Highlights d Comprehensive dataset of TB drug combination responses in multiple in vitro models d Computational modeling predicts mouse treatment outcome based on in vitro data d Ensembles of in vitro models predict treatment outcomes in in vivo environments d In vitro drug combination potencies predict outcomes in a relapsing mouse model

A lengthy multidrug chemotherapy is required to achieve a durable cure in tuberculosis. Variation in Mycobacterium tuberculosis drug response is created by the differing microenvironments in lesions, which create different bacterial drug susceptibilities. To better realize the potential of combination therapy to shorten treatment duration, multidrug therapy design should deliberately explore the vast combination space. We face a significant scaling challenge in making systematic drug combination measurements because it is not practical to use animal models for comprehensive drug combination studies, nor are there well validated high-throughput in vitro models that predict animal outcomes. We hypothesized that we could both prioritize combination therapies and quantify the predictive power of various in vitro models for drug development using a dataset of drug combination dose responses measured in multiple in vitro models. We systematically measured M. tuberculosis response to all 2- and 3-drug combinations among ten antibiotics in eight conditions that reproduce lesion microenvironments. Applying machine learning to this comprehensive dataset, we developed classifiers predictive of multidrug treatment outcome in a mouse model of disease relapse. We trained classifiers on multiple mouse models and identified ensembles of in vitro models that best describe in vivo treatment outcomes. Furthermore, we found that combination synergies are less important for predicting outcome than metrics of potency. Here, we map a path forward to rationally prioritize combinations for animal and clinical studies using systematic drug combination measurements with validated in vitro models. Our pipeline is generalizable to other difficult-to-treat diseases requiring combination therapies.

No abstract

SQ109 is a novel well-tolerated drug candidate in clinical development for the treatment of drug resistant tuberculosis (TB). It is the only inhibitor of the MmpL3 mycolic acid transporter in clinical development. No SQ109 resistant mutant has been directly isolated thus far, in vitro, in mice or in patients, tentatively attributed to its multiple targets. It is considered as a potential replacement for poorly tolerated components of multidrug-resistant TB regimens. To prioritize SQ109-containing combinations with best potential for cure and treatment shortening, one must understand its contribution against different bacterial populations in pulmonary lesions. Here we have characterized the pharmacokinetics of SQ109 in the rabbit model of active TB and its penetration at the sites of disease: lung tissue, cellular and necrotic lesions, and caseum. A two-compartment model with first-order absorption and elimination described the plasma pharmacokinetics. At the human-equivalent dose, parameter estimates fell within the ranges published for preclinical species. Tissue concentrations were modelled using an "effect" compartment, showing high accumulation in lung and cellular lesion areas with penetration coefficients in excess of 1,000, and lower passive diffusion in caseum after 7 daily doses. These results, together with the hydrophobic nature and high non-specific caseum binding of SQ109, suggest that multi-week dosing would be required to reach steady state in caseum and poorly vascularized compartments, similar to bedaquiline. Linking lesion pharmacokinetics to SQ109 potency in assays against replicating, non-replicating, and intracellular M. tuberculosis showed SQ109 concentrations markedly above pharmacokinetic-pharmacodynamic targets in lung and cellular lesions throughout the dosing interval. IMPORTANCE Drug-resistant tuberculosis (TB) accounts for over 20% of all fatalities due to drug-resistant pathogens. With recently approved drugs and a promising drug candidate pipeline, the challenge faced by clinical developers is prioritization of drug combinations with the best potential to improve cure rates and shorten treatment duration. To this end, one must understand the contribution of each partner drug against different bacterial populations in pulmonary TB lesions. SQ109 is a safe drug candidate in clinical development for the treatment of multidrug resistant TB. It is active against replicating and non-replicating Mycobacterium tuberculosis persisters in vitro, in mouse models and in patients. SQ109 exhibits extremely low frequency of resistance, unprecedented among all TB drugs so far. Here we characterize the pharmacokinetics and activity of SQ109 at the site of TB disease to inform the selection of drug regimens that account for its lesion-centric pharmacokinetic-pharmacodynamic parameters and best leverage its contribution to efficient disease cure.

No abstract