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Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

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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Leonhard Med, a trusted research environment for processing sensitive research data.

Michal J Okoniewski1, Anna Wiegand1, Diana Coman Schmid1

  • 1SIS Scientific IT Services, ETH Zurich, Binzmühlestrasse 130, 8092 Zurich, Switzerland, https://sis.id.ethz.ch/.

Journal of Integrative Bioinformatics
|August 2, 2024
PubMed
Summary
This summary is machine-generated.

Leonhard Med is a secure Trusted Research Environment (TRE) at ETH Zurich, enabling researchers to handle sensitive data. It offers robust security and flexibility for personalized health and omics data analysis.

Keywords:
cross-omics research platformshigh performance computinghuman bioinformaticspersonalized medicinesecure data processingtrusted research environments

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Area of Science:

  • Computer Science
  • Bioinformatics
  • Data Security

Background:

  • Sensitive research data requires secure handling environments.
  • ETH Zurich developed Leonhard Med to meet these needs.
  • Compliance with Swiss and international data protection laws is crucial.

Purpose of the Study:

  • To provide an overview of the Leonhard Med Trusted Research Environment (TRE).
  • To detail its development, operation, and features for secure sensitive data processing.
  • To highlight its capabilities for personalized health and omics data analysis.

Main Methods:

  • Overview of user perspective, legal framework, design history, and operations.
  • Description of security controls and compliance with data protection policies.
  • Explanation of the platform's evolution from bare-metal HPC to a virtualised private cloud.

Main Results:

  • Leonhard Med offers an efficient, highly secure TRE for sensitive data processing.
  • It provides a full stack of security controls compliant with Swiss legislation and ETH policies.
  • The platform supports national and international research collaborations.

Conclusions:

  • Leonhard Med is a flexible and secure platform for sensitive data analysis.
  • It facilitates access to cutting-edge research software for omics and personalized health applications.
  • The TRE ensures data confidentiality, integrity, and availability through robust measures.