DDMODEL00000259: The MTP-GPDI model for pre-clinical exposure response and PD interaction identification

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Short description:
In vitro time-kill experiments were performed with Mycobacterium tuberculosis using rifampicin, isoniazid or ethambutol alone as well as in different combinations at clinically relevant concentrations. The Multistate Tuberculosis Pharmacometric (MTP) model was used to characterize the natural growth and exposure-response relationships of each drug after mono-exposure. Pharmacodynamic interactions during combination exposure were characterized by linking the MTP model to the General Pharmacodynamic Interaction (GPDI) model with successful separation of potential effect on each drug’s potency (EC50) by the combining drug(s). Using pre-clinical information, the MTP-GPDI modelling approach was shown to correctly predict clinically observed pharmacodynamic interactions, as deviations from expected additivity.
Original code
  • A model-informed preclinical approach for prediction of clinical pharmacodynamic interactions of anti-TB drug combinations
  • Oskar Clewe, Sebastian G. Wicha, Corné P. de Vogel, Jurriaan E.M. de Steenwinkel, Ulrika SH Simonsson
  • Journal of Antimicrobial Chemotherapy, 11/2017
  • Department of Pharmaceutical Biosciences, Uppsala University
  • Background: Identification of pharmacodynamic interactions is not reasonable to carry out in a clinical setting for many reasons. The aim of this work was to develop a model-informed pre-clinical approach for prediction of clinical pharmacodynamic drug interactions in order to inform early anti-tuberculosis drug development. Methods: In vitro time-kill experiments were performed with Mycobacterium tuberculosis using rifampicin, isoniazid or ethambutol alone as well as in different combinations at clinically relevant concentrations. The Multistate Tuberculosis Pharmacometric (MTP) model was used to characterize the natural growth and exposure-response relationships of each drug after mono-exposure. Pharmacodynamic interactions during combination exposure were characterized by linking the MTP model to the General Pharmacodynamic Interaction (GPDI) model with successful separation of potential effect on each drug’s potency (EC50) by the combining drug(s). Results: All combinations showed pharmacodynamic interactions at colony-forming unit level where all combinations, except isoniazid plus ethambutol, showed more effect (synergy) than any of the drugs alone. Using pre-clinical information, the MTP-GPDI modelling approach was shown to correctly predict clinically observed pharmacodynamic interactions, as deviations from expected additivity. Conclusions: With the ability of predicting clinical pharmacodynamic interactions, using pre-clinical information, the MTP-GPDI model approach outlined in this study constitutes groundwork for model informed input to the development of new and enhancement of existing anti-tuberculosis combination regimens.
Oskar Clewe
Context of model development: Mechanistic Understanding;
Model compliance with original publication: Yes;
Model implementation requiring submitter’s additional knowledge: No;
Modelling context description: In vitro exposure response and PD interaction identification;
Modelling task in scope: estimation;
Nature of research: In vitro;
Therapeutic/disease area: Anti-infectives;
Annotations are correct.
This model is not certified.
  • Model owner: Oskar Clewe
  • Submitted: Nov 15, 2017 1:09:41 PM
  • Last Modified: Nov 15, 2017 1:09:41 PM
Revisions
  • Version: 11 public model Download this version
    • Submitted on: Nov 15, 2017 1:09:41 PM
    • Submitted by: Oskar Clewe
    • With comment: Edited model metadata online.
 
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