A Quantitative Method for the Study of HIV-1 and Mycobacterium tuberculosis Coinfection.

Mycobacterium tuberculosis and human immunodeficiency virus-1 (HIV-1) syndemic interactions are a major global health concern. Despite the clinical significance of coinfection, our understanding of the cellular pathophysiology and the therapeutic pharmacodynamic impact of coinfection is limited. Here, we use single-round infectious HIV-1 pseudotyped viral particles expressing green fluorescent protein alongside M. tuberculosis expressing mCherry to study pathogenesis and treatment. We report that HIV-1 infection inhibited intracellular replication of M. tuberculosis and demonstrate the therapeutic activity of antiviral treatment (efavirenz) and antimicrobial treatment (rifampicin). The described method could be applied for detailed mechanistic studies to inform the development of novel treatment strategies.

Intracellular Pharmacodynamic Modeling Is Predictive of the Clinical Activity of Fluoroquinolones against Tuberculosis.

Clinical studies of new antitubercular drugs are costly and time-consuming. Owing to the extensive tuberculosis (TB) treatment periods, the ability to identify drug candidates based on their predicted clinical efficacy is vital to accelerate the pipeline of new therapies. Recent failures of preclinical models in predicting the activity of fluoroquinolones underline the importance of developing new and more robust predictive tools that will optimize the design of future trials. Here, we used high-content imaging screening and pharmacodynamic intracellular (PDi) modeling to identify and prioritize fluoroquinolones for TB treatment. In a set of studies designed to validate this approach, we show moxifloxacin to be the most effective fluoroquinolone, and PDi modeling-based Monte Carlo simulations accurately predict negative culture conversion (sputum sterilization) rates compared to eight independent clinical trials. In addition, PDi-based simulations were used to predict the risk of relapse. Our analyses show that the duration of treatment following culture conversion can be used to predict the relapse rate. These data further support that PDi-based modeling offers a much-needed decision-making tool for the TB drug development pipeline.

Remdesivir-ivermectin combination displays synergistic interaction with improved in vitro activity against SARS-CoV-2.

A key element for the prevention and management of coronavirus disease 2019 is the development of effective therapeutics. Drug combination strategies offer several advantages over monotherapies. They have the potential to achieve greater efficacy, to increase the therapeutic index of drugs and to reduce the emergence of drug resistance. We assessed the in vitro synergistic interaction between remdesivir and ivermectin, both approved by the US Food and Drug Administration, and demonstrated enhanced antiviral activity against severe acute respiratory syndrome coronavirus-2. Whilst the in vitro synergistic activity reported here does not support the clinical application of this combination treatment strategy due to insufficient exposure of ivermectin in vivo, the data do warrant further investigation. Efforts to define the mechanisms underpinning the observed synergistic action could lead to the development of novel treatment strategies.

Measurement of the Intracellular Mycobacterium tuberculosis Drug Effect and Prediction of the Clinical Dose-Response Relationship Using Intracellular Pharmacodynamic Modeling (PDi).

The human disease tuberculosis (TB) is the leading cause of death from a single infectious agent. A quarter of the world's population is estimated to be latently infected. Drug development and screening is slow and costly. We have developed a physiologically relevant assay to screen drugs against TB when inside immune cells. This chapter will describe a newly developed preclinical drug screening assay for TB, using high-content imaging and pharmacokinetic/pharmacodynamic modeling.

Intracellular PD Modelling (PDi) for the Prediction of Clinical Activity of Increased Rifampicin Dosing.

Increasing rifampicin (RIF) dosages could significantly reduce tuberculosis (TB) treatment durations. Understanding the pharmacokinetic-pharmacodynamics (PK-PD) of increasing RIF dosages could inform clinical regimen selection. We used intracellular PD modelling (PDi) to predict clinical outcomes, primarily time to culture conversion, of increasing RIF dosages. PDi modelling utilizes in vitro-derived measurements of intracellular (macrophage) and extracellular Mycobacterium tuberculosis sterilization rates to predict the clinical outcomes of RIF at increasing doses. We evaluated PDi simulations against recent clinical data from a high dose (35 mg/kg per day) RIF phase II clinical trial. PDi-based simulations closely predicted the observed time-to-patient culture conversion status at eight weeks (hazard ratio: 2.04 (predicted) vs. 2.06 (observed)) for high dose RIF-based treatments. However, PDi modelling was less predictive of culture conversion status at 26 weeks for high-dosage RIF (99% predicted vs. 81% observed). PDi-based simulations indicate that increasing RIF beyond 35 mg/kg/day is unlikely to significantly improve culture conversion rates, however, improvements to other clinical outcomes (e.g., relapse rates) cannot be ruled out. This study supports the value of translational PDi-based modelling in predicting culture conversion rates for antitubercular therapies and highlights the potential value of this platform for the improved design of future clinical trials.

Pharmacokinetic-Pharmacodynamic modelling of intracellular Mycobacterium tuberculosis growth and kill rates is predictive of clinical treatment duration.

Tuberculosis (TB) treatment is long and complex, typically involving a combination of drugs taken for 6 months. Improved drug regimens to shorten and simplify treatment are urgently required, however a major challenge to TB drug development is the lack of predictive pre-clinical tools. To address this deficiency, we have adopted a new high-content imaging-based approach capable of defining the killing kinetics of first line anti-TB drugs against intracellular Mycobacterium tuberculosis (Mtb) residing inside macrophages. Through use of this pharmacokinetic-pharmacodynamic (PK-PD) approach we demonstrate that the killing dynamics of the intracellular Mtb sub-population is critical to predicting clinical TB treatment duration. Integrated modelling of intracellular Mtb killing alongside conventional extracellular Mtb killing data, generates the biphasic responses typical of those described clinically. Our model supports the hypothesis that the use of higher doses of rifampicin (35 mg/kg) will significantly reduce treatment duration. Our described PK-PD approach offers a much needed decision making tool for the identification and prioritisation of new therapies which have the potential to reduce TB treatment duration.

A rapid screening assay for identifying mycobacteria targeted nanoparticle antibiotics.

Antibiotic resistance is a serious problem. Nanotechnology offers enormous potential in medicine, yet there is limited knowledge regarding the toxicity of nanoparticles (NP) for mycobacterial species that cause serious human diseases (e.g. tuberculosis (TB) and leprosy). Mycobacterial diseases are a major global health problem; TB caused by Mycobacterium tuberculosis (Mtb) kills up to 2 million people annually and there are over 200 000 leprosy cases each year caused by Mycobacterium leprae (M. leprae). Few drugs are effective against these mycobacteria and increasing antibiotic resistance exacerbates the problem. As such, alternative therapies are urgently needed but most current assays used to assess the effectiveness of therapeutics against mycobacteria are slow and expensive. This study aimed to develop a rapid, low-cost assay which can be used for screening the antimicrobial properties of compounds against pathogenic mycobacteria and to assess the toxicity of three NP (silver [Ag], copper oxide [Cu(II)O], and zinc oxide [ZnO]) against a green fluorescent protein reporter strain of Mycobacterium avium subspecies paratuberculosis, a slow growing, pathogenic mycobacterial species causing paratuberculosis in ruminants. Fluorescence was used to monitor mycobacterial growth over time, with NP concentrations of 6.25-100 µg/mL tested for up to 7 days, and a method of data analysis was designed to permit comparison between results. Mycobacterial sensitivity to the NP was found to be NP composition specific and toxicity could be ranked in the following order: Ag > Cu(II)O > ZnO.