The project’s goal is to develop applications that use cutting-edge achievements in biotechnology and big data analytics to contribute to the fight against antibiotic-resistant bacteria. The project will use DNA sequencing technology to analyze the genomes of pathogenic bacteria and collect genome samples of drug-resistant bacteria in Vietnam and around the world. The project will rely on this huge data source to develop modern computational models to understand the mechanism of antibiotic resistance in bacteria. The project will deploy analytical technologies on a cloud computing platform to provide microbiology research scientists as well as doctors via the internet. On the one hand, this application will provide tools to analyze genomic data of super drug-resistant bacteria for scientists so they can focus on their professional research without having to establish an information technology department, which is very expensive. On the other hand, the project’s platform will collect a large amount of genomic data of antibiotic-resistant bacteria from around the world, from which the project can enhance the analysis capabilities of machine learning applications. In addition, the rapid collection of data on bacteria, especially drug-resistant bacteria, from laboratories and hospitals will provide important information about relevant infectious disease epidemics to government agencies so they can handle it promptly and effectively.
Main content
- Developing a cloud computing platform: The project will build a genome database of antibiotic-resistant bacteria along with a data analysis system that applies the new and most effective methods. This system will be integrated on a cloud computing platform and deployed through a website application where the system will interact with users, receive genetic data and provide analysis reports to users.
- Develop a system to manage the spread and outbreak of antibiotic-resistant bacteria: Since the cloud computing analysis platform will collect genetic data of antibiotic-resistant bacteria from users in hospitals and laboratories in various parts of the world, the project will be able to extract information about outbreaks of antibiotic-resistant bacteria in different locations. From there, the project will build a system to detect, monitor and predict the spread of epidemics, thereby providing accurate and timely information for organizations and government agencies to have appropriate response.
- Develop deep learning models to detect new antibiotic resistance mechanisms in bacteria: The bacterial genetic data source that is continuously updated while users use the cloud computing analysis system will be the basis for the project to develop and strengthen computational, machine learning and deep learning models in this project. These models will again be deployed in the application in content 1 to serve users.
Influence
- The antibiotic-resistant bacterial genome analysis system is integrated on a cloud computing platform and deployed through a website application that will be designed as an open service. Potential users include researchers in laboratories and research centers as well as medical staff in hospitals. The system will help them quickly and comprehensively diagnose antibiotic resistance in the bacterial samples they are researching. The project has the ambition to build a leading standard and centralized system that is the number one choice for users when they are looking for a tool to analyze the bacterial genomic data they are researching.
- The system for monitoring and predicting the spread and outbreak of antibiotic-resistant bacteria can be applied in organizations and government agencies in monitoring, managing and handling epidemics. The project is expected to transfer this technology to the Ministry of Health and a number of hospital systems in Vietnam as well as abroad.
- The project’s products can provide services for diagnosing drug resistance in bacteria extracted from patients, in order to find the best treatment. This application will be transferred to specific hospitals such as Hospital for Tropical Diseases.
