A multi-scale pipeline linking drug transcriptomics with pharmacokinetics predicts in vivo interactions of tuberculosis drugs

JM Cicchese, A Sambarey, D Kirschner… - Scientific Reports, 2021 - nature.com
Tuberculosis (TB) is the deadliest infectious disease worldwide. The design of new
treatments for TB is hindered by the large number of candidate drugs, drug combinations …

Transcriptomic signatures predict regulators of drug synergy and clinical regimen efficacy against tuberculosis

S Ma, S Jaipalli, J Larkins-Ford, J Lohmiller… - MBio, 2019 - Am Soc Microbiol
The rapid spread of multidrug-resistant strains has created a pressing need for new drug
regimens to treat tuberculosis (TB), which kills 1.8 million people each year. Identifying new …

Pre-clinical tools for predicting drug efficacy in treatment of tuberculosis

H Margaryan, DD Evangelopoulos, L Muraro Wildner… - Microorganisms, 2022 - mdpi.com
Combination therapy has, to some extent, been successful in limiting the emergence of drug-
resistant tuberculosis. Drug combinations achieve this advantage by simultaneously acting …

Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis

V Srinivas, RA Ruiz, M Pan, SRC Immanuel… - Cell Reports …, 2021 - cell.com
There is an urgent need for new drug regimens to rapidly cure tuberculosis. Here, we report
the development of drug response assayer (DRonA) and" MLSynergy," algorithms to …

Development of new tuberculosis drugs: translation to regimen composition for drug-sensitive and multidrug-resistant tuberculosis

JP Ernest, N Strydom, Q Wang, N Zhang… - Annual review of …, 2021 - annualreviews.org
Tuberculosis (TB) kills more people than any other infectious disease. Challenges for
developing better treatments include the complex pathology due to within-host immune …

Systematic measurement of combination-drug landscapes to predict in vivo treatment outcomes for tuberculosis

J Larkins-Ford, T Greenstein, N Van, YN Degefu… - Cell systems, 2021 - cell.com
Lengthy multidrug chemotherapy is required to achieve a durable cure in tuberculosis.
However, we lack well-validated, high-throughput in vitro models that predict animal …

A multi-pronged computational pipeline for prioritizing drug target strategies for latent tuberculosis

U Banerjee, S Sankar, A Singh, N Chandra - Frontiers in chemistry, 2020 - frontiersin.org
Tuberculosis is one of the deadliest infectious diseases worldwide and the prevalence of
latent tuberculosis acts as a huge roadblock in the global effort to eradicate tuberculosis …

The implications of model-informed drug discovery and development for tuberculosis

M Muliaditan, GR Davies, USH Simonsson… - Drug Discovery …, 2017 - Elsevier
Highlights•Dose selection for new combination therapy in tuberculosis has remained
empirical.•Novel tools are needed for effective translation of preclinical models to humans.•A …

The Mycobacterium tuberculosis Drugome and Its Polypharmacological Implications

SL Kinnings, L Xie, KH Fung, RM Jackson… - PLoS computational …, 2010 - journals.plos.org
We report a computational approach that integrates structural bioinformatics, molecular
modelling and systems biology to construct a drug-target network on a structural proteome …

Host-directed therapies for tuberculosis: quantitative systems pharmacology approaches

K Mehta, HP Spaink, THM Ottenhoff… - Trends in …, 2022 - cell.com
Host-directed therapies (HDTs) that modulate host–pathogen interactions offer an innovative
strategy to combat Mycobacterium tuberculosis (Mtb) infections. When combined with …