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Mycobacterium tuberculosis (Mtb) exists in various metabolic states, including a nonreplicating persister (NRP) phenotype which may affect response to therapy. We have adopted a model-informed strategy to accelerate discovery of effective Mtb treatment regimens and previously found pretomanid (PMD), moxifloxacin (MXF), and bedaquiline (BDQ) to readily kill logarithmic- and acid-phase Mtb. Here, we studied multiple concentrations of each drug in flask-based, time-kill studies against NRP Mtb in single-, two- and three-drug combinations, including the active M2 metabolite of BDQ. We used nonparametric population algorithms in the Pmetrics package for R to model the data and to simulate the 95% confidence interval of bacterial population decline due to the two-drug combination regimen of PMD + MXF and compared this to observed declines with three-drug regimens. PMD + MXF at concentrations equivalent to average or peak human concentrations effectively eradicated Mtb. Unlike other states for Mtb, we observed no sustained emergence of less susceptible isolates for any regimen. The addition of BDQ as a third drug significantly (P < 0.05) shortened time to total bacterial suppression by 3 days compared to the two-drug regimen, similar to our findings for Mtb in logarithmic or acid growth phases.

Mycobacterium tuberculosis metabolic state affects the response to therapy. Quantifying the effect of antimicrobials in the acid and nonreplicating metabolic phases of M. tuberculosis growth will help to optimize therapy for tuberculosis. As a brute-force approach to all possible drug combinations against M. tuberculosis in all different metabolic states is impossible, we have adopted a model-informed strategy to accelerate the discovery. Using multiple concentrations of each drug in time-kill studies, we examined single drugs and two- and three-drug combinations of pretomanid, moxifloxacin, and bedaquiline plus its active metabolite against M. tuberculosis in its acid-phase metabolic state. We used a nonparametric modeling approach to generate full distributions of interaction terms between pretomanid and moxifloxacin for susceptible and less susceptible populations. From the model, we could predict the 95% confidence interval of the simulated total bacterial population decline due to the 2-drug combination regimen of pretomanid and moxifloxacin and compare this to observed declines with 3-drug regimens. We found that the combination of pretomanid and moxifloxacin at concentrations equivalent to average or peak human concentrations effectively eradicated M. tuberculosis in its acid growth phase and prevented emergence of less susceptible isolates. The addition of bedaquiline as a third drug shortened time to total and less susceptible bacterial suppression by 8 days compared to the 2-drug regimen, which was significantly faster than the 2-drug kill.

Dose-range studies for polymyxin B (PMB) regimens of 0.75 to 12 mg/kg given every 12h (Q12h) were evaluated for bacterial killing and resistance prevention against an AmpC-overexpressing Pseudomonas aeruginosa (PA) and a blaKPC-3-harboring Klebsiella pneumoniae (KP) in 10-day in-vitro hollow fiber models. An exposure-response was observed. But all regimens failed due to regrowth. Lower-dose regimens amplified isolates that expressed transient, lower-level adaptive resistance to PMB (MICs: ≤ 4 mg/L). Higher PMB dosages amplified isolates that expressed this resistance mechanism, a higher-MIC "moderately stable" adaptive resistance, and a higher-MIC stable resistance to PMB. Failure of the highest dose regimens was solely due to subpopulations that expressed the two higher-level resistances. Total and bioactive PMB concentrations in broth declined below targeted PK profiles within hours of treatment initiation and prior to bacterial regrowth. With treatment failure, the total PMB measured in bacteria were substantially higher than in broth. But the bioactive PMB in broth and bacteria were low to non-detectable. Together these findings suggest a sequence of events for treatment failure of the clinical regimen. First, PMB concentrations in broth are diluted as PMB binds to bacteria, resulting in total and bioactive PMB in broth that are lower than targeted. Bacterial regrowth and treatment failure follow, with emergence of subpopulations that express transient lower-level adaptive resistance to PMB and possibly higher-level adaptive and stable resistances. Higher-dose PMB regimens can prevent the emergence of transient lower-level adaptive resistance but they do not prevent treatment failure due to isolates that express higher-level resistance mechanisms.

In recent years, clofazimine (CFZ) has been regaining prominence for the treatment of tuberculosis. However, it shows limited efficacy as a single drug and optimal combination partners have not been identified. Therefore, the objective of our analysis was to evaluate the efficacy of CFZ-containing two-drug regimens with pretomanid (PMD), bedaquiline (BDQ) or linezolid (LZD) by: (i) determining their pharmacodynamic (PD) mode of interaction against Mycobacterium tuberculosis (Mtb) strain H37Rv in log- phase and acid-phase metabolic states, and against Mtb strain 18b in a non-replicating persister (NRP) metabolic state; (ii) predicting bacterial cell kill of the drugs alone and in combination; and (iii) evaluating the relationship between the interaction mode and the extent of bacterial cell kill. The results of our Greco universal response surface analysis showed that CFZ was at least additive with a clear trend towards synergy when combined with PMD, BDQ and LZD against Mtb in all explored metabolic states under in vitro checkerboard assay conditions. The results further showed that all two-drug combination regimens exerted greater bacterial kill than any of the drugs alone. CFZ alone showed the least antimicrobial efficacy amongst the evaluated drugs, and there was a lack of correlation between the mode of interaction and the extent of bacterial kill. However, we may underestimate the effect of CFZ in this screening approach owing to limited in vitro study duration and neglect of target site accumulation. Clofazimine; Pretomanid; Bedaquiline; Linezolid; Combination chemotherapy; Mycobacterium tuberculosis.

The Mycobacterium tuberculosis drug discovery effort has generated a substantial number of new/repurposed drugs for therapy for this pathogen. The arrival of these drugs is welcome, but another layer of difficulty has emerged. Single agent therapy is insufficient for patients with late-stage tuberculosis because of resistance emergence. To achieve our therapeutic ends, it is requisite to identify optimal combination regimens. These regimens go through a lengthy and expensive evaluative process. If we have a modest group of 6 to 8 new or repurposed agents, this translates into 15 to 28 possible 2-drug combinations. There is neither time nor resources to give an extensive evaluation for all combinations. We sought a screening procedure that would identify combinations that had a high likelihood of achieving good bacterial burden decline. We examined pretomanid, moxifloxacin, linezolid, and bedaquiline in log-phase growth, acid-phase growth, and nonreplicative persister (NRP) phase in the Greco interaction model. We employed the interaction term α and the calculated bacterial burden decline as metrics to rank different regimens in different metabolic states. No relationship was found between α and bacterial kill. We chose bacterial kill as the prime metric. The combination of pretomanid plus moxifloxacin emerged as the clear frontrunner, as the largest bacterial declines were seen in log phase and acid phase with this regimen and it was second best in NRP phase. Bedaquiline also produced good kill. This screening process may identify optimal combinations that can be further evaluated in both the hollow-fiber infection model and in animal models of Mycobacterium tuberculosis infection.

Multidrug therapy is often required. Examples include antiviral therapy, nosocomial infections, and, most commonly, anti-Mycobacterium tuberculosis therapy. Our laboratory previously identified a mathematical approach to identify 2-drug regimens with a synergistic or additive interaction using a full factorial study design. Our objective here was to generate a method to identify an optimal 3-drug therapy. We studied M. tuberculosis isolate H37Rv in log-phase growth in flasks. Pretomanid and moxifloxacin were chosen as the base 2-drug regimen. Bedaquiline (plus M2 metabolite) was chosen as the third drug for evaluation. Total bacterial burden and bacterial burden less-susceptible to study drugs were enumerated. A large mathematical model was fit to all the data. This allowed extension to evaluation of the 3-drug regimen by employing a Monte Carlo simulation. Pretomanid plus moxifloxacin demonstrated excellent bacterial kill and suppressed amplification of less-susceptible pathogens. Total bacterial burden was driven to extinction in 3 weeks in 6 of 9 combination therapy evaluations. Only the lowest pretomanid/moxifloxacin exposures in combination did not extinguish the bacterial burden. No combination regimen allowed resistance amplification. Generation of 95% credible intervals about estimates of the interaction parameters α (α(s), α(r-p), and α(r-m)) by bootstrapping showed the interaction was near synergistic. The addition of bedaquiline/M2 metabolite was evaluated by forming a 95% confidence interval regarding the decline in bacterial burden. The addition of bedaquiline/M2 metabolite shortened the time to eradication by 1 week and was significantly different. A model-based system approach to evaluating combinations of 3 agents shows promise to rapidly identify the most promising combinations that can then be trialed.

Combination therapy is a successful approach to treat tuberculosis in patients with susceptible strains of Mycobacterium tuberculosis However, the emergence of resistant strains requires identification of new, effective therapies. Pretomanid (PA824) and moxifloxacin (MXF) are promising options currently under evaluation in clinical trials for the treatment of susceptible and resistant mycobacteria. We applied our recently described screening strategy to characterize the interaction between PA824 and MXF toward the killing of M. tuberculosis in logarithmic growth phase (log phase), acid phase, and nonreplicating-persister (NRP) phase. Respective in vitro data generated for the H37Rv and 18b strains were evaluated in a microdilution plate system containing both drugs in combination. The Universal Response Surface Approach model from Greco et al. (W. R. Greco, G. Bravo, and J. C. Parsons, Pharmacol Rev 47:331-385, 1995) was used to characterize the nature of the interaction between both drugs; synergistic or additive combinations would prompt additional evaluation in the hollow-fiber infection model (HFIM) and in animal studies. The interaction between MXF and PA824 was additive against M. tuberculosis organisms in acid phase (interaction parameter [α] = 5.56e-8 [95% confidence interval {CI} = -0.278 to 0.278] and α = 0.408 [95% CI = 0.105 to 0.711], respectively), NRP phase (α = 0.625 [95% CI = -0.556 to 1.81] and α = 2.92 [95% CI = 0.215 to 5.63], respectively), and log phase (α = 1.57e-6 [95% CI = -0.930 to 0.930] and α = 1.83e-6 [95% CI = -0.929 and 0.929], respectively), prompting further testing of this promising combination for the treatment of tuberculosis in the HFIM and in animal studies.

A major goal for improving tuberculosis therapy is to identify drug regimens with improved efficacy and shorter treatment durations. Shorter therapies improve patient adherence to the antibiotic regimens that, in turn, decreases resistance emergence. M. tuberculosis exists in multiple metabolic states. At the initiation of therapy, the bulk of the population is in Log-Phase growth. Consequently, it is logical to focus initial therapy on these organisms. Moxifloxacin has good early bactericidal activity against Log-Phase growth bacteria and is a logical component of initial therapy. It would be optimal if this agent also possessed activity against Acid-Phase and Non-Replicative Persister (NRP) Phenotype organisms. We studied multiple exposures to moxifloxacin (equivalent to 200 mg-800 mg daily) in our Hollow Fiber Infection Model against strain H37Rv in Acid-Phase and against strain 18b in streptomycin starvation, which is a model for NRP-Phase organisms. Moxifloxacin possesses good activity against Acid-Phase organisms, generating from 3.75 Log 10 (CFU/ml) cell kill (200 mg daily) to 5.16 Log 10 (CFU/ml) cell kill (800 mg daily) over the 28 days of the experiment. Moxifloxacin also has activity against the streptomycin-starved strain 18b. The 400 to 800 mg daily regimens achieved extinction at day 28, while the no-treatment control still had 1.96 Log 10 (CFU/ml) culturable. The lowest dose (200 mg daily) still had 0.7 Log 10 (CFU/ml) measurable at day 28, a net kill of 1.26 Log 10 (CFU/ml). Moxifloxacin is an attractive agent for early therapy, as it possesses activity against three metabolic states of M. tuberculosis .

Combination therapy is a successful approach to treat tuberculosis in patients with susceptible strains of Mycobacterium tuberculosis. However, the emergence of resistant strains requires identification of new, effective therapies. Pretomanid (PA824) and moxifloxacin (MXF) are promising options currently under evaluation in clinical trials for the treatment of susceptible and resistant mycobacteria. We applied our recently described screening strategy to characterize the interaction between PA824 and MXF toward the killing of M. tuberculosis in logarithmic growth phase (log phase), acid phase, and nonreplicating-persister (NRP) phase. Respective in vitro data generated for the H37Rv and 18b strains were evaluated in a microdilution plate system containing both drugs in combination. The Universal Response Surface Approach model from Greco et al. (W. R. Greco, G. Bravo, and J. C. Parsons, Pharmacol Rev 47:331–385, 1995) was used to characterize the nature of the interaction between both drugs; synergistic or additive combinations would prompt additional evaluation in the hollow-fiber infection model (HFIM) and in animal studies. The interaction between MXF and PA824 was additive against M. tuberculosis organisms in acid phase (interaction parameter [α] = 5.56e−8 [95% confidence interval {CI} = −0.278 to 0.278] and α = 0.408 [95% CI = 0.105 to 0.711], respectively), NRP phase (α = 0.625 [95% CI = −0.556 to 1.81] and α = 2.92 [95% CI = 0.215 to 5.63], respectively), and log phase (α = 1.57e−6 [95% CI = −0.930 to 0.930] and α = 1.83e−6 [95% CI = −0.929 and 0.929], respectively), prompting further testing of this promising combination for the treatment of tuberculosis in the HFIM and in animal studies.

Tuberculosis is the ninth-leading cause of death worldwide. Treatment success is approximately 80% for susceptible strains and decreases to 30% for extensively resistant strains. Shortening the therapy duration for Mycobacterium tuberculosis is a major goal, which can be attained with the use of combination therapy. However, the identification of the most promising combination is a challenge given the quantity of older and newer agents available. Our objective was to identify promising 2-drug combinations using an in vitro strategy to ultimately be tested in an in vitro hollow fiber infection model (HFIM) and in animal models. We studied the effect of the combination of linezolid (LZD) and bedaquiline (BDQ) on M. tuberculosis strain H37Rv in log- and acid-phase growth and M. tuberculosis strain 18b in log- and nonreplicating-persister-phase growth in a plate system containing a 9-by-8 matrix of concentrations of both drugs alone and in combinations. A characterization of the interaction as antagonistic, additive, or synergistic was performed using the Greco universal response surface approach (URSA) model. Our results indicate that the interaction between LZD and BDQ is additive for bacterial killing in both strains for both of the metabolic states tested. This prescreen strategy was suitable to identify LZD and BDQ as a promising combination to be further tested in the HFIM. The presence of nonoverlapping mechanisms of drug action suggests each drug in the combination will likely be effective in suppressing the emergence of resistance by M. tuberculosis to the companion drug, which holds promise in improving treatment outcomes for tuberculosis.

The therapy for treatment of Mycobacterium tuberculosis infections is long and arduous. It has been hypothesized that the therapy duration is driven primarily by populations of organisms in different metabolic states that replicate slowly or not at all (acid-phase and nonreplicative-persister [NRP]-phase organisms). Linezolid is an oxazolidinone antimicrobial with substantial activity against Log-phase M. tuberculosis . Here, we examined organisms in acid-phase growth and nonreplicative-persister-phenotype growth and determined the effect of differing clinically relevant exposures to linezolid in a hollow-fiber infection model (HFIM). The endpoints measured were bacterial kill over 29 days and whether organisms that were less susceptible to linezolid could be recovered during that period. In addition, we evaluated the effect of administration schedule on linezolid activity, contrasting daily administration with administration of twice the daily dose every other day. Linezolid demonstrated robust activity when administered daily against both acid-phase and NRP-phase organisms. We demonstrated a clear dose response, with 900 mg of linezolid daily generating ≥3 Log(CFU/ml) killing of acid-phase and NRP-phase M. tuberculosis over 29 days. Amplification of a population less susceptible to linezolid was not seen. Activity was reduced with every 48-h dosing, indicating that the minimum concentration ( C min )/MIC ratio drove the microbiological effect. We conclude that once-daily linezolid dosing has substantial activity against M. tuberculosis in acid-phase and NRP-phase metabolic states. Other studies have shown activity against Log-phase M. tuberculosis . Linezolid is a valuable addition to the therapeutic armamentarium for M. tuberculosis and has the potential for substantially shortening therapy duration.

Fosfomycin is the only expoxide antimicrobial and is currently under development in the United States as an intravenously administered product. We were interested in identifying the exposure indices most closely linked to its ability to kill bacterial cells and to suppress amplification of less susceptible subpopulations. We employed the hollow fiber infection model for this investigation and studied wild-type strain Pseudomonas aeruginosa PAO1. Because of anticipated rapid resistance emergence, we shortened the study duration to 24 h but sampled the system more intensively. Doses of 12 and 18 g/day and schedules of daily administration, administration every 8 h, and administration by continuous infusion for each daily dose were studied. We measured fosfomycin concentrations (by liquid chromatography-tandem mass spectrometry), the total bacterial burden, and the burden of less susceptible isolates. We applied a mathematical model to all the data simultaneously. There was a rapid emergence of resistance with all doses and schedules. Prior to resistance emergence, an initial kill of 2 to 3 log 10 (CFU/ml) was observed. The model demonstrated that the area under the concentration-time curve/MIC ratio was linked to total bacterial kill, while the time that the concentration remained above the MIC (or, equivalently, the minimum concentration/MIC ratio) was linked to resistance suppression. These findings were also seen in other investigations with Enterobacteriaceae ( in vitro systems) and P. aeruginosa (murine system). We conclude that for serious infections with high bacterial burdens, fosfomycin may be of value as a new therapeutic and may be optimized by administering the agent as a continuous or prolonged infusion or by use of a short dosing interval. For indications such as ventilator-associated bacterial pneumonia, it may be prudent to administer fosfomycin as part of a combination regimen.