Applying a Pharmacometrics-Enabled Machine Learning Analysis to Predict 2-Month Culture Conversion Using Phase 2a Data in a Tuberculosis Clinical Trial [0.03%]
基于药理学的机器学习分析预测结核病临床试验中两个月培养转换的模型构建与验证：二期a研究数据
Huifang You,Ulrika S H Simonsson
Huifang You
Phase 2a trials in tuberculosis patients traditionally assess early bactericidal activity over two weeks, often using the time-to-positivity biomarker, followed by a phase 2b study typically lasting 8-week with time-to-event of culture conv...
Clinical Trial
Clinical and translational science. 2026 Aug;19(8):e70694. DOI:10.1111/cts.70694 2026
Association of the NOS1AP rs10494366 Genetic Variant With Drug-Induced QT Prolongation [0.03%]
NOS1AP基因多态性与药物致QT间期延长的关系
Christina A Pippis,Ana I Lopez-Medina,Choudhary Anwar A Chahal et al.
Christina A Pippis et al.
Drug-induced QTc prolongation (diQTP) is a major risk factor for torsades de pointes and sudden cardiac death. This study evaluated whether carriers of the G allele of the NOS1AP rs10494366 T > G variant have greater risk for diQTP when pre...
Drug-Drug Interaction Risk Assessment Strategies for Biologics in Inflammatory Bowel Disease: A Literature-Based Evidence Mini-Review [0.03%]
基于文献的证据 mini-回顾：炎症性肠病生物制品药物-药物相互作用的风险评估策略
Claire Steinbronn,Susan E Stanley,Tjerk Bueters et al.
Claire Steinbronn et al.
Biologic therapies are traditionally regarded as having low potential for drug-drug interactions (DDIs) due to their large molecular size and limited direct involvement with drug-metabolizing enzymes and transporters (DMETs). However, accum...
A Serverless Pharmacogenomic Risk Dashboard: Translating Ensemble Models and Model-Based Scenario Rules to Clinical Decision Support [0.03%]
无服务器药物基因组学风险仪表板：将集成模型和基于模型的场景规则转换为临床决策支持
R Jerome Dixon,Elvin T Price
R Jerome Dixon
The "last mile" problem in healthcare AI-translating high-performance models into accessible, privacy-preserving point-of-care tools-remains unsolved for pharmacogenomic (PGx) risk assessment. No existing platform integrates opioid and poly...
Brexanolone, a First-In-Class Neurosteroid Medication: Mechanism of Action, Clinical, and Translational Science [0.03%]
新型神经甾体药物brexanolone：作用机制、临床及转化科学
Laura Gayanova,Katrina Sian,Jason Wells et al.
Laura Gayanova et al.
Given the increasing prevalence of postpartum depression (PPD) and the stigma associated with this condition, it is essential to address this significant health concern. Brexanolone is an FDA-approved treatment for PPD that works by positiv...
Correction to "European Network on Optimizing Treatment With Therapeutic Antibodies in Chronic Inflammatory Diseases: Overview, Progress and Perspectives" [0.03%]
对“欧洲关于慢性炎症性疾病治疗性抗体优化治疗网络：概览、进展和前景”的修正
Published Erratum
Clinical and translational science. 2026 Aug;19(8):e70696. DOI:10.1111/cts.70696 2026
Empowering Clinical Development With Disease Progression Modeling: Recommendations From the Clinical Trials Transformation Initiative [0.03%]
临床试验转型倡议下的疾病进展模型在药物开发中的应用与展望
Lindsay S Kehoe,Shu Chin Ma,Jiang Liu et al.
Lindsay S Kehoe et al.
Evaluating the benefit-risk profile of a medical product requires comprehensive evidence that integrates information across development stages. Technological advances and broader use of real-world data are enabling innovative quantitative p...
Device and Data Access Considerations for Digital Health Studies Using Consumer-Grade Wearables: An Experience-Based Tutorial [0.03%]
基于经验的教程：使用消费级可穿戴设备进行数字健康研究中的设备和数据访问注意事项
Mike Zhu,Joshua D Spencer,Sherry Chesak et al.
Mike Zhu et al.
Consumer-grade wearables, including smartwatches, fitness trackers, and smart rings, are accessible tools for studying pharmacologic responses in real-time, monitoring participant health in decentralized clinical trials, optimizing outcome ...
Deep-Learning: An Emerging Tool to Support Model-Informed Drug Development [0.03%]
深度学习：支持基于模型的药物开发的新工具
Roberto Gomeni,Françoise Bressolle-Gomeni
Roberto Gomeni
Traditional Model-Informed Drug Development (MIDD) primarily relies on hypothesis-driven (HD) models based on biological, physiological, and physicochemical principles. While these mechanistic models have been instrumental in drug developme...
Temporal Drivers of Opioid-Related ED Visits: An Ensemble Machine Learning Study With Consensus-Based Feature Attribution [0.03%]
基于共识特征归因的集成机器学习研究：阿片类药物相关急诊就诊的时间驱动因素
R Jerome Dixon,Elvin T Price
R Jerome Dixon
Identification of modifiable risk factors for prescription opioid use disorder (OUD)-related emergency department (ED) visits (ICD-10 F11.xx) is a clinical priority; however, most published models remain cross-sectional and lack pharmacogen...