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Related Concept Videos

Clinical Trials01:16

Clinical Trials

10.9K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
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Clinical Trials: Overview01:11

Clinical Trials: Overview

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Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
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Statistical Software for Data Analysis and Clinical Trials01:12

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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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Trial and Error and Algorithm01:12

Trial and Error and Algorithm

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A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
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Quantifying Work02:30

Quantifying Work

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As a system undergoes a change, its internal energy can change, and energy can be transferred from the system to the surroundings, or from the surroundings to the system.
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Nursing Clinical Information System01:27

Nursing Clinical Information System

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Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
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In Silico Clinical Trials for Cardiovascular Disease
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Quantifying and visualizing site performance in clinical trials.

Eric Yang1, Christopher O'Donovan1, JodiLyn Phillips1

  • 1Covance Inc., 210 Carnegie Center, Princeton, NJ 08540, USA.

Contemporary Clinical Trials Communications
|April 27, 2018
PubMed
Summary
This summary is machine-generated.

Operational data from central laboratory services can predict clinical trial site performance. Analyzing shipment metadata reveals patient enrollment, retention, and quality indicators to optimize site selection and trial execution.

Keywords:
Alzheimer's diseaseClinical trial optimizationData visualizationInvestigator performanceSite performance

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Area of Science:

  • Clinical trial operations
  • Pharmaceutical research
  • Biotechnology

Background:

  • Selecting high-quality clinical trial sites is crucial for success.
  • Site performance is predicted by historical track record but complicated by data availability and protocol complexity.
  • Central laboratory operational data offers key insights into clinical site performance.

Purpose of the Study:

  • To demonstrate how operational data from central laboratory services can provide insights into clinical site performance.
  • To guide operational planning and site selection for new clinical trials.

Main Methods:

  • Utilizing metadata from laboratory kit shipments to reconstruct patient visit schedules.
  • Deriving operational performance insights, including screening, enrollment, and drop-out rates.
  • Normalizing data for direct comparison of site performance across diverse studies.

Main Results:

  • Assembled a database of operational metrics from over 14,000 protocols and 23 million patient visits.
  • Assessed and compared investigator performance across various therapeutic areas and study designs.
  • Identified country and regional trends in clinical trial performance.

Conclusions:

  • Operational data from central laboratories offers a unique perspective on clinical site performance metrics.
  • Metrics such as patient enrollment and retention can guide trial operational planning and site selection.
  • Utilizing this data accelerates recruitment, improves quality, and reduces clinical trial costs.