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A Systematic Approach to Diagnostic Laboratory Software Requirements Analysis.

Thomas Krause1, Elena Jolkver1, Paul Mc Kevitt2

  • 1Faculty of Mathematics and Computer Science, University of Hagen, 58097 Hagen, Germany.

Bioengineering (Basel, Switzerland)
|April 21, 2022
PubMed
Summary

This study highlights the need for systematic requirements engineering in diagnostic laboratory software. It demonstrates a structured approach for developing software for quantitative polymerase chain reaction (qPCR) gene expression analysis, addressing regulatory demands.

Keywords:
gene expressionlaboratory diagnosticsmedical diagnosticsqPCRrequirements engineering

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Area of Science:

  • Medical Diagnostics and Laboratory Software Engineering
  • Genetics and Molecular Diagnostics

Background:

  • Genetics is increasingly vital in medical diagnostics, driving evolving needs for laboratory software.
  • Existing laboratory software often lags behind new diagnostic technologies and regulatory changes, focusing more on research than automation.
  • Despite regulatory requirements for diagnostic software, formal development procedures are lacking.

Purpose of the Study:

  • To demonstrate a systematic requirements analysis for diagnostic software.
  • To address the gap in formal software development processes for medical diagnostics.
  • To provide an example for developing software for quantitative polymerase chain reaction (qPCR) gene expression analysis.

Main Methods:

  • A multi-step research approach was employed.
  • Methods included a comprehensive literature review.
  • User interviews and market analysis were conducted to gather requirements.

Main Results:

  • The study revealed the significant complexity involved in developing diagnostic software.
  • Numerous requirements must be considered for the successful implementation of gene expression analysis systems.
  • A systematic approach is crucial for meeting regulatory standards like the European In Vitro Diagnostic Regulation and IEC 62304.

Conclusions:

  • Systematic requirements engineering is essential for ensuring the quality and regulatory compliance of diagnostic software.
  • The demonstrated methodology provides a framework for developing complex diagnostic systems.
  • Addressing the identified complexities is key for future advancements in automated genetic diagnostics.