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Liposomes are promising targeted drug delivery systems with the potential to improve the efficacy and safety profile of certain classes of drugs. Though attractive, there are unique analytical challenges associated with the development of liposomal drugs including human dose prediction given these are multi-component drug delivery systems. In this study, we developed a multimodal imaging approach to provide a comprehensive distribution assessment for an antibacterial drug, GSK2485680, delivered as a liposomal formulation (Lipo680) in a mouse thigh model of bacterial infection to support human dose prediction. Positron emission tomography (PET) imaging was used to track the in vivo biodistribution of Lipo680 over 48 h post-injection providing a clear assessment of the uptake in various tissues and, importantly, the selective accumulation at the site of infection. In addition, a pharmacokinetic model was created to evaluate the kinetics of Lipo680 in different tissues. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) was then used to quantify the distribution of GSK2485680 and to qualitatively assess the distribution of a liposomal lipid throughout sections of infected and non-infected hindlimb tissues at high spatial resolution. Through the combination of both PET and MALDI IMS, we observed excellent correlation between the Lipo680-radionuclide signal detected by PET with the GSK2485680 and lipid component signals detected by MALDI IMS. This multimodal translational method can reduce drug attrition by generating comprehensive biodistribution profiles of drug delivery systems to provide mechanistic insight and elucidate safety concerns. Liposomal formulations have potential to deliver therapeutics across a broad array of different indications, and this work serves as a template to aid in delivering future liposomal drugs to the clinic.

Liposomes are promising targeted drug delivery systems with the potential to improve the efficacy and safety profile of certain classes of drugs. Though attractive, there are unique analytical challenges associated with the development of liposomal drugs including human dose prediction given these are multi-component drug delivery systems. In this study, we developed a multimodal imaging approach to provide a comprehensive distribution assessment for an antibacterial drug, GSK2485680, delivered as a liposomal formulation (Lipo680) in a mouse thigh model of bacterial infection to support human dose prediction. Positron emission tomography (PET) imaging was used to track the in vivo biodistribution of Lipo680 over 48h post-injection providing a clear assessment of the uptake in various tissues and, importantly, the selective accumulation at the site of infection. In addition, a pharmacokinetic model was created to evaluate the kinetics of Lipo680 in different tissues. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) was then used to analyze and quantify the distribution of GSK2485680 and a liposomal lipid throughout sections of infected and non-infected thigh tissues at high spatial resolution. Through the combination of both PET and MALDI images, we observed an excellent correlation between the Lipo680-radionuclide signal from PET with GSK2485680 and lipid component signals from MALDI IMS. This multimodal translational method can reduce drug attrition by providing comprehensive biodistribution profiles of drug delivery systems to provide mechanistic insight and elucidate safety concerns. Liposomal formulations have broad potential to deliver therapeutics for other indications, and this work serves as a template to aid in delivering future liposomal drugs to the clinic.

Background Gepotidacin (GEP) is a novel triazaacenaphthylene bacterial type II topoisomerase inhibitor targeting both bacterial DNA gyrase and topoisomerase IV by a different mechanism from fluoroquinolone antibiotics. Although in vitro frequency of resistance to GEP in Neisseria gonorrhoeae (NG) is low, during a phase 2 trial, clinical resistance to gepotidacin in NG emerged in a subset of fluoroquinolone-resistant NG isolates that contained a pre-existing ParC D86N mutation by introduction of a new GyrA A92T mutation. The objective of this study was to evaluate the role of GyrA A92T & Parc D86N mutations in resistance to GEP. Methods We utilized the high frequency of natural transformation to introduce GyrA A92T and ParC D86N mutations, individually and in combination, into NG isolates either with GyrA S91F D95G mutations or with wild type (WT) GyrA by selection on ciprofloxacin (CIP) or GEP to generate isogenic strains for susceptibility evaluation. Results Results are summarized in enclosed table. Overall, GyrA A92T and ParC D86N mutations alone did not confer a significant (>4-fold) increase in GEP MIC; whereas together they gave >16-fold increases in GEP MIC. Importantly, quinolone target mutations (GyrA S91F D95G and ParC D86N) together showed no significant effect on the GEP MIC; while they gave >1000-fold increase in CIP MIC. As expected, GyrA A92T and ParC D86N mutations alone or together in WT GyrA background had no significant effect on CIP susceptibility. Susceptibility of isogenic NG strains to gepotidacin and ciprofloxacin Conclusion Our results indicated that unlike fluoroquinolones that primarily target DNA gyrase in NG, there is no obvious primary target for GEP, supporting well-balanced dual targeting of DNA gyrase and topoisomerase IV by GEP in NG. Though, the pre-existing ParC D86N mutation is a potential risk marker for clinical resistance development, as this mutation compromises dual targeting of GEP, our studies provide mechanistic insight for appropriate clinical dose selection to potentially suppress further resistance development in this subset of clinical isolates. Disclosures Pan Chan, PhD, GlaxoSmithKline (Employee, Shareholder) Karen Ingraham, MS, GlaxoSmithKline (Employee, Shareholder) Sharon Min, MS, GlaxoSmithKline (Employee, Shareholder) Nicole Scangarella-Oman, MS, GlaxoSmithKline plc. (Employee, Shareholder) Steve Rittenhouse, PhD, GlaxoSmithKline (Employee, Shareholder) Jianzhong Huang, PhD, GlaxoSmithKline (Employee, Shareholder)

During the course of our research on the lead optimisation of the NBTI (Novel Bacterial Type II Topoisomerase Inhibitors) class of antibacterials, we discovered a series of tricyclic compounds that showed good Gram-positive and Gram-negative potency. Herein we will discuss the various subunits that were investigated in this series and report advanced studies on compound 1 (GSK945237) which demonstrates good PK and in vivo efficacy properties.

Background Neisseria gonorrhoeae (NG) causes the sexually transmitted disease gonorrhea. It has developed resistance to every antibiotic introduced for gonorrhea treatment such that NG clinical isolates with multidrug resistance (MDR) are increasingly common. We hypothesize that natural transformation could be used to transfer genetic determinants of antibiotic resistance from drug-resistant NG clinical isolates without pre-knowledge of the genetic determinants to a new background under antibiotic selection to generate isogenic transformants for further characterization. Methods Natural transformation, PCR amplification and DNA sequencing, and antibiotic susceptibility testing were used in the studies. Results We have validated the hypothesis using genomic DNA from an MDR including ciprofloxacin-resistant NG clinical isolate as a donor and a ciprofloxacin-susceptible NG isolate as a recipient under the selective pressure of ciprofloxacin. This led to a series of transformants that contain single or multiple genetic resistance determinants being generated depending on the resistance levels and transformation frequencies. Antibiotic susceptibility testing and genetic characterization of the transformants allowed us to (i) identify ciprofloxacin resistance determinants including efflux mutation mtrR-79 and target mutations GyrA S91F D95G and ParC D86N, (ii) quantify the contribution of each genetic determinant responsible for the ciprofloxacin resistance and (iii) regenerate the ciprofloxacin resistance phenotype of the donor isolate to detect multiple paths of possible resistance development for ciprofloxacin. Furthermore, we also validated the hypothesis with a novel antibiotic gepotidacin to identify pre-existing genetic determinants contributing to varying susceptibility to this antibiotic. Finally, we envision that, along with whole genome sequencing, natural transformation could be used to identify and quantify novel genetic resistance determinants to current or novel antibiotics in drug-resistant NG clinical isolates. Conclusion We demonstrated the utility of natural transformation in dissecting the multifaceted nature of antibiotic resistance in NG clinical isolates. Disclosures Jianzhong Huang, PhD, GlaxoSmithKline (Employee, Shareholder) Karen Ingraham, MS, GlaxoSmithKline (Employee, Shareholder) Pan Chan, PhD, GlaxoSmithKline (Employee, Shareholder) Steve Rittenhouse, PhD, GlaxoSmithKline (Employee, Shareholder)