Challenges and applications of artificial intelligence in infectious diseases and antimicrobial resistance

npj Antimicrobials and Resistance, Journal Year: 2025, Volume and Issue: 3(1)

Published: Jan. 7, 2025

Artificial intelligence (AI) has transformed infectious disease control, enhancing rapid diagnosis and antibiotic discovery. While conventional tests delay diagnosis, AI-driven methods like machine learning deep assist in pathogen detection, resistance prediction, drug These tools improve stewardship identify effective compounds such as antimicrobial peptides small molecules. This review explores AI applications diagnostics, therapy, discovery, emphasizing both strengths areas needing improvement.

Language: Английский

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Revolutionizing Prostate Cancer Therapy: Artificial intelligence – based Nanocarriers for Precision Diagnosis and Treatment

Critical Reviews in Oncology/Hematology, Journal Year: 2025, Volume and Issue: unknown, P. 104653 - 104653

Published: Feb. 1, 2025

Language: Английский

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AI-powered drug discovery for neglected diseases: accelerating public health solutions in the developing world

Journal of Global Health, Journal Year: 2025, Volume and Issue: 15

Published: Jan. 10, 2025

The emergence of artificial intelligence (AI) in drug discovery represents a transformative development addressing neglected diseases, particularly the context developing world. Neglected often overlooked by traditional pharmaceutical research due to limited commercial profitability, pose significant public health challenges low- and middle-income countries. AI-powered offers promising solution accelerating identification potential candidates, optimising process, reducing time cost associated with bringing new treatments market. However, while AI shows promise, many its applications are still their early stages require human validation ensure accuracy reliability predictions. Additionally, models availability high-quality data, which is sparse regions where diseases most prevalent. This viewpoint explores application for examining current impact, related ethical considerations, broader implications It also highlights opportunities presented this context, emphasising need ongoing research, oversight, collaboration between stakeholders fully realise transforming global outcomes.

Language: Английский

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Integrating AI into Cancer Immunotherapy—A Narrative Review of Current Applications and Future Directions

Diseases, Journal Year: 2025, Volume and Issue: 13(1), P. 24 - 24

Published: Jan. 20, 2025

Background: Cancer remains a leading cause of morbidity and mortality worldwide. Traditional treatments like chemotherapy radiation often result in significant side effects varied patient outcomes. Immunotherapy has emerged as promising alternative, harnessing the immune system to target cancer cells. However, complexity responses tumor heterogeneity challenges its effectiveness. Objective: This mini-narrative review explores role artificial intelligence [AI] enhancing efficacy immunotherapy, predicting responses, discovering novel therapeutic targets. Methods: A comprehensive literature was conducted, focusing on studies published between 2010 2024 that examined application AI immunotherapy. Databases such PubMed, Google Scholar, Web Science were utilized, articles selected based relevance topic. Results: significantly contributed identifying biomarkers predict immunotherapy by analyzing genomic, transcriptomic, proteomic data. It also optimizes combination therapies most effective treatment protocols. AI-driven predictive models help assess response guiding clinical decision-making minimizing effects. Additionally, facilitates discovery targets, neoantigens, enabling development personalized immunotherapies. Conclusions: holds immense potential transforming related data privacy, algorithm transparency, integration must be addressed. Overcoming these hurdles will likely make central component future offering more treatments.

Language: Английский

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Flavonoids and Flavonoid-Based Nanopharmaceuticals as Promising Therapeutic Strategies for Colorectal Cancer—An Updated Literature Review

Pharmaceuticals, Journal Year: 2025, Volume and Issue: 18(2), P. 231 - 231

Published: Feb. 8, 2025

Colorectal cancer (CRC) represents one of the most serious health issues and third commonly diagnosed worldwide. However, treatment options for CRC are associated with adverse reactions, in some cases, resistance can develop. Flavonoids have emerged as promising alternatives prevention therapy due to their multitude biological properties ability target distinct processes involved pathogenesis. Their innate disadvantageous (e.g., low solubility stability, reduced bioavailability, lack tumor specificity) delayed potential inclusion flavonoids regimens but hastened design nanopharmaceuticals comprising a flavonoid agent entrapped nanosized delivery platform that not only counteract these inconveniences also provide an augmented therapeutic effect elevated safety profile by conferring targeted action. Starting brief presentation pathological features overview classes, present study comprehensively reviews anti-CRC activity different from mechanistic perspective while portraying latest discoveries made area flavonoid-containing nanocarriers proved efficient management. This review concludes showcasing future perspectives advancement flavonoid-based research.

Language: Английский

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Exploring the impact of bioactive peptides from fermented Milk proteins: A review with emphasis on health implications and artificial intelligence integration

Food Chemistry, Journal Year: 2025, Volume and Issue: unknown, P. 144047 - 144047

Published: March 1, 2025

Language: Английский

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Embracing the changes and challenges with modern early drug discovery

Expert Opinion on Drug Discovery, Journal Year: 2025, Volume and Issue: unknown

Published: March 17, 2025

The landscape of early drug discovery is rapidly evolving, fueled by significant advancements in artificial intelligence (AI) and machine learning (ML), which are transforming the way drugs discovered. As traditional faces growing challenges terms time, cost, efficacy, there a pressing need to integrate these emerging technologies enhance process. In this perspective, authors explore role AI ML modern discuss their application target identification, compound screening, biomarker discovery. This article based on thorough literature search using PubMed database identify relevant studies that highlight use AI/ML models computational chemistry, systems biology, data-driven approaches development. Emphasis placed how address key such as data integration, predictive performance, cost-efficiency pipeline. have potential revolutionize improving accuracy speed identifying viable candidates. However, successful integration requires overcoming related quality, model interpretability, for interdisciplinary collaboration.

Language: Английский

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Farmasi Cerdas: Era Baru Penemuan Obat dengan AI dan Big Data

MEDICINUS, Journal Year: 2025, Volume and Issue: 38(1), P. 27 - 36

Published: Jan. 1, 2025

Proses penemuan obat telah memasuki era baru dengan munculnya kecerdasan buatan (artificial intelligence/AI) dan big data. Pendekatan tradisional, panjang, mahal kini dilengkapi alternatif yang efisien berkat kemampuan AI untuk menganalisis pola kompleks data mengintegrasikan kumpulan berskala besar. Artikel ini membahas peran teknologi tersebut dalam mempercepat inovasi farmasi, mengulas aplikasi praktis, menyoroti tantangan serta prospek masa depan. Dengan data, industri farmasi dapat memajukan pengobatan presisi memperdalam pemahaman kita tentang biologi penyakit.

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Advancing Cancer Drug Delivery with Nanoparticles: Challenges and Prospects in Mathematical Modeling for In Vivo and In Vitro Systems

Cancers, Journal Year: 2025, Volume and Issue: 17(2), P. 198 - 198

Published: Jan. 9, 2025

Mathematical models are crucial for predicting the behavior of drug conjugate nanoparticles and optimizing delivery systems in cancer therapy. These simulate interactions among nanoparticle properties, tumor characteristics, physiological conditions, including resistance targeting specificity. However, they often rely on assumptions that may not accurately reflect vivo conditions. In vitro studies, while useful, fully capture complexities environment, leading to an overestimation nanoparticle-based therapy effectiveness. Advancements mathematical modeling, supported by preclinical data artificial intelligence, vital refining therapies improving their translation into effective clinical treatments.

Language: Английский

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Special Issue “Advances in Drug Discovery and Synthesis”

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(2), P. 584 - 584

Published: Jan. 11, 2025

In modern medicinal chemistry, drug discovery is a long, difficult, highly expensive and risky process for the identification of new compounds [...]

Language: Английский

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