Antimicrobial pharmacokinetics and preclinical in vitro models to support optimized treatment approaches for uncomplicated lower urinary tract infections

ABSTRACT

Introduction

Urinary tract infections (UTIs) are extremely common. Millions of people, particularly healthy women, are affected worldwide every year. One-in-two women will have a recurrence within 12-months of an initial UTI. Inadequate treatment risks worsening infection leading to acute pyelonephritis, bacteremia and sepsis. In an era of increasing antimicrobial resistance, it is critical to provide optimized antimicrobial treatment.

Areas covered

Literature was searched using PubMed and Google Scholar (up to 06/2020), examining the etiology, diagnosis and oral antimicrobial therapy for uncomplicated UTIs, with emphasis on urinary antimicrobial pharmacokinetics (PK) and the application of dynamic in vitro models for the pharmacodynamic (PD) profiling of pathogen response.

Expert opinion

The majority of antimicrobial agents included in international guidelines were developed decades ago without well-described dose–response relationships. Microbiology laboratories still apply standard diagnostic methodology that has essentially remained unchanged for decades. Furthermore, it is uncertain how relevant standard in vitro susceptibility is for predicting antimicrobial efficacy in urine. In order to optimize UTI treatments, clinicians must exploit the urine-specific PK of antimicrobial agents. Dynamic in vitro models are valuable tools to examine the PK/PD and urodynamic variables associated with UTIs, while informing uropathogen susceptibility reporting, optimized dosing schedules, clinical trials and treatment guidelines.

KEYWORDS:

• Antimicrobial resistance
• drug development
• in vitro infection models
• pharmacokinetics/pharmacodynamics
• urinary tract infection

Article highlights

• Urinary tract infections (UTIs) affect millions of people every year and are a common indication of antimicrobial use in the community and a potential driver for emergence of resistance.

• Yet, how we diagnose UTIs, report antimicrobial susceptibility and provide treatment recommendation are based on practices unchanged for decades and old pharmacokinetic (PK) and pharmacodynamic (PD) data.

• Greater understanding of the specific urinary PK characteristics of recommended oral antimicrobial agents and the interaction between the host and the uropathogen, can inform optimized selection and dosing when tackling multidrug resistant (MDR) phenotypes.

• The use of dynamic in vitro PK/PD models allows us to explore antimicrobial spectrum of activity, dosing and duration of therapy, and the drivers of emergence of resistance in a site-specific infection model.

• This robust preclinical data can promote the rational design of antimicrobial dosing, guide laboratory susceptibility testing and translate findings into clinical trials to inform treatment guidelines.

Acknowledgments

We thank Professor Johan W. Mouton (3 November 1956 - 9 July 2019) for his insights, expertise and guidance in establishing and supporting the pharmacodynamic profiling of antimicrobial agents through the use of dynamic in vitro modelling. I.J.A. was funded by an Australian Government Research Training Program Scholarship (APP1114690) from the National Health and Medical Research Council of Australia. A.Y.P. and J.A.R. are part funded through an Australian National Health and Medical Research Council Practitioner Fellowships (APP1117940 and APP1117065, respectively). J.A.R. would like to acknowledge funding for a NHMRC Centre of Research Excellence (APP1099452).

Declaration of interest

JA Roberts discloses consultancies/advisory boards for MSD (2019); QPEX (2019); Discuva Ltd (2019); Accelerate Diagnostics (2017); Bayer (2017); Biomerieux (2016). Speaking fees for MSD (2018); Biomerieux (2018), Pfizer (2019). Industry grants from MSD (2017); The Medicines Company (2017); Cardeas Pharma (2016); Biomerieux (2019); QPEX (2019); Pfizer (2019). J Meletiadis discloses research grants from Pfizer, Gilead, Astellas, MSD, F2G and VenatoRx. A Peleg discloses research funding from MSD through an investigator-initiated research project. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contributions

All authors were involved in the content development of the manuscript and approved the final version. The authors take full responsibility for the content of this article.

Additional information

Funding

This paper was not funded.