Nikhil Prasad Fact checked by:Thailand Medical News Team Oct 22, 2024 7 hours, 38 minutes ago
AI in Medicine: A New Approach to Monkeypox Treatment
Researchers from the Institute for Advanced Studies in Basic Sciences in Iran and Kimia Zist Parsian Pharmaceutical Company have developed a promising new tool to combat the Monkeypox (Mpox) virus, which has posed significant global health risks. The study uses advanced machine learning and deep learning to identify existing antiviral drugs that could help treat monkeypox more effectively.
New AI Framework Offers Hope for Treating Monkeypox
In recent years, monkeypox has emerged as a serious public health threat, with cases reported across the globe, including the United States. Despite this, there is still no approved drug specifically designed to treat the virus. This
AI in Medicine news report explores a study that introduces a new computer-based framework for predicting effective antiviral drugs, potentially offering a faster, cheaper path to treatment.
How Researchers Used AI to Combat Monkeypox
The research team focused on the use of drug repurposing - a method of finding new uses for drugs that have already been approved for other diseases. This is a cost-effective and time-saving approach that is gaining popularity, especially in dealing with viral outbreaks like COVID-19 and monkeypox.
The study collected data on several known viruses similar to monkeypox and used this information to generate a new dataset. With this data, they employed machine learning techniques and deep learning models to predict which existing antiviral drugs might be effective against monkeypox.
A key feature of the study is the use of a deep learning framework called "DRaW." This framework, along with other machine learning methods like decision trees and support vector machines (SVM), was used to process the data. The results from these different methods were then compared, and the most promising drugs were selected for further investigation.
Which Drugs Show the Most Promise?
Through their computational approach, the researchers identified five antiviral drugs that show promise in treating monkeypox. These are Tilorone, Valacyclovir, Ribavirin, Favipiravir, and Baloxavir marboxil. Each of these drugs has been previously approved for treating other viral infections, but this study suggests they could also be effective in treating monkeypox.
To confirm their predictions, the research team performed "docking studies," a method used to simulate how these drugs interact with the monkeypox virus at the molecular level. The study focused on a protein in the virus known as F-13, which plays a critical role in the virus’s growth and spread. The docking studies showed that all five of the proposed drugs could bind effectively to the F-13 protein, making them good candidates for monkeypox treatment.
Machine Learning and Deep Learning: A Powerful Combination
The study used both machine learning and deep learning techniques t
o analyze the data. Machine learning methods like decision trees and random forests can be highly effective at making predictions with limited computational resources. On the other hand, deep learning, as used in the DRaW model, is known for its ability to handle more complex data and produce more accurate results.
In this study, the deep learning model outperformed the other methods, showing the highest accuracy in predicting potential treatments. However, all the models confirmed that the five drugs selected were strong candidates for further testing. The researchers highlighted that this is the first time deep learning has been applied to drug repurposing for monkeypox, and the results are promising.
Potential Impact of This Research
The implications of this study could be significant, especially as the world continues to face viral outbreaks. Finding effective treatments for emerging diseases like monkeypox can be a lengthy and expensive process. Drug repurposing, combined with AI-driven methods, offers a faster and more affordable alternative.
One of the main advantages of using artificial intelligence in this context is its ability to quickly analyze large amounts of data and identify patterns that might not be obvious to humans. This can help speed up the drug discovery process, which is crucial in situations like the monkeypox outbreak, where time is of the essence.
Conclusion: A New Path Forward for Monkeypox Treatment
While more laboratory testing is needed to confirm the effectiveness of these drugs against monkeypox, the results of this study provide a solid starting point. The combination of drug repurposing and advanced computational methods has the potential to revolutionize how we approach treatment for viral diseases. By using existing drugs, researchers can bypass the long process of developing new medications, saving time and potentially saving lives.
This research could also pave the way for future studies on other emerging viruses. The AI framework developed in this study is not limited to monkeypox and could be adapted to identify treatments for a wide range of diseases. As artificial intelligence continues to improve, its role in healthcare, particularly in drug discovery and development, will likely expand.
The study findings were published in the peer-reviewed journal: PLOS ONE.
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0299342
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