scholarly journals In vitro and in vivo methods to assess pharmacokinetic drug– drug interactions in drug discovery and development

2020 ◽  
Vol 41 (1-2) ◽  
pp. 3-31 ◽  
Author(s):  
Chuang Lu ◽  
Li Di
Keyword(s):  
Drug Discovery ◽  
Drug Interactions ◽  
Drug Discovery And Development ◽  
Pharmacokinetic Drug

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

2020 ◽  
Vol 10 (7) ◽  
pp. 2376 ◽  
Author(s):  
Rob C. van Wijk ◽  
Rami Ayoun Alsoud ◽  
Hans Lennernäs ◽  
Ulrika S. H. Simonsson
Keyword(s):  
Drug Discovery ◽  
Drug Interactions ◽  
Development Strategy ◽  
Drug Exposure ◽  
Rapid Development ◽  
Drug Combinations ◽  
Pharmacodynamic Modeling ◽  
Drug Discovery And Development

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.

scholarly journals Carboxymefloquine, the Major Metabolite of the Antimalarial Drug Mefloquine, Induces Drug-Metabolizing Enzyme and Transporter Expression by Activation of Pregnane X Receptor

2014 ◽  
Vol 59 (1) ◽  
pp. 96-104 ◽  
Author(s):  
Rita Piedade ◽  
Stefanie Traub ◽  
Andreas Bitter ◽  
Andreas K. Nüssler ◽  
José P. Gil ◽  
...  
Keyword(s):  
Drug Interactions ◽  
Antimalarial Drug ◽  
Pregnane X Receptor ◽  
Antimalarial Drugs ◽  
Drug Metabolites ◽  
Protein Levels ◽  
Two Hybrid ◽  
Pharmacokinetic Drug

ABSTRACTMalaria patients are frequently coinfected with HIV and mycobacteria causing tuberculosis, which increases the use of coadministered drugs and thereby enhances the risk of pharmacokinetic drug-drug interactions. Activation of the pregnane X receptor (PXR) by xenobiotics, which include many drugs, induces drug metabolism and transport, thereby resulting in possible attenuation or loss of the therapeutic responses to the drugs being coadministered. While several artemisinin-type antimalarial drugs have been shown to activate PXR, data on nonartemisinin-type antimalarials are still missing. Therefore, this study aimed to elucidate the potential of nonartemisinin antimalarial drugs and drug metabolites to activate PXR. We screened 16 clinically used antimalarial drugs and six major drug metabolites for binding to PXR using the two-hybrid PXR ligand binding domain assembly assay; this identified carboxymefloquine, the major and pharmacologically inactive metabolite of the antimalarial drug mefloquine, as a potential PXR ligand. Two-hybrid PXR-coactivator and -corepressor interaction assays and PXR-dependent promoter reporter gene assays confirmed carboxymefloquine to be a novel PXR agonist which specifically activated the human receptor. In the PXR-expressing intestinal LS174T cells and in primary human hepatocytes, carboxymefloquine induced the expression of drug-metabolizing enzymes and transporters on the mRNA and protein levels. The crucial role of PXR for the carboxymefloquine-dependent induction of gene expression was confirmed by small interfering RNA (siRNA)-mediated knockdown of the receptor. Thus, the clinical use of mefloquine may result in pharmacokinetic drug-drug interactions by means of its metabolite carboxymefloquine. Whether thesein vitrofindings are ofin vivorelevance has to be addressed in future clinical drug-drug interaction studies.

scholarly journals Utilizing in vitro transporter data in IVIVE-PBPK: an overview

ADMET & DMPK ◽  
2017 ◽  
Vol 5 (4) ◽  
pp. 201-211 ◽  
Author(s):  
Pankajini Mallick
Keyword(s):  
Drug Discovery ◽  
Drug Transporters ◽  
Drug Discovery And Development ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Human Pharmacokinetic ◽  
Development Processes ◽  
Key Aspects

In vitro-in vivo extrapolation (IVIVE) integrated in physiologically-based pharmacokinetic (PBPK) models have been increasingly used during drug discovery and development processes to predict human pharmacokinetic (PK) parameters. Drug transporters can influence drug pharmacokinetics and are key aspects contributing to the development of a successful drug. This review provides a snapshot of challenges or shortcomings of in vitro and in vivo techniques for understanding the contribution of drug transporters to a drug’s pharmacokinetics. The paper also describes the potential of IVIVE-PBPK models as prospective approaches to predict the role of drug transporters in drug discovery and development.

ADMET Profiling in Drug Discovery and Development: Perspectives of in silico, in vitro and integrated approaches

2021 ◽  
Vol 22 ◽  
Author(s):  
Nour El-Huda Daoud ◽  
Pobitra Borah ◽  
Pran Kishore Deb ◽  
Katharigatta N. Venugopala ◽  
Wafa Hourani ◽  
...  
Keyword(s):  
Drug Discovery ◽  
In Silico ◽  
Predictive Power ◽  
Early Stage ◽  
In Vitro Models ◽  
Prediction Ability ◽  
Drug Discovery And Development ◽  
In Silico Admet

: In the drug discovery setting, undesirable ADMET properties of a pharmacophore with good predictive power obtained after a tedious drug discovery and development process may lead to late-stage attrition. The early-stage ADMET profiling has introduced a new dimension to leading development. Although several high-throughput in vitro models are available for ADMET profiling, however, the in silico methods are gaining more importance because of their economic and faster prediction ability without the requirements of tedious and expensive laboratory resources. Nonetheless, in silico ADMET tools alone are not accurate and, therefore, ideally adopted along with in vitro and or in vivo methods in order to enhance predictability power. This review summarizes the significance and challenges associated with the application of in silico tools as well as the possible scope of in vitro models for integration to improve the ADMET predictability power of these tools.

Sign in / Sign up

Export Citation Format

Share Document