Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

293
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
293
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

742
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...
742
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

348
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
348
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

111
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
111

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Lenalidomide-associated reversible TP53-mutated clonal hematopoiesis in plasma cell neoplasms.

Haematologica·2025
Same author

Comprehensive characterization of human bone marrow microenvironment shows age-related changes.

Haematologica·2025
Same author

The present and future of cardiological telemonitoring in Europe: a statement from seven European countries.

Herzschrittmachertherapie & Elektrophysiologie·2025
Same author

Perceived Trust and Professional Identity Threat in AI-Based Clinical Decision Support Systems: Scenario-Based Experimental Study on AI Process Design Features.

JMIR formative research·2025
Same author

Investigating Past, Present, and Future Trends on Interface Between Marine and Medical Research and Development: A Bibliometric Review.

Marine drugs·2025
Same author

Overcoming the not-invented-here syndrome in healthcare: The case of German ambulatory physiotherapists' adoption of digital health innovations.

PloS one·2023

Related Experiment Video

Updated: Aug 24, 2025

Exploring the Effects of Spaceflight on Mouse Physiology using the Open Access NASA GeneLab Platform
11:08

Exploring the Effects of Spaceflight on Mouse Physiology using the Open Access NASA GeneLab Platform

Published on: January 13, 2019

12.4K

Data platforms for open life sciences-A systematic analysis of management instruments.

Daniel Laufs1, Mareike Peters1, Carsten Schultz1

  • 1Technology Management Research Group, Faculty of Business, Economics and Social Sciences, Kiel University, Kiel, SH, Germany.

Plos One
|October 25, 2022
PubMed
Summary

This study provides a guideline for managing open data platforms in life sciences. It details success factors for data aggregation and exchange to foster innovation.

More Related Videos

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.3K
Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management
08:01

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

Published on: November 30, 2022

4.5K

Related Experiment Videos

Last Updated: Aug 24, 2025

Exploring the Effects of Spaceflight on Mouse Physiology using the Open Access NASA GeneLab Platform
11:08

Exploring the Effects of Spaceflight on Mouse Physiology using the Open Access NASA GeneLab Platform

Published on: January 13, 2019

12.4K
Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.3K
Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management
08:01

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

Published on: November 30, 2022

4.5K

Area of Science:

  • Life Science Data Platforms
  • Open Innovation Ecosystems
  • Data Management and Interoperability

Background:

  • Open data platforms face challenges in aggregating user-specific data and fostering collaborative exchange.
  • Existing research often focuses on data quality, neglecting the crucial aspect of data utilization for innovation.

Purpose of the Study:

  • To systematically categorize open life science data platforms based on technology and domain coverage.
  • To identify general and specific success factors for data platform management instruments.
  • To develop a practical guideline for establishing and operationalizing data platforms to maximize data value.

Main Methods:

  • Qualitative content analysis of 39 in-depth interviews with data platform experts and external stakeholders.
  • Systematic categorization of platforms by technology intermediation and domain scope.
  • Development of a guideline for seven key management instruments.

Main Results:

  • Identified distinct success factors for managing diverse open data platforms.
  • Highlighted the importance of data platforms in enabling data utilization for innovative outputs.
  • Proposed a structured guideline for seven management instruments to enhance platform establishment and data exploitation.

Conclusions:

  • The developed guideline aids in operationalizing data platforms and optimizing data value.
  • Findings support the exploitation of open innovation potential within the life sciences and other sectors.
  • Effective platform management is key to bridging data supply and demand for scientific advancement.