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Model-Informed Drug Discovery and Development Strategy for the Rapid Development of Anti-Tuberculosis Drug Combinations

1
Department of Pharmaceutical Biosciences, Uppsala University, Uppsala 75123, Sweden
2
Department of Pharmacy, Uppsala University, Uppsala 75123, Sweden
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(7), 2376; https://doi.org/10.3390/app10072376
Received: 29 February 2020 / Accepted: 25 March 2020 / Published: 31 March 2020
(This article belongs to the Special Issue Tuberculosis Drug Discovery and Development 2019)
The increasing emergence of drug-resistant tuberculosis requires new effective and safe drug regimens. However, drug discovery and development are challenging, lengthy and costly. The framework of model-informed drug discovery and development (MID3) is proposed to be applied throughout the preclinical to clinical phases to provide an informative prediction of drug exposure and efficacy in humans in order to select novel anti-tuberculosis drug combinations. The MID3 includes pharmacokinetic-pharmacodynamic and quantitative systems pharmacology models, machine learning and artificial intelligence, which integrates all the available knowledge related to disease and the compounds. A translational in vitro-in vivo link throughout modeling and simulation is crucial to optimize the selection of regimens with the highest probability of receiving approval from regulatory authorities. In vitro-in vivo correlation (IVIVC) and physiologically-based pharmacokinetic modeling provide powerful tools to predict pharmacokinetic drug-drug interactions based on preclinical information. Mechanistic or semi-mechanistic pharmacokinetic-pharmacodynamic models have been successfully applied to predict the clinical exposure-response profile for anti-tuberculosis drugs using preclinical data. Potential pharmacodynamic drug-drug interactions can be predicted from in vitro data through IVIVC and pharmacokinetic-pharmacodynamic modeling accounting for translational factors. It is essential for academic and industrial drug developers to collaborate across disciplines to realize the huge potential of MID3. View Full-Text
Keywords: tuberculosis; MID3; pharmacokinetics; pharmacodynamics; drug-drug interactions; in vitro; in vivo; drug development tuberculosis; MID3; pharmacokinetics; pharmacodynamics; drug-drug interactions; in vitro; in vivo; drug development
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MDPI and ACS Style

van Wijk, R.C.; Ayoun Alsoud, R.; Lennernäs, H.; Simonsson, U.S.H. Model-Informed Drug Discovery and Development Strategy for the Rapid Development of Anti-Tuberculosis Drug Combinations. Appl. Sci. 2020, 10, 2376. https://doi.org/10.3390/app10072376

AMA Style

van Wijk RC, Ayoun Alsoud R, Lennernäs H, Simonsson USH. Model-Informed Drug Discovery and Development Strategy for the Rapid Development of Anti-Tuberculosis Drug Combinations. Applied Sciences. 2020; 10(7):2376. https://doi.org/10.3390/app10072376

Chicago/Turabian Style

van Wijk, Rob C., Rami Ayoun Alsoud, Hans Lennernäs, and Ulrika S.H. Simonsson 2020. "Model-Informed Drug Discovery and Development Strategy for the Rapid Development of Anti-Tuberculosis Drug Combinations" Applied Sciences 10, no. 7: 2376. https://doi.org/10.3390/app10072376

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