[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127019-en":3,"doc-seo-127019-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},127019,2336474466412,"Ezra","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Sustainable integration of artificial intelligence and machine learning approaches within the African infectious disease vaccine research and development ecosystem","Artificial intelligence and machine learning are already used to support vaccine discovery for diseases such as COVID-19, HIV, and hepatitis, shortening the pathway from candidate identification to deployment. Progress is extending across Africa, especially South Africa, Kenya, and Nigeria, to enhance drug discovery and clinical development. To make these advances durable continent-wide, the work outlines needed investment in knowledge growth, stakeholder collaboration, and stronger regulatory, ethical, and infrastructural frameworks.","TYPE Perspective  \nPUBLISHED 17 December 2024 DOI 10.3389/fphar.2024.1499079  \nOPEN ACCESS  \nEDITED BY  \nGunjan Arora,  \nYale University, United States  \nREVIEWED BY  \nParul Mehrotra,  \nIndian Institute of Technology Delhi, India Myron Christodoulides,  \nUniversity of Southampton, United Kingdom  \n*CORRESPONDENCE  \nDaniel Ochiel,  \n [dr.danielochiel@gmail.com](dr.danielochiel@gmail.com)  \nRECEIVED 20 September 2024  \nACCEPTED 26 November 2024  \nPUBLISHED 17 December 2024  \nCITATION  \nHare J, Nielsen M, Kiragga A and Ochiel D (2024) Sustainable integration of artificial intelligence and machine learning approaches within the African infectious disease vaccine research and development ecosystem.  \nFront. Pharmacol. 15:1499079 .  \ndoi: 10.3389/fphar.2024.1499079  \nCOPYRIGHT  \n© 2024 Hare, Nielsen, Kiragga and Ochiel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nSustainable integration of artificial intelligence and machine learning approaches within the African infectious disease vaccine research and development ecosystem  \nJonathan Hare 1, Morten Nielsen 2, Agnes Kiragga 3 and Daniel Ochiel 4*  \n1Biolife Research Limited, Nairobi, Kenya, 2Department of Health Technology, Technical University of Denmark, Lyngby, Denmark, 3Data Science Program, Africa Population Health Centre, Nairobi, Kenya, 4Henry Jackson Foundation Medical Research International, Nairobi, Kenya  \nArtificial Intelligence and Machine Learning (AI/ML) techniques, including reverse vaccinology and predictive models, have already been applied for developing vaccine candidates for COVID-19, HIV, and Hepatitis, streamlining the vaccine development lifecycle from discovery to deployment. The application of AI and ML technologies for improving heath interventions, including drug discovery and clinical development, are expanding across Africa, particularly in South Africa, Kenya, and Nigeria. Further initiatives are required however to expand AI/ML capabilities across the continent to ensure the development of a sustainable ecosystem including enhancing the requisite knowledge base, fostering collaboration between stakeholders, ensuring robust regulatory and ethical frameworks and investment in requisite infrastructure.  \nKEYWORDS  \nmachine learning (ML), artiificial intelligence, vaccines, Africa, drug discovery  \n1 Introduction  \nVaccine research and development (R&D) has experienced a recent revolution following the emergence of SARS-CoV-2 as the causative agent of COVID-1), with multinational collaborative efforts to develop and deploy safe and effective vaccines globally with unprecedented speed (Hu et al., 2021) . However, a second revolution in vaccine R&D is currently underway, with the incorporation of Artificial Intelligence (AI) systems and particularly the subdivision of Machine Learning (ML) algorithms positioned to provide a step change in accelerating new vaccine discoveries (Elzarrad et al., 2022; Kaushik et al., 2023) which can contribute to achieving the five key global priorities for enhancing vaccines as a tool for climate resilience as part of the recently published one health approach (Jadeja et al., 2023) .  \nFrontiers in Pharmacology 01 [frontiersin.org](frontiersin.org)  \n2 AI/ML for accelerating infectious disease vaccine discovery  \nThe use of reverse vaccinology has revolutionized the vaccine design approach in recent times, focusing on identifying promising candidates for vaccine development through bioinformatics-based analysis of the genomics/proteomics interactions between the host and the pathogen (Patil and Shreffler, 2019) . The first vaccine ca","cbCaikzsk3Y7Jz5f","https://ap.wps.com/l/cbCaikzsk3Y7Jz5f","pdf",943693,1,7,"English","en",105,"# Introduction\n## AI/ML for accelerating infectious disease vaccine discovery","[{\"question\":\"What role do AI/ML techniques play in infectious disease vaccine research?\",\"answer\":\"AI/ML techniques, including reverse vaccinology and predictive models, accelerate vaccine candidate identification and streamline parts of the vaccine development lifecycle from discovery to deployment.\"},{\"question\":\"Which African regions are highlighted for expanding AI/ML-enabled vaccine efforts?\",\"answer\":\"The text highlights expanding initiatives across Africa, particularly in South Africa, Kenya, and Nigeria.\"},{\"question\":\"What additional steps are needed to build a sustainable AI/ML ecosystem for vaccine R\\u0026D in Africa?\",\"answer\":\"Further efforts are required to expand AI/ML capabilities through stronger knowledge bases, improved collaboration among stakeholders, robust regulatory and ethical frameworks, and investment in enabling infrastructure.\"}]","Sustainable integration of artificial intelligence and machine learning approaches within the African infectious disease vaccine research and development ecosystem | PDF",1785936357,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"sustainable-integration-of-artificial-intelligence-and-machine-learning-approaches-within-the-african-infectious-disease-vaccine-research-and-development-ecosystem","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/sustainable-integration-of-artificial-intelligence-and-machine-learning-approaches-within-the-african-infectious-disease-vaccine-research-and-development-ecosystem/127019/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What role do AI/ML techniques play in infectious disease vaccine research?","Question",{"text":75,"@type":76},"AI/ML techniques, including reverse vaccinology and predictive models, accelerate vaccine candidate identification and streamline parts of the vaccine development lifecycle from discovery to deployment.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which African regions are highlighted for expanding AI/ML-enabled vaccine efforts?",{"text":80,"@type":76},"The text highlights expanding initiatives across Africa, particularly in South Africa, Kenya, and Nigeria.",{"name":82,"@type":73,"acceptedAnswer":83},"What additional steps are needed to build a sustainable AI/ML ecosystem for vaccine R&D in Africa?",{"text":84,"@type":76},"Further efforts are required to expand AI/ML capabilities through stronger knowledge bases, improved collaboration among stakeholders, robust regulatory and ethical frameworks, and investment in enabling infrastructure.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]