PHARMACOKINETIC/PHARMACODYNAMIC MODEL OF ANTIBIOTIC THERAPY: CLINICAL USAGE
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Keywords

pharmacokinetics, pharmacodynamics, concentration-dependent antibacterial activity, time-dependent antibacterial activity

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Khaitovych, M. (2017). PHARMACOKINETIC/PHARMACODYNAMIC MODEL OF ANTIBIOTIC THERAPY: CLINICAL USAGE. Medical Science of Ukraine (MSU), 12(3-4), 114-121. Retrieved from https://msu-journal.com/index.php/journal/article/view/99

Abstract

Resume. Nowadays administration of antibacterial drugs requires appropriate knowledge of clinical pharmacology and clinical microbiology.

The «gold standard» in study of antibiotics’ activity is determination of minimal inhibitory concentration (MIC).

It was emphasized 3 groups of antibacterial drugs according to pharmacokinetic / pharmacodynamic (PC/PD) model, which effectiveness depend on concentration of antibiotic in blood; time of exposition; total exposition, which reflects area under the curve.

To the first group belong drugs, which have concentration-dependent bactericidal action (Cmax>МIC) and characterizes long-term postantibiotic effect (PAE) (aminoglycosides, metronidazole, ketolides etc.). For instance, in case of administration of gentamycin ratio Cmax/МIC 8:1 against gram-negative microorganism 1 time per day allow to obtain positive result and avoid adverse reactions.

To the second group relate beta-lactam antibiotics, for which are indicative time-dependent (T>MIC) bactericidal action in case of minimal PAE (except carbapenems). More frequent administration prolongs time (optimally -40-50% of dosage interval duration), when concentration become higher than MIC. Furthermore, prolonged infusions are used (up to 3 hours).

To the third group of antibiotics of PC/PD model respectively refer bacteriostatic drugs (azithromycin, clindamycin, tetracycline, tigecycline, linezolide etc.) as well as vancomycin and fluoroquinolones. For obtainment of clinical results in most of antibiotics of this group the ratio 24AUC/MIC must be 25-30 for gram-positive and 100-125 for gram-negative microorganisms.

Conclusion. So, the usage of PC/PD model offer the ability to manage of antibiotic transformation in the patient organism for the development of maximum possible effective and safety treatment, preventing antibiotic resistance.

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References

1. Gilbert D.N., Mollering S.R., Eliopulos D.M., Send A.M. Stenfordskiy spravochnik: antimikrobnaya terapiya // M.: EKSMO, 2009. 288 p. Mode of access: www.dovidnyk.org/dir/22/121.
2. Savel'yev V.S., Gel'fand B.R., Yakovlev S.V. [et al.]. Rossiyskiye Natsional'nyye Rekomendatsii: Strategiya i taktika primeneneiya antimikrobnykh sredstv v lechebnykh uchrezhdeniyakh Rossii // M.: Kompaniya BORGES, 2012. 92 p. Mode of access: www.antimicrob.net/upload/files/final_strategy.pdf.
3. Cherniy V.I., Kolesnikov A.N., Kuznetsova I.V. Farmakodinamicheskiye aspekty antibakterial'noy terapii // Novyny medytsyny ta farmatsii. 2009. Mode of access: www.mif-ua.com/archive/article/7843.
4. Albur M.S., Noel A., Bowker K., MacGowan A. The combination of colistin and fosfomycin is synergistic against NDM-1-producing Enterobacteriaceae in vitro pharmacokinetic/pharmacodynamic model experiments // Int. J. Antimicrob Agents. 2015. Vol. 46, Nо. 5. P. 560-567. Access mode: www.ncbi.nlm.nih.gov/pubmed/26387065.
5. Antibiotic guidelines 2015-2016 Treatment Recommendations For Adult Inpatients // Access mode: www.hopkinsmedicine.org/amp/guidelines/ antibiotic_guidelines.pdf.
6. Bellmann R. Pharmacokinetic and pharmacodynamic aspects in antibiotic treatment // Med. Klin. Intensiv. med Notfmed. 2014. Vol. 109, Nо3. P. 162-166. Access mode: http://europepmc.org/abstract/med/24643839.
7. Cieplik F., Tabenski L., Buchalla W., Maisch T. Antimicrobial photodynamic therapy for inactivation of biofilms formed by oral key pathogens // Frontiers in microbiology. 2014. Vol. 5. P. 1-171. Access mode: www.ncbi.nlm.nih.gov/pmc/articles/PMC4130309
8. Edgar R., Friedman N., Molshanski-Mor S., Qimron U. Reversing bacterial resistance to antibiotics by phage-mediated delivery of dominant sensitive genes // Appl. Microbiol. 2012. Vol.78, Nо. 3. P. 744-751. Access mode: http://aem.asm.org/content/early/2011/11/18/AEM.05741-11
9. Finberg R.W., Guharoy R. Clinical Use of Anti-infective Agents: A Guide on How to Prescribe Drugs Used to Treat Infections // Springer Science+Business Media, LLC 2012. DOI 10.1007/978-1-4614-1068-3_2.
10. Finch R.G. Antibiotic resistance: a view from the prescriber // Nat. Rev. Microbiol. 2004. Nо. 12. P. 989-994. Access mode: www.ncbi.nlm.nih.gov/pubmed/15550945.
11. Karslake J., Maltas J., Brumm P., Wood K.B. Population Density Modulates Drug Inhibition and Gives Rise to Potential Bistability of Treatment Outcomes for Bacterial Infections // PLOS Computational Biology. 2016. P. 1-21. Access mode: www.ncbi.nlm.nih.gov/pubmed/27764095.
12. Levison M.E., Levison J.H. Pharmacokinetics and Pharmacodynamics of Antibacterial Agents // Infect Dis Clin North Am. 2009. Vol. 23. Nо. 4. P. 791. Access mode: www.ncbi.nlm.nih.gov/pubmed/19909885.
13. Lundborg C.S., Tamhankar A.J. Understanding and changing human behaviour—antibiotic mainstreaming as an approach to facilitate modification of provider and consumer behaviour // Upsala Journal of Medical Sciences. 2014. Vol. 199, Nо. 2. P. 125-133. Access mode: www.ncbi.nlm.nih.gov/pmc/articles/PMC4034549.
14. Minodier P. Principles of antibiotic prophylaxis // Arch Pediatr. 2013. Vol. 20, Suppl. 3. S. 57-60. Access mode: http://link.springer.com/article/10.1007/BF01653540.
15. Nielsen E.I., Friberg L.E. Pharmacokinetic-pharmacodynamic modeling of antibacterial drugs // Pharmacol Rev. 2013. Vol. 65, Nо. 2. P. 1053-1090. Access mode: www.ncbi.nlm.nih.gov/pubmed/23803529.
16. Nolte O. Antimicrobial resistance in the 21st century: a multifaceted challenge // Protein Pept Lett. 2014. Vol. 21, Nо. 4. P. 330-335. Access mode: www.ncbi.nlm.nih.gov/pubmed/24164264.
17. Öbrink-Hansen K., Juul R.V., Storgaard M. [et al.]. Population pharmacokinetics of piperacillin in the early phase of septic shock: does standard dosing result in therapeutic plasma concentrations? // Antimicrob Agents Chemother. 2015. Vol. 19, No. 11. P. 7018-7026. Access mode: www.ncbi.nlm.nih.gov/pubmed/26349823.
18. Özgenç O. Methodology in improving antibiotic implementation policies // World J. Methodol. 2016. Vol. 6, No. 2. P. 143-153. Access mode: www.ncbi.nlm.nih.gov/pubmed/27376019.
19. Syed M.A.F. Pharmacokinetic and Pharmacodynamic Modeling of Antibiotics and Bacterial Drug Resistance / Acta Universitatis Upsaliensis. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy / 2013. Uppsala. 77 p. Access mode: www.farmbio.uu.se/forskning/researchgroups/pharmacometrics/thesis-display/?tarContentId=301941.
20. Velkov T., Bergen P.J., Lora-Tamayo J., Landersdorfer C.B. PK/PD models in antibacterial development // Curr. Opin. Microbiol. 2013. Vol. 16, No. 5. P. 573-579. Access mode: www.ncbi.nlm.nih.gov/pubmed/23871724.
21. Yadav R., Bulitta J.B., Nation R.L., Landersdorfer C.B. Optimization of synergistic combination regimens against carbapenem- and aminoglycoside-resistant clinical Pseudomonas aeruginosa isolates via mechanism-based pharmacokinetic/pharmacodynamic modeling // Antimicrob Agents Chemother. 2016. Access mode: http://aac.asm.org/content/early/2016/11/01/AAC.01011-16.abstract.
22. Zhang N., Gu X., Ye X., Wu X., Zhang B., Zhang L., Shen X., Jiang H., Ding H. The PK/PD Interactions of Doxycycline against Mycoplasma gallisepticum // Front Microbiol. 2016. Vol. 4, No. 7. P. 653. Access mode: www.ncbi.nlm.nih.gov/pubmed/27199972
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