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Comparisons of analysis methods for assessment of pharmacodynamic interactions including design recommendations
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
2018 (English)In: AAPS Journal, ISSN 1550-7416, E-ISSN 1550-7416, Vol. 20, article id 77Article in journal (Refereed) Published
Abstract [en]

Quantitative evaluation of potential pharmacodynamic (PD) interactions is important in tuberculosis drug development in order to optimize Phase 2b drug selection and ultimately to define clinical combination regimens. In this work, we used simulations to (1) evaluate different analysis methods for detecting PD interactions between two hypothetical anti-tubercular drugs in in vitro time-kill experiments, and (2) provide design recommendations for evaluation of PD interactions. The model used for all simulations was the Multistate Tuberculosis Pharmacometric (MTP) model linked to the General Pharmacodynamic Interaction (GPDI) model. Simulated data were re-estimated using the MTP–GPDI model implemented in Bliss Independence or Loewe Additivity, or using a conventional model such as an Empirical Bliss Independence-based model or the Greco model based on Loewe Additivity. The GPDI model correctly characterized different PD interactions (antagonism, synergism, or asymmetric interaction), regardless of the underlying additivity criterion. The commonly used conventional models were not able to characterize asymmetric PD interactions, i.e., concentration-dependent synergism and antagonism. An optimized experimental design was developed that correctly identified interactions in ≥ 94% of the evaluated scenarios using the MTP–GPDI model approach. The MTP–GPDI model approach was proved to provide advantages to other conventional models for assessing PD interactions of anti-tubercular drugs and provides key information for selection of drug combinations for Phase 2b evaluation.

Place, publisher, year, edition, pages
2018. Vol. 20, article id 77
Keywords [en]
optimized design, in vitro, pharmacodynamic interactions
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-318772DOI: 10.1208/s12248-018-0239-0ISI: 000436029800001PubMedID: 29931471OAI: oai:DiVA.org:uu-318772DiVA, id: diva2:1085401
Funder
Swedish Research CouncilEU, FP7, Seventh Framework Programme, 115337Available from: 2017-03-28 Created: 2017-03-28 Last updated: 2019-06-25Bibliographically approved
In thesis
1. Pharmacokinetic-Pharmacodynamic Evaluations and Experimental Design Recommendations for Preclinical Studies of Anti-tuberculosis Drugs
Open this publication in new window or tab >>Pharmacokinetic-Pharmacodynamic Evaluations and Experimental Design Recommendations for Preclinical Studies of Anti-tuberculosis Drugs
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Tuberculosis is an ancient infectious disease and a leading cause of death globally. Preclinical research is important for defining drugs and regimens which should be carried forward to human studies. This thesis aims to characterize the population pharmacokinetics and exposure-response relationships of anti-tubercular drugs alone and in combinations, and to suggest experimental designs for preclinical settings.

The population pharmacokinetics of rifampicin, isoniazid, ethambutol and pyrazinamide were described for the first time in two mouse models. This allowed for linking the population pharmacokinetic model to the Multistate Tuberculosis Pharmacometric (MTP) model for biomarker response, which was used to characterize exposure-response relationships in monotherapy. Pharmacodynamic interactions in combination therapies were quantitatively described by linking the MTP model to the General Pharmacodynamic Interaction (GPDI) model, which provided estimates of single drug effects together with a quantitative model-based evaluation framework for evaluation of pharmacodynamic interactions among drugs in combinations. Synergism (more than expected additivity) was characterized between rifampicin and ethambutol, while antagonism (less than expected additivity) was characterized between rifampicin and isoniazid in combination therapies.

The new single-dose pharmacokinetic design with enrichened individual sampling was more informative than the original design, in which only one sample was taken from each mouse in the pharmacokinetic studies. The new oral zipper design allows for informative pharmacokinetic sampling in a multiple-dose administration scenario for characterizing pharmacokinetic-pharmacodynamic relationships, with similar or lower bias and imprecision in parameter estimates and with a decreased total number of animals required by up to 7-fold compared to the original design. The optimized design for assessing pharmacodynamic interactions in the combination therapies, which was based on EC20, EC50 and EC80 of the single drug, provided lower bias and imprecision than a conventional reduced four-by-four microdilution checkerboard design at the same total number of samples required, which followed the 3Rs of animal welfare.

In summary, in this thesis the population pharmacokinetic-pharmacodynamic models of first-line drugs in mice were characterized through linking each population pharmacokinetic model to the MTP model. Pharmacodynamic interactions were quantitatively illustrated by the MTP-GPDI model. Lastly, experimental designs were optimized and recommended to both pharmacokinetic and pharmacodynamic studies for preclinical settings.  

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. p. 58
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 231
Keywords
tuberculosis, pharmacokinetics, pharmacodynamics, pharmacometrics, the Multistate Tuberculosis Pharmacometric model, the General Pharmacodynamic Interaction model, optimized design, rifampicin, isoniazid, ethambutol, pyrazinamide
National Category
Pharmaceutical Sciences
Research subject
Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-318845 (URN)978-91-554-9877-1 (ISBN)
Public defence
2017-05-19, B/B42, Biomedicinskt Centrum, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2017-04-27 Created: 2017-03-29 Last updated: 2018-01-13

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Chen, ChunliWicha, Sebastian G.Nordgren, RikardSimonsson, Ulrika S H

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