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CHARACTERISTICS OF DRUG COMBINATION THERAPY IN ONCOLOGY BY ANALYZING CLINICAL TRIAL DATA ON CLINICALTRIALS.GOV

机译:通过分析临床试验数据临床试验数据的临床药物组合治疗的特征.GOV

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Within the past few decades, drug combination therapy has been intensively studied in oncology and other complex disease areas,especially during the early drug discovery stage,as drug combinations have the potential to improve treatment response, minimize development of resistance or minimize adverse events. In the present, designing combination trials relies mainly on clinical and empirical experience. While empirical experience has indeed crafted efficacious combination therapy clinical trials (combination trials), however, garnering experience with patients can take a lifetime. The preliminary step to eliminating this barrier of time, then, is to understand the current state of combination trials. Thus, we present the first large-scale study of clinical trials (2008-2013) from ClinicalTrials.gov to compare combination trials to non-combination trials, with a focus on oncology. In this work, we developed a classifier to identify combination trials and oncology trials through natural language processing techniques. After clustering trials, we categorized them based on selected characteristics and observed trends present. Among the characteristics studied were primary purpose, funding source, endpoint measurement, allocation, and trial phase. We observe a higher prevalence of combination therapy in oncology (25.6% use combination trials) in comparison to other disease trials (6.9%). However, surprisingly the prevalence of combinations does not increase over the years. In addition, the trials supported by the NIH are significantly more likely to use combinations of drugs than those supported by industry. Our preliminary study of current combination trials may facilitate future trial design and move more preclinical combination studies to the clinical trial stage.
机译:在过去的几十年里,在肿瘤和其他复杂的疾病区域中,药物联合治疗已经深入研究了肿瘤和其他复杂的疾病区域,特别是在早期药物发现阶段,因为药物组合有可能改善治疗响应,最大限度地减少抗性的发展或最小化不良事件。在目前,设计组合试验主要依赖于临床和经验经验。虽然经验经验确实精心制作了有效的联合治疗临床试验(联合试验),但是,与患者的追溯经验可能需要一生。那时,消除该时间障碍的初步步骤是理解当前的组合试验状态。因此,我们介绍了来自Clinicaltrials.gov的临床试验(2008-2013)的第一个大规模研究,将组合试验与非组合试验进行比较,重点是肿瘤学。在这项工作中,我们开发了一种通过自然语言处理技术识别组合试验和肿瘤学试验的分类器。在聚类试验后,我们根据所选特征和所观察到的趋势分类。研究的特征是主要目的,资金来源,终点测量,分配和试验阶段。与其他疾病试验相比,我们观察肿瘤学中联合治疗的患病率更高(25.6%使用组合试验)(6.9%)。然而,令人惊讶的是,组合的患病率多年来不会增加。此外,NIH支持的试验更容易使用药物组合而不是行业支持的组合。我们对当前组合试验的初步研究可以促进未来的试验设计,并向临床试验阶段移动更锋利的联合研究。

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