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

Clinically Relevant Drug Product Specifications: Methods of Establishment01:29

Clinically Relevant Drug Product Specifications: Methods of Establishment

55
Product specifications define the acceptable quality of a pharmaceutical product by ensuring identity, purity, potency, and strength. These specifications serve as benchmarks during development, manufacturing, and post-approval quality control. Clinically relevant specifications are particularly important because they directly relate to a drug's safety and efficacy in clinical use.Dissolution studies are critical biopharmaceutic tools that link in vitro behavior to in vivo performance. They...
55
Synthetic Biology02:55

Synthetic Biology

5.1K
Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
5.1K
Dosage Regimen Designs: Nomograms and Tabulations01:23

Dosage Regimen Designs: Nomograms and Tabulations

47
Nomograms and tabulations are vital tools used by clinicians to design accurate and individualized dosage regimens. These instruments provide a straightforward method for adjusting dosages based on individual patient characteristics, including age, weight, and physiological condition. The foundation of a drug's nomogram is population pharmacokinetic data collected and analyzed using specific models. This data simplifies complex equations, presenting them diagrammatically or tabularly for easy...
47
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.0K
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...
1.0K
Dosage Regimens: Designs and Approaches01:28

Dosage Regimens: Designs and Approaches

93
Designing a dosage regimen, which refers to the manner of drug administration, is a complex process involving the selection of drug dose, route, and frequency. This process is underpinned by pharmacokinetic parameters derived from tests and population averages. These parameters are then tailored to patient-specific variables such as diagnosis, demographics, and allergy status. Once therapy commences, therapeutic response monitoring is critical and achieved through clinical and physical...
93
Preclinical Development: Overview01:28

Preclinical Development: Overview

5.4K
Preclinical development consists of a series of tests that ensure the safety and efficacy of a new therapeutic compound before it is tested in humans. There are four main phases to this process. First, safety pharmacology tests are conducted to ensure the drug does not produce any acutely harmful effects. These tests examine parameters such as bronchoconstriction, cardiac dysrhythmias, blood pressure changes, and ataxia. Next, preliminary toxicological testing is performed to determine the...
5.4K

You might also read

Related Articles

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

Sort by
Same author

GlobalMedQA: A Standardized Multilingual Dataset for Assessing Medical Knowledge in LLMs.

Studies in health technology and informatics·2026
Same author

Accurate Yet Privacy-Preserving Determination of Case Numbers Across German University Hospital Health Data.

Studies in health technology and informatics·2026
Same author

Blaze: A High-Performance Open Source FHIR Server with Embedded CQL Evaluation Engine.

Studies in health technology and informatics·2026
Same author

A Data-Centric Approach for Health Care and Research in a Health Knowledge Management Platform: Implementation and Requirement-Based Evaluation Study.

JMIR medical informatics·2026
Same author

Dietary intervention among young cancer survivors within the CARE for CAYA program.

Journal of cancer survivorship : research and practice·2026
Same author

A comprehensive European Colorectal Cancer Cohort dataset.

Scientific data·2026

Related Experiment Video

Updated: Nov 4, 2025

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

4.4K

Desiderata for a Synthetic Clinical Data Generator.

Joshua Wiedekopf1, Hannes Ulrich1, Andrea Essenwanger2

  • 1IT Center for Clinical Research, University of Lübeck, Germany.

Studies in Health Technology and Informatics
|May 27, 2021
PubMed
Summary

Generating realistic synthetic Electronic Health Records (EHRs) is crucial for research. This study defines requirements for adaptable EHR generators, addressing limitations in the German healthcare system.

Keywords:
RS-EHRRealistic Synthetic Electronic Health RecordsRequirementsSecondary UseSynthetic Data

More Related Videos

Automation of a Positron-emission Tomography PET Radiotracer Synthesis Protocol for Clinical Production
10:20

Automation of a Positron-emission Tomography PET Radiotracer Synthesis Protocol for Clinical Production

Published on: October 26, 2018

11.5K
Automated Robotic Liquid Handling Assembly of Modular DNA Devices
11:22

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

12.6K

Related Experiment Videos

Last Updated: Nov 4, 2025

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

4.4K
Automation of a Positron-emission Tomography PET Radiotracer Synthesis Protocol for Clinical Production
10:20

Automation of a Positron-emission Tomography PET Radiotracer Synthesis Protocol for Clinical Production

Published on: October 26, 2018

11.5K
Automated Robotic Liquid Handling Assembly of Modular DNA Devices
11:22

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

12.6K

Area of Science:

  • Medical Informatics
  • Health Data Science

Background:

  • The increasing adoption of Electronic Health Records (EHRs) facilitates secondary data use.
  • Privacy concerns and access barriers limit researchers' use of real patient data.
  • Synthetic EHR generation offers a viable alternative for research purposes.

Purpose of the Study:

  • To identify shortcomings in existing synthetic EHR generation methods.
  • To define requirements for ideal EHR generator projects adaptable to specific healthcare systems, particularly Germany's.
  • To facilitate future development of robust synthetic data generators.

Main Methods:

  • Analysis of three distinct case studies involving synthetic EHR generation.
  • Identification and documentation of limitations in prior synthetic data generation approaches.
  • Definition of a requirements list for adaptable EHR generator projects.

Main Results:

  • Prior synthetic EHR generation projects exhibit shortcomings, especially concerning adaptability to the German healthcare system.
  • A comprehensive, non-exhaustive list of requirements for ideal EHR generator projects has been defined.
  • The identified requirements aim to enhance the utility and applicability of synthetic EHRs across diverse settings.

Conclusions:

  • There is a need for synthetic EHR generators that are adaptable to specific healthcare system requirements.
  • The defined requirements provide a foundation for developing improved synthetic EHR generation tools.
  • Addressing these requirements will enable wider and more effective secondary use of EHR data for research.