The Role of In Vitro ADME Assays in Antimalarial Drug Discovery and Development

2005 ◽  
Vol 8 (1) ◽  
pp. 89-98 ◽  
Author(s):  
Todd Shearer ◽  
Kirsten Smith ◽  
Damaris Diaz ◽  
Constance Asher ◽  
Julio Ramirez
Keyword(s):  
Drug Discovery ◽  
Antimalarial Drug ◽  
Drug Discovery And Development

Sitagliptin: a potential drug for the treatment of SARS-CoV-2?

2020 ◽  
Author(s):  
Sanaa Bardaweel
Keyword(s):  
Clinical Trials ◽  
Drug Discovery ◽  
Antimalarial Drug ◽  
Drug Repurposing ◽  
Spike Protein ◽  
Diabetic Patients ◽  
Potential Drug ◽  
Chemokine Production ◽  
Drug Discovery And Development ◽  
Sequence Identity

Recently, an outbreak of fatal coronavirus, SARS-CoV-2, has emerged from China and is rapidly spreading worldwide. As the coronavirus pandemic rages, drug discovery and development become even more challenging. Drug repurposing of the antimalarial drug chloroquine and its hydroxylated form had demonstrated apparent effectiveness in the treatment of COVID-19 associated pneumonia in clinical trials. SARS-CoV-2 spike protein shares 31.9% sequence identity with the spike protein presents in the Middle East Respiratory Syndrome Corona Virus (MERS-CoV), which infects cells through the interaction of its spike protein with the DPP4 receptor found on macrophages. Sitagliptin, a DPP4 inhibitor, that is known for its antidiabetic, immunoregulatory, anti-inflammatory, and beneficial cardiometabolic effects has been shown to reverse macrophage responses in MERS-CoV infection and reduce CXCL10 chemokine production in AIDS patients. We suggest that Sitagliptin may be beneficial alternative for the treatment of COVID-19 disease especially in diabetic patients and patients with preexisting cardiovascular conditions who are already at higher risk of COVID-19 infection.

Challenges in Alzheimer's Disease Drug Discovery and Development: The Role of Modeling, Simulation, and Open Data

2020 ◽  
Vol 107 (4) ◽  
pp. 796-805 ◽  
Author(s):  
Daniela J. Conrado ◽  
Sridhar Duvvuri ◽  
Hugo Geerts ◽  
Jackson Burton ◽  
Carla Biesdorf ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Discovery ◽  
Open Data ◽  
Drug Discovery And Development ◽  
Modeling Simulation

Application of porcine gastrointestinal organoid units as a potential in vitro tool for drug discovery and development

2018 ◽  
Vol 39 (1) ◽  
pp. 4-15 ◽  
Author(s):  
Adedamola Olayanju ◽  
Lauren Jones ◽  
Karin Greco ◽  
Christopher E. Goldring ◽  
Tahera Ansari
Keyword(s):  
Drug Discovery ◽  
Drug Discovery And Development

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 The evolution of strategies to minimise the risk of human drug-induced liver injury (DILI) in drug discovery and development

2020 ◽  
Vol 94 (8) ◽  
pp. 2559-2585 ◽  
Author(s):  
Paul A. Walker ◽  
Stephanie Ryder ◽  
Andrea Lavado ◽  
Clive Dilworth ◽  
Robert J. Riley
Keyword(s):  
Drug Discovery ◽  
Liver Injury ◽  
Drug Uptake ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
New Chemical Entities ◽  
Preclinical Animal Models ◽  
Uptake Transporters

Abstract Early identification of toxicity associated with new chemical entities (NCEs) is critical in preventing late-stage drug development attrition. Liver injury remains a leading cause of drug failures in clinical trials and post-approval withdrawals reflecting the poor translation between traditional preclinical animal models and human clinical outcomes. For this reason, preclinical strategies have evolved over recent years to incorporate more sophisticated human in vitro cell-based models with multi-parametric endpoints. This review aims to highlight the evolution of the strategies adopted to improve human hepatotoxicity prediction in drug discovery and compares/contrasts these with recent activities in our lab. The key role of human exposure and hepatic drug uptake transporters (e.g. OATPs, OAT2) is also elaborated.

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