scholarly journals In Vitro Methods to Support Transporter Evaluation in Drug Discovery and Development

2013 ◽  
Vol 94 (1) ◽  
pp. 95-112 ◽  
Author(s):  
K L R Brouwer ◽  
D Keppler ◽  
K A Hoffmaster ◽  
D A J Bow ◽  
Y Cheng ◽  
...  
2018 ◽  
Vol 39 (1) ◽  
pp. 4-15 ◽  
Author(s):  
Adedamola Olayanju ◽  
Lauren Jones ◽  
Karin Greco ◽  
Christopher E. Goldring ◽  
Tahera Ansari

2020 ◽  
Vol 57 (3) ◽  
pp. 358-368
Author(s):  
Radhakrishna Sura ◽  
Terry Van Vleet ◽  
Brian R. Berridge

High-throughput in vitro models lack human-relevant complexity, which undermines their ability to accurately mimic in vivo biologic and pathologic responses. The emergence of microphysiological systems (MPS) presents an opportunity to revolutionize in vitro modeling for both basic biomedical research and applied drug discovery. The MPS platform has been an area of interdisciplinary collaboration to develop new, predictive, and reliable in vitro methods for regulatory acceptance. The current MPS models have been developed to recapitulate an organ or tissue on a smaller scale. However, the complexity of these models (ie, including all cell types present in the in vivo tissue) with appropriate structural, functional, and biochemical attributes are often not fully characterized. Here, we provide an overview of the capabilities and limitations of the microfluidic MPS model (aka organs-on-chips) within the scope of drug development. We recommend the engagement of pathologists early in the MPS design, characterization, and validation phases, because this will enable development of more robust and comprehensive MPS models that can accurately replicate normal biology and pathophysiology and hence be more predictive of human responses.


2020 ◽  
Vol 10 (7) ◽  
pp. 2376 ◽  
Author(s):  
Rob C. van Wijk ◽  
Rami Ayoun Alsoud ◽  
Hans Lennernäs ◽  
Ulrika S. H. Simonsson

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.


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