Skip to content

Research at St Andrews

Forecasting clinical dose-response from pre-clinical studies in tuberculosis research - translational predictions with rifampicin

Research output: Contribution to journalArticle

DOI

Open Access permissions

Open

Author(s)

Sebastian G. Wicha, Oskar Clewe, Robin J. Svensson, Stephen H. Gillespie, Yanmin Hu, Anthony R.m. Coates, Ulrika S.h. Simonsson

School/Research organisations

Abstract

A crucial step for accelerating tuberculosis drug development is bridging the gap between pre‐clinical and clinical trials. In this study, we developed a pre‐clinical model‐informed translational approach to predict drug effects across pre‐clinical systems and early clinical trials using the in vitro‐based Multistate Tuberculosis Pharmacometric (MTP) model using rifampicin as an example. The MTP model predicted rifampicin biomarker response observed in (i) a hollow‐fiber infection model, (ii) a murine study to determine PK/PD indices, and (iii) several clinical phase IIa early bactericidal activity (EBA) studies. In addition, we predicted rifampicin biomarker response at high doses of up to 50 mg/kg, leading to an increased median EBA0‐2 days (90% prediction interval) of 0.513 log CFU/mL/day (0.310; 0.701) compared to the standard dose of 10 mg/kg of 0.181 log/CFU/mL/day (0.076; 0.483). These results suggest that the translational approach could assist in the selection of drugs and doses in early‐phase clinical tuberculosis trials.
Close

Details

Original languageEnglish
JournalClinical Pharmacology & Therapeutics
VolumeEarly View
Early online date19 Jun 2018
DOIs
Publication statusE-pub ahead of print - 19 Jun 2018

    Research areas

  • Forward translational, Tuberculosis, Rifampicin

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. Mimicking in-vivo exposures to drug combinations in-vitro: anti-tuberculosis drugs in lung lesions and the hollow fiber model of infection

    Kloprogge, F., Hammond, R., Kipper, K., Gillespie, S. H. & Della Pasqua, O., 13 Sep 2019, In : Scientific Reports. 9, 8 p., 13228.

    Research output: Contribution to journalArticle

  2. A tuberculosis molecular bacterial load assay (TB-MBLA)

    Sabiiti, W., Mtafya, B. A., Alferes De Lima, D., Dombay, E., Baron, V. O., Azam, K., Orascova, K., Sloan, D. J. & Gillespie, S. H., 6 Sep 2019, (Accepted/In press) In : Journal of Visualized Experiments.

    Research output: Contribution to journalArticle

  3. Can phenotypic data complement our understanding of antimycobacterial effects for drug combinations?

    Kloprogge, F., Hammond, R., Copas, A., Gillespie, S. H. & Della Pasqua, O., 25 Aug 2019, In : Journal of Antimicrobial Chemotherapy. Advance article, 7 p.

    Research output: Contribution to journalArticle

  4. Toxicity related to standard TB therapy for pulmonary tuberculosis and treatment outcomes in the REMoxTB study according to HIV status

    Tweed, C. D., Crook, A. M., Dawson, R., Diacon, A. H., McHugh, T. D., Mendel, C. M., Meredith, S. K., Mohapi, L., Murphy, M. E., Nunn, A. J., Phillips, P. P. J., Singh, K. P., Spigelman, M. & Gillespie, S. H., 14 Aug 2019, In : BMC Pulmonary Medicine. 19, 9 p., 152.

    Research output: Contribution to journalArticle

  5. Model-based relationship between the molecular bacterial load assay and time-to-positivity in liquid culture

    Svensson, R. J., Sabiiti, W., Kibiki, G. S., Ntinginya, N. E., Bhatt, N., Davies, G., Gillespie, S. H. & Simonsson, U. S. H., 29 Jul 2019, In : Antimicrobial Agents and Chemotherapy. Early

    Research output: Contribution to journalArticle

Related by journal

  1. A population pharmacokinetic model incorporating saturable pharmacokinetics and autoinduction for high rifampicin doses

    Svensson, R. J., Aarnoutse, R. E., Diacon, A. H., Dawson, R., Gillespie, S. H., Boeree, M. J. & Simonsson, U. S. H., Apr 2018, In : Clinical Pharmacology & Therapeutics. 103, p. 674-683 10 p.

    Research output: Contribution to journalArticle

ID: 252974692