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https://dx.doi.org/10.60692/he...
Other literature type . 2022
Data sources: Datacite
https://dx.doi.org/10.60692/f3...
Other literature type . 2022
Data sources: Datacite
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To explore the pharmacological mechanism of action using digital twin

لاستكشاف آلية العمل الدوائية باستخدام التوأم الرقمي
Authors: Rahman et al.;

To explore the pharmacological mechanism of action using digital twin

Abstract

With the advent of medical technology and science, the number of animals used in research has increased. For decades, the use of animals in research and product testing has been a point of conflict. Experts and pharmaceutical manufacturers are harming animals worldwide during laboratory research. Animals have also played a significant role in the advancement of science; animal testing has enabled the discovery of various novel drugs. The misery, suffering, and deaths of animals are not worth the potential human benefits. As a result, animals must not be exploited in research to assess the drug mechanism of action (MOA). Apart from the ethical concern, animal testing has a few more downsides, including the requirement for skilled labor, lengthy processes, and cost. Because it is critical to investigate adverse effects and toxicities in the development of potentially viable drugs. Assessment of each target will consume the range of resources as well as disturb living nature. As the digital twin works in an autonomous virtual world without influencing the physical structure and biological system. Our proposed framework suggests that the digital twin is a great reliable model of the physical system that will be beneficial in assessing the possible MOA prior to time without harming animals. The study describes the creation of a digital twin to combine the information and knowledge obtained by studying the different drug targets and diseases. Mechanism of Action using Digital twin (MOA-DT) will enable the experts to use an innovative approach without physical testing to save animals, time, and resources. DT reflects and simulates the actual drug and its relationships with its target, however presenting a more accurate depiction of the drug, which leads to maximize efficacy and decrease the toxicity of a drug. In conclusion, it has been shown that drug discovery and development can be safe, effective, and economical in no time through the combination of the digital and physical models of a pharmaceutical as compared to experimental animals.

Keywords

Advanced Techniques in Bioimage Analysis and Microscopy, Action (physics), Biophysics, Geometry, Epistemology, Recombinant Protein Production in Mammalian and Insect Cells, Quantum mechanics, Data science, Biochemistry, Genetics and Molecular Biology, FOS: Mathematics, Risk analysis (engineering), Business, Molecular Biology, Biology, Product (mathematics), Ecology, Physics, Life Sciences, Mechanism (biology), Computer science, Animal testing, FOS: Philosophy, ethics and religion, Philosophy, FOS: Biological sciences, Bioimage Analysis, Mathematics

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
gold