Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches
The evolvement of COVID-19 vaccines is rapidly being revolutionized using artificial intelligence-based technologies. Small compounds, peptides, and epitopes are collected to develop new therapeutics. These substances can also guide artificial intelligence-based modeling, screening, or creation. Mac...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/14/12/665 |
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| author | Aritra Ghosh Maria M. Larrondo-Petrie Mirjana Pavlovic |
| author_facet | Aritra Ghosh Maria M. Larrondo-Petrie Mirjana Pavlovic |
| author_sort | Aritra Ghosh |
| collection | DOAJ |
| description | The evolvement of COVID-19 vaccines is rapidly being revolutionized using artificial intelligence-based technologies. Small compounds, peptides, and epitopes are collected to develop new therapeutics. These substances can also guide artificial intelligence-based modeling, screening, or creation. Machine learning techniques are used to leverage pre-existing data for COVID-19 drug detection and vaccine advancement, while artificial intelligence-based models are used for these purposes. Models based on artificial intelligence are used to evaluate and recognize the best candidate targets for future therapeutic development. Artificial intelligence-based strategies can be used to address issues with the safety and efficacy of COVID-19 vaccine candidates, as well as issues with manufacturing, storage, and logistics. Because antigenic peptides are effective at eliciting immune responses, artificial intelligence algorithms can assist in identifying the most promising COVID-19 vaccine candidates. Following COVID-19 vaccination, the first phase of the vaccine-induced immune response occurs when major histocompatibility complex (MHC) class II molecules (typically bind peptides of 12–25 amino acids) recognize antigenic peptides. Therefore, AI-based models are used to identify the best COVID-19 vaccine candidates and ensure the efficacy and safety of vaccine-induced immune responses. This study explores the use of artificial intelligence-based approaches to address logistics, manufacturing, storage, safety, and effectiveness issues associated with several COVID-19 vaccine candidates. Additionally, we will evaluate potential targets for next-generation treatments and examine the role that artificial intelligence-based models can play in identifying the most promising COVID-19 vaccine candidates, while also considering the effectiveness of antigenic peptides in triggering immune responses. The aim of this project is to gain insights into how artificial intelligence-based approaches could revolutionize the development of COVID-19 vaccines and how they can be leveraged to address challenges associated with vaccine development. In this work, we highlight potential barriers and solutions and focus on recent improvements in using artificial intelligence to produce COVID-19 drugs and vaccines, as well as the prospects for intelligent training in COVID-19 treatment discovery. |
| first_indexed | 2024-03-08T20:39:28Z |
| format | Article |
| id | doaj.art-072b1141f3fc430c8af4dac1a3b4aaa8 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-08T20:39:28Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-072b1141f3fc430c8af4dac1a3b4aaa82023-12-22T14:15:57ZengMDPI AGInformation2078-24892023-12-01141266510.3390/info14120665Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based ApproachesAritra Ghosh0Maria M. Larrondo-Petrie1Mirjana Pavlovic2Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USADepartment of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USADepartment of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USAThe evolvement of COVID-19 vaccines is rapidly being revolutionized using artificial intelligence-based technologies. Small compounds, peptides, and epitopes are collected to develop new therapeutics. These substances can also guide artificial intelligence-based modeling, screening, or creation. Machine learning techniques are used to leverage pre-existing data for COVID-19 drug detection and vaccine advancement, while artificial intelligence-based models are used for these purposes. Models based on artificial intelligence are used to evaluate and recognize the best candidate targets for future therapeutic development. Artificial intelligence-based strategies can be used to address issues with the safety and efficacy of COVID-19 vaccine candidates, as well as issues with manufacturing, storage, and logistics. Because antigenic peptides are effective at eliciting immune responses, artificial intelligence algorithms can assist in identifying the most promising COVID-19 vaccine candidates. Following COVID-19 vaccination, the first phase of the vaccine-induced immune response occurs when major histocompatibility complex (MHC) class II molecules (typically bind peptides of 12–25 amino acids) recognize antigenic peptides. Therefore, AI-based models are used to identify the best COVID-19 vaccine candidates and ensure the efficacy and safety of vaccine-induced immune responses. This study explores the use of artificial intelligence-based approaches to address logistics, manufacturing, storage, safety, and effectiveness issues associated with several COVID-19 vaccine candidates. Additionally, we will evaluate potential targets for next-generation treatments and examine the role that artificial intelligence-based models can play in identifying the most promising COVID-19 vaccine candidates, while also considering the effectiveness of antigenic peptides in triggering immune responses. The aim of this project is to gain insights into how artificial intelligence-based approaches could revolutionize the development of COVID-19 vaccines and how they can be leveraged to address challenges associated with vaccine development. In this work, we highlight potential barriers and solutions and focus on recent improvements in using artificial intelligence to produce COVID-19 drugs and vaccines, as well as the prospects for intelligent training in COVID-19 treatment discovery.https://www.mdpi.com/2078-2489/14/12/665COVID-19AI-based approachvaccine development |
| spellingShingle | Aritra Ghosh Maria M. Larrondo-Petrie Mirjana Pavlovic Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches Information COVID-19 AI-based approach vaccine development |
| title | Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches |
| title_full | Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches |
| title_fullStr | Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches |
| title_full_unstemmed | Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches |
| title_short | Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches |
| title_sort | revolutionizing vaccine development for covid 19 a review of ai based approaches |
| topic | COVID-19 AI-based approach vaccine development |
| url | https://www.mdpi.com/2078-2489/14/12/665 |
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