{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T03:34:44Z","timestamp":1777865684049,"version":"3.51.4"},"reference-count":79,"publisher":"The Royal Society","issue":"1949","license":[{"start":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T00:00:00Z","timestamp":1777507200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T00:00:00Z","timestamp":1777507200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,4,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Treatment of Mycobacterium tuberculosis is uniquely prolonged and complex among bacterial infections due to its unusual propensity for persistence during drug stress. Persisters are subpopulations of organisms tolerant to bactericidal antibiotics and characterized by a slower rate of elimination in the absence of genetic changes associated with resistance. The biological basis of this response is increasingly well understood and novel translational tools have become available that are capable of identifying and characterizing such organisms in vitro and in vivo. Recent in vivo and clinical observations have reaffirmed the existence of multiple subpopulations of organisms during treatment of tuberculosis (TB) but operationalizing this concept in pharmacodynamic modelling and clinical trials has been hampered by the availability of culture-based biomarkers alone. A phenomenological framework, which makes explicit use of the information from new tools, would assist with comparisons between preclinical and clinical data and may be able to support models that quantify the likely size of the pool of persister organisms from which relapses arise, facilitating more accurate predictions of the duration of therapy. Such an approach has the potential for significant translational impact in the development of new treatment regimens for TB.<\/jats:p>\n                  <jats:p>This article is part of the Theo Murphy meeting issue \u2018Evaluating anti-infective drugs\u2019<\/jats:p>","DOI":"10.1098\/rstb.2024.0536","type":"journal-article","created":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T07:15:15Z","timestamp":1777533315000},"source":"Crossref","is-referenced-by-count":0,"title":["Translational bacterial biomarkers and pharmacodynamic models in the treatment of tuberculosis"],"prefix":"10.1098","volume":"381","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3819-490X","authenticated-orcid":false,"given":"Geraint Rhys","family":"Davies","sequence":"first","affiliation":[{"name":"University of Liverpool 1 , ,","place":["Liverpool, UK"],"department":["Department of Clinical Infection Microbiology and Immunology"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"175","published-online":{"date-parts":[[2026,4,30]]},"reference":[{"key":"2026043003150697000_R1","unstructured":"World Health Organisation\n          . 2024World Health Organisation Global Tuberculosis Report. 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