Investigative Ophthalmology & Visual Science Cover Image for Volume 65, Issue 7
June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
Mathematical Modelling for Predicting the Synergistic Effect of Antibiotic-Host Defence Peptide Combination Therapy for the Treatment of Bacterial Keratitis
Author Affiliations & Notes
  • Paul A Roberts
    Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
  • Darren S J Ting
    Academic Unit of Ophthalmology, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom
    Birmingham and Midland Eye Centre, Birmingham, Birmingham, United Kingdom
  • Footnotes
    Commercial Relationships   Paul Roberts None; Darren S J Ting None
  • Footnotes
    Support  University of Birmingham Dynamic Investment Fund
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 5602. doi:
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      Paul A Roberts, Darren S J Ting; Mathematical Modelling for Predicting the Synergistic Effect of Antibiotic-Host Defence Peptide Combination Therapy for the Treatment of Bacterial Keratitis. Invest. Ophthalmol. Vis. Sci. 2024;65(7):5602.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Infectious keratitis (IK) is the leading cause of corneal blindness. Its treatment presents a challenge given the rapid clearance of drugs through drainage of the tear film, the emergence of antimicrobial resistance and the need for rapid eradication of infection before permanent corneal damage occurs. We used mathematical modelling to explain and predict the synergistic effects of antibiotic and host defence peptide (HDP) combination therapy in bacterial keratitis.

Methods : An ordinary differential equation (ODE) model was formulated to describe the evolving bacterial population, and antibiotic and HDP concentrations over time. Our equations account for bacterial division, the bactericidal effects of antibiotic and HDP, tear drainage and the development of resistance. The model was parameterised using data from the literature and through fitting to data from a previous experimental study, which used amikacin (an antibiotic) and CaD23 (a synthetic HDP) against a laboratory-strain S. aureus (SH1000), both individually and in combination. The full model was solved computationally, while reduced models were solved analytically (algebraically).

Results : Our model demonstrated that amikacin and CaD23 act synergistically, their combined effect against SH1000 being greater than the sum of their individual effects. Further, simulations predict clinically-realistic treatment regimens to expedite the eradication of bacterial infections, while reducing the risk of dose-dependent toxicity.

Conclusions : Antibiotic-HDP combination therapies present a promising route for treating bacterial IK, especially in light of their synergistic interaction. Further, our model provides a relatively quick and cost-effective means of trialling IK treatment regimens. In future work, we will expand our study to consider a range of antibiotics, HDPs and bacterial species.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

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