Efficacy and Safety of Oral and IV Levonadifloxacin Therapy in Management of Bacterial Infections: Findings of a Prospective, Observational, Multi-center, Post-marketing Surveillance Study

Background Antimicrobial resistance by bacteria poses a substantial threat to morbidity and mortality worldwide, and treatment of resistant infections is a challenge for the treating clinician. Levonadifloxacin is a novel broad-spectrum agent belonging to the benzoquinolizine subclass of quinolone, which can be used by both oral and intravenous administration for the treatment of infections caused by gram-positive organisms, including methicillin-resistant Staphylococcus aureus (MRSA). Patients and methods This prescription event monitoring study captured data from 1266 patients receiving levonadifloxacin (oral and/or IV) in a real-world setting to assess the safety and efficacy in the treatment of various bacterial infections. The duration of the study was 18 months. Study outcomes were clinical success and microbial success at the end of therapy. Global assessments were done for safety and efficacy at the end of therapy using a 5-point Likert scale (excellent, very good, good, satisfactory, and poor). Results The mean (median) duration of therapy was 7.2 (7.0) days, with a median time to clinical improvement of four days. Oral therapy was administered to 224 patients; 940 received IV, and 102 received IV followed by oral therapy. Patients were prescribed levonadifloxacin for gram-positive infections, skin and soft tissue infections, diabetic foot infections, septicemia, catheter-related blood-stream infections, bone and joint infections, febrile neutropenia, and respiratory infections, including COVID-19 pneumonia. The clinical cure on the eighth day was 95.7%, whereas the microbial success on the eighth day was 93.3% (n=60). For different types of infections, the clinical success rates ranged from 85.2% to 100%. There were only 30 treatment-emergent adverse events reported in 29 patients. Overall, about 95.6% of patients rated the efficacy as good to excellent, whereas only 3.8% of patients rated it satisfactory; for safety, 95.7% of patients rated it as good to excellent, with only 3.9% of patients rated it as satisfactory. Conclusions The excellent safety and efficacy profile of levonadifloxacin, when administered as an oral or intravenous therapy, makes it a desirable treatment modality for the management of various bacterial infections, including those caused by resistant pathogens such as MRSA and quinolone-resistant Staphylococcus aureus (QRSA). Features of levonadifloxacin, such as availability in both IV and oral form, minimal drug-drug interactions, lack of the need to adjust dosages in renal and hepatically impaired patients along with a broad spectrum of coverage, make it a suitable agent that meets several unmet clinical needs of physicians.

Nanoscaled Discovery of a Shunt Rifamycin from Salinispora arenicola Using a Three-Color GFP-Tagged Staphylococcus aureus Macrophage Infection Assay

Antimicrobial resistance has emerged as a global public health threat, and development of novel therapeutics for treating infections caused by multi-drug resistant bacteria is urgent. Staphylococcus aureus is a major human and animal pathogen, responsible for high levels of morbidity and mortality worldwide. The intracellular survival of S. aureus in macrophages contributes to immune evasion, dissemination, and resilience to antibiotic treatment. Here, we present a confocal fluorescence imaging assay for monitoring macrophage infection by green fluorescent protein (GFP)-tagged S. aureus as a front-line tool to identify antibiotic leads. The assay was employed in combination with nanoscaled chemical analyses to facilitate the discovery of a new, active rifamycin analogue. Our findings indicate a promising new approach for the identification of antimicrobial compounds with macrophage intracellular activity. The antibiotic identified here may represent a useful addition to our armory in tackling the silent pandemic of antimicrobial resistance.

Prediction of potential drug-microbe associations based on matrix factorization and a three-layer heterogeneous network

Microbes in the human body are closely linked to many complex human diseases and are emerging as new drug targets. These microbes play a crucial role in drug development and disease treatment. Traditional methods of biological experiments are not only time-consuming but also costly. Using computational methods to predict microbe-drug associations can effectively complement biological experiments. In this experiment, we constructed heterogeneity networks for drugs, microbes, and diseases using multiple biomedical data sources. Then, we developed a model with matrix factorization and a three-layer heterogeneous network (MFTLHNMDA) to predict potential drug-microbe associations. The probability of microbe-drug association was obtained by a global network-based update algorithm. Finally, the performance of MFTLHNMDA was evaluated in the framework of leave-one-out cross-validation (LOOCV) and 5-fold cross-validation (5-fold CV). The results showed that our model performed better than six state-of-the-art methods that had AUC of 0.9396 and 0.9385 + /- 0.0000, respectively. This case study further confirms the effectiveness of MFTLHNMDA in identifying potential drug-microbe associations and new drug-microbe associations.

Predicting microbe-drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy

MOTIVATION

Predicting the associations between human microbes and drugs (MDAs) is one critical step in drug development and precision medicine areas. Since discovering these associations through wet experiments is time-consuming and labor-intensive, computational methods have already been an effective way to tackle this problem. Recently, graph contrastive learning (GCL) approaches have shown great advantages in learning the embeddings of nodes from heterogeneous biological graphs (HBGs). However, most GCL-based approaches don't fully capture the rich structure information in HBGs. Besides, fewer MDA prediction methods could screen out the most informative negative samples for effectively training the classifier. Therefore, it still needs to improve the accuracy of MDA predictions.

RESULTS

In this study, we propose a novel approach that employs the Structure-enhanced Contrastive learning and Self-paced negative sampling strategy for Microbe-Drug Association predictions (SCSMDA). Firstly, SCSMDA constructs the similarity networks of microbes and drugs, as well as their different meta-path-induced networks. Then SCSMDA employs the representations of microbes and drugs learned from meta-path-induced networks to enhance their embeddings learned from the similarity networks by the contrastive learning strategy. After that, we adopt the self-paced negative sampling strategy to select the most informative negative samples to train the MLP classifier. Lastly, SCSMDA predicts the potential microbe-drug associations with the trained MLP classifier. The embeddings of microbes and drugs learning from the similarity networks are enhanced with the contrastive learning strategy, which could obtain their discriminative representations. Extensive results on three public datasets indicate that SCSMDA significantly outperforms other baseline methods on the MDA prediction task. Case studies for two common drugs could further demonstrate the effectiveness of SCSMDA in finding novel MDA associations.

AVAILABILITY

The source code is publicly available on GitHub https://github.com/Yue-Yuu/SCSMDA-master.

Meeting the Unmet Need in the Management of MDR Gram-Positive Infections with Oral Bactericidal Agent Levonadifloxacin

Levonadifloxacin (intravenous) and its oral prodrug alalevonadifloxacin are broad-spectrum antibacterial agents developed for the treatment of difficult-to-treat infections caused by multidrug-resistant Gram-positive bacteria, especially methicillin-resistant Staphylococcus aureus, atypical bacteria, anaerobic bacteria, and biodefence pathogens as well as Gram-negative bacteria. Levonadifloxacin has a well-defined mechanism of action involving a strong affinity for DNA gyrase as well as topoisomerase IV. Alalevonadifloxacin with widely differing solubility and oral bioavailability has pharmacokinetic profile identical to levonadifloxacin. Unlike existing MRSA drugs such as vancomycin and linezolid, which cause unfavorable side effects like nephrotoxicity, bone-marrow toxicity, and muscle toxicity, levonadifloxacin/alalevonadifloxacin has demonstrated superior safety and tolerability features with no serious adverse events. Levonadifloxacin/alalevonadifloxacin could be a useful weapon in the battle against infections caused by resistant microorganisms and could be a preferred antibiotic of choice for empirical therapy in the future.

Real-World Evidence of Efficacy and Safety of Levonadifloxacin (Oral and IV) in the Management of Acute Bacterial Skin and Skin Structure Infections (ABSSSI): Findings of a Retrospective, Multi-Center Study

Background

Antimicrobial resistance by bacteria poses a substantial threat to the success in the treatment of acute bacterial skin and skin structure infections (ABSSSI). Levonadifloxacin is a novel benzoquinolizine subclass of quinolone which has a broad spectrum of activity, available in both oral and intravenous formulations for the treatment of skin structure infections caused by Gram-positive pathogens including methicillin-resistant Staphylococcus aureus (MRSA).

Patients and methods

This prescription event monitoring study captured data of 227 patients receiving levonadifloxacin (oral and/or IV) in a real-world setting to assess the safety and efficacy in the treatment of ABSSSI. Study outcomes were a clinical and microbial success at the end of therapy and safety was assessed based on adverse events reported.

Results

One hundred and forty patients received IV levonadifloxacin therapy, 76 patients received oral alalevonadifloxacin, and 11 received IV followed by oral therapy. The mean duration of therapy was 7.3 days. Out of 227 patients, MRSA isolates were identified in 79 patients. Clinical success rates with oral, IV, and IV followed by oral levonadifloxacin therapy were 97.3%, 97.8%, and 100% respectively. The overall microbial success rate was 99.2% and only two patients reported two adverse events.

Conclusions

The excellent safety and efficacy profile of levonadifloxacin on oral and/or intravenous therapy, makes it a desirable treatment modality for management of ABSSSI. Unique features of levonadifloxacin such as availability of both IV and oral form, minimal drug-drug interactions, exemption from dosage adjustment in renal and hepatic impaired patients and a broad spectrum of coverage, makes it a suitable agent meeting several unmet clinical needs in contemporary patients.

Prescription-Event monitoring study on safety and efficacy of levonadifloxacin (oral and I.V.) in management of bacterial infections: Findings of real-world observational study

Background:

Levonadifloxacin is a novel broad-spectrum antibiotic belonging to the benzoquinolizine subclass of quinolones. It is available in intravenous as well as oral formulation for the treatment of infections caused by common Gram-positive bacterial pathogens including methicillin-resistant Staphylococcus aureus (MRSA).

Patients and Methods:

This study retrospectively assessed the real-world safety and efficacy of levonadifloxacin (oral and/or IV) in the treatment of 1229 patients across various clinical conditions. Study outcomes were clinical and microbiological success at the end of therapy.

Results:

The mean duration of levonadifloxacin therapy was 7.2 days, with a time to clinical improvement averaging at 4 days. Three hundred and three patients received oral therapy, 875 received IV, and 51 received a combination of IV followed by oral therapy. Patients were prescribed levonadifloxacin for skin and soft-tissue infections, diabetic foot infections, septicemia, catheter-related bloodstream infections, bone and joint infections, febrile neutropenia, and respiratory infections including COVID-19 pneumonia. High clinical success rates of 98.3%, 93.7%, and 96.1% with oral, IV, and IV followed by oral levonadifloxacin, respectively, were obtained. Only 11 mild adverse events were reported in 9 patients which included constipation, diarrhea, hyperglycemia, nausea, fatigue, and vomiting. Overall, 96.3% and 97.3% of investigators rated the efficacy and safety of levonadifloxacin as “good to excellent.”

Conclusions:

An excellent safety and efficacy profile of levonadifloxacin was observed in this study making it a suitable treatment option for management of various bacterial infections, including those caused by resistant Gram-positive pathogens such as MRSA and quinolone-resistant S. aureus.

Predicting human microbe-drug associations via graph convolutional network with conditional random field

Motivation

Human microbes play critical roles in drug development and precision medicine. How to systematically understand the complex interaction mechanism between human microbes and drugs remains a challenge nowadays. Identifying microbe-drug associations can not only provide great insights into understanding the mechanism, but also boost the development of drug discovery and repurposing. Considering the high cost and risk of biological experiments, the computational approach is an alternative choice. However, at present, few computational approaches have been developed to tackle this task.

Results

In this work, we leveraged rich biological information to construct a heterogeneous network for drugs and microbes, including a microbe similarity network, a drug similarity network, and a microbe-drug interaction network. We then proposed a novel Graph Convolutional Network (GCN) based framework for predicting human Microbe-Drug Associations, named GCNMDA. In the hidden layer of GCN, we further exploited the Conditional Random Field (CRF), which can ensure that similar nodes (i.e., microbes or drugs) have similar representations. To more accurately aggregate representations of neighborhoods, an attention mechanism was designed in the CRF layer. Moreover, we performed a random walk with restart (RWR) based scheme on both drug and microbe similarity networks to learn valuable features for drugs and microbes respectively. Experimental results on three different datasets showed that our GCNMDA model consistently achieved better performance than seven state-of-the-art methods. Case studies for three microbes including SARS-CoV-2 and two antimicrobial drugs (i.e., Ciprofloxacin and Moxifloxacin) further confirmed the effectiveness of GCNMDA in identifying potential microbe-drug associations.

Availability

Python codes and dataset are available at: https://github.com/longyahui/GCNMDA.

Supplementary information

Supplementary data are available at Bioinformatics online.

Chemistry, Biological Properties and Analytical Methods of Levonadifloxacin: A Review

Increased use of antibiotics globally has led to the threat of antibiotic resistance; this drove the urge of researchers toward discovering more potent and broad-spectrum antibiotics. Levonadifloxacin (LND) is the very first antibiotic developed by an Indian company Wockhardt. It is S (-) isomer of another broad-spectrum antibiotic Nadifloxacin which is used topically for skin, soft tissue bacterial infection. LND belongs to the benzo quinolizine category which is a subclass of fluoroquinolone, indicated for ABSSIS, CABP, and other infections including diabetic foot infection; formulated as l-arginine salt of levonadifloxacin (WCK177) for IV and l-alanine ester mesylate salt as alalevonadifloxacin (WCK2349) for oral administration. It generally shows dominant antibacterial activity against Gram-negative, and positive bacterial infections, particularly toward methicillin-resistant Staphylococcus aureus (MRSA) by dual inhibition of DNA gyrase and topoisomerase IV. Producing quality product that complies to regulatory requirements is a big concern for pharma industries. To this context, validated analytical methods for routine quality control are essential for quantification of LND as an API alone and together with pharmaceutical formulations. This review suggests therapeutic, pharmacological, and analytical aspects regarding the novel drug LND and particularly focuses on discussing various reported analytical methods present for analytical or bioanalytical estimation of the drug and suggest to develop a simple and validated method which also complies to green chemistry.

A comparative assessment of clinical, pharmacological and antimicrobial profile of novel anti-methicillin-resistant Staphylococcus aureus agent levonadifloxacin: Therapeutic role in nosocomial and community infections

Staphylococcus aureus is of significant clinical concern in both community- and hospital-onset infections. The key to the success of S. aureus as a pathogen is its ability to swiftly develop antimicrobial resistance. Methicillin-resistant S. aureus (MRSA) is not only resistant to nearly all beta-lactams but also demonstrates resistance to several classes of antibiotics. A high prevalence of MRSA is seen across worldwide. For many decades, vancomycin remained as gold standard antibiotic for the treatment of MRSA infections. In the past decades, linezolid, daptomycin, ceftaroline and telavancin received regulatory approval for the treatment of infections caused by resistant Gram-positive pathogens. Although these drugs may offer some advantages over vancomycin, they also have significant limitations. These includes vancomycin's slow bactericidal activity, poor lung penetration and nephrotxicity;linezolid therapy induced myelosuppression and high cost of daptomycin greatly limits their clinical use. Moreover, daptomycin also gets inactivated by lung naturally occurring surfactants. Thus, currently available therapeutic options are unable to provide safe and efficacious treatment for those patients suffering from hospital-acquired pneumonia, bloodstream infections (BSIs), bone and joint infections and diabetic foot infections (DFI). An unmet need also exists for a safe and efficacious oral option for switch-over convenience and community treatment. Herein, the review is intended to describe the supporting role of anti-staphylococcal antibiotics used in the management of S. aureus infections with a special reference to levonadifloxacin. Levonadifloxacin and its prodrug alalevonadifloxacin are novel benzoquinolizine subclass of quinolone with broad-spectrum of anti-MRSA activity. It has been recently approved for the treatment of complicated skin and soft-tissue infection as well as concurrent bacteraemia and DFI in India.