Anti-tuberculosis treatment strategies and drug development: challenges and priorities

Abstract

Despite two decades of intensified research to understand and cure tuberculosis disease, biological uncertainties remain and hamper progress. However, owing to collaborative initiatives including academia, the pharmaceutical industry and non-for-profit organizations, the drug candidate pipeline is promising. This exceptional success comes with the inherent challenge of prioritizing multidrug regimens for clinical trials and revamping trial designs to accelerate regimen development and capitalize on drug discovery breakthroughs. Most wanted are markers of progression from latent infection to active pulmonary disease, markers of drug response and predictors of relapse, in vitro tools to uncover synergies that translate clinically and animal models to reliably assess the treatment shortening potential of new regimens. In this Review, we highlight the benefits and challenges of 'one-size-fits-all' regimens and treatment duration versus individualized therapy based on disease severity and host and pathogen characteristics, considering scientific and operational perspectives.

Fig. 1. Global TB burden.

a | Incidence of tuberculosis (TB) per 100,000 population in 2020. Not applicable: WHO criteria for national prevalence survey not met. b | The top graphs represent the incidence of TB in South Africa, the Russian Federation and China from 1990 to 2020. Sub-Saharan Africa has been on an overall trajectory of increased incidence until 2010, mostly driven by the TB–HIV-1 epidemic and the 20-fold increased risk of reactivation in people positive for HIV-1. Initial increase in incidence and mortality in the Russian Federation coincides with the collapse of the Soviet Union and health-care system, which was brought under control after 2000. China has been on a consistent steady decline since 1990. The bottom graphs show the estimated impact of the COVID-19 pandemic on TB mortality in South Africa, the Russian Federation and China up to 2025. Plots were generated using publicly available TB burden data from WHO reports,^, and the World Bank database. Part b, top graphs, based on data from WHO global TB reports from 1990 to 2021 and adapted from the World Bank database, CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Part a and part b, bottom, adapted with permission from ref., WHO.

Fig. 2. TB infection, disease spectrum and associated challenges.

Tuberculosis (TB) presents as a spectrum along three axes: disease pathology and severity, bacterial persistence and drug tolerance, and genetic resistance. The pathology of TB disease is a dynamic continuum from fully latent asymptomatic infection to active disease with high bacterial burden in open cavities, leading to transmission and more frequent treatment failure. Individuals with latent TB infection who are progressing towards incipient TB are at high risk of developing active disease and would benefit from reactivation risk assessment and treatment. The spectrum of immunopathology creates a diversity of microenvironments to which the pathogen responds with metabolic and physiological adaptations leading to drug tolerance or phenotypic drug resistance and persistent disease. Drug tolerance as well as other patient and pathogen factors lead to a spectrum of genetic resistance both in terms of the number of drugs a bacterium is resistant to and the level of resistance to each drug. Such variability along three axes creates a gradient of decreased drug efficacy and lesion sterilization within and across patients, constitutes a multidimensional challenge for health-care programmes and complicates clinical trials.

Fig. 3. Anti-tuberculosis drug candidate pipeline and mechanism of drug action.

a | Shown are promising drug candidates currently in preclinical and clinical development, including the development of regimens that combine repurposed, repositioned and new drug classes. Approved drugs are indicated by an asterisk (delamanid was approved by the EMA only, and pretomanid was approved by the FDA for use in the bedaquiline–pretomanid–linezolid regimen). Drugs are colour coded by chemical class and target pathway. For a complete list of published candidates currently in the pipeline, from early preclinical development to regulatory approval, and a review of their mechanism of action, see Working Group on New TB Drugs and ref.. b | A simplified version of the cell envelope and the cytoplasmic membrane of Mycobacterium tuberculosis is shown with schematized versions of the targets of recently approved drugs and clinical candidates, with novel mechanisms of action, listed in part a. The majority of novel targets are membrane associated. The diarylquinolines bedaquiline, TBAJ-876 and TBAJ-587 target the ATP synthase. The nitroimidazoles pretomanid and delamanid exhibit a dual mode of action under low and normal oxygen tension, poison multiple essential pathways, and are bactericidal against replicating and non-replicating mycobacteria. SQ109 and the MPL series are the most advanced among a broad panel of agents targeting MmpL3, involved in export of trehalose monomycolate, a mycolic acid component. Three chemically distinct series all target DprE1: OPC167832, TBA7371 and BTZ043 (ref.). Both MmpL3 and DprE1 are unique to mycobacteria. GSK656 is the first oxaborole in clinical development targeting a mycobacterial tRNA synthetase and GSK286 is a new chemical entity with a novel mechanism of action related to cholesterol catabolism. Part b adapted from ref., Springer Nature Limited.

Fig. 4. Regimen prioritization.

Schematic illustration of the large number of possible combinations if drug candidates selected from 10 drug classes shown in Fig. 3 are combined in 3, 4 or 5 drug regimens (a minimum of 482 combinations assumes only 1 drug per class). In addition, owing to the varying drug doses, varying treatment durations and varying dosing frequencies, the number of clinical trial arms is within the thousands. Resource considerations underline the need for prioritization, using validated in vitro assays, drug interaction platforms, such as INDIGO or DiaMOND, pharmacokinetic (PK) and pharmacodynamic (PD) studies in preclinical species, and translational modelling tools, to select drug combinations with the highest potential to reduce treatment duration and improve cure in patients with tuberculosis, thus reducing the number of clinical trial arms to practical dimensions. New strategies, such as adaptive trial designs, doses and treatment duration tailored to patient characteristics, and longitudinal biomarkers of efficacy are required to accelerate the learning cycle, validate the in vitro and in vivo prioritization tools, and refine the computational approaches. Middle panel, top right, adapted from ref., Springer Nature Limited. Middle panel, bottom left, adapted from ref., Springer Nature Limited. Middle panel, top left, reprinted from ref., Springer Nature Limited.