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Related Concept Videos

Clinical Trials01:16

Clinical Trials

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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.
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Clinical Trials: Overview01:11

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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 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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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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Nursing Implementation01:15

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Implementation is the execution of the nursing care plan developed during the planning phase.
The five steps to implementing effective nursing care include reassessing the patient, reviewing and revising the existing nursing care plan, organizing the resources and care delivery, anticipating and preventing complications, and implementing nursing interventions.
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Proteomics01:33

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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In Silico Clinical Trials for Cardiovascular Disease
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Implementation of Proteomics in Clinical Trials.

Tianlin He1,2

  • 1Mosaiques Diagnostics GmbH, 30659, Hannover, Germany.

Proteomics. Clinical Applications
|February 1, 2019
PubMed
Summary

Protein and peptide biomarkers are revolutionizing clinical studies, aiding in disease diagnosis, prognosis, and patient stratification for precision medicine. Recent trials highlight their role in developing non-invasive diagnostic tools and predicting disease risk.

Keywords:
clinical trialsdiagnosisprognosisproteomic/protein assaysstratification

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Area of Science:

  • Clinical Proteomics and Peptidomics
  • Biomarker Discovery and Validation
  • Precision Medicine Applications

Background:

  • The field of protein (or peptide) biomarkers in clinical studies is rapidly advancing.
  • Mass spectrometry-based assays and antibody-based protein arrays have significantly improved biomarker identification and validation.
  • There is a growing need to understand the current implementation status of these biomarkers in clinical research.

Purpose of the Study:

  • To investigate the recent (last 6 years) implementation of protein/peptide biomarkers in clinical studies.
  • To highlight the current applications and trends in proteomics/peptidomics biomarker research.
  • To assess the role of protein biomarkers in disease diagnosis, prognosis, and patient stratification.

Main Methods:

  • Analysis of clinical trials from clinicaltrials.gov within the last six years.
  • Identification of trials directly utilizing protein or peptide biomarkers.
  • Categorization of trial applications based on their objectives (e.g., diagnosis, prognosis, stratification).

Main Results:

  • Forty-two clinical trials involving protein or peptide biomarkers were identified.
  • Most trials focus on non-invasive diagnostic tools for early detection.
  • Many trials aim to correlate protein abundance with disease risk, while fewer focus on patient stratification for intervention.

Conclusions:

  • Protein and peptide biomarkers are crucial for advancing disease management and precision medicine.
  • The research indicates a strong trend towards using biomarkers for early, non-invasive diagnostics and risk assessment.
  • Further research is needed to fully leverage protein biomarkers for patient stratification and targeted interventions.