The performance of digital technologies for measuring tuberculosis medication adherence: a systematic review.

INTRODUCTION: Digital adherence technologies (DATs), such as phone-based technologies and digital pillboxes, can provide more person-centric approaches to support tuberculosis (TB) treatment. However, there are varying estimates of their performance for measuring medication adherence. METHODS: We conducted a systematic review (PROSPERO-CRD42022313526), which identified relevant published literature and preprints from January 2000 to April 2023 in five databases. Studies reporting quantitative data on the performance of DATs for measuring TB medication adherence against a reference standard, with at least 20 participants, were included. Study characteristics and performance outcomes (eg, sensitivity, specificity and predictive values) were extracted. Sensitivity was the proportion correctly classified as adherent by the DAT, among persons deemed adherent by a reference standard. Specificity was the proportion correctly classified as non-adherent by the DAT, among those deemed non-adherent by a reference standard. RESULTS: Of 5692 studies identified by our systematic search, 13 met inclusion criteria. These studies investigated medication sleeves with phone calls (branded as '99DOTS'; N=4), digital pillboxes N=5), ingestible sensors (N=2), artificial intelligence-based video-observed therapy (N=1) and multifunctional mobile applications (N=1). All but one involved persons with TB disease. For medication sleeves with phone calls, compared with urine testing, reported sensitivity and specificity were 70%-94% and 0%-61%, respectively. For digital pillboxes, compared with pill counts, reported sensitivity and specificity were 25%-99% and 69%-100%, respectively. For ingestible sensors, the sensitivity of dose detection was ≥95% compared with direct observation. Participant selection was the most frequent potential source of bias. CONCLUSION: The limited number of studies available suggests suboptimal and variable performance of DATs for dose monitoring, with significant evidence gaps, notably in real-world programmatic settings. Future research should aim to improve understanding of the relationships of specific technologies, settings and user engagement with DAT performance and should measure and report performance in a more standardised manner.

A platform for predicting mechanism of action based on bacterial transcriptional responses identifies an unusual DNA gyrase inhibitor.

In the search for much-needed new antibacterial chemical matter, a myriad of compounds have been reported in academic and pharmaceutical screening endeavors. Only a small fraction of these, however, are characterized with respect to mechanism of action (MOA). Here, we describe a pipeline that categorizes transcriptional responses to antibiotics and provides hypotheses for MOA. 3D-printed imaging hardware PFIboxes) profiles responses of Escherichia coli promoter-GFP fusions to more than 100 antibiotics. Notably, metergoline, a semi-synthetic ergot alkaloid, mimics a DNA replication inhibitor. In vitro supercoiling assays confirm this prediction, and a potent analog thereof (MLEB-1934) inhibits growth at 0.25 µg/mL and is highly active against quinolone-resistant strains of methicillin-resistant Staphylococcus aureus. Spontaneous suppressor mutants map to a seldom explored allosteric binding pocket, suggesting a mechanism distinct from DNA gyrase inhibitors used in the clinic. In all, the work highlights the potential of this platform to rapidly assess MOA of new antibacterial compounds.