ClinicalTrials.gg
RecruitingNCT04923958R2D2TB NetworkUpdated Nov 9, 2026

Rapid Research in Diagnostics Development for TB Network

An interventional study of Novel mycobacterial culture techniques and Novel sputum smear microscopy techniques in Tuberculosis, sponsored by University of California, San Francisco. Recruiting at 16 sites in 8 countries. Open to participants aged 12 Years and older. Per ClinicalTrials.gov, last updated 2026-11-09.

Sponsored by University of California, San Francisco · Not applicable, Interventional, and Diagnostic

From the registry’s dates

  • Started Apr 2021; still recruiting 5 years 6 months later.
Updated Nov 9, 2026Sponsor changedGo to Updates ↓
Phase
Not applicable
Study type
Interventional
Enrollment
26,436
Allocation
Non-randomized
Ages
12 Years and older
Sex
All
01

Study summary

To reduce the burden of TB worldwide through more accurate, faster, simpler, and less expensive diagnosis of TB Every year, more than 3 million people with TB remain undiagnosed and 1 million die. Better diagnostics are essential to reducing the enormous burden of TB worldwide. The Rapid Research in Diagnostics Development for TB Network (R2D2 TB Network) brings together experts in TB care, technology assessment, diagnostics development, laboratory medicine, epidemiology, health economics and mathematical modeling with highly experienced clinical study sites in 10 countries.

Read the detailed description

The Rapid Research in Diagnostics Development for TB Network (R2D2 TB Network) study seeks to identify and rigorously assess promising early stage tuberculosis (TB) triage, diagnostic and drug resistance tests (hereafter referred to as "novel tests") in clinical studies conducted in settings of intended use. Rapid diagnosis, identification of drug resistance and effective treatment are critical for improving patient outcomes and reducing TB transmission. However, analysis of care cascades and prevalence surveys indicate that 40-60% of patients with TB are not initiated on effective treatment.1,2 The different types of tests required to reduce this "diagnostic gap" have been described in the form of target product profiles (TPPs). The highest- priority TPPs are for: 1) a point-of-care, non-sputum biomarker-based test to facilitate rapid TB diagnosis using easily accessible samples (a biomarker-based diagnostic test) and 2) a simple, low-cost test that can be used by front-line health workers to rule-out TB (a triage test). The R2D2 TB Network study will evaluate the sensitivity and specificity of novel triage and diagnostic tests against a reference standard including sputum Xpert® MTB/RIF (Mycobacterium tuberculosis/Rifampin) Ultra and sputum mycobacterial culture. The sensitivity and specificity of rapid drug susceptibility tests (rDST) will be compared against a reference standard including culture-based phenotypic DST and whole genome sequencing (WGS) of mycobacterial DNA. In addition, the usability of novel tests will be assessed through direct observations and surveys of routine health workers.

02

Conditions studied

  • Tuberculosis

Browse trials for

Keywords

  • Tuberculosis
  • Diagnostics
  • Global Health
03

In context

Tuberculosis

1,170 studies on the registry are indexed under Tuberculosis; 175 are open to participants now.

This study's planned enrollment of 26,436 is above the median of 150 across 820 interventional studies indexed under Tuberculosis.

Browse Tuberculosis studies →

Lead sponsor

University of California, San Francisco is the lead sponsor of 2,169 studies on the registry; 372 are open to participants now.

Of its 267 completed or terminated interventional studies of FDA-regulated products, 202 (76%) have results posted.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
12 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Eligibility criteria

Novel TB triage and diagnostic tests:

We will include non-hospitalized adults (age ≥ 12 years) with either 1) cough ≥2 weeks' duration, a commonly accepted criterion for identifying people with presumed pulmonary TB (to facilitate standardization across sites and comparison of test performance across sub-groups or 2) risk factors for which TB screening is recommended ( infection, self-reported close contact, history of mining work). People with risk factors will be included if they screen positive for TB based on WHO-recommended screening tools as specified below:

Positive TB screening definitions by risk factor:

  1. PLHIV (Risk Factor), CRP >5 mg/dL OR abnormal CXR (Positive TB screening definition)
  2. Self-reported Close Contact (Risk Factor), abnormal CXR (Positive TB screening definition)
  3. History of mining work (Risk Factor), abnormal CXR (Positive TB screening definition)

We will exclude people who:

  1. completed latent or active TB treatment within the past 12 months (to increase TB prevalence and reduce false-positive results, respectively);
  2. have taken any medication with anti-mycobacterial activity (including fluoroquinolones) for any reason, within 2 weeks of study entry (to reduce false-negatives);
  3. reside >20km from the study site or are unwilling to return for follow-up visits; or
  4. are unwilling to provide

Novel TB rDST assays:

We will include adults (age ≥12 years) who are positive for TB and RIF resistance according to routine diagnostic testing (based typically on Xpert MTB/RIF, Xpert MTB/RIF Ultra, or Hain MTBDRplus). We will exclude people who:

  1. have negative or contaminated results on all baseline (i.e., enrollment) sputum cultures
  2. are unable to provide at least two sputum specimens of 3 mL each within one day of enrollment
  3. are unable or unwilling to provide informed consent

Assessment of the usability of novel TB tests:

We will include health workers at each clinical site who are 1) aged ≥18 years and 2) involved in routine TB testing (collecting specimens for or performing TB tests). We will exclude staff who are unwilling to provide informed consent.

Terms in these criteria, in plain language(2)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

HIV

The human immunodeficiency virus, which weakens the immune system.

Many studies now accept people whose HIV is controlled on treatment, judged by the viral load and the CD4 count. Check the limits this study sets.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

05

Study design

Phase
Not applicable
Primary purpose
Diagnostic
Allocation
Non-randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
26,436 participants (estimated)

Study arms

  • Experimental
    Evaluation of various novel TB triage and diagnostic tests.

    For the novel TB triage and diagnostic tests, the investigators will conduct large-scale evaluation of design-locked tests in a cohort of adults with presumed TB, with nested feasibility/pilot studies of early and late prototype tests. The investigators aim to enroll 300-450 participants per year at each of five enrollment sites for evaluation of various novel TB triage and diagnostic tests and 50 health workers to assess test usability.

    Diagnostic Test: Novel mycobacterial culture techniques · Diagnostic Test: Novel sputum smear microscopy techniques · Diagnostic Test: Sputum-based molecular assays · Diagnostic Test: Tongue swab-based molecular assays · Diagnostic Test: Urine LAM assays · Diagnostic Test: Blood-based host immune response assays · Diagnostic Test: Breath-based assays · Diagnostic Test: Artificial intelligence-based digital health tools · Diagnostic Test: Phage-based assays

  • Experimental
    Evaluation of novel rDST assays

    Clinicians at participating sites will be asked to refer adult patients with rifampin-resistance identified by routine molecular testing. The investigators aim to enroll 100-200 patients per year at each of three enrollment sites for evaluation of novel rDST assays.

    Diagnostic Test: Cartridge-based molecular assays for detecting drug resistance · Diagnostic Test: Sequencing-based assays for detecting drug resistance

Interventions

  • Diagnostic testNovel mycobacterial culture techniques

    We will evaluate tests intended to make culture more sensitive, faster, and have less contamination.

  • Diagnostic testNovel sputum smear microscopy techniques

    We will evaluate new staining techniques or visualization methods to increase the sensitivity of smear microscopy.

  • Diagnostic testSputum-based molecular assays

    We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.

  • Diagnostic testTongue swab-based molecular assays

    We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.

  • Diagnostic testUrine LAM assays

    We will evaluate urine LAM assays incorporating techniques such as analyte concentration, higher sensitivity or specificity antibodies, or enhanced visualization to improve LAM detection.

  • Diagnostic testBlood-based host immune response assays

    We will evaluate assays measuring host immune response parameters intended for use at near point of care or point of care.

  • Diagnostic testBreath-based assays

    We will evaluate assays assessing volatile organic compounds or exhaled breath condensate for near point of care of point of care detection of TB.

  • Diagnostic testArtificial intelligence-based digital health tools

    We will evaluate AI-based algorithms evaluating images (chest x-ray, ultrasound) or sounds (cough sounds, lung sounds) including an Infrasound-to-ultrasound e-stethoscope (Level 42 AI, USA).

  • Diagnostic testPhage-based assays

    We will evaluate assays using phages to lyse mycobacterial cells for detection of DNA or antigens.

  • Diagnostic testCartridge-based molecular assays for detecting drug resistance

    We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.

  • Diagnostic testSequencing-based assays for detecting drug resistance

    We will evaluate targeted and whole genome sequencing assays.

06

What researchers measure

Primary outcomes

  1. Sensitivity

    Number of positive results for a given index test/(Total positive + negative results for a given index test) among patients with TB using the microbiological reference standard

    Time frame: 7 months

  2. Specificity

    Number of negative results for a given index test/(Total positive + negative results for a given index test) among patients without TB using the microbiological reference standard

    Time frame: 7 months

07

Study locations

16 of 16 sites recruiting
08

References and documents

Publications

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  • Walusimbi S, Bwanga F, De Costa A, Haile M, Joloba M, Hoffner S. Meta-analysis to compare the accuracy of GeneXpert, MODS and the WHO 2007 algorithm for diagnosis of smear-negative pulmonary tuberculosis. BMC Infect Dis. 2013 Oct 30;13:507. doi: 10.1186/1471-2334-13-507. PubMed 24172543 ↗
  • World Health Organization. Rapid Implementation of the Xpert MTB / RIF diagnostic test. Technical and operational 'how-to' practical considerations. Geneva, Switzerland, 2011.
  • Systematic Screening for Active Tuberculosis: Principles and Recommendations. Geneva: World Health Organization; 2013. Available from http://www.ncbi.nlm.nih.gov/books/NBK294083/ PubMed 25996015 ↗
  • World Health Organization. Drug-resistant TB. https://www.who.int/tb/areas-of-work/drug-resistant-tb/en/.
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  • Prasad R, Singh A, Balasubramanian V, Gupta N. Extensively drug-resistant tuberculosis in India: Current evidence on diagnosis & management. Indian J Med Res. 2017 Mar;145(3):271-293. doi: 10.4103/ijmr.IJMR_177_16. PubMed 28749390 ↗
  • Yoon C, Dowdy DW, Esmail H, MacPherson P, Schumacher SG. Screening for tuberculosis: time to move beyond symptoms. Lancet Respir Med. 2019 Mar;7(3):202-204. doi: 10.1016/S2213-2600(19)30039-6. No abstract available. PubMed 30823972 ↗
  • Organization WH. High-priority target product profiles for new tuberculosis diagnostics: report of a consensus meeting. Geneva, Switzerland: WHO Press; 2014. p. 98.
  • World Health Organization. High-priority target product profiles for new tuberculosis diagnostics: report of a consensus meeting. Geneva, Switzerland, 2014.
  • UNITAID. TB Diagnostics Market in Select High-Burden Countries: Current Market and Future Opportunities for Novel Diagnostics. Geneva, Switzerland, 2015.
  • Subbaraman R, Nathavitharana RR, Satyanarayana S, Pai M, Thomas BE, Chadha VK, Rade K, Swaminathan S, Mayer KH. The Tuberculosis Cascade of Care in India's Public Sector: A Systematic Review and Meta-analysis. PLoS Med. 2016 Oct 25;13(10):e1002149. doi: 10.1371/journal.pmed.1002149. eCollection 2016 Oct. PubMed 27780217 ↗
  • Farhat MR, Sultana R, Iartchouk O, Bozeman S, Galagan J, Sisk P, Stolte C, Nebenzahl-Guimaraes H, Jacobson K, Sloutsky A, Kaur D, Posey J, Kreiswirth BN, Kurepina N, Rigouts L, Streicher EM, Victor TC, Warren RM, van Soolingen D, Murray M. Genetic Determinants of Drug Resistance in Mycobacterium tuberculosis and Their Diagnostic Value. Am J Respir Crit Care Med. 2016 Sep 1;194(5):621-30. doi: 10.1164/rccm.201510-2091OC. PubMed 26910495 ↗
  • Lange C, Chesov D, Furin J, Udwadia Z, Dheda K. Revising the definition of extensively drug-resistant tuberculosis. Lancet Respir Med. 2018 Dec;6(12):893-895. doi: 10.1016/S2213-2600(18)30428-4. Epub 2018 Nov 9. No abstract available. PubMed 30420247 ↗
  • Makhado NA, Matabane E, Faccin M, Pincon C, Jouet A, Boutachkourt F, Goeminne L, Gaudin C, Maphalala G, Beckert P, Niemann S, Delvenne JC, Delmee M, Razwiedani L, Nchabeleng M, Supply P, de Jong BC, Andre E. Outbreak of multidrug-resistant tuberculosis in South Africa undetected by WHO-endorsed commercial tests: an observational study. Lancet Infect Dis. 2018 Dec;18(12):1350-1359. doi: 10.1016/S1473-3099(18)30496-1. Epub 2018 Oct 18. PubMed 30342828 ↗
  • Paris L, Magni R, Zaidi F, Araujo R, Saini N, Harpole M, Coronel J, Kirwan DE, Steinberg H, Gilman RH, Petricoin EF 3rd, Nisini R, Luchini A, Liotta L. Urine lipoarabinomannan glycan in HIV-negative patients with pulmonary tuberculosis correlates with disease severity. Sci Transl Med. 2017 Dec 13;9(420):eaal2807. doi: 10.1126/scitranslmed.aal2807. PubMed 29237757 ↗
  • Wood A, Barizuddin S, Darr CM, Mathai CJ, Ball A, Minch K, Somoskovi A, Hamasur B, Connelly JT, Weigl B, Andama A, Cattamanchi A, Gangopadhyay K, Bok S, Gangopadhyay S. Ultrasensitive detection of lipoarabinomannan with plasmonic grating biosensors in clinical samples of HIV negative patients with tuberculosis. PLoS One. 2019 Mar 26;14(3):e0214161. doi: 10.1371/journal.pone.0214161. eCollection 2019. PubMed 30913250 ↗
  • Nakhleh MK, Jeries R, Gharra A, Binder A, Broza YY, Pascoe M, Dheda K, Haick H. Detecting active pulmonary tuberculosis with a breath test using nanomaterial-based sensors. Eur Respir J. 2014 May;43(5):1522-5. doi: 10.1183/09031936.00019114. No abstract available. PubMed 24789953 ↗
  • Fernandez-Carballo BL, Broger T, Wyss R, Banaei N, Denkinger CM. Toward the Development of a Circulating Free DNA-Based In Vitro Diagnostic Test for Infectious Diseases: a Review of Evidence for Tuberculosis. J Clin Microbiol. 2019 Mar 28;57(4):e01234-18. doi: 10.1128/JCM.01234-18. Print 2019 Apr. PubMed 30404942 ↗
  • Ahmad Khan F, Pande T, Tessema B, Song R, Benedetti A, Pai M, Lonnroth K, Denkinger CM. Computer-aided reading of tuberculosis chest radiography: moving the research agenda forward to inform policy. Eur Respir J. 2017 Jul 13;50(1):1700953. doi: 10.1183/13993003.00953-2017. Print 2017 Jul. No abstract available. PubMed 28705949 ↗
  • Portevin D, Moukambi F, Clowes P, Bauer A, Chachage M, Ntinginya NE, Mfinanga E, Said K, Haraka F, Rachow A, Saathoff E, Mpina M, Jugheli L, Lwilla F, Marais BJ, Hoelscher M, Daubenberger C, Reither K, Geldmacher C. Assessment of the novel T-cell activation marker-tuberculosis assay for diagnosis of active tuberculosis in children: a prospective proof-of-concept study. Lancet Infect Dis. 2014 Oct;14(10):931-8. doi: 10.1016/S1473-3099(14)70884-9. Epub 2014 Aug 31. PubMed 25185458 ↗
  • Yoon C, Semitala FC, Atuhumuza E, Katende J, Mwebe S, Asege L, Armstrong DT, Andama AO, Dowdy DW, Davis JL, Huang L, Kamya M, Cattamanchi A. Point-of-care C-reactive protein-based tuberculosis screening for people living with HIV: a diagnostic accuracy study. Lancet Infect Dis. 2017 Dec;17(12):1285-1292. doi: 10.1016/S1473-3099(17)30488-7. Epub 2017 Aug 25. PubMed 28847636 ↗
  • Schmidt S. Bringing cheap and accurate tuberculosis tests to Africa. University of Wisconsin - News. 2018.
  • Luabeya AK, Wood RC, Shenje J, Filander E, Ontong C, Mabwe S, Africa H, Nguyen FK, Olson A, Weigel KM, Jones-Engel L, Hatherill M, Cangelosi GA. Noninvasive Detection of Tuberculosis by Oral Swab Analysis. J Clin Microbiol. 2019 Feb 27;57(3):e01847-18. doi: 10.1128/JCM.01847-18. Print 2019 Mar. PubMed 30541931 ↗
  • Mesman AW, Calderon R, Soto M, Coit J, Aliaga J, Mendoza M, Franke MF. Mycobacterium tuberculosis detection from oral swabs with Xpert MTB/RIF ULTRA: a pilot study. BMC Res Notes. 2019 Jun 20;12(1):349. doi: 10.1186/s13104-019-4385-y. PubMed 31221195 ↗
  • Liu C, Lyon CJ, Bu Y, Deng Z, Walters E, Li Y, Zhang L, Hesseling AC, Graviss EA, Hu Y. Clinical Evaluation of a Blood Assay to Diagnose Paucibacillary Tuberculosis via Bacterial Antigens. Clin Chem. 2018 May;64(5):791-800. doi: 10.1373/clinchem.2017.273698. Epub 2018 Jan 18. PubMed 29348166 ↗
  • Walker TM, Kohl TA, Omar SV, Hedge J, Del Ojo Elias C, Bradley P, Iqbal Z, Feuerriegel S, Niehaus KE, Wilson DJ, Clifton DA, Kapatai G, Ip CLC, Bowden R, Drobniewski FA, Allix-Beguec C, Gaudin C, Parkhill J, Diel R, Supply P, Crook DW, Smith EG, Walker AS, Ismail N, Niemann S, Peto TEA; Modernizing Medical Microbiology (MMM) Informatics Group. Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study. Lancet Infect Dis. 2015 Oct;15(10):1193-1202. doi: 10.1016/S1473-3099(15)00062-6. Epub 2015 Jun 23. PubMed 26116186 ↗
  • Colman RE, Mace A, Seifert M, Hetzel J, Mshaiel H, Suresh A, Lemmer D, Engelthaler DM, Catanzaro DG, Young AG, Denkinger CM, Rodwell TC. Whole-genome and targeted sequencing of drug-resistant Mycobacterium tuberculosis on the iSeq100 and MiSeq: A performance, ease-of-use, and cost evaluation. PLoS Med. 2019 Apr 30;16(4):e1002794. doi: 10.1371/journal.pmed.1002794. eCollection 2019 Apr. PubMed 31039166 ↗
  • de Vos M, Ley SD, Wiggins KB, Derendinger B, Dippenaar A, Grobbelaar M, Reuter A, Dolby T, Burns S, Schito M, Engelthaler DM, Metcalfe J, Theron G, van Rie A, Posey J, Warren R, Cox H. Bedaquiline Microheteroresistance after Cessation of Tuberculosis Treatment. N Engl J Med. 2019 May 30;380(22):2178-2180. doi: 10.1056/NEJMc1815121. No abstract available. PubMed 31141643 ↗
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  • Metcalfe JZ, Streicher E, Theron G, Colman RE, Penaloza R, Allender C, Lemmer D, Warren RM, Engelthaler DM. Mycobacterium tuberculosis Subculture Results in Loss of Potentially Clinically Relevant Heteroresistance. Antimicrob Agents Chemother. 2017 Oct 24;61(11):e00888-17. doi: 10.1128/AAC.00888-17. Print 2017 Nov. PubMed 28893776 ↗
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  • Yerlikaya S, Chirwa M, Ajide B, Castro MDM, Ha H, Kato-Maeda M, Kisakye E, Marcelo D, Mochizuki T, Rockman L, Steadman A, Thangakunam B, Bimba JS, Christopher DJ, Muyoyeta M, Phan H, Theron G, Yu C, Kremer K, Phillips PPJ, Nahid P, Denkinger CM, Cattamanchi A, Andama A; R2D2 TB Network and SMART4TB Consortia. Pulmonary Tuberculosis Detection with MiniDock MTB Using Swab Samples. N Engl J Med. 2026 Apr 30;394(17):1710-1722. doi: 10.1056/NEJMoa2509761. PubMed 42054680 ↗
  • Crowder R, Thangakunam B, Andama A, Christopher DJ, Dalay V, Nwamba W, Kik SV, Van Nguyen D, Viet Nhung N, Phillips PPJ, Ruhwald M, Theron G, Worodria W, Yu C, Nahid P, Cattamanchi A, Gupta-Wright A, Denkinger CM; R2D2 TB Network. Diagnostic Accuracy of Tuberculosis Screening Tests in a Prospective Multinational Cohort: Chest Radiography With Computer-Aided Detection, Xpert Tuberculosis Host Response, and C-Reactive Protein. Clin Infect Dis. 2026 Feb 25;82(2):e239-e247. doi: 10.1093/cid/ciae549. PubMed 39509711 ↗
  • Crowder R, Thangakunam B, Andama A, Christopher DJ, Dalay V, Dube-Nwamba W, Kik SV, Nguyen DV, Nhung NV, Phillips PP, Ruhwald M, Theron G, Worodria W, Yu C, Nahid P, Cattamanchi A, Gupta-Wright A, Denkinger CM; R2D2 TB Network. Head-to-head comparison of diagnostic accuracy of TB screening tests: Chest-X-ray, Xpert TB host response, and C-reactive protein. medRxiv [Preprint]. 2024 Jun 21:2024.06.20.24308402. doi: 10.1101/2024.06.20.24308402. PubMed 38947093 ↗
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Individual participant data

Plan to share: No

09

Timeline

1 registry update since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reachedSimilar studies: half by the dot; the band is the middle halfHalf of similar studies reached it by the dot; the band is the middle half, from a quarter to three quarters

Started Apr 2021 (actual). Primary completion is estimated for May 2031, 121 months after the start.

Of 169 non-industry interventional studies with no phase under Tuberculosis, half reached primary completion within 25 months of starting (the median), counting those still running; a quarter within 15 and three quarters within 41. This study's planned 121 months is above that.

Counting every sponsor, half of 171 studies reached it within 25 months; a quarter within 14 and three quarters within 41.

How these figures are worked out, and which studies are left out of them.

Registered
Jun 7, 2021
First posted
Jun 11, 2021
StartActual
Apr 14, 2021
Primary completionEst.
May 31, 2031
CompletionEst.
May 31, 2031
Last update
Nov 9, 2026
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
Sponsor
Collaborators added: Bingham University; collaborators removed: Zankli Research Center
Nov 9, 2026
Show all 1 update
  1. Nov 9, 2026
    Sponsor Collaborators added: Bingham University; collaborators removed: Zankli Research Center
    + 1 other change: verification date

From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗

10

Registry details

Key details

Study ID
NCT04923958
Collaborators
University Hospital Heidelberg, Christian Medical College, Vellore, India, Vietnam National Lung Hospital, De La Salle University Medical Center, University of Stellenbosch, Makerere University, Johns Hopkins Bloomberg School of Public Health, Harvard Medical School (HMS and HSDM), Stanford University, Foundation for Innovative New Diagnostics, Switzerland, Socios En Salud Sucursal, Peru, Federal University of Mato Grosso, Medical Research Council, National Center for Tuberculosis and Lung Disease, Tbilisi, Georgia, Centre for Infectious Disease Research in Zambia, National Institute of Allergy and Infectious Diseases (NIAID), University of California, Irvine, Johns Hopkins University, Bingham University
Responsible party
Sponsor
First posted
Jun 11, 2021
Start date
Apr 14, 2021
Primary completion
May 31, 2031 (estimated)
Completion
May 31, 2031 (estimated)
Last update
Nov 9, 2026

Study contacts

Adithya Cattamanchi, MD
Contact
adithya.cattamanchi@ucsf.edu
+1-415-206-5489
Catherine Cook, MPH
Contact
catherine.cook@ucsf.edu
603-988-9940
Adithya Cattamanchi, MD
principal investigator · University of California, San Francisco

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
Yes
View the source record on ClinicalTrials.gov ↗

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