{"title":"Artificial intelligence in nanotechnology for treatment of diseases.","authors":"Soroush Heydari, Niloofar Masoumi, Erfan Esmaeeli, Seyed Mohammad Ayyoubzadeh, Fatemeh Ghorbani-Bidkorpeh, Mahnaz Ahmadi","doi":"10.1080/1061186X.2024.2393417","DOIUrl":null,"url":null,"abstract":"<p><p>Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles (NPs) are utilised as DDSs with unique characteristics, leading to diverse applications across different diseases. However, the complexity, cost and time-consuming nature of laboratory processes, the large volume of data, and the challenges in data analysis have prompted the integration of artificial intelligence (AI) tools. AI has been employed in designing, characterising and manufacturing drug delivery nanosystems, as well as in predicting treatment efficiency. AI's potential to personalise drug delivery based on individual patient factors, optimise formulation design and predict drug properties has been highlighted. By leveraging AI and large datasets, developing safe and effective DDSs can be accelerated, ultimately improving patient outcomes and advancing pharmaceutical sciences. This review article investigates the role of AI in the development of nano-DDSs, with a focus on their therapeutic applications. The use of AI in DDSs has the potential to revolutionise treatment optimisation and improve patient care.</p>","PeriodicalId":15573,"journal":{"name":"Journal of Drug Targeting","volume":" ","pages":"1247-1266"},"PeriodicalIF":4.3000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Drug Targeting","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/1061186X.2024.2393417","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/27 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles (NPs) are utilised as DDSs with unique characteristics, leading to diverse applications across different diseases. However, the complexity, cost and time-consuming nature of laboratory processes, the large volume of data, and the challenges in data analysis have prompted the integration of artificial intelligence (AI) tools. AI has been employed in designing, characterising and manufacturing drug delivery nanosystems, as well as in predicting treatment efficiency. AI's potential to personalise drug delivery based on individual patient factors, optimise formulation design and predict drug properties has been highlighted. By leveraging AI and large datasets, developing safe and effective DDSs can be accelerated, ultimately improving patient outcomes and advancing pharmaceutical sciences. This review article investigates the role of AI in the development of nano-DDSs, with a focus on their therapeutic applications. The use of AI in DDSs has the potential to revolutionise treatment optimisation and improve patient care.
期刊介绍：
Journal of Drug Targeting publishes papers and reviews on all aspects of drug delivery and targeting for molecular and macromolecular drugs including the design and characterization of carrier systems (whether colloidal, protein or polymeric) for both vitro and/or in vivo applications of these drugs.
Papers are not restricted to drugs delivered by way of a carrier, but also include studies on molecular and macromolecular drugs that are designed to target specific cellular or extra-cellular molecules. As such the journal publishes results on the activity, delivery and targeting of therapeutic peptides/proteins and nucleic acids including genes/plasmid DNA, gene silencing nucleic acids (e.g. small interfering (si)RNA, antisense oligonucleotides, ribozymes, DNAzymes), as well as aptamers, mononucleotides and monoclonal antibodies and their conjugates. The diagnostic application of targeting technologies as well as targeted delivery of diagnostic and imaging agents also fall within the scope of the journal. In addition, papers are sought on self-regulating systems, systems responsive to their environment and to external stimuli and those that can produce programmed, pulsed and otherwise complex delivery patterns.
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