant Staphylococcus aureus in United States hospitals. Infect Dis Clin Pract 1992; 2: 452–5.CrossRefGoogle Scholar
  77. 77.
    Chan WC, Li RC, Ling JM, et al. Markly different rates and resistance profiles exhibited by seven commonly used and newer β-lactams on the selection of resistant variants of Enterobacter cloacae. J Antimicrob Chemother 1999; 43: 55–60.PubMedCrossRefGoogle Scholar
  78. 78.
    Fung-Tomc JC, Gradelski E, Huczko E, et al. Differences in the resistant variants of Entembacter cloacae selected by extended-spectrum cephalosporins. Antimicrob Agents Chemother 1996; 40: 1289–93.PubMedGoogle Scholar
  79. 79.
    Stapleton P, Shannon K, Phillips I. The ability of β-lactam antibiotics to select mutants with depressed β-lactamase synthesis from Citrobacter freundii. J Antimicrob Chemother 1995; 36: 483–96.PubMedCrossRefGoogle Scholar
  80. 80.
    Wiedemann B, Atkinson B. A. Susceptibility to antibiotics: species incidence and trends. In: Lorian V, editor. Antibiotics in laboratory medicine. 3rd ed. Baltimore: William & Wilkins Co., 1991; 962–1062.Google Scholar
  81. 81.
    Thomas JK, Forrest A, Bhavnani SM, et al. Pharmacodynamic evaluation of factors associated with the development of bacterial resistance in acutely ill patients during therapy. Antimicrob Agents Chemother 1998; 42(3): 521–7.PubMedGoogle Scholar
  82. 82.
    Schentag JJ, Birmingham MC, Paladino JA, et al. In nosocomial pneumonia, optimizing antibiotics other than aminoglycosides is a more important determinant of successful clinical outcome, and a better means of avoiding resistance. Semin Respir Infect 1997; 12(4): 278–93.PubMedGoogle Scholar

Copyright information

© Adis International Limited 1999

Authors and Affiliations

  1. 1.Department of Pharmacy, Faculty of MedicineThe Chinese University of Hong KongShatinHong Kong
  2. 2.Pharmacokinetic/Pharmacodynamic SciencesGenetics InstituteAndoverUSA
  3. 3.Department of Pharmaceutics, School of PharmacyState University of New York at BuffaloBuffaloUSA
  4. 4.Clinical Pharmacokinetics LaboratoryMillard Fillmore Health SystemBuffaloUSA

Personalised recommendations