(374f) Enhancing the Time-to-Positivity (TTP) Paradigm for the Design of Effective Combination Therapy: A Computer-Aided Approach

Objective: Time-to-Positivity (TTP) is the time elapsed from the beginning of culture incubation to the detection of a bacterial growth by an automated blood culture system [1, 2]. TTP has emerged as a simple and inexpensive method to provide diagnostic information for clinical infections [3]. Once such information is available, standard techniques may be used for the design of infection treatment with antimicrobials. The thesis of this work is that the same equipment in currently widespread use for TTP-based diagnosis can also be used for the design of personalized combination therapy. The enabler is a computer-aided method that we have developed. The objective of this presentation is to provide in vitro experimental evidence for the validity of the above thesis.

Methods:

Computational: The proposed computer-aided method includes: (a) development of a mathematical model describing bacterial population dynamics under antibiotic exposure, accounting for heterogeneous kill rates and time-invariant antibiotic concentrations [4]; (b) analytical derivation of time-to-positivity (TTP) as a function of microbial parameters and detection thresholds; (c) application of constrained quadratic optimization to estimate crucial parameters from experimental TTP data; and (d) use of the fitted model to design effective, antibiotic dosing regimens under clinically relevant pharmacokinetics.

Experimental: Two cases were considered: (a) Ceftazidime-Avibactam (CAZ-AVI) on Acinetobacter; (b) Cefiderocol-Avibactam (CFDC-AVI) on P. Aeruginosa. For each case, a number of concentrations in twofold dilutions were combined, and TTP measurements were taken in an automated optical density instrument. The resulting data were used for mathematical model calibration, and model predictions were tested under clinically relevant pharmacokinetics in an an in vitro hollow fiber infection model (HFIM).

Results: Predictions by the mathematical model were confirmed in the HFIM.

Conclusion: The results presented here pave the way for a breakthrough in how TTP measurements are collected and used. This breakthrough, if further developed, can ultimately provide valuable help for clinicians to better design individualized treatments of bacterial infections.

References

[1] D. N. Marco, M. Brey, S. Anguera, C. Pitart, I. Grafia, M. Bodro, et al., "Time to positivity as a predictor of catheter-related bacteremia and mortality in adults with Pseudomonas aeruginosa bloodstream infection," Critical Care, vol. 29, pp. 1-12, 2025.

[2] N. Cobos-Trigueros, A. J. Kaasch, A. Soriano, J.-L. Torres, A. Vergara, L. Morata, et al., "Time to positivity and detection of growth in anaerobic blood culture vials predict the presence of Candida glabrata in candidemia: a two-center European cohort study," Journal of Clinical Microbiology, vol. 52, pp. 3082-3084, 2014.

[3] Y. Haimi-Cohen, E. M. Vellozzi, and L. G. Rubin, "Initial concentration of Staphylococcus epidermidis in simulated pediatric blood cultures correlates with time to positive results with the automated, continuously monitored BACTEC blood culture system," Journal of clinical microbiology, vol. 40, pp. 898-901, 2002.

[4] M. Nikolaou and V. H. Tam, "A new modeling approach to the effect of antimicrobial agents on heterogeneous microbial populations," Journal of mathematical biology, vol. 52, pp. 154-182, 2006.