Evaluation of Antibiotic Therapy from Discovery to Modern Challenges

Bacterial infections obtained in hospitals result in longer hospital stays and higher mortality rates. Antibioticresistant bacteria worsen the issue by impeding or delaying effective therapy. Treatment regimens that use multiple antibiotics may be employed to manage antibiotic resistance and guarantee effective therapy. This includes giving patients medicine mixtures (combination therapy), randomly allocating pharmaceuticals to various patients (mixing), and routinely changing the hospital's default medication from drug A to drug B and back (cycling). The potential of antibiotic combination therapy, mixing, and cycling has been evaluated for over two decades using mathematical models. However, despite trends in their rankings among research, the picture is still shockingly ambiguous and inconsistent, with no clear consensus on which strategy most effectively limits the emergence and spread of antibiotic resistance. In this paper, we examine previous modeling research and illustrate through examples how methodological considerations make it more difficult to produce a coherent image. These elements include the model's implementation and analysis, as well as the selection of the criterion used to compare the protocols' impacts. After that, we talk about how to advance and offer ideas for future modeling paths, emphasizing the need for standardized evaluation metrics, realistic clinical assumptions, integration of empirical data, and interdisciplinary collaboration to better inform evidence-based antibiotic stewardship policies.

Antibiotic, Antibiotic Resistance, Antimicrobial Resistance (AMR)

1. Fleming A. On the antibacterial action of cultures of Penicillium, with special reference to their use in the isolation of B. influenzae. Br J Exp Pathol. 1929;10:226–236. [Google Scholar] [Crossref]

2. Chain E, Florey HW, Gardner AD, Heatley NG, Jennings MA, Orr-Ewing J, et al. [Google Scholar] [Crossref]

3. Penicillin as a chemotherapeutic agent. Lancet. 1940;236(6104):226–228. [Google Scholar] [Crossref]

4. Aminov RI. A brief history of the antibiotic era: lessons learned and challenges for the future. Front Microbiol. 2010;1:134. [Google Scholar] [Crossref]

5. Davies J, Davies D. Origins and evolution of antibiotic resistance. Microbiol Mol Biol Rev. 2010;74(3):417–433. [Google Scholar] [Crossref]

6. Ventola CL. The antibiotic resistance crisis. Pharm Ther. 2015;40(4):277–283. [Google Scholar] [Crossref]

7. World Health Organization. Antimicrobial resistance: global report on surveillance. Geneva: WHO; 2014. [Google Scholar] [Crossref]

8. World Health Organization. Global action plan on antimicrobial resistance. Geneva: WHO; 2015. [Google Scholar] [Crossref]

9. Munita JM, Arias CA. Mechanisms of antibiotic resistance. Microbiol Spectr. 2016;4(2). [Google Scholar] [Crossref]

10. Chambers HF. Methicillin resistance in staphylococci: molecular and biochemical basis. Clin Microbiol Rev. 1997;10(4):781–791. [Google Scholar] [Crossref]

11. Poole K. Efflux-mediated antimicrobial resistance. J Antimicrob Chemother. 2005;56(1):20–51. [Google Scholar] [Crossref]

12. Nikaido H. Multidrug resistance in bacteria. Annu Rev Biochem. 2009;78:119–146. [Google Scholar] [Crossref]

13. Li XZ, Nikaido H. Efflux-mediated drug resistance in bacteria. Drugs. 2009;69(12):1555–1623. [Google Scholar] [Crossref]

14. Delcour AH. Outer membrane permeability and antibiotic resistance. Biochim Biophys Acta. 2009;1794(5):808–816. [Google Scholar] [Crossref]

15. Nikaido H. Outer membrane barrier as a mechanism of antimicrobial resistance. Antimicrob Agents Chemother. 1989;33(11):1831–1836. [Google Scholar] [Crossref]

16. Hall-Stoodley L, Costerton JW, Stoodley P. Bacterial biofilms. Nat Rev Microbiol. 2004;2:95–108. [Google Scholar] [Crossref]

17. Donlan RM, Costerton JW. Biofilms: survival mechanisms of clinically relevant microorganisms. Clin Microbiol Rev. 2002;15(2):167–193. [Google Scholar] [Crossref]

18. Mah TF, O’Toole GA. Mechanisms of biofilm resistance. Trends Microbiol. 2001;9(1):34–39. [Google Scholar] [Crossref]

19. Stewart PS, Costerton JW. Antibiotic resistance of bacteria in biofilms. Lancet. 2001;358(9276):135–138. [Google Scholar] [Crossref]

20. Tenover FC. Mechanisms of antimicrobial resistance in bacteria. Am J Med. 2006;119(6):S3–S10. [Google Scholar] [Crossref]

21. Laxminarayan R, Duse A, Wattal C, Zaidi AKM, Wertheim HFL, Sumpradit N, et al. Antibiotic resistance—the need for global solutions. Lancet Infect Dis. 2013;13(12):1057–1098. [Google Scholar] [Crossref]

22. O’Neill J. Tackling drug-resistant infections globally: final report and recommendations. London: Review on AMR; 2016. [Google Scholar] [Crossref]

23. Levin BR, Bonten MJM. Cycling antibiotics may not be good for your health. Proc Natl Acad Sci USA. 2004;101(36):13101–13102. [Google Scholar] [Crossref]

24. Bergstrom CT, Lo M, Lipsitch M. Ecological theory suggests that antimicrobial cycling will not reduce resistance. Proc Natl Acad Sci USA. 2004;101(36):13285–13290. [Google Scholar] [Crossref]

25. Bonhoeffer S, Lipsitch M, Levin BR. Evaluating treatment protocols to prevent antibiotic resistance. Proc Natl Acad Sci USA. 1997;94(22):12106–12111. [Google Scholar] [Crossref]

26. Beardmore RE, Peña-Miller R. Antibiotic cycling versus mixing. PLoS Comput Biol. 2010;6(7):e1000814. [Google Scholar] [Crossref]

27. Wiesch PA, Kouyos R, Engelstädter J, Regoes RR, Bonhoeffer S. Population biological principles of drug resistance. Lancet Infect Dis. 2011;11(3):236–247. [Google Scholar] [Crossref]

28. MacLean RC, San Millan A. Microbial evolution and antibiotic resistance. Science. 2019;365(6458):1082–1083. [Google Scholar] [Crossref]

29. Andersson DI, Hughes D. Antibiotic resistance and its cost. Nat Rev Microbiol. 2010;8:260–271. [Google Scholar] [Crossref]

30. Blair JMA, Webber MA, Baylay AJ, Ogbolu DO, Piddock LJV. Molecular mechanisms of antibiotic resistance. Nat Rev Microbiol. 2015;13:42–51. [Google Scholar] [Crossref]

31. Rice LB. Federal funding for the study of antimicrobial resistance. J Infect Dis. 2008;197(8):1079–1081. [Google Scholar] [Crossref]

32. Spellberg B, Guidos R, Gilbert D, Bradley J, Boucher HW, Scheld WM, et al. The epidemic of antibiotic-resistant infections. Clin Infect Dis. 2008;46(2):155–164. [Google Scholar] [Crossref]

33. CDC. Antibiotic resistance threats in the United States. Atlanta: CDC; 2019. [Google Scholar] [Crossref]

34. European Centre for Disease Prevention and Control. Surveillance of antimicrobial resistance in Europe. Stockholm: ECDC; 2020. [Google Scholar] [Crossref]

35. Cosgrove SE. The relationship between antimicrobial resistance and patient outcomes. Clin Infect Dis. 2006;42(S2):S82–S89. [Google Scholar] [Crossref]

36. Roberts RR, Hota B, Ahmad I, Scott RD, Foster SD, Abbasi F, et al. Hospital costs of antimicrobial-resistant infections. Clin Infect Dis. 2009;49(8):1175–1184. [Google Scholar] [Crossref]

37. Levy SB, Marshall B. Antibacterial resistance worldwide. Nat Med. 2004;10:S122–S129. [Google Scholar] [Crossref]

38. Davies J. Inactivation of antibiotics and dissemination of resistance genes. Science. 1994;264(5157):375–382. [Google Scholar] [Crossref]

39. Bush K, Bradford PA. β-Lactams and β-lactamase inhibitors. Cold Spring Harb Perspect Med. 2016;6(8):a025247. [Google Scholar] [Crossref]

40. Drawz SM, Bonomo RA. Three decades of β-lactamase inhibitors. Clin Microbiol Rev. 2010;23(1):160–201. [Google Scholar] [Crossref]

41. Wright GD. Antibiotic resistance in the environment. Nat Rev Microbiol. 2010;8:260–271. [Google Scholar] [Crossref]

42. Baquero F, Martínez JL, Cantón R. Antibiotics and resistance in water environments. Curr Opin Biotechnol. 2008;19(3):260–265. [Google Scholar] [Crossref]

43. Martínez JL. Environmental pollution by antibiotics and resistance determinants. Environ Pollut. 2009;157(11):2893–2902. [Google Scholar] [Crossref]

44. Marshall BM, Levy SB. Food animals and antimicrobials. Clin Microbiol Rev. 2011;24(4):718–733. [Google Scholar] [Crossref]

45. Van Boeckel TP, Brower C, Gilbert M, Grenfell BT, Levin SA, Robinson TP, et al. Global trends in antimicrobial use in food animals. Proc Natl Acad Sci USA. 2015;112(18):5649–5654. [Google Scholar] [Crossref]

46. Woolhouse M, Ward M, van Bunnik B, Farrar J. Antimicrobial resistance in humans, livestock and environment. Philos Trans R Soc Lond B Biol Sci. 2015;370:20140083. [Google Scholar] [Crossref]

47. Otto M. MRSA virulence and spread. Nat Rev Microbiol. 2012;10:233–242. [Google Scholar] [Crossref]

48. Nordmann P, Naas T, Poirel L. Global spread of carbapenemase-producing Enterobacteriaceae. Emerg Infect Dis. 2011;17(10):1791–1798. [Google Scholar] [Crossref]

49. World Health Organization. Global tuberculosis report. Geneva: WHO; 2022. [Google Scholar] [Crossref]

50. Gillespie SH. Evolution of drug resistance in tuberculosis. Lancet Infect Dis. 2002;2(5):298–306. [Google Scholar] [Crossref]

51. Köser CU, Ellington MJ, Cartwright EJP, Gillespie SH, Brown NM, Farrington M, et al. Whole-genome sequencing for antimicrobial resistance. N Engl J Med. 2012;366:2267–2275. [Google Scholar] [Crossref]

52. Didelot X, Bowden R, Wilson DJ, Peto TEA, Crook DW. Transforming clinical microbiology with genome sequencing. Nat Rev Genet. 2012;13:601–612. [Google Scholar] [Crossref]

53. Høiby N, Bjarnsholt T, Givskov M, Molin S, Ciofu O. Antibiotic resistance in biofilms. Int J Antimicrob Agents. 2010;35(4):322–332. [Google Scholar] [Crossref]

54. Bjarnsholt T. The role of biofilms in chronic infections. APMIS. 2013;121:1–58. [Google Scholar] [Crossref]

55. Waters CM, Bassler BL. Quorum sensing: cell-to-cell communication in bacteria. Annu Rev Cell Dev Biol. 2005;21:319–346. [Google Scholar] [Crossref]

56. LaSarre B, Federle MJ. Exploiting quorum sensing to combat bacteria. Microbiol Mol Biol Rev. 2013;77(1):73–111. [Google Scholar] [Crossref]

57. Abedon ST, Kuhl SJ, Blasdel BG, Kutter EM. Phage treatment of infections. Bacteriophage. 2011;1(2):66–85. [Google Scholar] [Crossref]

58. Chan BK, Abedon ST, Loc-Carrillo C. Phage cocktails and resistance. Future Microbiol. 2013;8(6):769–783. [Google Scholar] [Crossref]

59. Bikard D, Barrangou R. Using CRISPR–Cas systems to combat AMR. Nat Rev Microbiol. 2017;15:513–525. [Google Scholar] [Crossref]

60. Wright GD. Q&A: Antibiotic resistance. Nat Rev Microbiol. 2007;5:175–186. [Google Scholar] [Crossref]

61. Holmes AH, Moore LSP, Sundsfjord A, Steinbakk M, Regmi S, Karkey A, et al. [Google Scholar] [Crossref]

62. Understanding drivers of AMR. Lancet. 2016;387(10014):176–187. [Google Scholar] [Crossref]

63. Prescott JF. Antimicrobial use in food and companion animals. Anim Health Res Rev. 2008;9(2):127–133. [Google Scholar] [Crossref]

64. Spellberg B, Bartlett JG, Gilbert DN. The future of antibiotics. N Engl J Med. 2013;368:299–302. [Google Scholar] [Crossref]

65. Payne DJ, Gwynn MN, Holmes DJ, Pompliano DL. Drugs for bad bugs. Nat Rev Drug Discov. 2007;6:29–40. [Google Scholar] [Crossref]

66. Silver LL. Challenges of antibacterial discovery. Clin Microbiol Rev. 2011;24(1):71–109. [Google Scholar] [Crossref]

67. Boucher HW, Talbot GH, Bradley JS, Edwards JE, Gilbert D, Rice LB, et al. Bad bugs, no drugs. Clin Infect Dis. 2009;48(1):1–12. [Google Scholar] [Crossref]

68. Llor C, Bjerrum L. Antimicrobial resistance: risk of overprescribing. Am J Infect Control. 2014;42(8):S159–S164. [Google Scholar] [Crossref]

69. Costelloe C, Metcalfe C, Lovering A, Mant D, Hay AD. Effect of antibiotic prescribing in primary care. BMJ. 2010;340:c2096. [Google Scholar] [Crossref]

70. Goossens H, Ferech M, Vander Stichele R, Elseviers M. Outpatient antibiotic use in Europe. Lancet. 2005;365(9459):579–587. [Google Scholar] [Crossref]

71. Dellit TH, Owens RC, McGowan JE, Gerding DN, Weinstein RA, Burke JP, et al. IDSA guidelines for antimicrobial stewardship. Clin Infect Dis. 2007;44(2):159–177. [Google Scholar] [Crossref]

72. Dyar OJ, Huttner B, Schouten J, Pulcini C. Stewardship strategies. Clin Microbiol Infect. 2017;23(11):793–798. [Google Scholar] [Crossref]

73. Read AF, Day T, Huijben S. Evolution of drug resistance and treatment strategies. Proc Natl Acad Sci USA. 2011;108(S2):10871–10878. [Google Scholar] [Crossref]

74. zur Wiesch PA, Abel S, Gkotzis S, Ocampo P, Engelstädter J, Hinkley T, et al. Classic resistance mutations with low fitness cost. Mol Biol Evol. 2015;32(2):457–468. [Google Scholar] [Crossref]

• Drone-Based Phenotyping and its Utilization in Crop Improvement: A Review
• An IoT-Enabled Smart Healthcare Monitoring System Using Machine Learning for Early Health Risk Prediction
• Strategic Integration of Artificial Intelligence for Achieving Operational Excellence in Container Freight Stations Using Evidence from Chennai, India
• Adoption of OTT platforms: Analyzing User Behavior through the UTAUT2 Model
• Customers’ Buying Behaviour in Relation to Online Food Delivery (Evidence from National Capital Region (NCR) of India)