**Rob C. van Wijk 1, Rami Ayoun Alsoud 1, Hans Lennernäs <sup>2</sup> and Ulrika S. H. Simonsson 1,\***


Received: 29 February 2020; Accepted: 25 March 2020; Published: 31 March 2020

**Featured Application: 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 e**ffi**cacy in humans in order to select novel anti-tuberculosis drug combinations for the treatment of tuberculosis.**

**Abstract:** 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.

**Keywords:** tuberculosis; MID3; pharmacokinetics; pharmacodynamics; drug-drug interactions; *in vitro*; *in vivo*; drug development
