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.

Deployment of in silico and in vitro safety assays in early-stage drug discovery

2012 ◽  
Vol 4 (10) ◽  
pp. 1211-1213 ◽  
Author(s):  
Yvonne Will ◽  
Thomas Schroeter
Keyword(s):  
Drug Discovery ◽  
In Silico ◽  
Early Stage

scholarly journals Inherited and Acquired Rhythm Disturbances in Sick Sinus Syndrome, Brugada Syndrome, and Atrial Fibrillation: Lessons from Preclinical Modeling

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3175
Author(s):  
Laura Iop ◽  
Sabino Iliceto ◽  
Giovanni Civieri ◽  
Francesco Tona
Keyword(s):  
Atrial Fibrillation ◽  
Cardiovascular Diseases ◽  
Brugada Syndrome ◽  
In Silico ◽  
Cardiac Fibrosis ◽  
Sick Sinus Syndrome ◽  
In Vitro Models ◽  
Global Functioning

Rhythm disturbances are life-threatening cardiovascular diseases, accounting for many deaths annually worldwide. Abnormal electrical activity might arise in a structurally normal heart in response to specific triggers or as a consequence of cardiac tissue alterations, in both cases with catastrophic consequences on heart global functioning. Preclinical modeling by recapitulating human pathophysiology of rhythm disturbances is fundamental to increase the comprehension of these diseases and propose effective strategies for their prevention, diagnosis, and clinical management. In silico, in vivo, and in vitro models found variable application to dissect many congenital and acquired rhythm disturbances. In the copious list of rhythm disturbances, diseases of the conduction system, as sick sinus syndrome, Brugada syndrome, and atrial fibrillation, have found extensive preclinical modeling. In addition, the electrical remodeling as a result of other cardiovascular diseases has also been investigated in models of hypertrophic cardiomyopathy, cardiac fibrosis, as well as arrhythmias induced by other non-cardiac pathologies, stress, and drug cardiotoxicity. This review aims to offer a critical overview on the effective ability of in silico bioinformatic tools, in vivo animal studies, in vitro models to provide insights on human heart rhythm pathophysiology in case of sick sinus syndrome, Brugada syndrome, and atrial fibrillation and advance their safe and successful translation into the cardiology arena.

scholarly journals Microphysiological Systems: A Pathologist’s Perspective

2020 ◽  
Vol 57 (3) ◽  
pp. 358-368
Author(s):  
Radhakrishna Sura ◽  
Terry Van Vleet ◽  
Brian R. Berridge
Keyword(s):  
Drug Discovery ◽  
Biomedical Research ◽  
Interdisciplinary Collaboration ◽  
Cell Types ◽  
In Vitro Models ◽  
In Vitro Methods ◽  
Microphysiological Systems ◽  
Regulatory Acceptance

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.

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.

In-silico Design, ADMET Screening, MM-GBSA Binding Free Energy of Some Novel Isoxazole Substituted 9-Anilinoacridines as HER2 Inhibitors Targeting Breast Cancer

2019 ◽  
Vol 11 (2) ◽  
pp. 118-128 ◽  
Author(s):  
Rajagopal Kalirajan ◽  
Arumugasamy Pandiselvi ◽  
Byran Gowramma ◽  
Pandiyan Balachandran
Keyword(s):  
Breast Cancer ◽  
Free Energy ◽  
In Silico ◽  
Therapeutic Potential ◽  
Binding Free Energy ◽  
Breast Cancers ◽  
Molecular Docking Study ◽  
In Silico Admet

Background: Human Epidermal development factor Receptor-2 (HER2) is a membrane tyrosine kinase which is overexpressed and gene amplified in human breast cancers. HER2 amplification and overexpression have been linked to important tumor cell proliferation and survival pathways for 20% of instances of breast cancer. 9-aminoacridines are significant DNA-intercalating agents because of their antiproliferative properties. Objective: Some novel isoxazole substituted 9-anilinoacridines(1a-z) were designed by in-silico technique for their HER2 inhibitory activity. Docking investigations of compounds 1a-z are performed against HER2 (PDB id-3PP0) by using Schrodinger suit 2016-2. Methods: Molecular docking study for the designed molecules 1a-z are performed by Glide module, in-silico ADMET screening by QikProp module and binding free energy by Prime-MMGBSA module of Schrodinger suit. The binding affinity of designed molecules 1a-z towards HER2 was chosen based on GLIDE score. Results: Many compounds showed good hydrophobic communications and hydrogen bonding associations to hinder HER2. The compounds 1a-z, aside from 1z have significant Glide scores in the scope of - 4.91 to - 10.59 when compared with the standard Ethacridine (- 4.23) and Tamoxifen (- 3.78). The in-silico ADMET properties are inside the suggested about drug likeness. MM-GBSA binding of the most intense inhibitor is positive. Conclusion: The outcomes reveal that this study provides evidence for the consideration of isoxazole substituted 9-aminoacridine derivatives as potential HER2 inhibitors. The compounds, 1s,x,v,a,j,r with significant Glide scores may produce significant anti breast cancer activity and further in vitro and in vivo investigations may prove their therapeutic potential.

Recommended Guidelines for Developing, Qualifying, and Implementing Complex In Vitro Models (CIVMs) for Drug Discovery

2020 ◽  
Vol 25 (10) ◽  
pp. 1174-1190
Author(s):  
Jason E. Ekert ◽  
Julianna Deakyne ◽  
Philippa Pribul-Allen ◽  
Rebecca Terry ◽  
Christopher Schofield ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Early Stage ◽  
Cell Types ◽  
In Vitro Models ◽  
Success Rates ◽  
Lead Discovery ◽  
Cellular Models ◽  
Discovery Phase ◽  
Early Drug

The pharmaceutical industry is continuing to face high research and development (R&D) costs and low overall success rates of clinical compounds during drug development. There is an increasing demand for development and validation of healthy or disease-relevant and physiological human cellular models that can be implemented in early-stage discovery, thereby shifting attrition of future therapeutics to a point in discovery at which the costs are significantly lower. There needs to be a paradigm shift in the early drug discovery phase (which is lengthy and costly), away from simplistic cellular models that show an inability to effectively and efficiently reproduce healthy or human disease-relevant states to steer target and compound selection for safety, pharmacology, and efficacy questions. This perspective article covers the various stages of early drug discovery from target identification (ID) and validation to the hit/lead discovery phase, lead optimization, and preclinical safety. We outline key aspects that should be considered when developing, qualifying, and implementing complex in vitro models (CIVMs) during these phases, because criteria such as cell types (e.g., cell lines, primary cells, stem cells, and tissue), platform (e.g., spheroids, scaffolds or hydrogels, organoids, microphysiological systems, and bioprinting), throughput, automation, and single and multiplexing endpoints will vary. The article emphasizes the need to adequately qualify these CIVMs such that they are suitable for various applications (e.g., context of use) of drug discovery and translational research. The article ends looking to the future, in which there is an increase in combining computational modeling, artificial intelligence and machine learning (AI/ML), and CIVMs.

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