Building optimal 3-drug combination chemotherapy regimens to eradicate Mycobacterium tuberculosis in its slow growth acid phase

Predicting tuberculosis drug efficacy in preclinical and clinical models from in vitro data

Multiple in vitro potency assays are used to evaluate compounds against Mycobacterium tuberculosis, but a consensus on clinically relevant assays is lacking. We aimed to identify an in vitro assay signature that predicts preclinical efficacy and early clinical outcome. Thirty-one unique in vitro assays were compiled for 10 TB drugs. In vitro EC50 values were compared to pharmacokinetic-pharmacodynamic (PK-PD)-model-derived EC50 values from mice evaluated via multinomial regression. External validation of best-performing in vitro assay combinations was performed using five new TB drugs. Best-performing assay signatures for acute and subacute infections were described by assays that reproduce conditions found in macrophages and foamy macrophages and chronic infection by the ex vivo caseum assay. Subsequent simulated mouse bacterial burden over time using predicted in vivo EC50 was within 2-fold of observations. This study helps us identify clinically relevant assays and prioritize successful drug candidates, saving resources and accelerating clinical success.

Predictions of Bedaquiline and Pretomanid Target Attainment in Lung Lesions of Tuberculosis Patients using Translational Minimal Physiologically Based Pharmacokinetic Modeling

BACKGROUND

Site-of-action concentrations for bedaquiline and pretomanid from tuberculosis patients are unavailable. The objective of this work was to predict bedaquiline and pretomanid site-of-action exposures using a translational minimal physiologically based pharmacokinetic (mPBPK) approach to understand the probability of target attainment (PTA).

METHODS

A general translational mPBPK framework for the prediction of lung and lung lesion exposure was developed and validated using pyrazinamide site-of-action data from mice and humans. We then implemented the framework for bedaquiline and pretomanid. Simulations were conducted to predict site-of-action exposures following standard bedaquiline and pretomanid, and bedaquiline once-daily dosing. Probabilities of average concentrations within lesions and lungs greater than the minimum bactericidal concentration for non-replicating (MBCNR) and replicating (MBCR) bacteria were calculated. Effects of patient-specific differences on target attainment were evaluated.

RESULTS

The translational modeling approach was successful in predicting pyrazinamide lung concentrations from mice to patients. We predicted that 94% and 53% of patients would attain bedaquiline average daily PK exposure within lesions (Cavg-lesion) > MBCNR during the extensive phase of bedaquiline standard (2 weeks) and once-daily (8 weeks) dosing, respectively. Less than 5% of patients were predicted to achieve Cavg-lesion > MBCNR during the continuation phase of bedaquiline or pretomanid treatment, and more than 80% of patients were predicted to achieve Cavg-lung >MBCR for all simulated dosing regimens of bedaquiline and pretomanid.

CONCLUSIONS

The translational mPBPK model predicted that the standard bedaquiline continuation phase and standard pretomanid dosing may not achieve optimal exposures to eradicate non-replicating bacteria in most patients.

Pharmacodynamics and Bactericidal Activity of Combination Regimens in Pulmonary Tuberculosis: Application to Bedaquiline-Pretomanid-Pyrazinamide

A critical barrier to codevelopment of tuberculosis (TB) regimens is a limited ability to identify optimal drug and dose combinations in early-phase clinical testing. While pharmacokinetic-pharmacodynamic (PKPD) target attainment is the primary tool for exposure-response optimization of TB drugs, the PD target is a static index that does not distinguish individual drug contributions to the efficacy of a multidrug combination. A PKPD model of bedaquiline-pretomanid-pyrazinamide (BPaZ) for the treatment of pulmonary TB was developed as part of a dynamic exposure-response approach to regimen development. The model describes a time course relationship between the drug concentrations in plasma and their individual as well as their combined effect on sputum bacillary load assessed by solid culture CFU counts and liquid culture time to positivity (TTP). The model parameters were estimated using data from the phase 2A studies NC-001-(J-M-Pa-Z) and NC-003-(C-J-Pa-Z). The results included a characterization of BPaZ activity as the most and least sensitive to changes in pyrazinamide and bedaquiline exposures, respectively, with antagonistic activity of BPa compensated by synergistic activity of BZ and PaZ. Simulations of the NC-003 study population with once-daily bedaquiline at 200 mg, pretomanid at 200 mg, and pyrazinamide at 1,500 mg showed BPaZ would require 3 months to attain liquid culture negativity in 90% of participants. These results for BPaZ were intended to be an example application with the general approach aimed at entirely novel drug combinations from a growing pipeline of new and repurposed TB drugs.

Combination Therapy to Kill Mycobacterium tuberculosis in Its Nonreplicating Persister Phenotype

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.

Evaluating the effect of clofazimine against Mycobacterium tuberculosis when given alone or in combination with pretomanid, bedaquiline or linezolid

Clofazimine (CFZ) has been regaining prominence for treating tuberculosis in recent years. However, as a single drug, it shows limited efficacy and optimal combination partners have not been identified. Therefore, the objective of our analysis was to evaluate the efficacy of CFZ-containing two-drug regimen with pretomanid (PMD), bedaquiline (BDQ) or linezolid (LZD) by determining: i) their pharmacodynamic (PD) mode of interaction against Mycobacterium tuberculosis (Mtb) strain H37Rv in log- and acid-metabolic states, and Mtb strain 18b in a non-replicating persister metabolic state, ii) to predict bacterial cell kill of the drugs alone and in combination, and iii) to evaluate the relationship between the interaction mode and bacterial cell kill amount. 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. They further showed that all 2-drug combination regimens exerted more 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 amount of bacterial kill. However, we may underestimate the effect of CFZ in this screening approach due to limited in vitro study duration and neglect of target site accumulation.