Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials

Federer, Callie; Yoo, Minjae; Tan, Aik Choon

doi:10.1089/adt.2016.742

Cited by 18 publications

(16 citation statements)

References 27 publications

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“…2 The post-processing steps include regular expressions, and a dictionary-based approach for extracting certain elds as information was entered in various formats in published results. 3 Validation of the data acquired on ClinicalTrials.gov: The reliability of the data was ensured by checking the consistency of the number of clinical trial entries in the downloaded CSV le with the retrieved results.…”

Section: Data Processingmentioning

confidence: 99%

Visualization analysis of the characteristics of COVID-19 clinical trials

Cai

Zheng

Huang

et al. 2020

Preprint

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Background As a highly contagious disease, COVID-19 is raging on and is faced by every human being. Clinical trials are one of the most important means of investigating treatments for COVID-19, and their effective implementations may address the massive spread of the pandemic. As clinical trials continue to be conducted, the inability to view large amounts of data at a glance becomes a problem for many researchers. In order to provide reference and assistance for clinical trial design, this study collected and analyzed the current COVID-19 clinical trial registration data from multiple sources, and subsequently discussed their research status and developmental trend. Method The registered data of COVID-19 clinical trials were gathered from the ChiCTR and ClinicalTrials.gov website, which were transformed by Python and further demonstrated by Apache ECharts. Results As of March 28, 2020, records of 677 eligible registered trials had been retrieved. Overall, there are 407 (60.12%) interventional studies and 270 (39.12%) observational studies; 522 (77.10%) trials were conducted by hospitals; 53.32% of trials would be completed within six months; 523 (77.25%) subjects in trials were confirmed cases. Among interventional studies, 70.27% of the trials were randomized parallel studies; 55 (13.51%) trials considered time condition for clinical recovery as the primary endpoint, and 46 (11.30%) trials through clinical parameters and laboratory index as the primary endpoint. In the selection of intervention measures, chemical or biological agents constituted 43.49%, of which antiviral ones accounted for 14.50%, and antimalarials accounted for 8.85%, and 98 (24.14%) cases of studies involving TCM or integrated medicine. In addition, this study further analyzed antiviral drugs and explored possibilities of using combined drugs. Although a large number of clinical trials are already underway, interim research data will be helpful for future trial design and drug selection. Conclusions By compiling representative information of topical COVID-19 clinical trial registration, this study complements and enhances the effects of future researchers' trial designs.

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Section: Data Processingmentioning

confidence: 99%

Visualization analysis of the characteristics of COVID-19 clinical trials

Cai

Zheng

Huang

et al. 2020

Preprint

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“…The AEs extracted from these trials span across 26 AE categories. [19] The Big Data Challenges and Opportunities:-It has been always observed that arrival of any new technology brings along with it some challenges or limitations. Similarly, Big Data also has challenges and some shortcomings as below listed [20]:- Evidence of practical benefits of big data analytics is scarce  Methodological issues, such as data quality, data inconsistency and instability, limitations of observational studies, validation, analytical issues, and legal issues exist.…”

Section: A Data Survey Was Carried Out By Scorr Marketingmentioning

confidence: 99%

Clinical Research - A Big Data Science Approach

Mathias¹,

Goveas²,

Rajak³

et al. 2018

IJTSRD

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Big data" is defined as the collection of large and complex datasets available in structured, semi structured, and unstructured form which are dif to process using traditional database management tools or data processing applications. Big Data is als defined from 5Vs which refers to Volume, Variety, Velocity, Veracity and Value .Clinical Research is one of the most important as well as promising part of health research. This article provides an overview on some specific aspects of clinical research adapted to Big Data Science path ways be utilized for transforming millions of data points into predictions & simulation to provide cost effective medicines in reduced timelines. This article also highlights the opportunities & challenges Data brings with it.

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“…Drug-induced gastrointestinal toxicities (DI-GITs) are the most common category of adverse events (AEs) both during clinical trials 1 and after drug approval. 2 When incidence of druginduced AEs is broken down by individual symptoms, five GI AEs (nausea, vomiting, constipation, diarrhoea, and abdominal pain) rank among the 12 most frequent.…”

Section: Introductionmentioning

confidence: 99%

“…2 When incidence of druginduced AEs is broken down by individual symptoms, five GI AEs (nausea, vomiting, constipation, diarrhoea, and abdominal pain) rank among the 12 most frequent. 1 These AEs occur across all drug modalities and span all therapeutic areas. 3 However, the consequences of GIT often differ from those in other organ systems with respect to timing of discovery, medical response, impact on drug development, and effects on patients.…”

Section: Introductionmentioning

confidence: 99%