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Gholap AD, Uddin MJ, Faiyazuddin M, Omri A, Gowri S, Khalid M. Advances in artificial intelligence for drug delivery and development: A comprehensive review. Comput Biol Med 2024; 178:108702. [PMID: 38878397 DOI: 10.1016/j.compbiomed.2024.108702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 05/12/2024] [Accepted: 06/01/2024] [Indexed: 07/24/2024]
Abstract
Artificial intelligence (AI) has emerged as a powerful tool to revolutionize the healthcare sector, including drug delivery and development. This review explores the current and future applications of AI in the pharmaceutical industry, focusing on drug delivery and development. It covers various aspects such as smart drug delivery networks, sensors, drug repurposing, statistical modeling, and simulation of biotechnological and biological systems. The integration of AI with nanotechnologies and nanomedicines is also examined. AI offers significant advancements in drug discovery by efficiently identifying compounds, validating drug targets, streamlining drug structures, and prioritizing response templates. Techniques like data mining, multitask learning, and high-throughput screening contribute to better drug discovery and development innovations. The review discusses AI applications in drug formulation and delivery, clinical trials, drug safety, and pharmacovigilance. It addresses regulatory considerations and challenges associated with AI in pharmaceuticals, including privacy, data security, and interpretability of AI models. The review concludes with future perspectives, highlighting emerging trends, addressing limitations and biases in AI models, and emphasizing the importance of collaboration and knowledge sharing. It provides a comprehensive overview of AI's potential to transform the pharmaceutical industry and improve patient care while identifying further research and development areas.
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Affiliation(s)
- Amol D Gholap
- Department of Pharmaceutics, St. John Institute of Pharmacy and Research, Palghar, Maharashtra, 401404, India.
| | - Md Jasim Uddin
- Department of Pharmaceutical Technology, Faculty of Pharmacy, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
| | - Md Faiyazuddin
- School of Pharmacy, Al-Karim University, Katihar, Bihar, 854106, India; Centre for Global Health Research, Saveetha Institute of Medical and Technical Sciences, Tamil Nadu, India.
| | - Abdelwahab Omri
- Department of Chemistry and Biochemistry, The Novel Drug and Vaccine Delivery Systems Facility, Laurentian University, Sudbury, ON, P3E 2C6, Canada.
| | - S Gowri
- PG & Research, Department of Physics, Cauvery College for Women, Tiruchirapalli, Tamil Nadu, 620018, India
| | - Mohammad Khalid
- James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK; Sunway Centre for Electrochemical Energy and Sustainable Technology (SCEEST), School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, 47500 Selangor Darul Ehsan, Malaysia; University Centre for Research and Development, Chandigarh University, Mohali, Punjab, 140413, India.
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2
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Ferrara F, Castagna T, Pantolini B, Campanardi MC, Roperti M, Grotto A, Fattori M, Dal Maso L, Carrara F, Zambarbieri G, Zovi A, Capuozzo M, Langella R. The challenge of antimicrobial resistance (AMR): current status and future prospects. NAUNYN-SCHMIEDEBERG'S ARCHIVES OF PHARMACOLOGY 2024:10.1007/s00210-024-03318-x. [PMID: 39052061 DOI: 10.1007/s00210-024-03318-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Accepted: 07/18/2024] [Indexed: 07/27/2024]
Abstract
Antimicrobial resistance (AMR) represents a critical global threat, compromising the effectiveness of antibacterial drugs as bacteria adapt and survive exposure to many classes of these drugs. This phenomenon is primarily fueled by the widespread overuse and misuse of antibacterial drugs, exerting selective pressure on bacteria and promoting the emergence of multi-resistant strains. AMR poses a top-priority challenge to public health due to its widespread epidemiological and economic implications, exacerbated not only by the diminishing effectiveness of currently available antimicrobial agents but also by the limited development of genuinely effective new molecules. In addressing this issue, our research aimed to examine the scientific literature narrating the Italian situation in the common European context of combating AMR. We sought to delineate the current state of AMR and explore future prospects through an analysis of strategies to counter antibacterial drug resistance. Adopting the "One Health" model, our objective was to comprehensively engage diverse sectors, integrate various disciplines, and propose programs, policies, and regulations. This narrative review, based on PubMed research related to antibiotic resistance, emphasizes the urgent need for a coordinated and proactive approach at both national and European levels to mitigate the impact of AMR and pave the way for effective strategies to counter this global health challenge.
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Affiliation(s)
- Francesco Ferrara
- Pharmaceutical Department, Asl Napoli 3 Sud, Dell'amicizia Street 72, 80035, Nola, Naples, Italy.
| | - Tommaso Castagna
- Pharmacy Unit, ASST Di Lecco, Dell'Eremo Street 9/11, 23900, Lecco, Italy
| | | | | | - Martina Roperti
- IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, 20159, Milan, Italy
| | - Alessandra Grotto
- University of Milan, Festa del Perdono Street 7, 20122, Milan, Italy
| | - Martina Fattori
- Istituto Europeo Di Oncologia, Ripamonti Street 435, 20122, Milan, Italy
| | - Lucia Dal Maso
- Pharmaceutical Department, ASST Santi Paolo E Carlo, Antonio Rudinì Street 8, 20159, Milan, Italy
| | - Federica Carrara
- Pharmaceutical Department, Humanitas Gavazzeni, Mauro Gavazzeni Street 21, 24125, Bergamo, BG, Italy
| | - Giulia Zambarbieri
- Pharmaceutical Department, Humanitas Gavazzeni, Mauro Gavazzeni Street 21, 24125, Bergamo, BG, Italy
| | - Andrea Zovi
- Ministry of Health, Viale Giorgio Ribotta 5, 00144, Rome, Italy
| | - Maurizio Capuozzo
- Pharmaceutical Department, Asl Napoli 3 Sud, Dell'amicizia Street 72, 80035, Nola, Naples, Italy
| | - Roberto Langella
- Italian Society of Hospital Pharmacy (SIFO), SIFO Secretariat of the Lombardy Region, Via Carlo Farini, 81, 20159, Milan, Italy
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3
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Marino A, Augello E, Stracquadanio S, Bellanca CM, Cosentino F, Spampinato S, Cantarella G, Bernardini R, Stefani S, Cacopardo B, Nunnari G. Unveiling the Secrets of Acinetobacter baumannii: Resistance, Current Treatments, and Future Innovations. Int J Mol Sci 2024; 25:6814. [PMID: 38999924 PMCID: PMC11241693 DOI: 10.3390/ijms25136814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Revised: 06/18/2024] [Accepted: 06/19/2024] [Indexed: 07/14/2024] Open
Abstract
Acinetobacter baumannii represents a significant concern in nosocomial settings, particularly in critically ill patients who are forced to remain in hospital for extended periods. The challenge of managing and preventing this organism is further compounded by its increasing ability to develop resistance due to its extraordinary genomic plasticity, particularly in response to adverse environmental conditions. Its recognition as a significant public health risk has provided a significant impetus for the identification of new therapeutic approaches and infection control strategies. Indeed, currently used antimicrobial agents are gradually losing their efficacy, neutralized by newer and newer mechanisms of bacterial resistance, especially to carbapenem antibiotics. A deep understanding of the underlying molecular mechanisms is urgently needed to shed light on the properties that allow A. baumannii enormous resilience against standard therapies. Among the most promising alternatives under investigation are the combination sulbactam/durlobactam, cefepime/zidebactam, imipenem/funobactam, xeruborbactam, and the newest molecules such as novel polymyxins or zosurabalpin. Furthermore, the potential of phage therapy, as well as deep learning and artificial intelligence, offer a complementary approach that could be particularly useful in cases where traditional strategies fail. The fight against A. baumannii is not confined to the microcosm of microbiological research or hospital wards; instead, it is a broader public health dilemma that demands a coordinated, global response.
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Affiliation(s)
- Andrea Marino
- Unit of Infectious Diseases, Department of Clinical and Experimental Medicine, University of Catania, ARNAS Garibaldi Hospital, 95122 Catania, Italy
| | - Egle Augello
- Department of Biomedical and Biotechnological Science, Section of Pharmacology, University of Catania, 95123 Catania, Italy
- Clinical Toxicology Unit, University Hospital of Catania, 95123 Catania, Italy
| | - Stefano Stracquadanio
- Department of Biomedical and Biotechnological Sciences, Section of Microbiology, University of Catania, Via Santa Sofia 97, 95123 Catania, Italy
| | - Carlo Maria Bellanca
- Department of Biomedical and Biotechnological Science, Section of Pharmacology, University of Catania, 95123 Catania, Italy
- Clinical Toxicology Unit, University Hospital of Catania, 95123 Catania, Italy
| | - Federica Cosentino
- Unit of Infectious Diseases, Department of Clinical and Experimental Medicine, University of Catania, ARNAS Garibaldi Hospital, 95122 Catania, Italy
| | - Serena Spampinato
- Unit of Infectious Diseases, Department of Clinical and Experimental Medicine, University of Catania, ARNAS Garibaldi Hospital, 95122 Catania, Italy
| | - Giuseppina Cantarella
- Department of Biomedical and Biotechnological Science, Section of Pharmacology, University of Catania, 95123 Catania, Italy
| | - Renato Bernardini
- Department of Biomedical and Biotechnological Science, Section of Pharmacology, University of Catania, 95123 Catania, Italy
- Clinical Toxicology Unit, University Hospital of Catania, 95123 Catania, Italy
| | - Stefania Stefani
- Department of Biomedical and Biotechnological Sciences, Section of Microbiology, University of Catania, Via Santa Sofia 97, 95123 Catania, Italy
| | - Bruno Cacopardo
- Unit of Infectious Diseases, Department of Clinical and Experimental Medicine, University of Catania, ARNAS Garibaldi Hospital, 95122 Catania, Italy
| | - Giuseppe Nunnari
- Unit of Infectious Diseases, Department of Clinical and Experimental Medicine, University of Catania, ARNAS Garibaldi Hospital, 95122 Catania, Italy
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Mihaylova S, Tsvetkova A, Georgieva E, Vankova D. Bioactive Phyto-Compounds with Antimicrobial Effects and AI: Results of a Desk Research Study. Microorganisms 2024; 12:1055. [PMID: 38930437 PMCID: PMC11205534 DOI: 10.3390/microorganisms12061055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 05/20/2024] [Accepted: 05/22/2024] [Indexed: 06/28/2024] Open
Abstract
Resistance of microorganisms to antibiotics represents a formidable global challenge, manifesting in intricate public health ramifications including escalated mortality rates and augmented healthcare costs. The current efforts to manage antimicrobial resistance (AMR) are limited mainly to the standard therapeutic approaches. The aim of this study is to present and analyze the role of artificial intelligence (AI) in the search for new phyto-compounds and novel interactions with antimicrobial effects. The ambition of the current research study is to support researchers by providing summarized information and ideas for future research in the battle with AMR. Inevitably, the AI role in healthcare is growing exponentially. The reviewed AI models reveal new data on essential oils (EOs) as potential therapeutic agents. In terms of antibacterial activity, EOs show activity against MDR bacteria, reduce resistance by sensitizing bacteria to the action of antibiotics, and improve therapeutic efficiency when combined with antibiotics. AI models can also serve for the detailed study of other therapeutic applications of EOs such as respiratory diseases, immune diseases, neurodegenerative diseases, and oncological diseases. The last 5 years have seen an increasing application of AI in the search for potential plant sources to control AMR. For the time being, the application of machine-learning (ML) models is greater in the studies of EOs. Future attention of research teams may also be directed toward a more efficient search for plant antimicrobial peptides (PAMPs). Of course, investments in this direction are a necessary preface, but the excitement of new possibilities should not override the role of human intelligence in directing research processes. In this report, tradition meets innovation to address the "silent pandemic" of AMR.
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Affiliation(s)
- Silviya Mihaylova
- Medical College, Medical University of Varna, 9002 Varna, Bulgaria; (A.T.); (E.G.)
| | - Antoaneta Tsvetkova
- Medical College, Medical University of Varna, 9002 Varna, Bulgaria; (A.T.); (E.G.)
| | - Emiliya Georgieva
- Medical College, Medical University of Varna, 9002 Varna, Bulgaria; (A.T.); (E.G.)
| | - Desislava Vankova
- Department of Social Medicine and Health Care Organisation, Faculty of Public Health, Medical University of Varna, 9002 Varna, Bulgaria;
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5
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Xiao J, Yin M, Yang M, Ren J, Liu C, Lian J, Lu X, Jiang Y, Yao Y, Luo J. Lipase and pH-responsive diblock copolymers featuring fluorocarbon and carboxyl betaine for methicillin-resistant staphylococcus aureus infections. J Control Release 2024; 369:39-52. [PMID: 38508523 DOI: 10.1016/j.jconrel.2024.03.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/08/2024] [Accepted: 03/13/2024] [Indexed: 03/22/2024]
Abstract
The emergence of multidrug-resistant bacteria along with their resilient biofilms necessitates the development of creative antimicrobial remedies. We designed versatile fluorinated polymer micelles with surface-charge-switchable properties, demonstrating enhanced efficacy against Methicillin-Resistant Staphylococcus Aureus (MRSA) in planktonic and biofilm states. Polymethacrylate diblock copolymers with pendant fluorocarbon chains and carboxyl betaine groups were prepared using reversible addition-fragmentation chain transfer polymerization. Amphiphilic fluorinated copolymers self-assembled into micelles, encapsulating ciprofloxacin in their cores (CIP@FCBMs) for antibacterial and antibiofilm applications. As a control, fluorine-free copolymer micelles loaded with ciprofloxacin (CIP@BCBMs) were prepared. Although both CIP@FCBMs and CIP@BCBMs exhibited pH-responsive surface charges and lipase-triggered drug release, CIP@FCBMs exhibited powerful antimicrobial and antibiofilm activities in vitro and in vivo, attributed to superior serum stability, higher drug loading, enhanced fluorination-facilitated cellular uptake, and lipase-triggered drug release. Collectively, reversing surface charge, on-demand antibiotic release, and fluorination-mediated nanoparticles hold promise for treating bacterial infections and biofilms.
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Affiliation(s)
- Jipeng Xiao
- College of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China; Precision Medicine Translational Research Center, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Meihui Yin
- College of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China; Precision Medicine Translational Research Center, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Min Yang
- College of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China
| | - Jinghang Ren
- CCTEG Xi'an Research Institute (Group) Co., Ltd, Xi'an 710000, Shanxi, China
| | - Cheng Liu
- CCTEG Xi'an Research Institute (Group) Co., Ltd, Xi'an 710000, Shanxi, China.
| | - Jiali Lian
- College of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China
| | - Xinyu Lu
- College of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China
| | - Yuchen Jiang
- College of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China
| | - Yongchao Yao
- Precision Medicine Translational Research Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Jianbin Luo
- College of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China.
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6
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Du S, Hu X, Menéndez-Arias L, Zhan P, Liu X. Target-based drug design strategies to overcome resistance to antiviral agents: opportunities and challenges. Drug Resist Updat 2024; 73:101053. [PMID: 38301487 DOI: 10.1016/j.drup.2024.101053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/22/2023] [Accepted: 01/09/2024] [Indexed: 02/03/2024]
Abstract
Viral infections have a major impact in human health. Ongoing viral transmission and escalating selective pressure have the potential to favor the emergence of vaccine- and antiviral drug-resistant viruses. Target-based approaches for the design of antiviral drugs can play a pivotal role in combating drug-resistant challenges. Drug design computational tools facilitate the discovery of novel drugs. This review provides a comprehensive overview of current drug design strategies employed in the field of antiviral drug resistance, illustrated through the description of a series of successful applications. These strategies include technologies that enhance compound-target affinity while minimizing interactions with mutated binding pockets. Furthermore, emerging approaches such as virtual screening, targeted protein/RNA degradation, and resistance analysis during drug design have been harnessed to curtail the emergence of drug resistance. Additionally, host targeting antiviral drugs offer a promising avenue for circumventing viral mutation. The widespread adoption of these refined drug design strategies will effectively address the prevailing challenge posed by antiviral drug resistance.
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Affiliation(s)
- Shaoqing Du
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, 44 West Culture Road, 250012 Jinan, Shandong, PR China
| | - Xueping Hu
- Institute of Frontier Chemistry, School of Chemistry and Chemical Engineering, Shandong University, Qingdao 266237, PR China
| | - Luis Menéndez-Arias
- Centro de Biología Molecular "Severo Ochoa" (Consejo Superior de Investigaciones Científicas & Universidad Autónoma de Madrid), Madrid, Spain.
| | - Peng Zhan
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, 44 West Culture Road, 250012 Jinan, Shandong, PR China; China-Belgium Collaborative Research Center for Innovative Antiviral Drugs of Shandong Province, 44 West Culture Road, 250012 Jinan, Shandong, PR China.
| | - Xinyong Liu
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, 44 West Culture Road, 250012 Jinan, Shandong, PR China; China-Belgium Collaborative Research Center for Innovative Antiviral Drugs of Shandong Province, 44 West Culture Road, 250012 Jinan, Shandong, PR China.
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Baddal B, Taner F, Uzun Ozsahin D. Harnessing of Artificial Intelligence for the Diagnosis and Prevention of Hospital-Acquired Infections: A Systematic Review. Diagnostics (Basel) 2024; 14:484. [PMID: 38472956 DOI: 10.3390/diagnostics14050484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 01/23/2024] [Accepted: 02/19/2024] [Indexed: 03/14/2024] Open
Abstract
Healthcare-associated infections (HAIs) are the most common adverse events in healthcare and constitute a major global public health concern. Surveillance represents the foundation for the effective prevention and control of HAIs, yet conventional surveillance is costly and labor intensive. Artificial intelligence (AI) and machine learning (ML) have the potential to support the development of HAI surveillance algorithms for the understanding of HAI risk factors, the improvement of patient risk stratification as well as the prediction and timely detection and prevention of infections. AI-supported systems have so far been explored for clinical laboratory testing and imaging diagnosis, antimicrobial resistance profiling, antibiotic discovery and prediction-based clinical decision support tools in terms of HAIs. This review aims to provide a comprehensive summary of the current literature on AI applications in the field of HAIs and discuss the future potentials of this emerging technology in infection practice. Following the PRISMA guidelines, this study examined the articles in databases including PubMed and Scopus until November 2023, which were screened based on the inclusion and exclusion criteria, resulting in 162 included articles. By elucidating the advancements in the field, we aim to highlight the potential applications of AI in the field, report related issues and shortcomings and discuss the future directions.
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Affiliation(s)
- Buket Baddal
- Department of Medical Microbiology and Clinical Microbiology, Faculty of Medicine, Near East University, North Cyprus, Mersin 10, 99138 Nicosia, Turkey
- DESAM Research Institute, Near East University, North Cyprus, Mersin 10, 99138 Nicosia, Turkey
| | - Ferdiye Taner
- Department of Medical Microbiology and Clinical Microbiology, Faculty of Medicine, Near East University, North Cyprus, Mersin 10, 99138 Nicosia, Turkey
- DESAM Research Institute, Near East University, North Cyprus, Mersin 10, 99138 Nicosia, Turkey
| | - Dilber Uzun Ozsahin
- Department of Medical Diagnostic Imaging, College of Health Science, University of Sharjah, Sharjah 27272, United Arab Emirates
- Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
- Operational Research Centre in Healthcare, Near East University, North Cyprus, Mersin 10, 99138 Nicosia, Turkey
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8
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Sahoo P. Complementary supramolecular drug associates in perfecting the multidrug therapy against multidrug resistant bacteria. Front Immunol 2024; 15:1352483. [PMID: 38415251 PMCID: PMC10897028 DOI: 10.3389/fimmu.2024.1352483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 01/23/2024] [Indexed: 02/29/2024] Open
Abstract
The inappropriate and inconsistent use of antibiotics in combating multidrug-resistant bacteria exacerbates their drug resistance through a few distinct pathways. Firstly, these bacteria can accumulate multiple genes, each conferring resistance to a specific drug, within a single cell. This accumulation usually takes place on resistance plasmids (R). Secondly, multidrug resistance can arise from the heightened expression of genes encoding multidrug efflux pumps, which expel a broad spectrum of drugs from the bacterial cells. Additionally, bacteria can also eliminate or destroy antibiotic molecules by modifying enzymes or cell walls and removing porins. A significant limitation of traditional multidrug therapy lies in its inability to guarantee the simultaneous delivery of various drug molecules to a specific bacterial cell, thereby fostering incremental drug resistance in either of these paths. Consequently, this approach prolongs the treatment duration. Rather than using a biologically unimportant coformer in forming cocrystals, another drug molecule can be selected either for protecting another drug molecule or, can be selected for its complementary activities to kill a bacteria cell synergistically. The development of a multidrug cocrystal not only improves tabletability and plasticity but also enables the simultaneous delivery of multiple drugs to a specific bacterial cell, philosophically perfecting multidrug therapy. By adhering to the fundamental tenets of multidrug therapy, the synergistic effects of these drug molecules can effectively eradicate bacteria, even before they have the chance to develop resistance. This approach has the potential to shorten treatment periods, reduce costs, and mitigate drug resistance. Herein, four hypotheses are presented to create complementary drug cocrystals capable of simultaneously reaching bacterial cells, effectively destroying them before multidrug resistance can develop. The ongoing surge in the development of novel drugs provides another opportunity in the fight against bacteria that are constantly gaining resistance to existing treatments. This endeavour holds the potential to combat a wide array of multidrug-resistant bacteria.
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Affiliation(s)
- Pathik Sahoo
- International Center for Materials and Nanoarchitectronics (MANA), Research Center for Advanced Measurement and Characterization (RCAMC), National Institute for Materials Science, Tsukuba, Japan
- Foundation of Physics Research Center (FoPRC), Celico, Italy
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9
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Ji S, An F, Zhang T, Lou M, Guo J, Liu K, Zhu Y, Wu J, Wu R. Antimicrobial peptides: An alternative to traditional antibiotics. Eur J Med Chem 2024; 265:116072. [PMID: 38147812 DOI: 10.1016/j.ejmech.2023.116072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 12/04/2023] [Accepted: 12/17/2023] [Indexed: 12/28/2023]
Abstract
As antibiotic-resistant bacteria and genes continue to emerge, the identification of effective alternatives to traditional antibiotics has become a pressing issue. Antimicrobial peptides are favored for their safety, low residue, and low resistance properties, and their unique antimicrobial mechanisms show significant potential in combating antibiotic resistance. However, the high production cost and weak activity of antimicrobial peptides limit their application. Moreover, traditional laboratory methods for identifying and designing new antimicrobial peptides are time-consuming and labor-intensive, hindering their development. Currently, novel technologies, such as artificial intelligence (AI) are being employed to develop and design new antimicrobial peptide resources, offering new opportunities for the advancement of antimicrobial peptides. This article summarizes the basic characteristics and antimicrobial mechanisms of antimicrobial peptides, as well as their advantages and limitations, and explores the application of AI in antimicrobial peptides prediction amd design. This highlights the crucial role of AI in enhancing the efficiency of antimicrobial peptide research and provides a reference for antimicrobial drug development.
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Affiliation(s)
- Shuaiqi Ji
- College of Food Science, Shenyang Agricultural University, Shenyang, 110866, PR China; Shenyang Key Laboratory of Microbial Fermentation Technology Innovation, Shenyang, 110866, PR China
| | - Feiyu An
- College of Food Science, Shenyang Agricultural University, Shenyang, 110866, PR China; Liaoning Engineering Research Center of Food Fermentation Technology, Shenyang, 110866, PR China
| | - Taowei Zhang
- College of Food Science, Shenyang Agricultural University, Shenyang, 110866, PR China; Shenyang Key Laboratory of Microbial Fermentation Technology Innovation, Shenyang, 110866, PR China
| | - Mengxue Lou
- College of Food Science, Shenyang Agricultural University, Shenyang, 110866, PR China; Liaoning Engineering Research Center of Food Fermentation Technology, Shenyang, 110866, PR China
| | - Jiawei Guo
- College of Food Science, Shenyang Agricultural University, Shenyang, 110866, PR China; Shenyang Key Laboratory of Microbial Fermentation Technology Innovation, Shenyang, 110866, PR China
| | - Kexin Liu
- College of Food Science, Shenyang Agricultural University, Shenyang, 110866, PR China; Shenyang Key Laboratory of Microbial Fermentation Technology Innovation, Shenyang, 110866, PR China
| | - Yi Zhu
- College of Food Science, Shenyang Agricultural University, Shenyang, 110866, PR China; Liaoning Engineering Research Center of Food Fermentation Technology, Shenyang, 110866, PR China
| | - Junrui Wu
- College of Food Science, Shenyang Agricultural University, Shenyang, 110866, PR China; Liaoning Engineering Research Center of Food Fermentation Technology, Shenyang, 110866, PR China; Shenyang Key Laboratory of Microbial Fermentation Technology Innovation, Shenyang, 110866, PR China.
| | - Rina Wu
- College of Food Science, Shenyang Agricultural University, Shenyang, 110866, PR China; Liaoning Engineering Research Center of Food Fermentation Technology, Shenyang, 110866, PR China; Shenyang Key Laboratory of Microbial Fermentation Technology Innovation, Shenyang, 110866, PR China.
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10
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Liu GY, Yu D, Fan MM, Zhang X, Jin ZY, Tang C, Liu XF. Antimicrobial resistance crisis: could artificial intelligence be the solution? Mil Med Res 2024; 11:7. [PMID: 38254241 PMCID: PMC10804841 DOI: 10.1186/s40779-024-00510-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
Antimicrobial resistance is a global public health threat, and the World Health Organization (WHO) has announced a priority list of the most threatening pathogens against which novel antibiotics need to be developed. The discovery and introduction of novel antibiotics are time-consuming and expensive. According to WHO's report of antibacterial agents in clinical development, only 18 novel antibiotics have been approved since 2014. Therefore, novel antibiotics are critically needed. Artificial intelligence (AI) has been rapidly applied to drug development since its recent technical breakthrough and has dramatically improved the efficiency of the discovery of novel antibiotics. Here, we first summarized recently marketed novel antibiotics, and antibiotic candidates in clinical development. In addition, we systematically reviewed the involvement of AI in antibacterial drug development and utilization, including small molecules, antimicrobial peptides, phage therapy, essential oils, as well as resistance mechanism prediction, and antibiotic stewardship.
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Affiliation(s)
- Guang-Yu Liu
- Department of Immunology and Pathogen Biology, School of Basic Medical Sciences, Hangzhou Normal University, Key Laboratory of Aging and Cancer Biology of Zhejiang Province, Key Laboratory of Inflammation and Immunoregulation of Hangzhou, Hangzhou Normal University, Hangzhou, 311121, China
| | - Dan Yu
- National Key Discipline of Pediatrics Key Laboratory of Major Diseases in Children Ministry of Education, Laboratory of Dermatology, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China
| | - Mei-Mei Fan
- Department of Immunology and Pathogen Biology, School of Basic Medical Sciences, Hangzhou Normal University, Key Laboratory of Aging and Cancer Biology of Zhejiang Province, Key Laboratory of Inflammation and Immunoregulation of Hangzhou, Hangzhou Normal University, Hangzhou, 311121, China
| | - Xu Zhang
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, MN, 55905, USA
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Ze-Yu Jin
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Christoph Tang
- Sir William Dunn School of Pathology, University of Oxford, Oxford, OX1 3RE, UK.
| | - Xiao-Fen Liu
- Institute of Antibiotics, Huashan Hospital, Fudan University, Key Laboratory of Clinical Pharmacology of Antibiotics, National Health Commission of the People's Republic of China, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China.
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11
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Li Z, Wang H, Hou J, Li M, Shi X, Liu B, Chen Z, Liu Q, Fu Q. Cylindrical granules in the development of mesalazine solid formulations (Ⅱ): The contribution of high aspect ratio to favorable tabletability. Int J Pharm 2024; 649:123665. [PMID: 38048889 DOI: 10.1016/j.ijpharm.2023.123665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 11/27/2023] [Accepted: 12/01/2023] [Indexed: 12/06/2023]
Abstract
Recently, cylindrical granules have been applied in pharmaceutical fields and their aspect ratio (AR) is considered an important factor in the manufacturing process. However, the relationships between AR and the tableting process were seldom reported. This study aims to clarify the role of AR in the tableting process of cylindrical granules. First, mesalazine cylindrical granules with different AR were extruded, and their physical attributes were then comprehensively characterized. Subsequently, their compression behaviors and tableting performances were systematically assessed. Notably, it was found that the cylindrical granules with high AR possessed good anti-deformation capacity and favorable tabletability. Finally, the dissolution test suggested that tablets compressed from cylindrical granules with higher AR showed lower dissolution rates. Collectively, findings in this study identified that the AR of cylindrical granules was a critical factor in the tableting process and provided valuable guidance for the application of these granules in oral solid formulations.
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Affiliation(s)
- Zhaohua Li
- Wuya College of Innovation, Shenyang Pharmaceutical University, No. 103, Wenhua Road, Shenyang 110016, China
| | - Hongge Wang
- Wuya College of Innovation, Shenyang Pharmaceutical University, No. 103, Wenhua Road, Shenyang 110016, China
| | - Jiayue Hou
- Wuya College of Innovation, Shenyang Pharmaceutical University, No. 103, Wenhua Road, Shenyang 110016, China
| | - Mo Li
- Liaoning Institute for Drug Control, No. 7 Chongshan West Road, Shenyang 110016, China
| | - Xianbao Shi
- Department of Pharmacy, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou 121012, China
| | - Bingyang Liu
- Wuya College of Innovation, Shenyang Pharmaceutical University, No. 103, Wenhua Road, Shenyang 110016, China
| | - Ziang Chen
- School of Pharmacy, Shenyang Pharmaceutical University, No. 103, Wenhua Road, Shenyang 110016, China
| | - Qiwei Liu
- School of Pharmacy, Shenyang Pharmaceutical University, No. 103, Wenhua Road, Shenyang 110016, China
| | - Qiang Fu
- Wuya College of Innovation, Shenyang Pharmaceutical University, No. 103, Wenhua Road, Shenyang 110016, China.
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12
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Silva-Júnior EFD. "You've got the Body I've got the Brains" - Could the current AI-based tools replace the human ingenuity for designing new drug candidates? Bioorg Med Chem 2023; 94:117475. [PMID: 37741120 DOI: 10.1016/j.bmc.2023.117475] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/12/2023] [Accepted: 09/12/2023] [Indexed: 09/25/2023]
Abstract
The emergence of artificial intelligence (AI) tools has transformed the landscape of drug discovery, providing unprecedented speed, efficiency, and cost-effectiveness in the search for new therapeutics. From target identification to drug formulation and delivery, AI-driven algorithms have revolutionized various aspects of medicinal chemistry, significantly accelerating the drug design process. Despite the transformative power of AI, this perspective article emphasizes the limitations of AI tools in drug discovery, requiring inventive skills of medicinal chemists. However, the article highlighted that there is a need for a harmonious integration of AI-based tools and human expertise in drug discovery. Such a synergistic approach promises to lead to groundbreaking therapies that address unmet medical needs and benefit humankind. As the world evolves technologically, the question remains: When will AI tools effectively design and develop drugs? The answer may lie in the seamless collaboration between AI and human researchers, unlocking transformative therapies that combat diseases effectively.
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Affiliation(s)
- Edeildo Ferreira da Silva-Júnior
- Institute of Chemistry and Biotechnology, Federal University of Alagoas, Lourival Melo Mota Avenue, AC. Simões Campus, 57072-970 Alagoas, Maceió, Brazil
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13
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Theodosiou AA, Read RC. Artificial intelligence, machine learning and deep learning: Potential resources for the infection clinician. J Infect 2023; 87:287-294. [PMID: 37468046 DOI: 10.1016/j.jinf.2023.07.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 07/12/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND Artificial intelligence (AI), machine learning and deep learning (including generative AI) are increasingly being investigated in the context of research and management of human infection. OBJECTIVES We summarise recent and potential future applications of AI and its relevance to clinical infection practice. METHODS 1617 PubMed results were screened, with priority given to clinical trials, systematic reviews and meta-analyses. This narrative review focusses on studies using prospectively collected real-world data with clinical validation, and on research with translational potential, such as novel drug discovery and microbiome-based interventions. RESULTS There is some evidence of clinical utility of AI applied to laboratory diagnostics (e.g. digital culture plate reading, malaria diagnosis, antimicrobial resistance profiling), clinical imaging analysis (e.g. pulmonary tuberculosis diagnosis), clinical decision support tools (e.g. sepsis prediction, antimicrobial prescribing) and public health outbreak management (e.g. COVID-19). Most studies to date lack any real-world validation or clinical utility metrics. Significant heterogeneity in study design and reporting limits comparability. Many practical and ethical issues exist, including algorithm transparency and risk of bias. CONCLUSIONS Interest in and development of AI-based tools for infection research and management are undoubtedly gaining pace, although the real-world clinical utility to date appears much more modest.
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Affiliation(s)
- Anastasia A Theodosiou
- Clinical and Experimental Sciences and NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Tremona Road, SO166YD Southampton, United Kingdom.
| | - Robert C Read
- Clinical and Experimental Sciences and NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Tremona Road, SO166YD Southampton, United Kingdom
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