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In the wake of emerging antimicrobial resistance, antibacterial drug development has become more critical. At the same time, development of antibacterial drugs targeting specific pathogens or resistance phenotypes that may have low prevalence presents challenges because it is difficult to conduct large, randomized controlled trials for such drugs. Animal models have increasingly supported clinical development of antibacterials; however, more work is needed to optimize the design and application of these animal models to ensure clear and actionable translation to further human investigation. This review discusses recent case studies of animal infection models used to support antibacterial drug development in order to illuminate considerations for future development of novel antibacterial drugs.

Background Nonclinical (animal and in vitro) models are commonly used during the development of antibacterial drugs. Pharmacokinetic (PK) and pharmacodynamic (PD) data obtained from these nonclinical models are used to generate a PK-PD target, which can then be bridged to humans in a probability of PK-PD target attainment (PTA) analysis to support selection of the dose regimen for phase 3 trials and in vitro susceptibility testing criteria (breakpoints) to guide clinical usage. Methods Two recently approved tetracycline antibacterial drugs, eravacycline (ERV) and omadacycline (OMD), were evaluated. PK-PD data from nonclinical models and clinical microbiological response were collected from each of the respective clinical pharmacology reviews and assessments published by FDA and EMA, respectively. The highest MICs (minimum inhibitory concentrations) reflecting 80% success in the ability of the drug to inhibit growth in the target bacteria were identified from clinical and nonclinical data and termed the MIC cutoff. The nonclinical MIC cutoff was obtained from the PTA analysis using the PK-PD targets from animal studies. The clinical MIC cutoff was obtained from microbiological response (microbiological intent-to-treat population) data from clinical trial experience. The ratios of the clinical and nonclinical MIC cutoffs were calculated and used to evaluate potential discrepancies between the animal model prediction and clinical trial experience. Results The drug development programs for ERV and OMD included murine infection models and in vitro models to characterize PK-PD. The clinical to nonclinical MIC cutoff ratios ranged from 4 to 32. Higher values of the MIC cutoff signify that the drug can treat larger proportions of the bacterial population; therefore, high clinical to nonclinical MIC cutoff ratios signify that the drugs had more activity in reducing the bacterial population in clinical than in nonclinical studies. Conclusion Thus, the nonclinical models for ERV and OMD under-predicted microbiological response and breakpoints. While nonclinical models are generally useful, more characterization of translational factors may be needed to allow nonclinical models to be more predictive of clinical trial outcomes. Disclosures All authors: No reported disclosures.

Mucous-penetrating nanoparticles consisting of poly lactic acid-co-glycolic acid (PLGA)-polyethylene glycol (PEG) could improve targeting of microbicidal drugs for sexually transmitted diseases by intravaginal inoculation. Nanoparticles can induce inflammatory responses, which may exacerbate the inflammation that occurs in the vaginal tracts of women with yeast infections. This study evaluated the effects of these drug-delivery nanoparticles on VK2(E6/E7) vaginal epithelial cell proinflammatory responses to Candida albicans yeast infections. Vaginal epithelial cell monolayers were infected with C. albicans and exposed to 100 μg/ml 49.5 nm PLGA-PEG nanospheres or 20 μg/ml 1.1 x 500 nm PEG-functionalized graphene oxide (GO-PEG) sheets. The cells were assessed for changes in mRNA and protein expression of inflammation-related genes by RT-qPCR and physiological markers of cell stress using high content analysis and flow cytometry. C. albicans exposure suppressed apoptotic gene expression, but induced oxidative stress in the cells. The nanomaterials induced cytotoxicity and programmed cell death responses alone and with C. albicans. PLGA-PEG nanoparticles induced mRNA expression of apoptosis-related genes and induced poly (ADP-ribose) polymerase (PARP) cleavage, increased BAX/BCL2 ratios, and chromatin condensation indicative of apoptosis. They also induced autophagy, endoplasmic reticulum stress, and DNA damage. They caused the cells to excrete inflammatory recruitment molecules chemokine (C-X-C motif) ligand 1 (CXCL1), interleukin-1α (IL1A), interleukin-1β (IL1B), calprotectin (S100A8), and tumor necrosis factor α (TNF). GO-PEG nanoparticles induced expression of necrosis-related genes and cytotoxicity. They reduced autophagy and endoplasmic reticulum stress, and apoptotic gene expression responses. The results show that stealth nanoparticle drug-delivery vehicles may cause intracellular damage to vaginal epithelial cells by several mechanisms and that their use for intravaginal drug delivery may exacerbate inflammation in active yeast infections by increased inflammatory recruitment.