Metaverse for Healthcare: A Survey on Potential Applications, Challenges and Future Directions

IEEE Access, Год журнала: 2023, Номер 11, С. 12765 - 12795

Опубликована: Янв. 1, 2023

The rapid progress in digitalization and automation have led to an accelerated growth healthcare, generating novel models that are creating new channels for rendering treatment at reduced cost. Metaverse is emerging technology the digital space which has huge potential enabling realistic experiences patients as well medical practitioners. a confluence of multiple technologies such artificial intelligence, virtual reality, augmented internet devices, robotics, quantum computing, etc. through directions providing quality healthcare services can be explored. amalgamation these ensures immersive, intimate personalized patient care. It also provides adaptive intelligent solutions eliminates barriers between providers receivers. This article comprehensive review emphasizing on state art, adopt applications, related projects. issues adaptation applications identified plausible highlighted part future research directions.

Язык: Английский

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The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies

Pharmaceuticals, Год журнала: 2023, Номер 16(6), С. 891 - 891

Опубликована: Июнь 18, 2023

Artificial intelligence (AI) has the potential to revolutionize drug discovery process, offering improved efficiency, accuracy, and speed. However, successful application of AI is dependent on availability high-quality data, addressing ethical concerns, recognition limitations AI-based approaches. In this article, benefits, challenges drawbacks in field are reviewed, possible strategies approaches for overcoming present obstacles proposed. The use data augmentation, explainable AI, integration with traditional experimental methods, as well advantages pharmaceutical research also discussed. Overall, review highlights provides insights into opportunities realizing its field. Note from human-authors: This article was created test ability ChatGPT, a chatbot based GPT-3.5 language model, assist human authors writing articles. text generated by following our instructions (see Supporting Information) used starting point, automatically generate content evaluated. After conducting thorough review, practically rewrote manuscript, striving maintain balance between original proposal scientific criteria. using purpose discussed last section.

Язык: Английский

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Targeting ferroptosis opens new avenues for the development of novel therapeutics

Signal Transduction and Targeted Therapy, Год журнала: 2023, Номер 8(1)

Опубликована: Сен. 21, 2023

Abstract Ferroptosis is an iron-dependent form of regulated cell death with distinct characteristics, including altered iron homeostasis, reduced defense against oxidative stress, and abnormal lipid peroxidation. Recent studies have provided compelling evidence supporting the notion that ferroptosis plays a key pathogenic role in many diseases such as various cancer types, neurodegenerative disease, involving tissue and/or organ injury, inflammatory infectious diseases. Although precise regulatory networks underlie are largely unknown, particularly respect to initiation progression diseases, recognized bona fide target for further development treatment prevention strategies. Over past decade, considerable progress has been made developing pharmacological agonists antagonists these ferroptosis-related conditions. Here, we provide detailed overview our current knowledge regarding ferroptosis, its pathological roles, regulation during disease progression. Focusing on use chemical tools preclinical studies, also summarize recent advances targeting across growing spectrum ferroptosis-associated Finally, discuss new challenges opportunities potential strategy treating

Язык: Английский

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The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century

Bioengineering, Год журнала: 2024, Номер 11(4), С. 337 - 337

Опубликована: Март 29, 2024

As healthcare systems around the world face challenges such as escalating costs, limited access, and growing demand for personalized care, artificial intelligence (AI) is emerging a key force transformation. This review motivated by urgent need to harness AI’s potential mitigate these issues aims critically assess integration in different domains. We explore how AI empowers clinical decision-making, optimizes hospital operation management, refines medical image analysis, revolutionizes patient care monitoring through AI-powered wearables. Through several case studies, we has transformed specific domains discuss remaining possible solutions. Additionally, will methodologies assessing solutions, ethical of deployment, importance data privacy bias mitigation responsible technology use. By presenting critical assessment transformative potential, this equips researchers with deeper understanding current future impact on healthcare. It encourages an interdisciplinary dialogue between researchers, clinicians, technologists navigate complexities implementation, fostering development AI-driven solutions that prioritize standards, equity, patient-centered approach.

Язык: Английский

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Clinical trial design in the era of precision medicine

Genome Medicine, Год журнала: 2022, Номер 14(1)

Опубликована: Авг. 31, 2022

Abstract Recent rapid biotechnological breakthroughs have led to the identification of complex and unique molecular features that drive malignancies. Precision medicine has exploited next-generation sequencing matched targeted therapy/immunotherapy deployment successfully transform outlook for several fatal cancers. Tumor liquid biopsy genomic profiling transcriptomic, immunomic, proteomic interrogation can now all be leveraged optimize therapy. Multiple new trial designs, including basket umbrella trials, master platform N-of-1 patient-centric studies, are beginning supplant standard phase I, II, III protocols, allowing accelerated drug evaluation approval molecular-based individualized treatment. Furthermore, real-world data, as well exploitation digital apps structured observational registries, utilization machine learning and/or artificial intelligence, may further accelerate knowledge acquisition. Overall, clinical trials evolved, shifting from tumor type-centered gene-directed histology-agnostic with innovative adaptive designs personalized combination treatment strategies tailored individual biomarker profiles. Some, but not all, novel demonstrate therapy correlates superior outcomes compared non-matched across types in specific To improve precision paradigm, strategy matching drugs patients based on should implemented earlier disease course, cancers comprehensive multi-omic (genomics, transcriptomics, proteomics, immunomic) profiling. overcome cancer complexity, moving drug-centric is critical. This review focuses design, advantages, limitations, challenges a spectrum era oncology.

Язык: Английский

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Trends in the approval of cancer therapies by the FDA in the twenty-first century

Nature Reviews Drug Discovery, Год журнала: 2023, Номер 22(8), С. 625 - 640

Опубликована: Июнь 21, 2023

Язык: Английский

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Advancing pharmacy and healthcare with virtual digital technologies

Advanced Drug Delivery Reviews, Год журнала: 2022, Номер 182, С. 114098 - 114098

Опубликована: Янв. 5, 2022

Язык: Английский

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Artificial Intelligence in Drug Toxicity Prediction: Recent Advances, Challenges, and Future Perspectives

Journal of Chemical Information and Modeling, Год журнала: 2023, Номер 63(9), С. 2628 - 2643

Опубликована: Апрель 26, 2023

Toxicity prediction is a critical step in the drug discovery process that helps identify and prioritize compounds with greatest potential for safe effective use humans, while also reducing risk of costly late-stage failures. It estimated over 30% candidates are discarded owing to toxicity. Recently, artificial intelligence (AI) has been used improve toxicity as it provides more accurate efficient methods identifying potentially toxic effects new before they tested human clinical trials, thus saving time money. In this review, we present an overview recent advances AI-based prediction, including various machine learning algorithms deep architectures, six major properties Tox21 assay end points. Additionally, provide list public data sources useful tools research community highlight challenges must be addressed enhance model performance. Finally, discuss future perspectives prediction. This review can aid researchers understanding pave way discovery.

Язык: Английский

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Small molecules and their impact in drug discovery: A perspective on the occasion of the 125th anniversary of the Bayer Chemical Research Laboratory

Drug Discovery Today, Год журнала: 2022, Номер 27(6), С. 1560 - 1574

Опубликована: Фев. 22, 2022

The year 2021 marks the 125th anniversary of Bayer Chemical Research Laboratory in Wuppertal, Germany. A significant number prominent small-molecule drugs, from Aspirin to Xarelto, have emerged this research site. In review, we shed light on historic cornerstones drug research, discussing current and future trends discovery as well providing a personal outlook with focus small molecules.

Язык: Английский

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Machine learning for synergistic network pharmacology: a comprehensive overview

Briefings in Bioinformatics, Год журнала: 2023, Номер 24(3)

Опубликована: Апрель 6, 2023

Abstract Network pharmacology is an emerging area of systematic drug research that attempts to understand actions and interactions with multiple targets. has changed the paradigm from ‘one-target one-drug’ highly potent ‘multi-target drug’. Despite that, this synergistic approach currently facing many challenges particularly mining effective information such as targets, mechanism action, organism interaction massive, heterogeneous data. To overcome bottlenecks in multi-target discovery, computational algorithms are welcomed by scientific community. Machine learning (ML) especially its subfield deep (DL) have seen impressive advances. Techniques developed within these fields now able analyze learn huge amounts data disparate formats. In terms network pharmacology, ML can improve discovery decision making big Opportunities apply occur all stages research. Examples include screening biologically active small molecules, target identification, metabolic pathways protein–protein analysis, hub gene analysis finding binding affinity between compounds proteins. This review summarizes premier algorithmic concepts forecasts future opportunities, potential applications well several remaining implementing pharmacology. our knowledge, study provides first comprehensive assessment approaches we hope it encourages additional efforts toward development acceptance pharmaceutical industry.

Язык: Английский

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