Publications


A list of projects being supported by data collected by the PreDiCT-TB Consortium can be found here. For further information, please e-mail James Kerwin (jkerwin@liverpool.ac.uk), PreDiCT-TB Data Manager (Liverpool).

The following articles have been published as a result of the research carried out for the PreDiCT-TB Project.  Please click on the first author to take you to the Journal/Publisher.

Journal Articles:

  1. Clewe O, Goutelle S, Conte Jr. JE: A pharmacometric pulmonary model predicting the extent and rate of distribution from plasma to epithelial lining fluid and alveolar cells – using refampicin as an example (2015).  Eur J Clin Pharmacol 71:313-319
  2. Svensson EM, Acharya C, Clauson B, Dooley KE, Karlsson MO (2015).  Pharmacokinetic Interactions for Drugs with a Long Half-Life – Evidence for the Need of Model-Based Analysis.  The AAPS Journal DOI: 10.1208/s12248-015-9829-2
  3. Clewe O, Karlsson MO, Simonsson USH (2015).  Evaluation of optimized bronchoalveolar lavage sampling designs for characterization of pulmonary drug distribution. J Pharmacokinet Pharmacodyn 42:699-708
  4. Hu Y, Liu A, Ortega-Munro F, Alameda-Martin L, Mitchison D, Coates A (2015).  High-dose rifampicin kills persisters, shortens treatment duration, and reduces relapse rate in vitro and in vivo.  Frontiers in Microbiology  6:641. doi: 10.3389/fmicb.2015.00641
  5. Ates LS, Ummels R, Commandeur S, van der Weerd R, Sparrius M, Weerdenburg E, Alber M, Kalscheuer R, Piersma SR, Abdallah AM, El Ghany MA, Abdel-Haleem AM, Pain A, Jimenez CR, Bitter W, Houben ENG (2015).  Essential Role of the ESX-5 Secretion System in Outer Membrane Permeability of Pathogenic Mycobacteria.  PLoS Genet 11(5): e1005190. doi:10.1371/journal.pgen.1005190
  6. van de Weerd R, Berbis MA, Sparrius M, Maaskant JJ, Boot M, Paauw NJ, de Vries N, Boon L, Baba O, Canada FJ, Geurtsen J, Jimenez-Barbero J, Appelmelk BJ (2015).  A Murine Monoclonal Antibody to Glycogen: Characterization of Epitope-Fine Specificity by Saturation Transfer Difference (STD) NMR Spectroscoy and Its Use in Mycobacterial Capsular α-Glucan Research. ChemBioChem, 16: 977–989. doi: 10.1002/cbic.201402713
  7. Jeeves RE, Marriott AAN, Pullan ST, Hatch KA, Allnutt JC, Freire-Martin I, Hendon-Dunn CL, Watson R, Witney AA, Tyler RH, Arnold C, Marsh PD, McHugh TD, Bacon J (2015).  Mycobacterium tuberculosis Is Resistant to Isoniazid at a Slow Growth Rate by Sincle Nucleotide Polymorphisms in katG Codon Ser315.  PLoS ONE 10(9): e0138253. doi:10.1371/journal.pone.0138253
  8. Vocat A, Hartkoorn RC, Lechartier B, Zhang M, Dhar N, Cole ST, Sala C (2015).  Bioluminescence for Assessing Drug Potency against Nonreplicting Mycobacterium tuberculosis.  59:4012–4019. doi:10.1128/AAC.00528-15
  9. Evangelopoulos D, da Fonseca JD, Waddell SJ (2015).  Understanding anti-tuberculosis drug efficacy: rethinking bacterial populations and how we model them.  International Journal of Infectious Diseases 32:76-80
  10. Evangelopoulos D, McHugh TD (2015). Improving the Tuberculosis Drug Development Pipeline.  Chem Biol Drug Des 86:951-960.
  11. Maglica Z, Ozdemir E, McKinney JD (2015). Single-Cell Tracking Reveals Antibiotic-Induced Changes in Mycobacterial Energy Metabolism.  mBio 6(1):e02236-14. doi:10.1128/mBio.02236-14
  12. Santi I, McKinney JD (2015). Chromosome Organization and Replisome Dynamics in Mycobacterium smegmatis.  mBio 6(1):e01999-14. doi:10.1128/mBio.01999-14
  13. Manina G, Dhar N and McKinney JD: Stress and host immunity amplify M. tuberculosis phenotypoic heterogeneity and induce nongrowing metabolically active forms (2015). Cell Host Microbe 17:32-46
  14. Hu Y, Menendez MC, Garcia MJ, Oravcova K, Gillespie SH, Davies GR, Mitchison DA, Coates ARM: HspX knock-out in Mycobacterium tuberculosis leads to shorter antibiotic treatment and lower relapse rate in a mouse model – A potential novel therapeutic target. DOI: Tuberculosis 10.1016/j.tube.2014.11.002
  15. Bacon J: A global threat (2014) International Innovation – The Human Element: A quest for knowledge and progress in health care 165:96-98
  16. Ordas A, Raterink R-J, Jansen HJ, Cunningham F, Wiweger MI, Jong-Raaden S, Bates RH, Barros D, Meijer AH, Vreeken RJ, Ballel-Pages L, Dirks RP, Hankemeier T, Spaink HP:  A method for testing drug efficacy in a zebrafish integrative high-throughput disease screening pipeline (2015).  Antimicrob. Agents and Chemother 59:753-762
  17. Sisniega A, Abella M, Desco M, Vaquero JJ: Dual-exposure technique for extending the dynamic range of x-ray flat panel detectors (2014) Phys. Med. Biol. 59:421-439
  18. Cusso L, Vaquero JJ, Bacharach S, Desco M:  Comparison of methods to reduct myocardial 18F-FDG uptake in mice: Calcium channel blockers versus high-fat diets (2014)  Plos One 9(9):1-6
  19. Svensson EM, Dooley KE, Karlsson MO:  Impact of Iopinavir/ritonavir or nevirapine on bedaquiline exposures: potential implications for patients with TB/HIV co-infection (2014) Antimicrob. Agents Chemother.
  20. Veneman WJ, Marin-Juez R, de Sonneville J, Ordas A, Jong-Raadsen S, Meijer AH, Spaink HP:  Establishment and optimization of a high throughput setup to study staphylococcus epidermidis and mycobacterium marinum infection as a mode for drug discovery (2014) Journal of Visualized Experiments 88:1-9; video article
  21. Svensson EM, Aweeka F, Park J-G, Marzan F, Dooley KE, Karlssn MO:  Model-based estimates of the effects of Efavirenz on Bedaquiline pharmacokinetics and suggested dose adjustments for patients coinfected with HIV and Tuberculosis (2013) 57(6):2780-2787

Book/Book Chapters:

  1. Tuberculosis:  Kaufmann, S.H.E., Rubin, E., Zumla, A. (Hrsg.).  Cold Spring Harbor Perspectives in Medicine Cold Spring Harbor Laboratory Press, New York.  ISBN: 978-1-621820-73-4, 2014, 664 pp.
  2. Evangelopoulos D & Waddell SJ:  The use of transcriptomics to predict drug efficacy and treatment outcome in tuberculosis in Ebook “Advances in Tuberculosis Medicinal Chemistry” from the Future Science Group.

 

Consortium Partners

PreDiCT-TB brings together twenty-one leading European research partners in tuberculosis from both Industry and Academia

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The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement n° 115337, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution.

The communication contained within this site reflects the author’s view and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained therein.