Navigating the complexities of drug development for inflammatory bowel disease

Nature Reviews Drug Discovery, Journal Year: 2024, Volume and Issue: 23(7), P. 546 - 562

Published: May 22, 2024

Language: Английский

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Efficacy and effectiveness of antipsychotics in schizophrenia: network meta-analyses combining evidence from randomised controlled trials and real-world data

The Lancet Psychiatry, Journal Year: 2024, Volume and Issue: 11(2), P. 102 - 111

Published: Jan. 9, 2024

Language: Английский

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The hospital at home in the USA: current status and future prospects

npj Digital Medicine, Journal Year: 2024, Volume and Issue: 7(1)

Published: Feb. 27, 2024

Abstract The annual cost of hospital care services in the US has risen to over $1 trillion despite relatively worse health outcomes compared similar nations. These trends accentuate a growing need for innovative delivery models that reduce costs and improve outcomes. HaH—a program provides patients acute-level at home—has made significant progress past two decades. Technological advancements remote patient monitoring, wearable sensors, information technology infrastructure, multimodal data processing have contributed its rise across hospitals. More recently, COVID-19 pandemic brought HaH into mainstream, especially US, with reimbursement waivers model financially acceptable hospitals payors. However, continues face serious challenges gain widespread adoption. In this review, we evaluate peer-reviewed evidence discuss promises, challenges, what it would take tap future potential HaH.

Language: Английский

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New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology

npj Precision Oncology, Journal Year: 2024, Volume and Issue: 8(1)

Published: Jan. 30, 2024

Until recently the application of artificial intelligence (AI) in precision oncology was confined to activities drug development and had limited impact on personalisation therapy. Now, a number approaches have been proposed for cell therapies with AI applied therapy design, planning delivery at patient's bedside. Some cell-based are already tuneable individual optimise efficacy, reduce toxicity, adapt dosing regime, design combination and, preclinically, even personalise receptor therapies. Developments AI-based healthcare accelerating through adoption foundation models, generalist medical models proposed. The these is being explored realistic short-term advances include personalised drugs With this pace development, limiting step will likely be capacity appropriateness regulatory frameworks. This article explores emerging concepts new ideas regulation AI-enabled cancer context existing governance

Language: Английский

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Envisioning the Future of Personalized Medicine: Role and Realities of Digital Twins

Journal of Medical Internet Research, Journal Year: 2024, Volume and Issue: 26, P. e50204 - e50204

Published: May 13, 2024

Digital twins have emerged as a groundbreaking concept in personalized medicine, offering immense potential to transform health care delivery and improve patient outcomes. It is important highlight the impact of digital on medicine across understanding health, risk assessment, clinical trials drug development, monitoring. By mirroring individual profiles, offer unparalleled insights into patient-specific conditions, enabling more accurate assessments tailored interventions. However, their application extends beyond benefits, prompting significant ethical debates over data privacy, consent, biases care. The rapid evolution this technology necessitates careful balancing act between innovation responsibility. As field continues evolve, hold tremendous promise transforming revolutionizing While challenges exist, continued development integration revolutionize ushering an era treatments improved well-being. can assist recognizing trends indicators that might signal presence diseases or forecast likelihood developing specific medical along with progression such diseases. Nevertheless, use human gives rise dilemmas related informed ownership, for discrimination based profiles. There critical need robust guidelines regulations navigate these challenges, ensuring pursuit advanced solutions does not compromise rights This viewpoint aims ignite comprehensive dialogue responsible advocating future where serves cornerstone personalized, ethical, effective

Language: Английский

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Assessing the Risk of Bias in Randomized Clinical Trials With Large Language Models

JAMA Network Open, Journal Year: 2024, Volume and Issue: 7(5), P. e2412687 - e2412687

Published: May 22, 2024

Importance Large language models (LLMs) may facilitate the labor-intensive process of systematic reviews. However, exact methods and reliability remain uncertain. Objective To explore feasibility using LLMs to assess risk bias (ROB) in randomized clinical trials (RCTs). Design, Setting, Participants A survey study was conducted between August 10, 2023, October 30, 2023. Thirty RCTs were selected from published Main Outcomes Measures structured prompt developed guide ChatGPT (LLM 1) Claude 2) assessing ROB these a modified version Cochrane tool by CLARITY group at McMaster University. Each RCT assessed twice both models, results documented. The compared with an assessment 3 experts, which considered criterion standard. Correct rates, sensitivity, specificity, F1 scores calculated reflect accuracy, overall for each domain tool; consistent rates Cohen κ gauge consistency; time measure efficiency. Performance 2 differences. Results Both demonstrated high correct rates. LLM 1 reached mean rate 84.5% (95% CI, 81.5%-87.3%), significantly higher 89.5% 87.0%-91.8%). difference 0.05 0.01-0.09). In most domains, domain-specific around 80% 90%; however, sensitivity below 0.80 observed domains (random sequence generation), (allocation concealment), 6 (other concerns). Domains 4 (missing outcome data), 5 (selective reporting), had 0.50. assessments 84.0% 87.3% 2. 1’s exceeded 7 2’s 8 domains. (SD) needed 77 (16) seconds 53 (12) Conclusions this applying assessment, substantial accuracy consistency evaluating RCTs, suggesting their potential as supportive tools review processes.

Language: Английский

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Artificial intelligence in drug development

Nature Medicine, Journal Year: 2025, Volume and Issue: 31(1), P. 45 - 59

Published: Jan. 1, 2025

Language: Английский

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Oxidative Stress and Cardiovascular Complications in Type 2 Diabetes: From Pathophysiology to Lifestyle Modifications

Antioxidants, Journal Year: 2025, Volume and Issue: 14(1), P. 72 - 72

Published: Jan. 9, 2025

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder that significantly increases the risk of cardiovascular disease, which leading cause morbidity and mortality among diabetic patients. A central pathophysiological mechanism linking T2DM to complications oxidative stress, defined as an imbalance between reactive oxygen species (ROS) production body’s antioxidant defenses. Hyperglycemia in promotes stress through various pathways, including formation advanced glycation end products, activation protein kinase C, mitochondrial dysfunction, polyol pathway. These processes enhance ROS generation, endothelial vascular inflammation, exacerbation damage. Additionally, disrupts nitric oxide signaling, impairing vasodilation promoting vasoconstriction, contributes complications. This review explores molecular mechanisms by pathogenesis disease T2DM. It also examines potential lifestyle modifications, such dietary changes physical activity, reducing mitigating risks this high-risk population. Understanding these critical for developing targeted therapeutic strategies improve outcomes

Language: Английский

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Digital twins as global learning health and disease models for preventive and personalized medicine

Genome Medicine, Journal Year: 2025, Volume and Issue: 17(1)

Published: Feb. 7, 2025

Abstract Ineffective medication is a major healthcare problem causing significant patient suffering and economic costs. This issue stems from the complex nature of diseases, which involve altered interactions among thousands genes across multiple cell types organs. Disease progression can vary between patients over time, influenced by genetic environmental factors. To address this challenge, digital twins have emerged as promising approach, led to international initiatives aiming at clinical implementations. Digital are virtual representations health disease processes that integrate real-time data simulations predict, prevent, personalize treatments. Early applications DTs shown potential in areas like artificial organs, cancer, cardiology, hospital workflow optimization. However, widespread implementation faces several challenges: (1) characterizing dynamic molecular changes biological scales; (2) developing computational methods into DTs; (3) prioritizing mechanisms therapeutic targets; (4) creating interoperable DT systems learn each other; (5) designing user-friendly interfaces for clinicians; (6) scaling technology globally equitable access; (7) addressing ethical, regulatory, financial considerations. Overcoming these hurdles could pave way more predictive, preventive, personalized medicine, potentially transforming delivery improving outcomes.

Language: Английский

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Evaluating the impact of the Radiomics Quality Score: a systematic review and meta-analysis

European Radiology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 10, 2025

Abstract Objectives Conduct a systematic review and meta-analysis on the application of Radiomics Quality Score (RQS). Materials methods A search was conducted from January 1, 2022, to December 31, 2023, for reviews which implemented RQS. Identification articles prior 2022 via previously published review. scores individual radiomics papers, their associated criteria scores, these all readers were extracted. Errors in RQS noted corrected. The papers matched with publication date, imaging modality, country, where available. Results total 130 included, quality 117/130 (90.0%), 98/130 (75.4%), multiple reader data 24/130 (18.5%) 3258 correlated study date publication. Criteria scoring errors discovered 39/98 (39.8%) articles. Overall mean 9.4 ± 6.4 (95% CI, 9.1–9.6) (26.1% 17.8% (25.3%–26.7%)). positively year (Pearson R = 0.32, p < 0.01) significantly higher after (year 2018, 5.6 6.1 (5.1–6.1); ≥ 10.1 (9.9–10.4); 0.01). Only 233/3258 (7.2%) 50% maximum different across modalities ( Ten year, one negatively correlated. Conclusion adherence is increasing time, although vast majority studies are developmental rarely provide high level evidence justify clinical translation proposed models. Key Points Question What have achieved has it increased sufficient? Findings extracted resulted score 6.4. time. Clinical relevance Although many not demonstrated sufficient translation. As new appraisal tools emerge, current role may change.

Language: Английский

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