In vitro and In vivo Relevance of the P-glycoprotein Probe Substrates in Drug Discovery and Development: Focus on Rhodamine 123, Digoxin and Talinolol

2011 ◽  
Vol 01 (02) ◽  
Author(s):  
Ana Fortuna ◽  
Gilberto Alves ◽  
Amílcar Falcão
Keyword(s):  
Drug Discovery ◽  
Rhodamine 123 ◽  
Drug Discovery And Development ◽  
P Glycoprotein

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.

Effects of Polyoxyethylene Alkyl Ethers on the Intestinal Transport and Absorption of Rhodamine 123: A P-glycoprotein Substrate by In Vitro and In Vivo Studies

2016 ◽  
Vol 105 (4) ◽  
pp. 1526-1534 ◽  
Author(s):  
Wanting Zhao ◽  
Sachiyo Uehera ◽  
Keiichiro Tanaka ◽  
Shuhei Tadokoro ◽  
Kosuke Kusamori ◽  
...  
Keyword(s):  
Intestinal Transport ◽  
Rhodamine 123 ◽  
In Vivo Studies ◽  
P Glycoprotein ◽  
Alkyl Ethers

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.

Current Approaches to Drug Discovery for Chagas Disease: Methodological Advances

2019 ◽  
Vol 22 (8) ◽  
pp. 509-520
Author(s):  
Cauê B. Scarim ◽  
Chung M. Chin
Keyword(s):  
Drug Discovery ◽  
Chagas Disease ◽  
Drug Candidates ◽  
Lead Compounds ◽  
New Drug ◽  
Compound Libraries ◽  
Screening Assays ◽  
Cruzi Infection

Background: In recent years, there has been an improvement in the in vitro and in vivo methodology for the screening of anti-chagasic compounds. Millions of compounds can now have their activity evaluated (in large compound libraries) by means of high throughput in vitro screening assays. Objective: Current approaches to drug discovery for Chagas disease. Method: This review article examines the contribution of these methodological advances in medicinal chemistry in the last four years, focusing on Trypanosoma cruzi infection, obtained from the PubMed, Web of Science, and Scopus databases. Results: Here, we have shown that the promise is increasing each year for more lead compounds for the development of a new drug against Chagas disease. Conclusion: There is increased optimism among those working with the objective to find new drug candidates for optimal treatments against Chagas disease.

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